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## **Meet the editor**

Dr. Amal Ali Elkordy is a Senior Lecturer in Pharmaceutics in the Department of Pharmacy, Health and Well-being, Faculty of Applied Sciences, University of Sunderland, UK. Her area of research interest is the stabilisation of protein formulations (using spray drying and crystallisation technology) and their delivery via oral and pulmonary routes. Her work in this field has

been recognised by the award of two prizes at the British Pharmaceutical Conference in 2002 and in 2004. Her more recent work is concerned with the enhancement of poorly water soluble drugs and gene therapeutics (awarded national recognition from the College of Mental Health Pharmacists, 2010). Dr. Elkordy has many publications in peer-review journals and she was invited speaker in a number of conferences.

Contents

**Preface IX** 

**Section 1 Application of Differential Scanning Calorimetry** 

Chapter 1 **Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 3** 

Chapter 2 **Thermal Stability of the Nanostructured Powder** 

**and Characterization of Novel Organic** 

**Section 2 Application of Isothermal Titration Calorimetry for Analysis of Proteins and DNA 71** 

**Mixtures Prepared by Mechanical Alloying 21**  Safia Alleg, Saida Souilah and Joan Joseph Suñol

**Nicotinium Trifluoroacetate Single Crystals 49** 

Chapter 4 **Isothermal Titration Calorimetry: Thermodynamic Analysis** 

Jose C. Martinez, Javier Murciano-Calles, Eva S. Cobos, Manuel Iglesias-Bexiga, Irene Luque and Javier Ruiz-Sanz

**Events by Using Equilibrium Models 73** 

Chapter 6 **Insights into the Relative DNA Binding Affinity and** 

Chapter 5 **Applications of Calorimetric Techniques in** 

Ruel E. McKnight

**of the Binding Thermograms of Molecular Recognition** 

**the Formation of Protein-Polyelectrolytes Complexes 105**  Diana Romanini, Mauricio Javier Braia and María Cecilia Porfiri

**Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 129** 

**into Pharmaceuticals 1** 

Chapter 3 **Studies on Growth, Crystal Structure** 

P.V. Dhanaraj and N.P. Rajesh

Adriana Gregorova

## Contents

### **Preface XIII**


Ruel E. McKnight


Contents VII

Chapter 16 **Thermal Analysis of Sulfur and Selenium Compounds** 

**Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 385**

Chapter 17 **Calorimetric Determination of Heat Capacity,** 

Jindřich Leitner, David Sedmidubský, Květoslav Růžička and Pavel Svoboda

Chapter 18 **Differential Scanning Calorimetry Studies of** 

Eric A. Smith and Phoebe K. Dea

Chapter 19 **Oxidative Stability of Fats and Oils Measured by Differential Scanning Calorimetry for Food and Industrial Applications 445**  M.D.A. Saldaña and S.I. Martínez-Monteagudo

**with Multiple Applications, Including Anticancer Drugs 365** 

**Phospholipid Membranes: The Interdigitated Gel Phase 407**

Daniel Plano, Juan Antonio Palop and Carmen Sanmartín


VI Contents

Chapter 7 **Thermodynamic Signatures of Macromolecular Complexes ‒**

**Section 3 Application of MicroCalorimetry to Study Protein Stability** 

**Lyoprotector of Bovine Plasma Proteins 197**

Mercedes E. Campderrós and Noemi E. Zaritzky

**Section 4 Thermal Analysis of Phase Transitions of Polymers**

Stefka G. Taneva, Sonia Bañuelos and María A. Urbaneja

**of Lysozyme Crystals Using Microcalorimetry 185**  Amal A. Elkordy, Robert T. Forbes and Brian W. Barry

Laura T. Rodriguez Furlán, Javier Lecot, Antonio Pérez Padilla,

**on Compatible Softened Polymer Composites 221** 

Luis Alberto Alcazar-Vara and Eduardo Buenrostro-Gonzalez

W. Steinmann, S. Walter, M. Beckers, G. Seide and T. Gries

**Paraffinic Systems by DSC Measurements 253**

**and Crystallization in Polymeric Fibers 277** 

**Section 5 Indirect Calorimetry to Measure Energy Expenditure 307** 

**by Indirect Calorimetry in Obesity 309** Eliane Lopes Rosado, Vanessa Chaia Kaippert

**Section 6 Applications of Calorimetry into Propellants, Alloys,** 

Chapter 14 **Thermal Decomposition Kinetics of Aged Solid Propellant** 

Chapter 15 **Numerical Solutions for Structural Relaxation of Amorphous** 

R. F. B. Gonçalves, J. A. F. F. Rocco and K. Iha

**Based on Ammonium Perchlorate – AP/HTPB Binder 325** 

**Alloys Studied by Activation Energy Spectrum Model 343**

**a Nuclear Chaperone 153** 

**and Folding Reversibility 183** 

Chapter 8 **Determination of Folding Reversibility** 

Chapter 9 **Calorimetric Study of Inulin as Cryo- and** 

**and Paraffinic Wax 219**

Chapter 10 **Silver Particulate Films** 

Pratima Parashar

Chapter 11 **Liquid-Solid Phase Equilibria of** 

Chapter 13 **Energy Expenditure Measured** 

Kazu-masa Yamada

Chapter 12 **Thermal Analysis of Phase Transitions**

and Roberta Santiago de Brito

**Mixed Oxides and Lipids 323**

**Insights on the Stability and Interactions of Nucleoplasmin,** 


Preface

This book (carrying at the beginning the name of "Calorimetry") started when I received an invitation from the InTech Open Access Publisher to be the editor of the book for my experience and publications in the field of applications of calorimetry and biocalorimetry in the analysis of small and large drug molecules. I welcomed the invitation and I was enthusiastic to handle chapters submitted from colleagues all over the world with the aim of disseminating the high quality research in application of calorimetry for the benefits of scientists, students, academics and industry

Calorimetry is an analytical method which can thermodynamically characterise the phase transition by determining heat capacities, enthalpies and melting temperatures of substances including oils, lipids, biological macromolecules, small drug molecules and polymers. It was an honour to read submitted chapters, to write a chapter and to divide the book into sections. Accordingly, the name of the book was changed into "Applications of Calorimetry in a Wide Context - Differential Scanning Calorimetry, Isothermal

Finally, without the support of many other expert colleagues, who helped in the review process, completion of this book would have been difficult. The editor would like to thank the following scientists who have helped in the peer-review process: Prof. Brian Barry, Bradford School of Pharmacy, University of Bradford, UK; Dr. Paul Carter, Department of Pharmacy, Health and Well-being, University of Sunderland, UK; Dr. Shu Cheng Chaw, Department of Pharmacy, Health and Well-being, University of Sunderland, UK; Dr. Eman Ali Elkordy, Faculty of Medicine, University of Tanta, Egypt; Prof. Gamal El Maghraby, Faculty of Pharmacy, University of Tanta, Egypt; Dr. Ebtessam Ahmed Essa, Faculty of Pharmacy, University of Umm Al Qura, Saudi Arabia; Prof. Robert Forbes, Bradford School of Pharmacy, University of

Titration Calorimetry and Microcalorimetry" to reflect the content of the book.

Bradford, UK; Dr. Wendy Hulse, Formulation technical specialist 2, Ipsen, UK.

**Dr. Amal Ali Elkordy,**

Faculty of Applied Sciences, University of Sunderland, Sunderland, United Kingdom

Department of Pharmacy, Health and Well-being,

(pharmaceutical, biopharmaceutical and food industries).

## Preface

This book (carrying at the beginning the name of "Calorimetry") started when I received an invitation from the InTech Open Access Publisher to be the editor of the book for my experience and publications in the field of applications of calorimetry and biocalorimetry in the analysis of small and large drug molecules. I welcomed the invitation and I was enthusiastic to handle chapters submitted from colleagues all over the world with the aim of disseminating the high quality research in application of calorimetry for the benefits of scientists, students, academics and industry (pharmaceutical, biopharmaceutical and food industries).

Calorimetry is an analytical method which can thermodynamically characterise the phase transition by determining heat capacities, enthalpies and melting temperatures of substances including oils, lipids, biological macromolecules, small drug molecules and polymers. It was an honour to read submitted chapters, to write a chapter and to divide the book into sections. Accordingly, the name of the book was changed into "Applications of Calorimetry in a Wide Context - Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry" to reflect the content of the book.

Finally, without the support of many other expert colleagues, who helped in the review process, completion of this book would have been difficult. The editor would like to thank the following scientists who have helped in the peer-review process: Prof. Brian Barry, Bradford School of Pharmacy, University of Bradford, UK; Dr. Paul Carter, Department of Pharmacy, Health and Well-being, University of Sunderland, UK; Dr. Shu Cheng Chaw, Department of Pharmacy, Health and Well-being, University of Sunderland, UK; Dr. Eman Ali Elkordy, Faculty of Medicine, University of Tanta, Egypt; Prof. Gamal El Maghraby, Faculty of Pharmacy, University of Tanta, Egypt; Dr. Ebtessam Ahmed Essa, Faculty of Pharmacy, University of Umm Al Qura, Saudi Arabia; Prof. Robert Forbes, Bradford School of Pharmacy, University of Bradford, UK; Dr. Wendy Hulse, Formulation technical specialist 2, Ipsen, UK.

> **Dr. Amal Ali Elkordy,** Department of Pharmacy, Health and Well-being, Faculty of Applied Sciences, University of Sunderland, Sunderland, United Kingdom

**Section 1** 

**Application of Differential Scanning** 

**Calorimetry into Pharmaceuticals** 

**Application of Differential Scanning Calorimetry into Pharmaceuticals** 

**Chapter 1** 

© 2013 Gregorova, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Application of Differential Scanning Calorimetry** 

Generally, polymers can be classified according to their thermal and mechanical properties into thermoplastics, thermosets and elastomers. Thermoplastics are amorphous or semicrystalline polymers that soft or melt during heating and solidify during cooling. The heating/cooling/heating process can be repeated without perceptible changes in thermal and mechanical properties of thermoplastics. Thermosets during heating undergo chemical changes and this process is irreversible. Elastomers can be vulcanized (cross-linked under assistance of heat, light, or special chemicals like sulfur, peroxides) that makes them reversibly stretchable for small deformations but vulcanization is the irreversible process.

The resulted properties of polymer materials and mixtures depend on the chemical and physical properties of neat polymers, additives as well as the used processing methodology. Differential scanning calorimetry (DSC) is a physical characterization method used to study thermal behavior of neat polymers, copolymers, polymer blends and composites. Generally, the non-isothermal DSC is used for the identification of neat basic polymers as well as the determination of their purity and stability. Amorphous polymers exhibit a glass transition temperature and semi-crystalline polymers may possess the glass transition temperature, a crystallization temperature, a melting temperature with various crystallization and melting enthalpies. However, these properties alter by both a presence of additives and applied polymer processing methodologies. Basically, a small quantity of sample (up to 10 mg) in pan from various materials (e.g. aluminum pan) and empty pan (reference) are treated under a defined temperature program (various combinations of thermal scansheating/cooling, and isothermal cycles), a pressure (stable) and an atmosphere (inert or reactive). Principally, sample and reference are maintained at the same temperature, while any transition occurred in the sample needs an energy supply, which is recorded by the DSC as a rate dQ/dt against a temperature or a time. The DSC is the thermal analysis mainly used

**to the Characterization of Biopolymers** 

Additional information is available at the end of the chapter

Adriana Gregorova

http://dx.doi.org/10.5772/53822

**1. Introduction** 

## **Application of Differential Scanning Calorimetry to the Characterization of Biopolymers**

Adriana Gregorova

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53822

### **1. Introduction**

Generally, polymers can be classified according to their thermal and mechanical properties into thermoplastics, thermosets and elastomers. Thermoplastics are amorphous or semicrystalline polymers that soft or melt during heating and solidify during cooling. The heating/cooling/heating process can be repeated without perceptible changes in thermal and mechanical properties of thermoplastics. Thermosets during heating undergo chemical changes and this process is irreversible. Elastomers can be vulcanized (cross-linked under assistance of heat, light, or special chemicals like sulfur, peroxides) that makes them reversibly stretchable for small deformations but vulcanization is the irreversible process.

The resulted properties of polymer materials and mixtures depend on the chemical and physical properties of neat polymers, additives as well as the used processing methodology. Differential scanning calorimetry (DSC) is a physical characterization method used to study thermal behavior of neat polymers, copolymers, polymer blends and composites. Generally, the non-isothermal DSC is used for the identification of neat basic polymers as well as the determination of their purity and stability. Amorphous polymers exhibit a glass transition temperature and semi-crystalline polymers may possess the glass transition temperature, a crystallization temperature, a melting temperature with various crystallization and melting enthalpies. However, these properties alter by both a presence of additives and applied polymer processing methodologies. Basically, a small quantity of sample (up to 10 mg) in pan from various materials (e.g. aluminum pan) and empty pan (reference) are treated under a defined temperature program (various combinations of thermal scansheating/cooling, and isothermal cycles), a pressure (stable) and an atmosphere (inert or reactive). Principally, sample and reference are maintained at the same temperature, while any transition occurred in the sample needs an energy supply, which is recorded by the DSC as a rate dQ/dt against a temperature or a time. The DSC is the thermal analysis mainly used

© 2013 Gregorova, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

4 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

to determine a first-order transition (melting) and a second order endothermic transition (glass transition). The sudden change in the specific heat value, *Cp* corresponds with the glass transition temperature as follows (Bower, 2002):

$$\frac{d\mathbb{Q}}{dt} = m\mathbb{C}\_p \tag{1}$$

Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 5

There are two types of DSC systems: 1) heat-flux (sample and reference pans are in an identical furnace block) and 2) power compensation (sample and reference pans are in two separate furnace blocks). From the practical point of view, it is important to pay attention to

a selection of pans (e.g. Al-, Pt-, Ni-, Cu-, Quartz-pans, hermetic or non-hermetic pans),

a temperature program (heating cycle usually should start about 50°C under and finish

a sufficient slow scanning rate (to avoid the neglecting of the requested thermal

a sufficient purity and source of sample (neat polymer, polymer blend, composite,

The aim of this chapter is to show some examples of the practical use of the DSC within the investigation of an amorphous biopolymer – lignin and semi-crystalline biodegradable polymer – poly(lactic acid) as well as to discuss the dependence of the thermal thermal properties on the value of the molecular weight of polymer, the polymer processing

Amorphous and semicrystalline polymers undergo a phase change from a glassy to rubbery

At *Tg* the segmental mobility of molecular chains increases and a polymer is more elastic and flexible. The value of *Tg* is dependent on the various factors such as a molecular weight of polymer, a presence of moisture, a presence of the crystalline phase (in the case of semicrystalline polymers). The dependence of *Tg* on a number-average molecular weight is

*g g*

**2.1. Thermal properties of Kraft lignin extracted with organic solvents** 

weight properties and thermal properties of Kraft lignin is shown.

*<sup>K</sup> T T*

where *<sup>g</sup> <sup>T</sup>* is a glass transition for polymer with the infinite number-average molecular weight, K is an empirical parameter related to the free volume in polymer and Mn is a

In this sub-chapter, an example of the effect of various extraction solvents on molecular

*n*

(3)

*M*

about 10-20°C above the expected measured transition temperature),

issues influencing an accuracy of results as follows: an instrument calibration, baseline subtractions,

a proper thermal contact between sample and pans,

before or after processing, kind of the processing).

methodology and the presence of additives in the polymer mixtures.

**2. Effect of molecular weight on glass transition temperature** 

a selection of working gas (N2, He, O2),

stage at a glass transition temperature (*Tg*).

number-average molecular weight of polymer.

described by Flory-Fox equation:

transition),

where *m* is the mass of the sample.

However, the determination of the glass transition of polymers with a high crystallinity content is limited. The first-order transitions such as the crystallization of a polymer during a heating (cold crystallization) or a cooling cycle (crystallization) and a melting of polymer crystals can be described by the following formula (Bower, 2002):

$$\frac{d\mathbb{Q}}{dt} = \kappa \Delta T = \kappa \mathop{\rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \rm \$$

where is a thermal conductance between a sample holder and a sample, *T* is a temperature increase rate, and t0 is the start of transition.

Figure 1 shows the example of thermal transitions occurring in the injection molded sample of poly(lactic acid) (PLA) such as the glass transition, the cold crystallization and the melting. PLA is a thermoplastic aliphatic semi-crystalline biodegradable polyester. The presented molded sample had been cooled very rapidly during the processing (injection molding), so as the consequence during the second heating cycle appeared the cold crystallization peak.

**Figure 1.** DSC thermogram of commercial poly(lactic acid) with Mw = 70 400 and PDI = 1.8 detected during 2nd heating cycle (0-180°C, 10°C/min, N2 atmosphere)

There are two types of DSC systems: 1) heat-flux (sample and reference pans are in an identical furnace block) and 2) power compensation (sample and reference pans are in two separate furnace blocks). From the practical point of view, it is important to pay attention to issues influencing an accuracy of results as follows:


Applications of Calorimetry in a Wide Context –

where *m* is the mass of the sample.

crystallization peak.

glass transition temperature as follows (Bower, 2002):

4 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

crystals can be described by the following formula (Bower, 2002):

temperature increase rate, and t0 is the start of transition.

during 2nd heating cycle (0-180°C, 10°C/min, N2 atmosphere)

to determine a first-order transition (melting) and a second order endothermic transition (glass transition). The sudden change in the specific heat value, *Cp* corresponds with the

*dQ mC*

However, the determination of the glass transition of polymers with a high crystallinity content is limited. The first-order transitions such as the crystallization of a polymer during a heating (cold crystallization) or a cooling cycle (crystallization) and a melting of polymer

> *dQ dQ T Tt t dt dt*

Figure 1 shows the example of thermal transitions occurring in the injection molded sample of poly(lactic acid) (PLA) such as the glass transition, the cold crystallization and the melting. PLA is a thermoplastic aliphatic semi-crystalline biodegradable polyester. The presented molded sample had been cooled very rapidly during the processing (injection molding), so as the consequence during the second heating cycle appeared the cold

**Figure 1.** DSC thermogram of commercial poly(lactic acid) with Mw = 70 400 and PDI = 1.8 detected

 

where is a thermal conductance between a sample holder and a sample, *T*

*p*

<sup>0</sup> ( )

*dt* (1)

0

(2)

is a

*t*


The aim of this chapter is to show some examples of the practical use of the DSC within the investigation of an amorphous biopolymer – lignin and semi-crystalline biodegradable polymer – poly(lactic acid) as well as to discuss the dependence of the thermal thermal properties on the value of the molecular weight of polymer, the polymer processing methodology and the presence of additives in the polymer mixtures.

### **2. Effect of molecular weight on glass transition temperature**

Amorphous and semicrystalline polymers undergo a phase change from a glassy to rubbery stage at a glass transition temperature (*Tg*).

At *Tg* the segmental mobility of molecular chains increases and a polymer is more elastic and flexible. The value of *Tg* is dependent on the various factors such as a molecular weight of polymer, a presence of moisture, a presence of the crystalline phase (in the case of semicrystalline polymers). The dependence of *Tg* on a number-average molecular weight is described by Flory-Fox equation:

$$T\_{\mathcal{g}} = T\_{\mathcal{g}}^{\circ} + \frac{K}{M\_n} \tag{3}$$

where *<sup>g</sup> <sup>T</sup>* is a glass transition for polymer with the infinite number-average molecular weight, K is an empirical parameter related to the free volume in polymer and Mn is a number-average molecular weight of polymer.

#### **2.1. Thermal properties of Kraft lignin extracted with organic solvents**

In this sub-chapter, an example of the effect of various extraction solvents on molecular weight properties and thermal properties of Kraft lignin is shown.

6 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Lignin is polydisperse amorphous natural polymer consisting of branched network phenylpropane units with phenolic, hydroxyl, methoxyl and carbonyl groups. Its molecular weight properties as well as functional groups depend on its genetic origin and used isolation method. Differential scanning calorimetry is the useful method to determine its glass transition temperature. The value of Tg depends on the molecular weight, the thermal treatment, the humidity content and the presence of various contaminants in lignin sample.

Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 7

Polarity index

4.0 5.1

M*<sup>w</sup>* (g/mol) PDI

Solvent Chemical formula Hildebrand solubility parameter

chromatography (GPC) with the using of tetrahydrofuran as an eluent.

Tetrahydrofuran

C4H8O CH3COCH3

**Table 1.** Solvents used for Kraft lignin extraction

Sample Tg

tetrahydrofuran, dichlormethane, methanol and 1,4-dioxane

Acetone

(MPa)1/2

The determined thermal and molecular weight properties of Kraft lignins are shown in Table 2. The glass transition temperature (Tg) and the specific heat change (Cp) were assessed by the differential scanning calorimetry (DSC) under the nitrogen flow, using the second heating cycle. Molecular weight properties were determined by a gel permeation

(°C)

Kraft lignin\_acetone 114 0.086 1030 1800 1.7 Kraft lignin\_tetrahydrofuran 124 0.222 1170 3150 2.7 Kraft lignin\_dichlormethane 59 0.260 750 940 1.3 Kraft lignin\_methanol 105 0.368 910 1300 1.4 Kraf lignin\_1,4-dioxane 120 0.367 1150 3070 2.7

**Figure 4.** DSC thermograms of Kraft lignin extracted in acetone, tetrahydrofuran, dichlormethane, methanol and 1,4-dioxane detected during second heating scan (5-180°C, 10°C/min, N2 atmosphere)

**Table 2.** Thermal and molecular weight properties of Kraft lignins extracted in acetone,

Cp (Jg°C)

M*<sup>n</sup>* (g/mol)

Dichlormethane CH2Cl2 20.2 3.1

1,4-Dioxane C4H8O2 20.5 4.8 Methanol CH3OH 29.7 5.1

18.5 19.7

Generally, phenyl groups together with the cross-linking restrict the molecular motion of lignin as an amorphous polymer in contrast to propane chains. Moreover, the intermolecular hydrogen bonding decrease *Tg* in the contrast to the methoxyl groups (Hatakeyama & Hatakeyama, 2010). Lignin might be defined as a natural polymeric product produced by the enzymatic dehydrogenation polymerization of the primary methoxylated precursors such as *p*-coumaryl-, coniferyl- and sinapyl- alcohols (Figure 2).

**Figure 2.** Lignin monomer building units

The structure of lignins depends on their natural origin and also on the external and internal conditions existing during lignin macromolecule synthesis and isolations. The large heterogeneity of lignin´s structures makes it difficult to determine the overall structure of lignin. High variability of substituents on phenyl propane unit together with auto-coupling reaction gives rise to different lignin´s structures depending on its origin and isolation method (Figure 3).

**Figure 3.** Lignin isolation methods

Kraft lignin used in this study was isolated from commercial spent pulping black liquor through the acidification with 98% sulphuric acid to pH=2 (Zellstoff Pöls AG, Austria). Precipitated, filtered, washed and dried Kraft lignin was extracted at the room temperature with organic solvents with Hildebrand solubility parameters in the range of 18.5-29.7 MPa1/2 (see Table 1) and then again filtered and dried.


**Table 1.** Solvents used for Kraft lignin extraction

Applications of Calorimetry in a Wide Context –

**Figure 2.** Lignin monomer building units

method (Figure 3).

**Figure 3.** Lignin isolation methods

(see Table 1) and then again filtered and dried.

6 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

precursors such as *p*-coumaryl-, coniferyl- and sinapyl- alcohols (Figure 2).

Lignin is polydisperse amorphous natural polymer consisting of branched network phenylpropane units with phenolic, hydroxyl, methoxyl and carbonyl groups. Its molecular weight properties as well as functional groups depend on its genetic origin and used isolation method. Differential scanning calorimetry is the useful method to determine its glass transition temperature. The value of Tg depends on the molecular weight, the thermal treatment, the humidity content and the presence of various contaminants in lignin sample. Generally, phenyl groups together with the cross-linking restrict the molecular motion of lignin as an amorphous polymer in contrast to propane chains. Moreover, the intermolecular hydrogen bonding decrease *Tg* in the contrast to the methoxyl groups (Hatakeyama & Hatakeyama, 2010). Lignin might be defined as a natural polymeric product produced by the enzymatic dehydrogenation polymerization of the primary methoxylated

The structure of lignins depends on their natural origin and also on the external and internal conditions existing during lignin macromolecule synthesis and isolations. The large heterogeneity of lignin´s structures makes it difficult to determine the overall structure of lignin. High variability of substituents on phenyl propane unit together with auto-coupling reaction gives rise to different lignin´s structures depending on its origin and isolation

Kraft lignin used in this study was isolated from commercial spent pulping black liquor through the acidification with 98% sulphuric acid to pH=2 (Zellstoff Pöls AG, Austria). Precipitated, filtered, washed and dried Kraft lignin was extracted at the room temperature with organic solvents with Hildebrand solubility parameters in the range of 18.5-29.7 MPa1/2

The determined thermal and molecular weight properties of Kraft lignins are shown in Table 2. The glass transition temperature (Tg) and the specific heat change (Cp) were assessed by the differential scanning calorimetry (DSC) under the nitrogen flow, using the second heating cycle. Molecular weight properties were determined by a gel permeation chromatography (GPC) with the using of tetrahydrofuran as an eluent.


**Table 2.** Thermal and molecular weight properties of Kraft lignins extracted in acetone, tetrahydrofuran, dichlormethane, methanol and 1,4-dioxane

**Figure 4.** DSC thermograms of Kraft lignin extracted in acetone, tetrahydrofuran, dichlormethane, methanol and 1,4-dioxane detected during second heating scan (5-180°C, 10°C/min, N2 atmosphere)

8 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Figure 4 shows the thermograms of the individual Kraft lignins extracted with various organic solvents.

Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 9

1 2 ( ) *HH H H mm c* (4)

*M*<sup>w</sup> (g/mol) PDI

properties of PLA but also their thermal properties such as the glass transition temperature (*Tg*), the melting temperature (*Tm*) (in this case *Tm* was determined as the peak temperature of the melting peak) and the crystallinity (see Figure 6. and Table 4). As an adequate indicator of the crystallinity was chosen the specific heat of fusion, calculated as follows:

where ΔHm1 and ΔHm2 are enthalpy values of the first and second melting peak, ΔHc is the

Mn (g/mol)

**Table 3.** Description of PLA samples and their molecular properties determined by GPC in chloroform

**Figure 5.** DSC thermogram of PLA\_0 detected during heating/cooling/heating scan (30-170°C, 170-0°C,

By the comparison of the content of the crystalline phase determined from 1st heating and 2nd heating cycle, it can be seen that PLA samples during second heating cycle exhibit an amorphous character despite of the initially crystalline character determined from 1st heating scan. A thermal history is very important issue that influence the arrangement of amorphous/crystalline phase and consequently influence the physico-mechanical properties

PLA\_0 0 21400 35600 1.7 PLA\_1 0.7 1950 3200 1.6 PLA\_2 1.3 5600 9300 1.7 PLA\_3 2.5 7000 13000 1.9

enthalpy of cold crystallization.


of poly(lactic acid).

Sample Concentration of

succinic anhydride

(mol%)

As can be seen from the results, the extraction as the last step used during the isolation process of Kraft lignin has a big effect on molecular as well as thermal properties of lignin.

### **2.2. Thermal properties of Poly(lactic acid) synthetized through azeotropic dehydration condensation**

This sub-chapter shows the connection between PLA structure, its molecular weight properties and its thermal properties.

Poly(lactic acid) (PLA) is a biodegradable, thermoplastic, aliphatic polyester, which monomer can be derived from annually renewable resources. The glass transition temperature value is an important attribute that influences viscoelastic properties of PLA. The increase of the ambient temperature above *Tg* of PLA causes the sharp loss of its stiffness. The *Tg* values of PLA are influenced by its molecular weight, crystallinity, thermal history during processing, character of the side-chain groups and the presence of additives in the composition. The DSC analysis is one of the suitable methods to characterize the effect of the modification of PLA reactive side-chain groups on its thermal properties.

It is worth to mention that the melting temperature and the heat of fusion of polymers are influenced by thermal history applied during the polymer synthesis or processing. Therefore DSC results derived from 1st heating cycle give information concerning an actual state of polymer crystals and the application of cooling cycle erase the previous thermal history, e.g. annealing during processing. Some semi-crystalline polymers with the slow crystallization ability like poly(lactic acid) do not have time to crystallize during cooling and thus crystallize during 2nd heating cycle (cold crystallization) and consequently the melting peak may appear as double peak due to the content of different kinds of crystals. The melting behaviour of PLA is complex with regard to its multiple melting behaviour and polymorphism and has been intensively studied by several authors (Yasiniwa et al., 2004; Yasuniwa et al., 2006; Yasuniwa et al., 2007; Di Lorenzo, 2006).

PLA sample in the following example, marked as *PLA 0*, was synthetized by an azeotropic dehydration condensation in a refluxing boiling m-xylene from 80% L-lactic acid. During the azeotropic dehydration condensation samples *PLA\_1-3* were modified by succinic anhydride in the concentration 0.7, 1.3 and 2.5 mol% (Gregorova et al., 2011a). Table 3 summarizes the nomenclature and molecular properties of non-modified PLA and PLA modified with various concentration of succinic anhydride.

Figure 5 shows DSC heating/cooling/heating thermogram of non-modified PLA with the molecular weight of 35 600 g/mol.

Generally, glass transition temperature is determined from the second heating cycle to provide *Tg* value independent on the thermal history during processing. The modification of PLA side-chain groups by succinic anhydride influenced not just molecular weight properties of PLA but also their thermal properties such as the glass transition temperature (*Tg*), the melting temperature (*Tm*) (in this case *Tm* was determined as the peak temperature of the melting peak) and the crystallinity (see Figure 6. and Table 4). As an adequate indicator of the crystallinity was chosen the specific heat of fusion, calculated as follows:

Applications of Calorimetry in a Wide Context –

organic solvents.

**dehydration condensation** 

properties and its thermal properties.

8 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Figure 4 shows the thermograms of the individual Kraft lignins extracted with various

As can be seen from the results, the extraction as the last step used during the isolation process of Kraft lignin has a big effect on molecular as well as thermal properties of lignin.

This sub-chapter shows the connection between PLA structure, its molecular weight

Poly(lactic acid) (PLA) is a biodegradable, thermoplastic, aliphatic polyester, which monomer can be derived from annually renewable resources. The glass transition temperature value is an important attribute that influences viscoelastic properties of PLA. The increase of the ambient temperature above *Tg* of PLA causes the sharp loss of its stiffness. The *Tg* values of PLA are influenced by its molecular weight, crystallinity, thermal history during processing, character of the side-chain groups and the presence of additives in the composition. The DSC analysis is one of the suitable methods to characterize the effect

It is worth to mention that the melting temperature and the heat of fusion of polymers are influenced by thermal history applied during the polymer synthesis or processing. Therefore DSC results derived from 1st heating cycle give information concerning an actual state of polymer crystals and the application of cooling cycle erase the previous thermal history, e.g. annealing during processing. Some semi-crystalline polymers with the slow crystallization ability like poly(lactic acid) do not have time to crystallize during cooling and thus crystallize during 2nd heating cycle (cold crystallization) and consequently the melting peak may appear as double peak due to the content of different kinds of crystals. The melting behaviour of PLA is complex with regard to its multiple melting behaviour and polymorphism and has been intensively studied by several authors (Yasiniwa et al., 2004;

PLA sample in the following example, marked as *PLA 0*, was synthetized by an azeotropic dehydration condensation in a refluxing boiling m-xylene from 80% L-lactic acid. During the azeotropic dehydration condensation samples *PLA\_1-3* were modified by succinic anhydride in the concentration 0.7, 1.3 and 2.5 mol% (Gregorova et al., 2011a). Table 3 summarizes the nomenclature and molecular properties of non-modified PLA and PLA

Figure 5 shows DSC heating/cooling/heating thermogram of non-modified PLA with the

Generally, glass transition temperature is determined from the second heating cycle to provide *Tg* value independent on the thermal history during processing. The modification of PLA side-chain groups by succinic anhydride influenced not just molecular weight

**2.2. Thermal properties of Poly(lactic acid) synthetized through azeotropic** 

of the modification of PLA reactive side-chain groups on its thermal properties.

Yasuniwa et al., 2006; Yasuniwa et al., 2007; Di Lorenzo, 2006).

modified with various concentration of succinic anhydride.

molecular weight of 35 600 g/mol.

$$
\Sigma \Delta H = (\Delta H\_{m1} + \Delta H\_{m2}) - \Delta H\_c \tag{4}
$$

where ΔHm1 and ΔHm2 are enthalpy values of the first and second melting peak, ΔHc is the enthalpy of cold crystallization.


**Table 3.** Description of PLA samples and their molecular properties determined by GPC in chloroform

**Figure 5.** DSC thermogram of PLA\_0 detected during heating/cooling/heating scan (30-170°C, 170-0°C, -30-170°C, 10°C/min, N2 atmosphere)

By the comparison of the content of the crystalline phase determined from 1st heating and 2nd heating cycle, it can be seen that PLA samples during second heating cycle exhibit an amorphous character despite of the initially crystalline character determined from 1st heating scan. A thermal history is very important issue that influence the arrangement of amorphous/crystalline phase and consequently influence the physico-mechanical properties of poly(lactic acid).

10 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry


Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 11

**Figure 7.** Structure of PLA\_3 (PLA synthesized by the azeotropic dehydration condensation and

The crystallinity value of PLA was modified during thermoprocessing by the thermal annealing at 110°C for 0, 5, 10, 15, 20, 30, 45, 60 and 120 min, respectively and afterwards cooled down to the room temperature. The samples are designated as PLA\_3\_110\_X, where

The clear effect of the thermal annealing on the PLA melting behavior is shown in Figure 8.

**Figure 8.** DSC thermograms of PLA\_3 annealed at 110°C for 0-120 min (1st heating, 30-160°C, 10°C/min,

The change of the annealing time influenced the value of the specific melting enthalpy

The crystals morphology of PLA samples annealed at 110°C and various times were investigated by using of the light microscope with crossed polarizers (Figure 9). It can be seen that a shape and dimensions of the created crystals depend on the annealing time.

The DSC as well as the light microscopy analyses showed that the thermo-processed films without the annealing processing step have an amorphous character (Figure 9a), and on other side the application of the annealing processing step at 110°C during thermoforming instead of a quick direct cooling step (to the room temperature) promotes the growth of crystals. A kind, a size, a thickness, and a content of arisen crystals depend on the annealing temperature and time. DSC data displayed in Table 5 showed that the value of the specific

(ΣΔH) due to the enabling of a growth of crystals (Table 5).

modified by 2.5 mol% succinic anhydride)

X indicates annealing time.

N2 atmosphere)

**Table 4.** Thermal properties of PLA synthetized through the azetropic dehydration condensation from 80% L-Lactic acid and modified by succinic anhydride

**Figure 6.** DSC thermograms of PLA samples with modified side chain groups and various molecular properties detected during second heating scan (-30-170°C, 10°C/min, N2 atmosphere)

### **3. Effect of thermal treatment on thermal behavior of poly(lactic acid)**

As was already discussed in the previous sub-chapter, PLA is the semi-crystalline polymer with the slow crystallization ability. Mechanical properties as well as gas barrier properties of PLA depend also on its gained crystallinity value. The resulting crystallinity of PLA can be modified by a thermal treatment (annealing) for some time at the crystallization temperature during the thermal processing of a sample. The change of a crystals size and a form during the annealing can be revealed by a X-Ray analysis but the change in the percentage of crystalline phase is detectable also by the DSC analysis. This section describes the progress of the PLA crystalline phase due to the applied annealing treatment. Moreover, the obtained DSC data are supported by a light microscopy study.

The followed data were obtained by the analysis of the thermal compression molded poly(lactic acid) synthetized by the azeotropic dehydration condenstation (PLA\_3) (Figure 7).

**Figure 7.** Structure of PLA\_3 (PLA synthesized by the azeotropic dehydration condensation and modified by 2.5 mol% succinic anhydride)

Hm1 (J/g)

Tm2 (°C)

80% L-Lactic acid and modified by succinic anhydride

Sample

(Figure 7).

Tm1 (°C)

10 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

1st heating cycle 2nd heating cycle

H (J/g)

Tg (°C)

PLA\_0 157 37.8 - - 37.8 56 116 27.3 150 14.3 157 15.4 2.4 PLA\_1 145 18.8 - - 18.8 47 106 27.1 132 9.5 143 18.6 1.0 PLA\_2 143 10.7 152 15.8 26,5 50 107 23.6 140 7.8 151 20.0 4.2 PLA\_3 139 7.4 152 13.5 20,9 50 109 25.9 139 9.9 150 20.1 4.1 **Table 4.** Thermal properties of PLA synthetized through the azetropic dehydration condensation from

**Figure 6.** DSC thermograms of PLA samples with modified side chain groups and various molecular

**3. Effect of thermal treatment on thermal behavior of poly(lactic acid)** 

As was already discussed in the previous sub-chapter, PLA is the semi-crystalline polymer with the slow crystallization ability. Mechanical properties as well as gas barrier properties of PLA depend also on its gained crystallinity value. The resulting crystallinity of PLA can be modified by a thermal treatment (annealing) for some time at the crystallization temperature during the thermal processing of a sample. The change of a crystals size and a form during the annealing can be revealed by a X-Ray analysis but the change in the percentage of crystalline phase is detectable also by the DSC analysis. This section describes the progress of the PLA crystalline phase due to the applied annealing treatment. Moreover,

The followed data were obtained by the analysis of the thermal compression molded poly(lactic acid) synthetized by the azeotropic dehydration condenstation (PLA\_3)

properties detected during second heating scan (-30-170°C, 10°C/min, N2 atmosphere)

the obtained DSC data are supported by a light microscopy study.

Tc (°C) Hc (J/g) Tm1 (°C) Hm1 (J/g)

Tm2 (°C) Hm2 (J/g)

H (J/g)

Hm2 (J/g)

> The crystallinity value of PLA was modified during thermoprocessing by the thermal annealing at 110°C for 0, 5, 10, 15, 20, 30, 45, 60 and 120 min, respectively and afterwards cooled down to the room temperature. The samples are designated as PLA\_3\_110\_X, where X indicates annealing time.

The clear effect of the thermal annealing on the PLA melting behavior is shown in Figure 8.

**Figure 8.** DSC thermograms of PLA\_3 annealed at 110°C for 0-120 min (1st heating, 30-160°C, 10°C/min, N2 atmosphere)

The change of the annealing time influenced the value of the specific melting enthalpy (ΣΔH) due to the enabling of a growth of crystals (Table 5).

The crystals morphology of PLA samples annealed at 110°C and various times were investigated by using of the light microscope with crossed polarizers (Figure 9). It can be seen that a shape and dimensions of the created crystals depend on the annealing time.

The DSC as well as the light microscopy analyses showed that the thermo-processed films without the annealing processing step have an amorphous character (Figure 9a), and on other side the application of the annealing processing step at 110°C during thermoforming instead of a quick direct cooling step (to the room temperature) promotes the growth of crystals. A kind, a size, a thickness, and a content of arisen crystals depend on the annealing temperature and time. DSC data displayed in Table 5 showed that the value of the specific

12 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry


Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 13

annealing time even decreased it. However, light micrographs of *PLA\_3* (see Figure 9 b-i) show clear differences of the character of crystals, arisen from the samples annealed under and above 30 min. The application of the longer annealing time caused the creation of overgrowth crystals. The difference in the character of crystals can be also detected by the change of the height of the melting peak and by their shift to the higher temperatures. The

annealed just for 10 min, however the crystal morphology is markedly different. Furthermore, the change of the crystal morphology was indicated by the increase of the melting temperature (Tm1 and Tm2) about 10 and 3°C, respectively. Also the optical micrograph displayed in Figure 9i showed the difference in the crystal morphology in a comparison to the previous samples annealed at the lower time. As a remark can be highlighted that the crystal morphology has an essential influence on resulting physico-

The intramolecular transesterification with the formation of cyclic oligomers and byproducts like acrylic acid, carbon oxide and acetaldehyde is considered as one of the main mechanisms of the PLA thermal degradation. Above 200°C five reaction pathways have been found: intra-and intermolecular ester exchange, cis-elimination, radical and concerted nonradical reactions, radical reactions and Sn-catalyzed depolymerisation (Kopinke et al., 1996). It has been suggested that CH groups of the main chain and the character of functional end groups affect thermal and hydrolytic sensitivity of PLA (Lee et al., 2001; Ramkumar & Bhattacharya, 1998). In our previous work it was shown that thermal sensitivity of PLA might be improved by the modification of its functional end groups (Gregorova et al., 2011a). This sub-chapter shows that the DSC analysis can be used to

**Figure 10.** DSC curves of low molecular weight PLA synthetized by azeotropic dehydration

cycle from 30 to 350°C at heating rate of 10°C/min, in nitrogen flow.

condensation (PLA\_0) and modified by 2.5 mol.% succinic anhydride (PLA\_3), detected by 1st heating

**4. Thermal stability of biopolymers determined by DSC** 

**4.1. Effect of functional end groups on poly(lactic acid) stability** 

*H* of PLA annealed for 120 min (*PLA\_3\_110\_120*) is comparable to that of

value of *Σ*

mechanical properties of PLA materials.

determine the thermal stability of poly(lactic acid).

**Table 5.** Thermal properties of PLA\_3 films, annealed at 110°C for 0-120 min

**Figure 9.** Polarized optical micrographs (magnification 400) of crystals of polylactic acid modified with succinic anhydride (PLA\_3) grown from the melt and annealed at 110°C for 5-120 min

heat of fusion markedly increased up to 15 min of the annealing time, but the extension of the annealing time up to 30 min increased *H* just slightly and further extension of the annealing time even decreased it. However, light micrographs of *PLA\_3* (see Figure 9 b-i) show clear differences of the character of crystals, arisen from the samples annealed under and above 30 min. The application of the longer annealing time caused the creation of overgrowth crystals. The difference in the character of crystals can be also detected by the change of the height of the melting peak and by their shift to the higher temperatures. The value of *ΣH* of PLA annealed for 120 min (*PLA\_3\_110\_120*) is comparable to that of annealed just for 10 min, however the crystal morphology is markedly different. Furthermore, the change of the crystal morphology was indicated by the increase of the melting temperature (Tm1 and Tm2) about 10 and 3°C, respectively. Also the optical micrograph displayed in Figure 9i showed the difference in the crystal morphology in a comparison to the previous samples annealed at the lower time. As a remark can be highlighted that the crystal morphology has an essential influence on resulting physicomechanical properties of PLA materials.

### **4. Thermal stability of biopolymers determined by DSC**

Applications of Calorimetry in a Wide Context –

Tc1 (°C)

1st heating cycle

Tm1 (°C)

Hc1 (J/g)

Sample

12 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Hm1 (J/g)

**Table 5.** Thermal properties of PLA\_3 films, annealed at 110°C for 0-120 min

Tm1Peak height

Tm2 (°C) Hm2 (J/g)

Tm2Peak height

H (J/g)

(mW)

(mW)

PLA\_3\_110\_0 104 21.8 139 4.6 0.14 151 20.5 0.39 3.3 PLA\_3\_110\_5 - - - - - 152 12.6 1.18 12.6 PLA\_3\_110\_10 - - 143 6.1 0.26 151 15.4 0.67 21.5 PLA\_3\_110\_15 - - 143 20.1 0.51 151 13.5 0.65 33.6 PLA\_3\_110\_20 - - 143 19.9 0.76 151 15.9 1.0 35.8 PLA\_3\_110\_30 - - 144 20.8 1.1 151 15.6 1.4 36.4 PLA\_3\_110\_45 - - 144 14.5 0.87 151 13.0 1.03 27.5 PLA\_3\_110\_60 - - 144 15.2 0.87 151 11.8 0.88 27.0 PLA\_3\_110\_120 - - 149 10.3 0.44 154 5.6 0.44 15.9

**Figure 9.** Polarized optical micrographs (magnification 400) of crystals of polylactic acid modified with succinic anhydride (PLA\_3) grown from the melt and annealed at 110°C for 5-120 min

the annealing time up to 30 min increased

heat of fusion markedly increased up to 15 min of the annealing time, but the extension of

*H* just slightly and further extension of the

#### **4.1. Effect of functional end groups on poly(lactic acid) stability**

The intramolecular transesterification with the formation of cyclic oligomers and byproducts like acrylic acid, carbon oxide and acetaldehyde is considered as one of the main mechanisms of the PLA thermal degradation. Above 200°C five reaction pathways have been found: intra-and intermolecular ester exchange, cis-elimination, radical and concerted nonradical reactions, radical reactions and Sn-catalyzed depolymerisation (Kopinke et al., 1996). It has been suggested that CH groups of the main chain and the character of functional end groups affect thermal and hydrolytic sensitivity of PLA (Lee et al., 2001; Ramkumar & Bhattacharya, 1998). In our previous work it was shown that thermal sensitivity of PLA might be improved by the modification of its functional end groups (Gregorova et al., 2011a). This sub-chapter shows that the DSC analysis can be used to determine the thermal stability of poly(lactic acid).

**Figure 10.** DSC curves of low molecular weight PLA synthetized by azeotropic dehydration condensation (PLA\_0) and modified by 2.5 mol.% succinic anhydride (PLA\_3), detected by 1st heating cycle from 30 to 350°C at heating rate of 10°C/min, in nitrogen flow.

14 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The obtained DSC data, displayed in Figure 10, showed that the modification of low molecular weight PLA with succinic anhydride caused the decrease of its melting temperature and crystallinity. Furthermore, the detected values of the onset degradation temperature, the degradation temperature in peak and the enthalpy of degradation indicate the improvement of thermal stability, caused by the modification of hydroxyl functional end group by succinic anhydride.

Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 15

for polypropylene (Gregorova et al., 2005a). This section shows that DSC is the sensitive

The polypropylene samples, stabilized with Björkman beech lignin (Mw= 2000, PDI= 1.2), used in this example were thermal processed with the injection molding (Gregorova et al., 2005a). Figure 11 shows the change of the onset oxidation temperature (Tonset) recorded for polypropylene stabilized with lignin. Generally, additives should be compatible with polymer matrix to keep physico-mechanical properties on the desired level; therefore it is necessary to know the lowest active concentration of the additive. It can be seen that the studied Björkman beech lignin increased *Tonset* about 15-30°C depending on the used concentration. On the base of the obtained mechanical properties of polypropylene/lignin composites, 2 wt% of Björkman beech lignin was determined as the optimal concentration to stabilize polypropylene. It was shown that the higher concentration of non-modified lignin deteriorated the mechanical

method able to determine the stabilizing effect of lignin in polypropylene.

properties of polypropylene (Gregorova et al., 2005a, Gregorova et al., 2005b).

**Figure 11.** Thermal stability of polypropylene expressed as onset degradation temperature (Tonset) in dependence on lignin concentration, heating scan 30 to 500°C, heating rate of 1, 3, 5, 7, 10 and 15

The incorporation of filler in PLA may change its crystallization behaviour and consequently its thermal properties. Some filler, such as wood flour or wood fibers, promote the transcrystallization and thus modify crystalline morphology of PLA (Mathew et al.; 2005 Pilla et al., 2008; Matthew et al., 2006; Hrabalova et al. 2010). This section describes the ability of hydrothermally pretreated beech flour to support a nucleation of PLA. Moreover, the effect of quick cooling and thermal annealing during thermal processing of PLA films is

°C/min, oxygen flow (Gregorova et al., 2005a).

recorded.

**5. Thermal properties of poly(lactic acid) composites** 

### **4.2. Stabilizing effect of lignin used as filler for natural rubber**

Natural rubber (NR) is highly unsaturated polymer exhibiting poor resistance to oxidation. For the inhibition of the degradation process during thermo-oxidation can be used stabilizers such as phenol and amine derived additives. NR for the production of vulcanized products is mixed with the number of the other compounding ingredients to obtain the desired properties of vulcanizates (e.g sulfur, accelerators, and filler). Lignin is biopolymer that can be used as an active filler for rubber. It was found that some lignins can play dual role in rubber compounds, influencing their mechanical properties as well as their stability [11].

The obtained data were obtained by using of vulcanizates based on natural rubber (NR) and filled with 0, 10, 20 and 30 phr of Björkman beech lignin (Mw= 2000, PDI= 1.2) (Kosikova et al., 2007). Samples are designated as NR\_Lignin\_X, where X presents concentration of lignin in phr (parts per hundred rubber).

Table 6 shows values of degradation temperature determined as the onset and the peak temperature in dependence on the lignin concentration in natural rubber vulcanizates. It can be seen that lignin used as filler exhibit also the stabilizing effect, while the best stabilizing effect was reached in the case of 20 phr presence of Björkman beech lignin.


**Table 6.** DSC data evaluated from 1st heating cycle analysis (30-500°C, 10°C/min, air atmosphere) of vulcanizates based on natural rubber (NR) and NR filled with Björkman beech lignin (Kosikova et al., 2007)

### **4.3. Stabilizing effect of lignin used as additive in polypropylene**

It was already reported that the lignin in the certain circumstances can support the biodegradability of polymer samples (Kosikova et al., 1993a; Kosikova et al., 1993b; Mikulasova&Kosikova, 1999). On the other side lignin with the important functional groups and the low molecular weight with the narrow polydispersity can be used as the stabilizer for polypropylene (Gregorova et al., 2005a). This section shows that DSC is the sensitive method able to determine the stabilizing effect of lignin in polypropylene.

Applications of Calorimetry in a Wide Context –

group by succinic anhydride.

in phr (parts per hundred rubber).

[11].

2007)

14 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**4.2. Stabilizing effect of lignin used as filler for natural rubber** 

The obtained DSC data, displayed in Figure 10, showed that the modification of low molecular weight PLA with succinic anhydride caused the decrease of its melting temperature and crystallinity. Furthermore, the detected values of the onset degradation temperature, the degradation temperature in peak and the enthalpy of degradation indicate the improvement of thermal stability, caused by the modification of hydroxyl functional end

Natural rubber (NR) is highly unsaturated polymer exhibiting poor resistance to oxidation. For the inhibition of the degradation process during thermo-oxidation can be used stabilizers such as phenol and amine derived additives. NR for the production of vulcanized products is mixed with the number of the other compounding ingredients to obtain the desired properties of vulcanizates (e.g sulfur, accelerators, and filler). Lignin is biopolymer that can be used as an active filler for rubber. It was found that some lignins can play dual role in rubber compounds, influencing their mechanical properties as well as their stability

The obtained data were obtained by using of vulcanizates based on natural rubber (NR) and filled with 0, 10, 20 and 30 phr of Björkman beech lignin (Mw= 2000, PDI= 1.2) (Kosikova et al., 2007). Samples are designated as NR\_Lignin\_X, where X presents concentration of lignin

Table 6 shows values of degradation temperature determined as the onset and the peak temperature in dependence on the lignin concentration in natural rubber vulcanizates. It can be seen that lignin used as filler exhibit also the stabilizing effect, while the best stabilizing

(°C)

NR\_Lignin\_0 184 326 886 NR\_Lignin\_10 183 349 833 NR\_Lignin\_20 301 368 363 NR\_Lignin\_30 296 364 318 **Table 6.** DSC data evaluated from 1st heating cycle analysis (30-500°C, 10°C/min, air atmosphere) of vulcanizates based on natural rubber (NR) and NR filled with Björkman beech lignin (Kosikova et al.,

It was already reported that the lignin in the certain circumstances can support the biodegradability of polymer samples (Kosikova et al., 1993a; Kosikova et al., 1993b; Mikulasova&Kosikova, 1999). On the other side lignin with the important functional groups and the low molecular weight with the narrow polydispersity can be used as the stabilizer

Tpeak (°C) H (J/g)

effect was reached in the case of 20 phr presence of Björkman beech lignin.

**4.3. Stabilizing effect of lignin used as additive in polypropylene** 

Sample Tonset

The polypropylene samples, stabilized with Björkman beech lignin (Mw= 2000, PDI= 1.2), used in this example were thermal processed with the injection molding (Gregorova et al., 2005a). Figure 11 shows the change of the onset oxidation temperature (Tonset) recorded for polypropylene stabilized with lignin. Generally, additives should be compatible with polymer matrix to keep physico-mechanical properties on the desired level; therefore it is necessary to know the lowest active concentration of the additive. It can be seen that the studied Björkman beech lignin increased *Tonset* about 15-30°C depending on the used concentration. On the base of the obtained mechanical properties of polypropylene/lignin composites, 2 wt% of Björkman beech lignin was determined as the optimal concentration to stabilize polypropylene. It was shown that the higher concentration of non-modified lignin deteriorated the mechanical properties of polypropylene (Gregorova et al., 2005a, Gregorova et al., 2005b).

**Figure 11.** Thermal stability of polypropylene expressed as onset degradation temperature (Tonset) in dependence on lignin concentration, heating scan 30 to 500°C, heating rate of 1, 3, 5, 7, 10 and 15 °C/min, oxygen flow (Gregorova et al., 2005a).

### **5. Thermal properties of poly(lactic acid) composites**

The incorporation of filler in PLA may change its crystallization behaviour and consequently its thermal properties. Some filler, such as wood flour or wood fibers, promote the transcrystallization and thus modify crystalline morphology of PLA (Mathew et al.; 2005 Pilla et al., 2008; Matthew et al., 2006; Hrabalova et al. 2010). This section describes the ability of hydrothermally pretreated beech flour to support a nucleation of PLA. Moreover, the effect of quick cooling and thermal annealing during thermal processing of PLA films is recorded.

16 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The sample used in this section were thermoplastic processed compounds of commercial poly(lactic acid) (PLA 7000D, NatureWorks LLC, USA) plasticized with 10 vol% of polyethylene glycol 1500 and filled with 30 wt% of hydrothermally pretreated beech flour (Gregorova et al., 2011b). Composite films were prepared by thermal molding in press at 160°C, 10 MPa for 5 min and by modification of cooling process were prepared two morphologies: amorphous (quick cooling) and semi-crystalline (thermal annealing at 100°C for 45 min). The samples are designated as pPLA\_X\_100\_Y, where X indicates filler (0-no filler, WF- hydrothermally pretreated beech flour) and Y shows annealing time.

The thermal behavior of quenched and annealed PLA composites, investigated by differential scanning calorimetry (heating cycle from 20 to 180°C, 10°C/min, 60 ml/L nitrogen flow) is summarized in Table 11 and shows that both filler incorporation of wood flour and thermal annealing influenced melting behavior and crystallinity of PLA composites. Specific melting enthalpy as an indicator of crystallinity degree of PLA in the composite was calculated as follows:

$$
\Sigma \Delta H = \frac{(\Delta H\_{m1} + \Delta H\_{m2}) - \Delta H\_c}{\nu} \tag{5}
$$

Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 17

2011b). The presence of filler marginally decreased specific enthalpy values of PLA. The presence of multiple melting peaks in thermograms of annealed samples can be explained by applied annealing that induce other crystal population, namely ´ (initially created with grain like morphology) and (during annealing created with spherulitic morphology) crystals (Zhang et al., 2008; Pan et al., 2008). Melting temperature for unannealed neat or filled PLA samples were recorded between 134-140°C for the first melting peak and 150- 151°C for the second melting peak. The growth of crystals during annealing increased the values of temperature of both melting peaks depending on the mixture composition. The change in the value of the ratio of the first and the second melting peaks indicates the modification of size of the present crystals. The *Tg* value after an annealing treatment can be taken as an indicator for the occurred changes in an amorphous/crystal ratio but also in PLA/filler interaction level. The increase of an interfacial compatibility between wood filler and poly(lactic acid) can be detected by an shift of a glass transition to the higher

Differential scanning calorimetry is the method to characterize thermal behavior of polymeric materials on the base of the differences obtained in the heat flow between a sample and a reference under various temperature programs. In the addition to the quality and compositional analyses of polymers, DSC is applicable to the investigation of the thermal changes occurring in polymer systems during chemical reactions (e.g. polymerisation), oxidative degradation, vaporization, sublimation and desorptionThe selection of a proper temperature program is an important issue for the proper DSC analysis (e.g. a position and a shape of melting peak depend inherently on the nature of polymer and on the used heating scan rate). Thermal properties of biopolymers depend on many factors such as their natural origin, purity, composition, processing, thermal treatment, mechanical stressing, and aging. In this chapter, non-isothermal DSC was introduced as an method to investigate thermal properties of biopolymers, namely amorphous lignin and semi-crystalline poly(lactic acid). It can be concluded that DSC is one of the available methods to determine thermal properties of lignin with various molecular weight properties and composition.. Moreover, DSC can serve as a method to determine stabilizing effect of lignin used as an additive in polymer samples. Furthermore, DSC can be used as the quick method to measure melting behavior and the crystallinity of poly(lactic acid). The thermal history during polymer processing as well as the incorporation of some filler (e.g. wood flour) or additives can modify the crystallinity of PLA. The percentage of the crystallinity is one of the most important characteristics that influence its physico-mechanical behavior (stiffness, toughness, brittleness, barrier resistance, thermal stability and optical clarity). DSC is the valuable method for the investigation of thermal properties of biopolymers. However, it is necessary to use also the other additional physical and chemical testing methods to obtain complex data

temperature (Gregorova & Wimmer, 2012).

describing biopolymers, such as lignin and poly(lactic acid).

**6. Conclusions** 

where Hm1 and Hm2 are enthalpy values of the first and second melting peak, Hc is the enthalpy of the cold crystallization and is volume fraction of PLA in the composite.


**Table 7.** DSC thermal data of non-annealed and annealed PLA composites determined (Gregorova et al.; 2011b)

Samples that were after melting quickly cooled down to room temperature (quenched) exhibit cold crystallization and the double melting behavior that may be attributed to the melting of the original crystals and those of formed through the cold crystallization from the glassy state (Ling & Spruiell, 2006). The known slow crystallization ability of PLA and quick cooling process caused that quenched samples remained mostly amorphous that was proved by low value of specific enthalpy *H*. Thermograms of annealed samples displayed a marked double melting peak showing high degree of crystallinity (Gregorova et al.; 2011b). The presence of filler marginally decreased specific enthalpy values of PLA. The presence of multiple melting peaks in thermograms of annealed samples can be explained by applied annealing that induce other crystal population, namely ´ (initially created with grain like morphology) and (during annealing created with spherulitic morphology) crystals (Zhang et al., 2008; Pan et al., 2008). Melting temperature for unannealed neat or filled PLA samples were recorded between 134-140°C for the first melting peak and 150- 151°C for the second melting peak. The growth of crystals during annealing increased the values of temperature of both melting peaks depending on the mixture composition. The change in the value of the ratio of the first and the second melting peaks indicates the modification of size of the present crystals. The *Tg* value after an annealing treatment can be taken as an indicator for the occurred changes in an amorphous/crystal ratio but also in PLA/filler interaction level. The increase of an interfacial compatibility between wood filler and poly(lactic acid) can be detected by an shift of a glass transition to the higher temperature (Gregorova & Wimmer, 2012).

### **6. Conclusions**

Applications of Calorimetry in a Wide Context –

composite was calculated as follows:

Sample Hc

pPLA\_0\_100\_0 pPLA\_0\_100\_45 pPLA\_WF\_100\_0 pPLA\_WF\_100\_45

al.; 2011b)

(J/g)

18.5 - 14.2 -

proved by low value of specific enthalpy

Tc (°)

82 - 95 -

Hm1 (J/g)

0.4 11.8 1.7 6.1

Tm1 (°)

1 2 ( ) *HH H mm c <sup>H</sup>*

time.

16 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The sample used in this section were thermoplastic processed compounds of commercial poly(lactic acid) (PLA 7000D, NatureWorks LLC, USA) plasticized with 10 vol% of polyethylene glycol 1500 and filled with 30 wt% of hydrothermally pretreated beech flour (Gregorova et al., 2011b). Composite films were prepared by thermal molding in press at 160°C, 10 MPa for 5 min and by modification of cooling process were prepared two morphologies: amorphous (quick cooling) and semi-crystalline (thermal annealing at 100°C for 45 min). The samples are designated as pPLA\_X\_100\_Y, where X indicates filler (0-no filler, WF- hydrothermally pretreated beech flour) and Y shows annealing

The thermal behavior of quenched and annealed PLA composites, investigated by differential scanning calorimetry (heating cycle from 20 to 180°C, 10°C/min, 60 ml/L nitrogen flow) is summarized in Table 11 and shows that both filler incorporation of wood flour and thermal annealing influenced melting behavior and crystallinity of PLA composites. Specific melting enthalpy as an indicator of crystallinity degree of PLA in the

(5)

H (J/g) Hm1/ Hm2 Tg

0.02 0.83 0.13 0.73

*H*. Thermograms of annealed samples displayed

(°C)

where Hm1 and Hm2 are enthalpy values of the first and second melting peak, Hc is the

1st heating cycle 2nd heating cycle

Tm2 (°)

5.6 26.0 0.4 14.4

enthalpy of the cold crystallization and is volume fraction of PLA in the composite.

Hm2 (J/g)

23.7 14.2 12.9 8.4

**Table 7.** DSC thermal data of non-annealed and annealed PLA composites determined (Gregorova et

Samples that were after melting quickly cooled down to room temperature (quenched) exhibit cold crystallization and the double melting behavior that may be attributed to the melting of the original crystals and those of formed through the cold crystallization from the glassy state (Ling & Spruiell, 2006). The known slow crystallization ability of PLA and quick cooling process caused that quenched samples remained mostly amorphous that was

a marked double melting peak showing high degree of crystallinity (Gregorova et al.;

Differential scanning calorimetry is the method to characterize thermal behavior of polymeric materials on the base of the differences obtained in the heat flow between a sample and a reference under various temperature programs. In the addition to the quality and compositional analyses of polymers, DSC is applicable to the investigation of the thermal changes occurring in polymer systems during chemical reactions (e.g. polymerisation), oxidative degradation, vaporization, sublimation and desorptionThe selection of a proper temperature program is an important issue for the proper DSC analysis (e.g. a position and a shape of melting peak depend inherently on the nature of polymer and on the used heating scan rate). Thermal properties of biopolymers depend on many factors such as their natural origin, purity, composition, processing, thermal treatment, mechanical stressing, and aging. In this chapter, non-isothermal DSC was introduced as an method to investigate thermal properties of biopolymers, namely amorphous lignin and semi-crystalline poly(lactic acid). It can be concluded that DSC is one of the available methods to determine thermal properties of lignin with various molecular weight properties and composition.. Moreover, DSC can serve as a method to determine stabilizing effect of lignin used as an additive in polymer samples. Furthermore, DSC can be used as the quick method to measure melting behavior and the crystallinity of poly(lactic acid). The thermal history during polymer processing as well as the incorporation of some filler (e.g. wood flour) or additives can modify the crystallinity of PLA. The percentage of the crystallinity is one of the most important characteristics that influence its physico-mechanical behavior (stiffness, toughness, brittleness, barrier resistance, thermal stability and optical clarity). DSC is the valuable method for the investigation of thermal properties of biopolymers. However, it is necessary to use also the other additional physical and chemical testing methods to obtain complex data describing biopolymers, such as lignin and poly(lactic acid).

18 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

### **Author details**

#### Adriana Gregorova

*Graz University of Technology, Institute for Chemistry and Technology of Materials, Austria* 

### **7. References**

Bower, B.I. (2002). *An Introduction to Polymer Physics*. Cambridge University Press, New York

Application of Differential Scanning Calorimetry to the Characterization of Biopolymers 19

Kosikova, B.; Kacurakova, M.& Demianova V. (1993a). Photooxidation of the composite lignin/polypropylene films. *Chemical Papers*, Vol.47, pp. 132-136, ISSN 0366-

Kosikova, B.; Demianova, V.& Kacurakova, M. (1993b). Sulphur-free lignins as composites of polypropylene films. *Journal of Applied Polymer Science*, Vol. 47, No. 6, pp. 1065-1073,

Kosikova, B.; Gregorova, A.; Osvald, A.& Krajcovicova, J. (2007). Role of Lignin Filler in Stabilization of Natural Rubber-Based Composites. *Journal of Applied Polymer Science*,

Lee, S-H.; Kim, S.H.; Han, Y-K.& Kim Y.H. (2001). Synthesis and degradation of end-groupfunctionalized polylactide. *Journal of Polymer Science Part A: Polymer Chemistry*, Vol. 39,

Ling, X.& Spruiell, J.E. (2006). Analysis of the complex thermal behaviour of poly(L-lactic acid) film. I. Samples crystallized from the glassy state. *Journal of Polymer Science Part B:* 

Mathew, A.P.; Oksman, K.& Sain, M. (2005). Mechanical properties of biodegradable composites from poly lactic acid (PLA) and microcrystalline cellulose (MCC). *Journal of* 

Mathew, A.P.; Oksman, K.& Sain, M. (2006). The effect of morphology and chemical characteristics of cellulose reinforcements on the crystallinity of polylactic acid.

*Journal of Applied Polymer Science*, Vol. 101, No. 1, pp. 300-310, ISSN 1097-4628 Mikulasova, M.& Kosikova, B. (1999). Biodegradability of lignin-polypropylene composite

Pan, P.; Zhu, B.; Kai, W.; Dong, T.& Inoue, Y. (2008). Polymorphic Transition in Disordered Poly(L-lactide) Crystals Induced by Annealing at Elevated Temperatures.

Pilla, S.; Gong, S.; O´Neil, E.; Rowell, M.& Krzysik, A.M. (2008). Polylactide-pine wood flour composites. *Polymer Engineering Science*, Vol.48, No. 3, pp. 578-587, ISSN 1548-

Ramkumar, D.H.S.& Bhattacharya, M. (1998). Steady shear and dynamic properties of biodegradable polyesters. *Polymer Engineering Science*, Vol. 38, No. 9, pp. 1426-1435,

Yasuniwa, M.; Tsubakihara, S.; Sugimoto, Y.& Nakafuku, C. (2004). Thermal analysis of the double-melting behavior of poly(L-Lactic acid). *Journal of Polymer Science Part B: Polymer* 

Yasuniwa, M.; Tsubakihara, S.; Iura, K.; Ono, Y.; Dan, Y.& Takashashi K. (2006). Crystallization behavior of Poly(L-lactic acid). *Polymer*, Vol. 47, No. 21, pp. 7554-7563,

*Polymer Physics*, Vol. 44, No. 22, pp. 3200-3214, ISSN 1099-0488

films. *Folia Microbiologica*, Vol. 44, pp. 669-672, ISSN 0015-5632

*Macromolecules*, Vol.41, No. 12, pp. 4296-4304, ISSN 1520-5835

*Physics*, Vol.42, No. 1, pp. 25-32, ISSN 1099-0488

*Applied Polymer Science*, Vol.97, No. 5, pp. 2014-2015, ISSN 1097-4628

6352

2634

ISSN 1548-2634

ISSN 0032-3861

ISSN 1097-4628

Vol. 103, No. 2, pp. 1226-1231, ISSN 1097-4628

No. 7, pp. 973-985, ISSN 1099-0518


Kosikova, B.; Kacurakova, M.& Demianova V. (1993a). Photooxidation of the composite lignin/polypropylene films. *Chemical Papers*, Vol.47, pp. 132-136, ISSN 0366- 6352

Applications of Calorimetry in a Wide Context –

*Macromol. Symp.*, Vol.234, pp. 176-183

No. 3, pp. 553-558, ISSN 0141-3910

Vol. 19, No.2, pp. 372-381, ISSN 1566-2543

pp. 11-12, Springer-Verlag Berlin Heidelberg

*Stabilility*, Vol. 53, No. 3, pp. 329-342, ISSN 0141-3910

pp. 1534-1540, ISSN 1097-4628

**Author details** 

Adriana Gregorova

**7. References** 

York

ISSN 1336-4561

September 2011

62100-348-9

18 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*Graz University of Technology, Institute for Chemistry and Technology of Materials, Austria* 

Bower, B.I. (2002). *An Introduction to Polymer Physics*. Cambridge University Press, New

Di Lorenzo, M.L. (2006). The Crystallization and Melting Processes of Poly(L-lactic acid).

Gregorova, A.; Cibulkova, Z.; Kosikova, B.& Simon P. (2005a). Stabilization effect of lignin in polypropylene and recycled polypropylene. *Polymer Degradation and Stability*, Vol. 89,

Gregorova, A.; Kosikova, B.& Osvald, A. (2005b). The study of lignin influence on properties of polypropylene composites. *Wood Research*, Vol. 50, No. 2, pp. 41-48,

Gregorova A.; Schalli M.& Stelzer F. (2011a). Functionalization of polylactic acid through azeotropic dehydrative condensation. *19th Annual Meeting of the BioEnvironmental Polymer Society BEPS, Book of Abstracts, PO-4*, ISBN 978-3-9502992-3-6, Vienna Austria,

Gregorova, A.; Sedlarik, V.; Pastorek, M.; Jachandra, H.& Stelzer, F. (2011b). Effect of compatibilizing agent on the properties of highly crystalline composites based on poly(lactic acid) and wood flour and/or mica. *Journal of Polymers and the Environment*,

Gregorova, A& Wimmer R. (2012). Filler-Matrix Compatibility of Poly(lactic acid) Based Composites. In: Piemonte V., Editor. *Polylactic Acid: Synthesis, Properties and Applications*, Piemonte, V., pp. 97-119, Nova Science Publishers NY, ISBN 978-1-

Hatakeyama, H. & Hatakeyama T. (2010). Lignin Structure, Properties and Applications. In: *Biopolymers Lignin, Proteins, Bioactive Nanocomposites*, Abe A., Dusek K., Kobayashi S.,

Hrabalova, M.; Gregorova, A.; Wimmer, R.; Sedlarik, V.; Machovsky, M.& Mundigler N. (2010). Effect of Wood Flour Loading and Thermal Annealing on Viscoelastic Properties of Poly(lactic acid) Composite Films. *Journal of Applied Polymer Science*, Vol. 118, No. 3,

Kopinke, F.D.; Remmler, M.; Mackenzie, K.; Möder, M.& Wachsen, O. (1996). Thermal decomposition of biodegradable polyesters-II. Poly(lactic acid). *Polymer Degradation and* 


20 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Yasuniwa, M.; Iura, K.& Dan Y. (2007). Melting behavior of poly(L-lactic acid): Effects of crystallization temperature and time. *Polymer*, Vol. 48, No. 18, pp. 5398-5407, ISSN 0032- 3861

**Chapter 2** 

© 2013 Alleg et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Thermal Stability of the Nanostructured Powder** 

Nanocrystalline materials present an attractive potential for technological applications and provide an excellent opportunity to study the nature of solid interfaces and to extend knowledge of the structure-property relationship in solid materials down to the nanometer regime. Nanocrystalline materials can be produced by various methods such as mechanical alloying, inert gas condensation, sol–gel process, electrodeposition, chemical vapour deposition, heat treatment of amorphous ribbons, high speed deformation, etc. Mechanical alloying is a non-equilibrium process resulting in solid state alloying beyond the equilibrium solubility limit. During the milling process, mixtures of elemental or prealloyed powders are subjected to heavy plastic deformation through high-energy collision from the balls. The processes of fracturing and cold welding, as well as their kinetics and predominance at any stage, depend mostly on the deformation characteristics of the starting powders. As a result of the induced heavy plastic deformation into the powder particles during the milling process, nanostructured materials are produced by the structural decomposition of coarser-grained structure. This leads to a continuous refinement of the

Solid-state processing is a way to obtain alloys in states far-from-equilibrium. The microstructural manifestations of the departures from equilibrium achieved by mechanical alloying can be classified as follows: (i) **augmented defect concentrations** such as vacancies, interstitials, dislocations, stacking faults, twin boundaries, grain boundaries as well as an increased level of chemical disorder in ordered solid solutions and compounds; (ii) **microstructural refinement** which involves finer scale distributions of different phases and of solutes; (iii) **extended solid solubility**; a stable crystalline phase may be found with solute levels beyond the solubility limit at ambient temperature, or beyond the equilibrium limit at any temperature; and (iv) **metastable phases** which may form during processing like crystalline, quasicrystalline and intermetallic compounds. Chemical reactions can

and reproduction in any medium, provided the original work is properly cited.

**Mixtures Prepared by Mechanical Alloying** 

Safia Alleg, Saida Souilah and Joan Joseph Suñol

internal structure of the powder particles to nanometer scales.

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54151

**1. Introduction** 

Zhang, J.; Tashiro, K.; Tsuji, H.& Domb, A.J. (2008). Disorder-to-Order Phase Transition and Multiple Melting Behavior of Poly(L-lactide) Investigated by Simultaneous Measurements of WAXD and DSC. *Macromolecules*, Vol.41, No. 4, pp. 1352-1357, ISSN 1520-5835

## **Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying**

Safia Alleg, Saida Souilah and Joan Joseph Suñol

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54151

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

3861

1520-5835

20 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Yasuniwa, M.; Iura, K.& Dan Y. (2007). Melting behavior of poly(L-lactic acid): Effects of crystallization temperature and time. *Polymer*, Vol. 48, No. 18, pp. 5398-5407, ISSN 0032-

Zhang, J.; Tashiro, K.; Tsuji, H.& Domb, A.J. (2008). Disorder-to-Order Phase Transition and Multiple Melting Behavior of Poly(L-lactide) Investigated by Simultaneous Measurements of WAXD and DSC. *Macromolecules*, Vol.41, No. 4, pp. 1352-1357, ISSN

> Nanocrystalline materials present an attractive potential for technological applications and provide an excellent opportunity to study the nature of solid interfaces and to extend knowledge of the structure-property relationship in solid materials down to the nanometer regime. Nanocrystalline materials can be produced by various methods such as mechanical alloying, inert gas condensation, sol–gel process, electrodeposition, chemical vapour deposition, heat treatment of amorphous ribbons, high speed deformation, etc. Mechanical alloying is a non-equilibrium process resulting in solid state alloying beyond the equilibrium solubility limit. During the milling process, mixtures of elemental or prealloyed powders are subjected to heavy plastic deformation through high-energy collision from the balls. The processes of fracturing and cold welding, as well as their kinetics and predominance at any stage, depend mostly on the deformation characteristics of the starting powders. As a result of the induced heavy plastic deformation into the powder particles during the milling process, nanostructured materials are produced by the structural decomposition of coarser-grained structure. This leads to a continuous refinement of the internal structure of the powder particles to nanometer scales.

> Solid-state processing is a way to obtain alloys in states far-from-equilibrium. The microstructural manifestations of the departures from equilibrium achieved by mechanical alloying can be classified as follows: (i) **augmented defect concentrations** such as vacancies, interstitials, dislocations, stacking faults, twin boundaries, grain boundaries as well as an increased level of chemical disorder in ordered solid solutions and compounds; (ii) **microstructural refinement** which involves finer scale distributions of different phases and of solutes; (iii) **extended solid solubility**; a stable crystalline phase may be found with solute levels beyond the solubility limit at ambient temperature, or beyond the equilibrium limit at any temperature; and (iv) **metastable phases** which may form during processing like crystalline, quasicrystalline and intermetallic compounds. Chemical reactions can

© 2013 Alleg et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

22 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

proceed towards equilibrium in stages, and the intermediate stages can yield a metastable phase. In the solid state amorphization reaction, an amorphous alloy can be produced by the reaction of two solid metallic elements. Severe mechanical deformation can lead to metastable states. The deformation forces the production of disturbed configurations or brings different phases into intimate contact promoting solid-state reactions.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 23

*G H TS* – (1)

states as for stable states. However, only the thermodynamically stable state is in global equilibrium; a metastable state has higher Gibbs energy than the true equilibrium state.

Thermodynamically, a system will be in stable equilibrium, under the given conditions of

Where H is enthalpy, T absolute temperature and S entropy. According to equation (1), a system can be most stable either by increasing the entropy or decreasing the enthalpy or both. At low temperatures, solids are the most stable phases since they have the strongest atomic bonding (the lowest H), while at high temperatures the -TS term dominate. Therefore, phases with more freedom of atomic movement, such as liquids and gases are most stable. Hence, in the solid-state transformations, a close packed structure is more stable at low temperatures, while a less close packed structure is most stable at higher temperatures. A metastable state is one in internal equilibrium, that is, within the range of configurations to which there is access by continuous change, the system has the lowest possible free energy. However, if there were large fluctuations (the nucleation of a more stable phase), transformation to the new phase would occur if the change in free energy, ΔG, is negative. A phase is non-equilibrium or metastable if it's Gibbs free energy is higher than in the equilibrium state for the given composition. If the Gibbs free energy of this phase is lower than that of other competing phases (or mixtures thereof), then it can exist in a metastable equilibrium. Consequently, non-equilibrium phases can be synthesized and retained at room temperature and pressure when the free energy of the stable phases is raised to a higher level than under equilibrium conditions, but is maintained at a value below those of other competing phases. Also, if the kinetics during synthesis is not fast enough to allow the formation of equilibrium phase(s), then metastable phases could form.

During the mechanical alloying process, continuous fracturing, cold welding and rewelding of the powder particles lead to the reduction of grain size down to the nanometer scale, and to the increase of the atomic level strain. In addition, the material is usually under far-fromequilibrium conditions containing metastable crystalline, quasi-crystalline or amorphous phases. All of these effects, either alone or in combination, make the material highly metastable. Therefore, the transformation behaviour of these powders to the equilibrium state by thermal treatments is of both scientic and technological importance. Scientically, it is instructive to know whether transformations in ball milled materials take place *via* the same transformation paths and mechanisms that occur in stable equilibrium phases or not. Technologically, it will be useful to know the maximal use temperature of the ball milled material without any transformation occurring and thus, losing the special attributes of this powder product. One of the most useful techniques for studying transformation behaviour of metastable phases is differential scanning calorimetry (DSC) or differential thermal analysis (DTA). Hence, a small quantity of the powder milled for a given time is heated at a

temperature and pressure, if it is at the lowest value of the Gibbs free energy:

**3. Transformation mechanism** 

The alloying process can be carried out using different apparatus such as planetary mills, attrition mills, vibratory mills, shaker mills, etc. [1]. A broad range of alloys, solid solutions, intermetallics and composites have been prepared in the nanocrystalline, quasicrystalline or amorphous state [2-10]. A significant increase in solubility limit has been reported in many mechanically alloyed systems [11, 12]. Several studies of the alloy formation process during mechanical alloying have led to conflicting conclusions like the interdiffusion of elements, the interactions on interface boundaries and/or the diffusion of solute atoms in the host matrix. Indeed, the alloying process is complex and hence, involves optimization of several parameters to achieve the desired product such as type mill, raw material, milling intensity or milling speed, milling container, milling atmosphere, milling time, temperature of milling, ball-to-powder weight ratio, process control agent, etc. The formation of stable and/or metastable crystalline phases usually competes with the formation of the amorphous phase. For alloys with a negative heat of mixing, the phase formation has been explained by an interdiffusion reaction of the components occurring during the milling process [13]. Even though the number of phases reported to form in different alloy systems is unusually large [14], and property evaluations have been done in only some cases and applications have been explored, the number of investigations devoted to an understanding of the mechanism through which the alloy phase's form is very limited. This chapter summarizes the information available in this area. The obtained disordered structures by mechanical alloying are metastable and therefore, they will experience an ordering transition during heating resulting in exothermic and/or endothermic reactions. The thermal properties of materials are strongly related to the size of nanocrystals essentially when the radius of nanocrystals is smaller than 10 nm. Hence, an important task of thermal analyses is to find the size-dependent function of the thermodynamic amounts of nanocrystalline materials.

### **2. Thermodynamic stability**

The state of a physical system evolves irreversibly towards a time-independent state in which no further macroscopic physical or chemical changes can be seen. This is the state of thermodynamic equilibrium characterized, for example, by a uniform temperature throughout the system but also by other futures. A non-equilibrium state can be defined as a state where irreversible processes drive the system towards the equilibrium state at different rates ranging from extremely fast to extremely slow. In this latter case, the isolated system may appear to have reached equilibrium. Such a system, which fulfils the characteristics of an equilibrium system but is not the true equilibrium state, is called a metastable state. Both stable and metastable states are in internal equilibrium since they can explore their complete phase space, and the thermodynamic properties are equally well defined for metastable states as for stable states. However, only the thermodynamically stable state is in global equilibrium; a metastable state has higher Gibbs energy than the true equilibrium state.

Thermodynamically, a system will be in stable equilibrium, under the given conditions of temperature and pressure, if it is at the lowest value of the Gibbs free energy:

$$
\mathbf{G} = \mathbf{H} - \mathbf{T} \mathbf{S} \tag{1}
$$

Where H is enthalpy, T absolute temperature and S entropy. According to equation (1), a system can be most stable either by increasing the entropy or decreasing the enthalpy or both. At low temperatures, solids are the most stable phases since they have the strongest atomic bonding (the lowest H), while at high temperatures the -TS term dominate. Therefore, phases with more freedom of atomic movement, such as liquids and gases are most stable. Hence, in the solid-state transformations, a close packed structure is more stable at low temperatures, while a less close packed structure is most stable at higher temperatures. A metastable state is one in internal equilibrium, that is, within the range of configurations to which there is access by continuous change, the system has the lowest possible free energy. However, if there were large fluctuations (the nucleation of a more stable phase), transformation to the new phase would occur if the change in free energy, ΔG, is negative. A phase is non-equilibrium or metastable if it's Gibbs free energy is higher than in the equilibrium state for the given composition. If the Gibbs free energy of this phase is lower than that of other competing phases (or mixtures thereof), then it can exist in a metastable equilibrium. Consequently, non-equilibrium phases can be synthesized and retained at room temperature and pressure when the free energy of the stable phases is raised to a higher level than under equilibrium conditions, but is maintained at a value below those of other competing phases. Also, if the kinetics during synthesis is not fast enough to allow the formation of equilibrium phase(s), then metastable phases could form.

#### **3. Transformation mechanism**

Applications of Calorimetry in a Wide Context –

22 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

brings different phases into intimate contact promoting solid-state reactions.

function of the thermodynamic amounts of nanocrystalline materials.

The state of a physical system evolves irreversibly towards a time-independent state in which no further macroscopic physical or chemical changes can be seen. This is the state of thermodynamic equilibrium characterized, for example, by a uniform temperature throughout the system but also by other futures. A non-equilibrium state can be defined as a state where irreversible processes drive the system towards the equilibrium state at different rates ranging from extremely fast to extremely slow. In this latter case, the isolated system may appear to have reached equilibrium. Such a system, which fulfils the characteristics of an equilibrium system but is not the true equilibrium state, is called a metastable state. Both stable and metastable states are in internal equilibrium since they can explore their complete phase space, and the thermodynamic properties are equally well defined for metastable

**2. Thermodynamic stability** 

proceed towards equilibrium in stages, and the intermediate stages can yield a metastable phase. In the solid state amorphization reaction, an amorphous alloy can be produced by the reaction of two solid metallic elements. Severe mechanical deformation can lead to metastable states. The deformation forces the production of disturbed configurations or

The alloying process can be carried out using different apparatus such as planetary mills, attrition mills, vibratory mills, shaker mills, etc. [1]. A broad range of alloys, solid solutions, intermetallics and composites have been prepared in the nanocrystalline, quasicrystalline or amorphous state [2-10]. A significant increase in solubility limit has been reported in many mechanically alloyed systems [11, 12]. Several studies of the alloy formation process during mechanical alloying have led to conflicting conclusions like the interdiffusion of elements, the interactions on interface boundaries and/or the diffusion of solute atoms in the host matrix. Indeed, the alloying process is complex and hence, involves optimization of several parameters to achieve the desired product such as type mill, raw material, milling intensity or milling speed, milling container, milling atmosphere, milling time, temperature of milling, ball-to-powder weight ratio, process control agent, etc. The formation of stable and/or metastable crystalline phases usually competes with the formation of the amorphous phase. For alloys with a negative heat of mixing, the phase formation has been explained by an interdiffusion reaction of the components occurring during the milling process [13]. Even though the number of phases reported to form in different alloy systems is unusually large [14], and property evaluations have been done in only some cases and applications have been explored, the number of investigations devoted to an understanding of the mechanism through which the alloy phase's form is very limited. This chapter summarizes the information available in this area. The obtained disordered structures by mechanical alloying are metastable and therefore, they will experience an ordering transition during heating resulting in exothermic and/or endothermic reactions. The thermal properties of materials are strongly related to the size of nanocrystals essentially when the radius of nanocrystals is smaller than 10 nm. Hence, an important task of thermal analyses is to find the size-dependent

During the mechanical alloying process, continuous fracturing, cold welding and rewelding of the powder particles lead to the reduction of grain size down to the nanometer scale, and to the increase of the atomic level strain. In addition, the material is usually under far-fromequilibrium conditions containing metastable crystalline, quasi-crystalline or amorphous phases. All of these effects, either alone or in combination, make the material highly metastable. Therefore, the transformation behaviour of these powders to the equilibrium state by thermal treatments is of both scientic and technological importance. Scientically, it is instructive to know whether transformations in ball milled materials take place *via* the same transformation paths and mechanisms that occur in stable equilibrium phases or not. Technologically, it will be useful to know the maximal use temperature of the ball milled material without any transformation occurring and thus, losing the special attributes of this powder product. One of the most useful techniques for studying transformation behaviour of metastable phases is differential scanning calorimetry (DSC) or differential thermal analysis (DTA). Hence, a small quantity of the powder milled for a given time is heated at a

#### 24 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

constant rate to high temperatures under vacuum or in an inert atmosphere to avoid oxidation. Depending on the phase transformations, DSC/DTA scans exhibit endothermic and/or exothermic peaks related to absorption or evolution of heat, respectively, as shown in Fig. 1.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 25

��� (2)

� �(�)��(�) (3)

��(�) � �(�−�)�− ln(�−�)�(���)⁄� (4)

�(�) � �����(� �� ⁄ ) (5)

�. Further informations about the

have not been many detailed crystallization studies of amorphous alloys synthesized by the

The crystallization temperature corresponds to the maximum of the exothermic peak,�� and it increases with increasing heating rate. A relation between heating rate and position of the transformation peak �� first described by Kissinger [17], has been extensively used to

Where A is a constant and R is the universal gas constant. The activation energy �� can be

transformation temperatures, the number of stages in which the transformation is occurring, details about the product(s) of each individual transformation (crystal structure, microstructure and chemical composition), and the activation energy (and also the atomic mechanism) can be obtained with the combination of DSC/DTA and X-rays diffraction/transmission electron microscopy techniques. The Kissinger method may not be useful in all studies of decomposition. For example, it may not be applicable for metallic glasses which may decompose by nucleation/growth, or a combination of both processes, where the decomposition is seldom described by rst-order reaction kinetics [18, 19]. Solid state reactions sometimes exhibit first-order kinetics, this is one form of the Avrami-Erofeev equation (n=1). Such kinetic behaviour may be observed in decompositions of fine powders if particle nucleation occurs on a random basis and growth does not advance beyond the individual crystallite nucleated. The physical interpretation of �� depends on the details of nucleation and growth mechanisms, and in some cases equation (2) is not valid. For each crystallization peak, the calorimetric results can be explained using the Johnson-Mehl-

�� against � �

��

��

mechanical alloying process [16].

calculated from the slope �

With:

**3.1. Non-isothermal transformation** 

determine the apparent activation energy for crystallization ��:

���

 ln � �� � � �� �� ���

� � of the plot � �

Avrami-Erofe've kinetics equation [20] for the transformed fraction:

growth and segregation at dislocations (n=2/3)[21].

�� ��

��(�) gives the transformation rate at time t and temperature T in terms of the rate constant:

�� is the pre-exponential factor; � is the effective activation energy and � is the kinetic exponent. According to the Avrami exponent value, the reaction may be three-dimensional, interface-controlled growth with constant nucleation rate (n=4); three-dimensional, interface-controlled growth with zero nucleation rate (n=3) or diffusion-controlled with

**Figure 1.** A schematic DSC curve depicting the different stages during crystallization of an amorphous phase where Tg is the glass transition temperature; Tm the melting temperature, Tx1 and Tx2 are the onset crystallization temperatures [15].

The values of the peak onset temperature and peak areas depend on the position of the baseline. Therefore, the accurate baseline can be obtained by heating the sample to the desired temperature, then cooled it back to the ambient temperature and then reheated it to higher temperatures. The second DSC scan could be used either as the baseline or subtracted from the rst scan to obtain the accurate peak positions and areas. There are two types of transformations: reversible and irreversible. For the former, the product phase will revert back to the parent phase. For example, transformation from one equilibrium phase to another on heating gives rise to an endothermic peak during melting and exothermic peak during cooling. However, during irreversible transformation of metastable phases such as amorphous phases, a peak of the opposite sign is not observed. In fact, there will be no peak at all. Furthermore, because metastable phases are always more energetic than the corresponding equilibrium phases, they often exhibit exothermic peaks in the DSC/DTA curves. If an amorphous alloy powder is heated to higher temperatures, one expects to observe a broad exothermic reaction at relatively low temperatures related to structural relaxation of the amorphous phase, a glass transition temperature as well as one or more exothermic peaks corresponding to crystallization event at higher temperatures. Structural changes that occur during crystallization can be investigated by X-rays diffraction or Mössbauer spectrometry by quenching the sample from a temperature just above the DSC/DTA peak temperature. Transmission electron microscopy investigations can also be conducted to uncover the microstructural and crystal structure changes on a ner scale. In addition, compositional changes can be detected. It may be pointed out, however, that there have not been many detailed crystallization studies of amorphous alloys synthesized by the mechanical alloying process [16].

#### **3.1. Non-isothermal transformation**

Applications of Calorimetry in a Wide Context –

crystallization temperatures [15].

in Fig. 1.

24 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

constant rate to high temperatures under vacuum or in an inert atmosphere to avoid oxidation. Depending on the phase transformations, DSC/DTA scans exhibit endothermic and/or exothermic peaks related to absorption or evolution of heat, respectively, as shown

**Figure 1.** A schematic DSC curve depicting the different stages during crystallization of an amorphous phase where Tg is the glass transition temperature; Tm the melting temperature, Tx1 and Tx2 are the onset

The values of the peak onset temperature and peak areas depend on the position of the baseline. Therefore, the accurate baseline can be obtained by heating the sample to the desired temperature, then cooled it back to the ambient temperature and then reheated it to higher temperatures. The second DSC scan could be used either as the baseline or subtracted from the rst scan to obtain the accurate peak positions and areas. There are two types of transformations: reversible and irreversible. For the former, the product phase will revert back to the parent phase. For example, transformation from one equilibrium phase to another on heating gives rise to an endothermic peak during melting and exothermic peak during cooling. However, during irreversible transformation of metastable phases such as amorphous phases, a peak of the opposite sign is not observed. In fact, there will be no peak at all. Furthermore, because metastable phases are always more energetic than the corresponding equilibrium phases, they often exhibit exothermic peaks in the DSC/DTA curves. If an amorphous alloy powder is heated to higher temperatures, one expects to observe a broad exothermic reaction at relatively low temperatures related to structural relaxation of the amorphous phase, a glass transition temperature as well as one or more exothermic peaks corresponding to crystallization event at higher temperatures. Structural changes that occur during crystallization can be investigated by X-rays diffraction or Mössbauer spectrometry by quenching the sample from a temperature just above the DSC/DTA peak temperature. Transmission electron microscopy investigations can also be conducted to uncover the microstructural and crystal structure changes on a ner scale. In addition, compositional changes can be detected. It may be pointed out, however, that there The crystallization temperature corresponds to the maximum of the exothermic peak,�� and it increases with increasing heating rate. A relation between heating rate and position of the transformation peak �� first described by Kissinger [17], has been extensively used to determine the apparent activation energy for crystallization ��:

$$\ln \frac{\beta}{T\_{\text{P}}^2} = \left( \cdot \frac{E\_{\text{a}}}{\text{RT}\_{\text{P}}} \right) + A \tag{2}$$

Where A is a constant and R is the universal gas constant. The activation energy �� can be calculated from the slope � ��� � � of the plot � � �� �� against � � �� �. Further informations about the transformation temperatures, the number of stages in which the transformation is occurring, details about the product(s) of each individual transformation (crystal structure, microstructure and chemical composition), and the activation energy (and also the atomic mechanism) can be obtained with the combination of DSC/DTA and X-rays diffraction/transmission electron microscopy techniques. The Kissinger method may not be useful in all studies of decomposition. For example, it may not be applicable for metallic glasses which may decompose by nucleation/growth, or a combination of both processes, where the decomposition is seldom described by rst-order reaction kinetics [18, 19]. Solid state reactions sometimes exhibit first-order kinetics, this is one form of the Avrami-Erofeev equation (n=1). Such kinetic behaviour may be observed in decompositions of fine powders if particle nucleation occurs on a random basis and growth does not advance beyond the individual crystallite nucleated. The physical interpretation of �� depends on the details of nucleation and growth mechanisms, and in some cases equation (2) is not valid. For each crystallization peak, the calorimetric results can be explained using the Johnson-Mehl-Avrami-Erofe've kinetics equation [20] for the transformed fraction:

$$\frac{dx}{dt} = K(T)f\_n(\mathbf{x})\tag{3}$$

With:

$$f\_n(\mathbf{x}) = n(1-\mathbf{x}) \{-\ln(1-\mathbf{x})\}^{(n-1)/n} \tag{4}$$

��(�) gives the transformation rate at time t and temperature T in terms of the rate constant:

$$K\{T\} = k\_0 \exp\{E/RT\} \tag{5}$$

�� is the pre-exponential factor; � is the effective activation energy and � is the kinetic exponent. According to the Avrami exponent value, the reaction may be three-dimensional, interface-controlled growth with constant nucleation rate (n=4); three-dimensional, interface-controlled growth with zero nucleation rate (n=3) or diffusion-controlled with growth and segregation at dislocations (n=2/3)[21].

26 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

#### **3.2. Isothermal transformation**

Isothermal transformation kinetics study at different temperatures can be conducted by the Kolmogorov-Johnson-Mehl-Avrami formalism [22-25] in which the fraction transformed, �, exhibits a time dependence of the form:

$$\mathbf{x}(t) = 1 - \exp(-kt)^{\mathbf{n}} \tag{6}$$

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 27

Depending on the microstructure, the mechanical alloying process can be divided into many stages: initial, intermediate, final and complete [35]. Since the powder particles are soft in the early stage of milling, so they are flattened by the compressive forces due to the collisions of the balls. Therefore, both flattened and un-flattened layers of particles come into intimate contact with each other leading to the building up of ingredients. A wide range of particle sizes can be observed due to the difference in ductility of the brittle and ductile powder particles. The relatively hard particles tend to resist the attrition and compressive forces. However, if the powder mixture contains both ductile and brittle particles (Fig. 2a), the hard particles may remain less deformed while the ductile ones tend to bind the hard particles together [10, 36]. Cold welding is expected to be predominant in fcc metals (Fig. 2b)

During the intermediate stage of milling, significant changes occur in the morphology of the powder particles. Greater plastic deformation leads to the formation of layered structures (Fig. 2d). Fracturing and cold welding are the dominant milling processes. Depending on the dominant forces, a particle may either become smaller in size through fracturing or may agglomerate by welding as the milling process progresses. Significant refinement in particle size is evident at the final stage of milling. Equilibrium between fracturing and cold welding leads to the homogeneity of the particles at the macroscopic scale as shown in Fig. 2d for the Fe50Co50 powder mixture [37, 38]. True alloy with composition similar to the starting constituents is formed at the completion of the mechanical alloying process (Fig. 2e) as evidenced by the energy dispersive X analysis, EDX, (Fig. 2f). The large plastic deformation that takes place during the milling process induces local melting leading to the formation of new alloys through a melting mechanism and/or diffusion at relatively high temperature.

Mechanical alloying is a non-equilibrium process resulting in solid state alloying beyond the equilibrium solubility limit. Several studies of the alloy formation process during mechanical alloying have led to conflicting conclusions such as the interdiffusion of elements, the interactions on interface boundaries and/or the diffusion of solute atoms in the host matrix. Indeed, Moumeni et al. have reported that the FeCo solid solution was formed by the interdiffusion of Fe and Co atoms with a predominance of Co diffusion into the Fe matrix according to the spectrometry results [37]. However, Brüning et al. have shown that the FeCo solid solution was formed by the dissolution of Co atoms in the Fe lattice [39]. Sorescu et al. [40] have attributed the increase of the hyperfine magnetic field to a progressive dissolution of Co atoms in the bccFe phase. Such discrepancies have been attributed to the milling conditions and/or to the fitting procedure of the Mössbauer spectra. The role of grain boundaries, the proportions and the thickness of which are dependent on the milling energy affect thus, the hyperfine structure originating some misinterpretations.

Diffusion in mechanical alloying differs from the steady state diffusion since the balance of atom concentration at the interface between two different components may be destroyed by subsequent fracturing of the powder particles. Consequently, new surfaces with different compositions meet each other to form new diffusion couples when different powder particles are cold welded together. Large difference in composition at the interface therefore promotes interdiffusion. In addition, the change in temperature during the milling process

as compared to fracture in bcc and hcp metals (Fig. 2c).

Where � is the Avrami exponent that reects the nucleation rate and/or the growth mechanism; �(�) is the volume of transformed fraction; � is the time, and � is a thermallyactivated rate constant. The double logarithmic plot ln(− ln(�−�)) against ln � should give a straight line, the slope of which represents the order of reaction or Avrami parameter �. The rate constant � is a temperature-sensitive factor �������(���⁄ ) �� , where �� is the apparent activation energy and �� a constant. �(�) corresponds to the ratio between the area under the peak of the isothermal DSC trace, at different times, and the total area. Such analysis was conducted on the phase transformation mechanisms in many mechanically alloyed powders since the milling process occurs at ambient temperature for different milling durations [26-31]. If the Kolmogorov-Johnson-Mehl-Avrami analysis is valid, the value of � should not change with either the volume fraction transformed, V� or the temperature of transformation. Calka and Radlinski [32] have shown that the usual method of applying the Kolmogorov-Johnson-Mehl-Avrami equation and calculating the mean value of Avrami exponent over a range of volume fraction transformed, may be inappropriate, even misleading, if competing reactions or changes in growth dimensionality occur during the transformation progress. Also, a close examination of the Avrami plots reveals that there are deviations from linearity over the full range of volume fraction transformed [33]. The first derivative of the Avrami plot � �ln(− ln(�−�))�⁄� ln � against the volume fraction transformed [34], which effectively gives the local value of � with ��, seems to be more sensitive. Such a plot allows a more detailed evaluation of the data and can emphasize changes in reaction kinetics during the transformation process.

#### **4. Mechanical alloying process**

Mechanical alloying has received a great interest in developing different material systems. It is a solid state process that provides a means to overcome the drawback of formation of new alloys starting from mixture of low and/or high melting temperature elements. Mechanical alloying is a ball milling process where a powder mixture placed in the vials is subjected to high-energy collisions from the balls. The two important processes involved in ball milling are fracturing and cold welding of powder particles in a dry high energy ball-mill. The alloying process can be carried out using different apparatus such as planetary or horizontal mills, attrition or spex shaker mill. The elemental or prealloyed powder mixture is charged in the jar (or vial) together with some balls. As a result of the induced heavy plastic deformation into the powder particles during the milling process, nanostructured materials are produced by the structural decomposition of coarser-grained structure. This leads to a continuous refinement of the internal structure of the powder particles down to nanometer scales.

Depending on the microstructure, the mechanical alloying process can be divided into many stages: initial, intermediate, final and complete [35]. Since the powder particles are soft in the early stage of milling, so they are flattened by the compressive forces due to the collisions of the balls. Therefore, both flattened and un-flattened layers of particles come into intimate contact with each other leading to the building up of ingredients. A wide range of particle sizes can be observed due to the difference in ductility of the brittle and ductile powder particles. The relatively hard particles tend to resist the attrition and compressive forces. However, if the powder mixture contains both ductile and brittle particles (Fig. 2a), the hard particles may remain less deformed while the ductile ones tend to bind the hard particles together [10, 36]. Cold welding is expected to be predominant in fcc metals (Fig. 2b) as compared to fracture in bcc and hcp metals (Fig. 2c).

Applications of Calorimetry in a Wide Context –

exhibits a time dependence of the form:

**4. Mechanical alloying process** 

scales.

**3.2. Isothermal transformation** 

26 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

emphasize changes in reaction kinetics during the transformation process.

Mechanical alloying has received a great interest in developing different material systems. It is a solid state process that provides a means to overcome the drawback of formation of new alloys starting from mixture of low and/or high melting temperature elements. Mechanical alloying is a ball milling process where a powder mixture placed in the vials is subjected to high-energy collisions from the balls. The two important processes involved in ball milling are fracturing and cold welding of powder particles in a dry high energy ball-mill. The alloying process can be carried out using different apparatus such as planetary or horizontal mills, attrition or spex shaker mill. The elemental or prealloyed powder mixture is charged in the jar (or vial) together with some balls. As a result of the induced heavy plastic deformation into the powder particles during the milling process, nanostructured materials are produced by the structural decomposition of coarser-grained structure. This leads to a continuous refinement of the internal structure of the powder particles down to nanometer

Isothermal transformation kinetics study at different temperatures can be conducted by the Kolmogorov-Johnson-Mehl-Avrami formalism [22-25] in which the fraction transformed, �,

Where � is the Avrami exponent that reects the nucleation rate and/or the growth mechanism; �(�) is the volume of transformed fraction; � is the time, and � is a thermallyactivated rate constant. The double logarithmic plot ln(− ln(�−�)) against ln � should give a straight line, the slope of which represents the order of reaction or Avrami parameter �. The rate constant � is a temperature-sensitive factor �������(���⁄ ) �� , where �� is the apparent activation energy and �� a constant. �(�) corresponds to the ratio between the area under the peak of the isothermal DSC trace, at different times, and the total area. Such analysis was conducted on the phase transformation mechanisms in many mechanically alloyed powders since the milling process occurs at ambient temperature for different milling durations [26-31]. If the Kolmogorov-Johnson-Mehl-Avrami analysis is valid, the value of � should not change with either the volume fraction transformed, V� or the temperature of transformation. Calka and Radlinski [32] have shown that the usual method of applying the Kolmogorov-Johnson-Mehl-Avrami equation and calculating the mean value of Avrami exponent over a range of volume fraction transformed, may be inappropriate, even misleading, if competing reactions or changes in growth dimensionality occur during the transformation progress. Also, a close examination of the Avrami plots reveals that there are deviations from linearity over the full range of volume fraction transformed [33]. The first derivative of the Avrami plot � �ln(− ln(�−�))�⁄� ln � against the volume fraction transformed [34], which effectively gives the local value of � with ��, seems to be more sensitive. Such a plot allows a more detailed evaluation of the data and can

�(�) � � − ��� (−��)� (6)

During the intermediate stage of milling, significant changes occur in the morphology of the powder particles. Greater plastic deformation leads to the formation of layered structures (Fig. 2d). Fracturing and cold welding are the dominant milling processes. Depending on the dominant forces, a particle may either become smaller in size through fracturing or may agglomerate by welding as the milling process progresses. Significant refinement in particle size is evident at the final stage of milling. Equilibrium between fracturing and cold welding leads to the homogeneity of the particles at the macroscopic scale as shown in Fig. 2d for the Fe50Co50 powder mixture [37, 38]. True alloy with composition similar to the starting constituents is formed at the completion of the mechanical alloying process (Fig. 2e) as evidenced by the energy dispersive X analysis, EDX, (Fig. 2f). The large plastic deformation that takes place during the milling process induces local melting leading to the formation of new alloys through a melting mechanism and/or diffusion at relatively high temperature.

Mechanical alloying is a non-equilibrium process resulting in solid state alloying beyond the equilibrium solubility limit. Several studies of the alloy formation process during mechanical alloying have led to conflicting conclusions such as the interdiffusion of elements, the interactions on interface boundaries and/or the diffusion of solute atoms in the host matrix. Indeed, Moumeni et al. have reported that the FeCo solid solution was formed by the interdiffusion of Fe and Co atoms with a predominance of Co diffusion into the Fe matrix according to the spectrometry results [37]. However, Brüning et al. have shown that the FeCo solid solution was formed by the dissolution of Co atoms in the Fe lattice [39]. Sorescu et al. [40] have attributed the increase of the hyperfine magnetic field to a progressive dissolution of Co atoms in the bccFe phase. Such discrepancies have been attributed to the milling conditions and/or to the fitting procedure of the Mössbauer spectra. The role of grain boundaries, the proportions and the thickness of which are dependent on the milling energy affect thus, the hyperfine structure originating some misinterpretations.

Diffusion in mechanical alloying differs from the steady state diffusion since the balance of atom concentration at the interface between two different components may be destroyed by subsequent fracturing of the powder particles. Consequently, new surfaces with different compositions meet each other to form new diffusion couples when different powder particles are cold welded together. Large difference in composition at the interface therefore promotes interdiffusion. In addition, the change in temperature during the milling process

28 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 29

Mechanical alloying process was used to prepare nanocrystalline and/or amorphous alloys such as Fe, Fe-Co, Fe-Co-Nb-B, Fe-P and Ni-P from pure elemental powders in high-energy planetary ball-mills Fritsch Pulverisette P7 and Retsch PM 400/2, and vibratory ball-mill spex 8000. The milling process was performed at room temperature, under argon atmosphere, with different milling conditions such as rotation speed, ball-to-powder weight ratio, milling time and composition. In order to avoid the temperature increase inside the vials, the milling process was interrupted for 1530 min after each 3060 min depending on the raw mixture.

Particles powder morphology evolution during the milling process was followed by scanning electron microscopy. Structural changes were investigated by X-ray diffraction in a

Fe and Fe50Co50 were prepared by mechanical alloying from pure elemental iron and cobalt powders in a planetary ball mill Fritsch P7, under argon atmosphere, using hardened steel vials and balls. The milling intensity was 400 rpm and the ball-to-powder weight ratio was 20:1. A disordered bcc FeCo solid solution is obtained after 24 h of milling (Fig 3), having a lattice parameter, a = 0.2861(5) nm, larger than that of the coarse-grained FeCo phase (a = 0.2825(5) nm). Such a difference in the lattice parameter value may be due to heavily cold worked and plastically deformed state of the powders during the milling process, and to the introduction of several structural defects (vacancies, interstitials, triple defect disorder, etc.).

**Figure 3.** Rietveld refinement of the XRD pattern of the Fe50Co50 powders milled for 40 h [7].

*)* Bragg Brentano geometry with Cu-Kα radiation (*λCu*=0.15406 nm). The microstructural parameters were obtained from the refinement of the X-rays diffraction patterns by using the MAUD program [41, 42] which is based on the Rietveld method. Differential scanning calorimetry was performed under argon atmosphere. Magnetic and hyperfine characterizations were studied by vibrating sample magnetometer and Mössbauer

**5. Experimental section** 

spectrometry, respectively.

**6. Fe and FeCo-based alloys** 

**6.1. Fe and Fe-Co powders** 

(*2*

**Figure 2.** Morphologies of powder particles of the ball-milled Fe75Si15B10 (a), Ni20Co80 (b), Fe57Cr31Co12 (c and d), and Fe50Co50 powders (e) with the corresponding EDX analysis (f).

is very significant due to the exothermic reaction causing local combustion. Two major phenomena can contribute to the increase in milling temperature: friction during collisions and localized plastic deformation. At low temperatures, surface diffusion dominates over grain boundary and lattice diffusion. As the temperature is increased, however, grain boundary diffusion predominates, and at higher temperature lattice diffusion becomes the principal mode of diffusion. The first key factor controlling the formation of new alloys is the activation energy which is related to the formation of defects during balls-powder-balls and/or balls-powder-vials collisions. The second key is the vial temperature which is associated with plastic deformation as well as sliding between powder particles and high energetic balls and powder particles. The third key is the crystallite size that is related to the formation of nanometer crystalline structure during the milling process.

### **5. Experimental section**

Applications of Calorimetry in a Wide Context –

28 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 2.** Morphologies of powder particles of the ball-milled Fe75Si15B10 (a), Ni20Co80 (b), Fe57Cr31Co12 (c

is very significant due to the exothermic reaction causing local combustion. Two major phenomena can contribute to the increase in milling temperature: friction during collisions and localized plastic deformation. At low temperatures, surface diffusion dominates over grain boundary and lattice diffusion. As the temperature is increased, however, grain boundary diffusion predominates, and at higher temperature lattice diffusion becomes the principal mode of diffusion. The first key factor controlling the formation of new alloys is the activation energy which is related to the formation of defects during balls-powder-balls and/or balls-powder-vials collisions. The second key is the vial temperature which is associated with plastic deformation as well as sliding between powder particles and high energetic balls and powder particles. The third key is the crystallite size that is related to the

and d), and Fe50Co50 powders (e) with the corresponding EDX analysis (f).

formation of nanometer crystalline structure during the milling process.

Mechanical alloying process was used to prepare nanocrystalline and/or amorphous alloys such as Fe, Fe-Co, Fe-Co-Nb-B, Fe-P and Ni-P from pure elemental powders in high-energy planetary ball-mills Fritsch Pulverisette P7 and Retsch PM 400/2, and vibratory ball-mill spex 8000. The milling process was performed at room temperature, under argon atmosphere, with different milling conditions such as rotation speed, ball-to-powder weight ratio, milling time and composition. In order to avoid the temperature increase inside the vials, the milling process was interrupted for 1530 min after each 3060 min depending on the raw mixture.

Particles powder morphology evolution during the milling process was followed by scanning electron microscopy. Structural changes were investigated by X-ray diffraction in a (*2)* Bragg Brentano geometry with Cu-Kα radiation (*λCu*=0.15406 nm). The microstructural parameters were obtained from the refinement of the X-rays diffraction patterns by using the MAUD program [41, 42] which is based on the Rietveld method. Differential scanning calorimetry was performed under argon atmosphere. Magnetic and hyperfine characterizations were studied by vibrating sample magnetometer and Mössbauer spectrometry, respectively.

### **6. Fe and FeCo-based alloys**

### **6.1. Fe and Fe-Co powders**

Fe and Fe50Co50 were prepared by mechanical alloying from pure elemental iron and cobalt powders in a planetary ball mill Fritsch P7, under argon atmosphere, using hardened steel vials and balls. The milling intensity was 400 rpm and the ball-to-powder weight ratio was 20:1. A disordered bcc FeCo solid solution is obtained after 24 h of milling (Fig 3), having a lattice parameter, a = 0.2861(5) nm, larger than that of the coarse-grained FeCo phase (a = 0.2825(5) nm). Such a difference in the lattice parameter value may be due to heavily cold worked and plastically deformed state of the powders during the milling process, and to the introduction of several structural defects (vacancies, interstitials, triple defect disorder, etc.).

**Figure 3.** Rietveld refinement of the XRD pattern of the Fe50Co50 powders milled for 40 h [7].

30 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

With increasing milling time, the crystallite size decreases down to the nanometer scale and the internal strain increases. The double logarithmic plot of the crystallite size versus milling time exhibits two-stage behaviour for both Fe and Fe50Co50 powders (Fig. 4). A linear fit gives slopes of 0.65 and –0.20 for short and extended milling times, respectively, in the case of Fe; and slopes of –0.85 and –0.03, respectively, for short and extended milling times in the case of Fe50Co50 mixture. The critical crystallite size achievable by ball milling is defined by the crossing point between the two regimes with different slopes [43]. Consequently, the obtained critical crystallite sizes are of about 13.8 and 15 nm for Fe and Fe50Co50 powders, respectively. By using different milling conditions (mills type, milling intensity and temperature) to prepare nanostructured Fe powders, Börner et al. have obtained the two-regime behaviour, for the grain refinement by using the Spex mill, with slopes of –0.41 and –0.08 for short and extended milling times, respectively. However, the crystallite sizes show only a simple linear relation with slopes of –0.265 and –0.615 by using the Retsch MM2 shaker and the Misuni vibration mill, respectively. The obtained critical crystallite size value was 19 nm [44].

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 31

**F e 5 0C o 5 0**

**F e**

**200 400 600 800 1000**

**T em perature (°C )**

temperature, ܶఈ՜ఊ. The depression of Curie temperature with increasing milling duration (Fig. 6), which is ascribed to changes in local order, indicates that the nearest-neighbour coordination is essentially changed in the magnetic nanocrystallites. This reflects to some extent that there are more open disordered spaces or the nearestneighbour coordination distance in the nanometer sized crystallites is increased, caused by lattice distortion. In fact, if the crystallite sizes are small enough, the structural distortions associated with surfaces or interfaces can lower the Curie temperature. This can be correlated to the increase of the lattice parameter and its deviation from that of the perfect crystal. It has been reported on far-from-equilibrium nanostructured metals, that interfaces present a reduced atomic coordination and a wide distribution of interatomic spacing compared to the crystals and consequently, the atomic arrangement at the grain boundary may be considered close to the amorphous configuration and should therefore alter the Curie temperature. The most reported values of TC do not deviate strongly from that of the bulk materials. For example, the TC of 360°C for Ni[C] nanocrystals is in good agreement with that of bulk Ni [47]. Host et al. have reported a Tc value of 1093°C for carbon arc produced Co[C] nanoparticles, in good agreement with the 1115°C value for bulk Co [48]. The Curie temperature of 10 nm Gd is

**0 10 20 30 40**

**Fe**

**0,2864**

**0,2866**

**0,2868**

**0,2870**

**Lattice parameter (nm)**

**0,2872**

**0,2874**

**0,2876**

**Milling time (h)**

**Figure 6.** Evolution of the Curie temperature and the lattice parameter of the Fe powders as a function

**Figure 5.** DSC scans of nanostructured Fe and Fe50Co50 powders milled for 40 h [7].

**40 h**

**760**

of milling time [7].

**762**

**764**

**Curie temperature (°C)**

**766**

**768**

**Exo. Heat flow (a.u.)**

**Figure 4.** Double logarithmic plot of the crystallite size against milling time for nanostructured Fe and Fe50Co50 powders [7].

DSC scans of nanostructured Fe and Fe50Co50 powders milled for 40 h are shown in Fig. 5. The non-equilibrium state is revealed by the broad exothermic reaction for both samples, in the temperature range 100700°C, which is consistent with the energy release during heating due to recovery, grain growth and relaxation processes. As a result of the cold work during the milling process, the main energy contribution is stored in the form of grain boundaries and related strains within the nanostructured grains which are induced through grain boundary stresses [45]. It has been reported that the stored energies during the alloying process largely exceed those resulting from conventional cold working of metals and alloys. Indeed, they can achieve values typical for crystallization enthalpies of metallic glasses corresponding to about 40% of the heat of fusion, ΔHf [45]. The major sources of mechanical energy storage are both atomic disorder and nanocrystallite boundaries because the transition heats evolving in the atomic reordering and in the grain growth are comparable in value [46].

For the nanostructured Fe powders, the first endothermic peak is linked to the bcc ferroparamagnetic transition temperature, TC, and the second peak to the bccfcc transition

**Figure 5.** DSC scans of nanostructured Fe and Fe50Co50 powders milled for 40 h [7].

30 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

mill, respectively. The obtained critical crystallite size value was 19 nm [44].

**Milling time (h) 1 10**

**10**

**Figure 4.** Double logarithmic plot of the crystallite size against milling time for nanostructured Fe and

DSC scans of nanostructured Fe and Fe50Co50 powders milled for 40 h are shown in Fig. 5. The non-equilibrium state is revealed by the broad exothermic reaction for both samples, in the temperature range 100700°C, which is consistent with the energy release during heating due to recovery, grain growth and relaxation processes. As a result of the cold work during the milling process, the main energy contribution is stored in the form of grain boundaries and related strains within the nanostructured grains which are induced through grain boundary stresses [45]. It has been reported that the stored energies during the alloying process largely exceed those resulting from conventional cold working of metals and alloys. Indeed, they can achieve values typical for crystallization enthalpies of metallic glasses corresponding to about 40% of the heat of fusion, ΔHf [45]. The major sources of mechanical energy storage are both atomic disorder and nanocrystallite boundaries because the transition heats evolving in the atomic reordering and in the grain growth are

For the nanostructured Fe powders, the first endothermic peak is linked to the bcc ferroparamagnetic transition temperature, TC, and the second peak to the bccfcc transition

**<d> (nm)**

**<sup>100</sup> Fe50Co50**

**dcritical**

**Milling time (h)**

**1 10 100**

**dcritical**

**10**

Fe50Co50 powders [7].

comparable in value [46].

**100**

**<d> (nm)**

**Fe**

With increasing milling time, the crystallite size decreases down to the nanometer scale and the internal strain increases. The double logarithmic plot of the crystallite size versus milling time exhibits two-stage behaviour for both Fe and Fe50Co50 powders (Fig. 4). A linear fit gives slopes of 0.65 and –0.20 for short and extended milling times, respectively, in the case of Fe; and slopes of –0.85 and –0.03, respectively, for short and extended milling times in the case of Fe50Co50 mixture. The critical crystallite size achievable by ball milling is defined by the crossing point between the two regimes with different slopes [43]. Consequently, the obtained critical crystallite sizes are of about 13.8 and 15 nm for Fe and Fe50Co50 powders, respectively. By using different milling conditions (mills type, milling intensity and temperature) to prepare nanostructured Fe powders, Börner et al. have obtained the two-regime behaviour, for the grain refinement by using the Spex mill, with slopes of –0.41 and –0.08 for short and extended milling times, respectively. However, the crystallite sizes show only a simple linear relation with slopes of –0.265 and –0.615 by using the Retsch MM2 shaker and the Misuni vibration

> temperature, ܶఈ՜ఊ. The depression of Curie temperature with increasing milling duration (Fig. 6), which is ascribed to changes in local order, indicates that the nearest-neighbour coordination is essentially changed in the magnetic nanocrystallites. This reflects to some extent that there are more open disordered spaces or the nearestneighbour coordination distance in the nanometer sized crystallites is increased, caused by lattice distortion. In fact, if the crystallite sizes are small enough, the structural distortions associated with surfaces or interfaces can lower the Curie temperature. This can be correlated to the increase of the lattice parameter and its deviation from that of the perfect crystal. It has been reported on far-from-equilibrium nanostructured metals, that interfaces present a reduced atomic coordination and a wide distribution of interatomic spacing compared to the crystals and consequently, the atomic arrangement at the grain boundary may be considered close to the amorphous configuration and should therefore alter the Curie temperature. The most reported values of TC do not deviate strongly from that of the bulk materials. For example, the TC of 360°C for Ni[C] nanocrystals is in good agreement with that of bulk Ni [47]. Host et al. have reported a Tc value of 1093°C for carbon arc produced Co[C] nanoparticles, in good agreement with the 1115°C value for bulk Co [48]. The Curie temperature of 10 nm Gd is

**Figure 6.** Evolution of the Curie temperature and the lattice parameter of the Fe powders as a function of milling time [7].

32 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

decreased by about 10 K from that of coarse-grained Gd while the magnetic transition is broader [49]. According to both Tc and ���� temperature values, the paramagnetic nanostructured bcc Fe domain is extended by about 50°C at the expense of both magnetic bcc Fe and nonmagnetic fcc Fe as compared to coarse-grained bcc Fe.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 33

about 8:1 and a rotation speed of 350 rpm. In order to avoid the increase of the temperature

**Figure 8.** Rietveld refinement of the XRD patterns of 7Nb and 3Nb powders milled for 48 and 96 h

nanostructured Feborides with *Bhyp* ranged from 24 to 30 T [28, 56, 57].

The XRD patterns of 7Nb and 3Nb mixtures milled for 48 h (Fig. 8) are consistent of a large number of overlapping diffraction peaks related to different phases. The Rietveld refinement reveals the formation of a partially amorphous structure of about ~78%, where nanocrystalline tetragonalFe2B, tetragonalFe3B and bccFeCo type phases were embedded for 3Nb powders [53]. Whereas, for 7Nb powders, the milling product is a mixture of amorphous (~73.6%), bccNb(B), tetragonalFe2B, orthorhombicFe3B and bcc FeCo type phases [54]. Further milling (up to 96 h) leads to the increase of the amorphous phase proportion for 7Nb and the mechanical recrystallization in the case of 3Nb mixture (Fig. 8) as evidenced by the decrease and the increase of the diffraction peaks intensity, respectively. The formation of the amorphous phase is confirmed by the Mössbauer spectrometry results as shown in Fig. 9. After 48 h of milling, the Mössbauer spectra exhibit more or less sharp absorption lines superimposed upon a broadened spectral component assigned to the structural disorder of the amorphous state [55]. For 3Nb powders, the mechanical recrystallization is confirmed by the emergence of sharp sextet related to the primary crystallization of αFe and FeCo after 96 h of milling. However, a stationary state is achieved for 7Nb powders. The increase of the average hyperfine magnetic field, < *Bhyp* >, from 19.18 to 23.14 T after 96 h of milling of 3Nb powders is correlated to the decrease/increase of the amorphous/nanocrystalline relative area. The nanocrystalline (NC) component consists of Fe sites with *Bhyp*>31 T and the interfacial (IF) one is related to the

inside the vials, the milling process was interrupted after 30 min for 15 min.

[53, 54].

The disorder-order phase transformation temperature of the nanostructured FeCo powders which is nearly constant (~724°C) along of the milling process (Fig. 7), is comparable to that of bulk Fe-Co alloys. It is commonly accepted that Fe-Co undergoes an ordering transition at around 730°C, where the bcc structure takes the ordered α'CsCl(B2)-type structure [50]. The ordering effect in the FeCo nanocrystals has been revealed by the changes in the magnetization upon heating and the temperature variation of the coercivity on heating and cooling [51]. Also, the phase transformation temperature from bcc to fcc structure in the Fe50Co50 powders is rather milling time independent (~982°C). The lower resistivity of Fe50Co50 compared to that of pure Fe at 300 K [52] and the higher Curie temperature of Fe50Co50 suggest that there is less scattering of the conduction electrons by the magnetic excitations. Thus, the Curie temperature cannot be clearly observed because there is a phase transformation from the bcc to fcc form at 985°C.

**Figure 7.** Evolution of the order-disorder, ����� and the bccfcc, ����, temperatures of the Fe50Co50 powders as a function of milling time [7].

#### **6.2. Fe-Co-Nb-B powders**

Nanostructured and disordered structures obtained by mechanical alloying are usually metastable. Depending on the Nb and B contents, the mechanically alloyed Fe-Co-Nb-B powders structure may be partially amorphous either magnetic and/or paramagnetic. Pure elemental powders of iron (6-8 µm, 99.7%), cobalt (45 µm, 99.8%), niobium (74 µm, 99.85%) and amorphous boron (> 99%) were mixed to give nominal compositions of Fe57Co21Nb7B15 and Fe61Co21Nb3B15 (wt. %), labelled as 7Nb and 3Nb, respectively. The milling process was performed in a planetary ball-mill Fritsch Pulverisette 7, under argon atmosphere, using hardened steel balls and vials. The ball-to-powder weight ratio was about 19/2 and the rotation speed was 700 rpm. For the (Fe50Co50)62Nb8B30 mixture, the milling process was performed in a planetary ball-mill Retsch PM400/2, with a ball-to-powder weight ratio of about 8:1 and a rotation speed of 350 rpm. In order to avoid the increase of the temperature inside the vials, the milling process was interrupted after 30 min for 15 min.

Applications of Calorimetry in a Wide Context –

transformation from the bcc to fcc form at 985°C.

**990**

**Fe50Co50**

**975**

powders as a function of milling time [7].

**6.2. Fe-Co-Nb-B powders** 

**980**

**985**

**T(°C)**

32 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

bcc Fe and nonmagnetic fcc Fe as compared to coarse-grained bcc Fe.

decreased by about 10 K from that of coarse-grained Gd while the magnetic transition is broader [49]. According to both Tc and ���� temperature values, the paramagnetic nanostructured bcc Fe domain is extended by about 50°C at the expense of both magnetic

The disorder-order phase transformation temperature of the nanostructured FeCo powders which is nearly constant (~724°C) along of the milling process (Fig. 7), is comparable to that of bulk Fe-Co alloys. It is commonly accepted that Fe-Co undergoes an ordering transition at around 730°C, where the bcc structure takes the ordered α'CsCl(B2)-type structure [50]. The ordering effect in the FeCo nanocrystals has been revealed by the changes in the magnetization upon heating and the temperature variation of the coercivity on heating and cooling [51]. Also, the phase transformation temperature from bcc to fcc structure in the Fe50Co50 powders is rather milling time independent (~982°C). The lower resistivity of Fe50Co50 compared to that of pure Fe at 300 K [52] and the higher Curie temperature of Fe50Co50 suggest that there is less scattering of the conduction electrons by the magnetic excitations. Thus, the Curie temperature cannot be clearly observed because there is a phase

**0 10 20 30 40**

Nanostructured and disordered structures obtained by mechanical alloying are usually metastable. Depending on the Nb and B contents, the mechanically alloyed Fe-Co-Nb-B powders structure may be partially amorphous either magnetic and/or paramagnetic. Pure elemental powders of iron (6-8 µm, 99.7%), cobalt (45 µm, 99.8%), niobium (74 µm, 99.85%) and amorphous boron (> 99%) were mixed to give nominal compositions of Fe57Co21Nb7B15 and Fe61Co21Nb3B15 (wt. %), labelled as 7Nb and 3Nb, respectively. The milling process was performed in a planetary ball-mill Fritsch Pulverisette 7, under argon atmosphere, using hardened steel balls and vials. The ball-to-powder weight ratio was about 19/2 and the rotation speed was 700 rpm. For the (Fe50Co50)62Nb8B30 mixture, the milling process was performed in a planetary ball-mill Retsch PM400/2, with a ball-to-powder weight ratio of

**Figure 7.** Evolution of the order-disorder, ����� and the bccfcc, ����, temperatures of the Fe50Co50

**Milling time (h)**

**724**

**726**

**T'(°C)**

**728**

**Figure 8.** Rietveld refinement of the XRD patterns of 7Nb and 3Nb powders milled for 48 and 96 h [53, 54].

The XRD patterns of 7Nb and 3Nb mixtures milled for 48 h (Fig. 8) are consistent of a large number of overlapping diffraction peaks related to different phases. The Rietveld refinement reveals the formation of a partially amorphous structure of about ~78%, where nanocrystalline tetragonalFe2B, tetragonalFe3B and bccFeCo type phases were embedded for 3Nb powders [53]. Whereas, for 7Nb powders, the milling product is a mixture of amorphous (~73.6%), bccNb(B), tetragonalFe2B, orthorhombicFe3B and bcc FeCo type phases [54]. Further milling (up to 96 h) leads to the increase of the amorphous phase proportion for 7Nb and the mechanical recrystallization in the case of 3Nb mixture (Fig. 8) as evidenced by the decrease and the increase of the diffraction peaks intensity, respectively. The formation of the amorphous phase is confirmed by the Mössbauer spectrometry results as shown in Fig. 9. After 48 h of milling, the Mössbauer spectra exhibit more or less sharp absorption lines superimposed upon a broadened spectral component assigned to the structural disorder of the amorphous state [55]. For 3Nb powders, the mechanical recrystallization is confirmed by the emergence of sharp sextet related to the primary crystallization of αFe and FeCo after 96 h of milling. However, a stationary state is achieved for 7Nb powders. The increase of the average hyperfine magnetic field, < *Bhyp* >, from 19.18 to 23.14 T after 96 h of milling of 3Nb powders is correlated to the decrease/increase of the amorphous/nanocrystalline relative area. The nanocrystalline (NC) component consists of Fe sites with *Bhyp*>31 T and the interfacial (IF) one is related to the nanostructured Feborides with *Bhyp* ranged from 24 to 30 T [28, 56, 57].

34 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 35

**125 h**

**-8 -4 <sup>0</sup> <sup>4</sup> <sup>8</sup>**

A

B

C

**V (mm/s)**

vials. The ball-to-powder weight ratio was about 8:1 and the rotation speed was 200 rpm [58]. The crystallite size decreases with increasing milling duration to about (7.1 ± 0.3) nm for the B-richest alloy (A). The XRD patterns (Fig. 12) reveal the formation of a bcc Fe-rich solid solution after 80 h of milling having an average lattice parameter of about 0.2871 nm

**Transmission**

**Figure 11.** Room temperature Mössbauer spectra of the (Fe50Co50)62Nb8B30 powders milled for 25 and

Depending on the structural state after each milling time, several exothermic and endothermic peaks appear on heating of the mechanically alloyed Fe-Co-Nb-B powders. Representative DSC scans of 7Nb and 3Nb (Fig. 13) as well as (Fe50Co50)62Nb8B30 powder mixtures (Fig. 14) exhibit different thermal effects (Table 1). For all ball milled powders, the first exothermic peak that spreads over the temperature range 100300°C can be attributed to recovery, strains and structural relaxation. The important heat release (20.56 J/g) for 3Nb powders might be related to the amount of structural defects. The second exothermic peak (2), at 415°C, can be attributed to the -Fe and/or -FeCo primary nanocrystallization. This temperature is smaller than that obtained for the ball-milled 7Nb and (Fe50Co50)62Nb8B30 powders. Such a difference might be attributed to the Nb content since Co usually increases

40 60 80 100 2 theta / º

**Figure 12.** XRD patterns of alloys A, B and C milled for 80 h [58].

Intensity / a.u.

for the three alloys.

125 h.

**Figure 9.** Room temperature Mössbauer spectra of 3Nb and 7Nb powders milled for 48 and 96 h [55].

**Figure 10.** XRD patterns of the (Fe50Co50)62Nb8B30 powders milled for 25 and 100 h.

For the (Fe50Co50)62Nb8B30 powders mixture milled for 25 and 100 h, the best Rietveld refinements of the XRD patterns were obtained with two components: bccFeCo and amorphous phase (Fig. 10). The complete transformation of the heavily deformed FeB and bcc FeCo type phases into an amorphous state is achieved, after 125 h of milling, through the mechanically enhanced solid-state amorphization which requires the existence of chemical disordering, point defects (vacancies, interstitials) and lattice defects (dislocations). Indeed, the severe plastic deformation strongly distorts the unit cell structures making them less crystalline. The powder particles are subjected to continuous defects that lead to a gradual change in the free energy of the crystalline phases above those of amorphous ones, and hence to a disorder in atomic arrangement. The Mössbauer spectra confirm the formation of a paramagnetic amorphous structure, where about 3.8% of FeCo and Fe2B nanograins are embedded, after 125 h of milling (Fig. 11).

Nanocrystalline Fe72.5Co7.5Nb5+xB15-x with x=0, 5 and 10 at.% labelled as A, B and C, respectively, were prepared by mechanical alloying from pure elemental powders in a planetary ball-mill Retsch PM400, under argon atmosphere, using stainless steel balls and vials. The ball-to-powder weight ratio was about 8:1 and the rotation speed was 200 rpm [58]. The crystallite size decreases with increasing milling duration to about (7.1 ± 0.3) nm for the B-richest alloy (A). The XRD patterns (Fig. 12) reveal the formation of a bcc Fe-rich solid solution after 80 h of milling having an average lattice parameter of about 0.2871 nm for the three alloys.

Applications of Calorimetry in a Wide Context –

**IF NC**

**48 h**

**NC**

**96 h**

**Transmission**

**-8 -4 0 4 8**

**IF**

34 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Amorphous**

**3Nb**

**Figure 10.** XRD patterns of the (Fe50Co50)62Nb8B30 powders milled for 25 and 100 h.

nanograins are embedded, after 125 h of milling (Fig. 11).

**Figure 9.** Room temperature Mössbauer spectra of 3Nb and 7Nb powders milled for 48 and 96 h [55].

For the (Fe50Co50)62Nb8B30 powders mixture milled for 25 and 100 h, the best Rietveld refinements of the XRD patterns were obtained with two components: bccFeCo and amorphous phase (Fig. 10). The complete transformation of the heavily deformed FeB and bcc FeCo type phases into an amorphous state is achieved, after 125 h of milling, through the mechanically enhanced solid-state amorphization which requires the existence of chemical disordering, point defects (vacancies, interstitials) and lattice defects (dislocations). Indeed, the severe plastic deformation strongly distorts the unit cell structures making them less crystalline. The powder particles are subjected to continuous defects that lead to a gradual change in the free energy of the crystalline phases above those of amorphous ones, and hence to a disorder in atomic arrangement. The Mössbauer spectra confirm the formation of a paramagnetic amorphous structure, where about 3.8% of FeCo and Fe2B

Nanocrystalline Fe72.5Co7.5Nb5+xB15-x with x=0, 5 and 10 at.% labelled as A, B and C, respectively, were prepared by mechanical alloying from pure elemental powders in a planetary ball-mill Retsch PM400, under argon atmosphere, using stainless steel balls and

**V(mm/s) -8 -4 0 4 8**

**NC**

**96h**

**48h**

**Transmission**

**IF**

**IF**

**NC Amorphous**

**V(mm/s)**

**7Nb**

**Figure 11.** Room temperature Mössbauer spectra of the (Fe50Co50)62Nb8B30 powders milled for 25 and 125 h.

**Figure 12.** XRD patterns of alloys A, B and C milled for 80 h [58].

Depending on the structural state after each milling time, several exothermic and endothermic peaks appear on heating of the mechanically alloyed Fe-Co-Nb-B powders. Representative DSC scans of 7Nb and 3Nb (Fig. 13) as well as (Fe50Co50)62Nb8B30 powder mixtures (Fig. 14) exhibit different thermal effects (Table 1). For all ball milled powders, the first exothermic peak that spreads over the temperature range 100300°C can be attributed to recovery, strains and structural relaxation. The important heat release (20.56 J/g) for 3Nb powders might be related to the amount of structural defects. The second exothermic peak (2), at 415°C, can be attributed to the -Fe and/or -FeCo primary nanocrystallization. This temperature is smaller than that obtained for the ball-milled 7Nb and (Fe50Co50)62Nb8B30 powders. Such a difference might be attributed to the Nb content since Co usually increases

36 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

the onset of crystallization by about 20°C because this atom inhibits atomic movement raising the kinetic barrier for crystallization. The small exothermic peaks centred at ~623.5°C (3) and ~675.7°C (4) in the 3Nb powders can be related to the crystallization of Fe-borides.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 37

1 138.83 7.58 420 **2 475.76 27.98** 

1 136.8 2.1 344.5 **2 459.5 169.5** 

286.4

phase transition but a kinetic event dependent on the rearrangement of the system and experimental time scales. Therefore, the transition would be a purely dynamic phenomenon.

Milling time (h) **Peak T(°C) H (J/g) Tg (°C)** 

**Table 1.** Peak temperature, Tp, enthalpy release, H, and glass transition temperature, Tg, of 7Nb and

**Figure 15.** DSC scans at a heating rate of 10 K.min-1 of the ball-milled A, B and C powders for

**0 20 40 60 80 100 120**

**400**

**405**

**410**

**Tg (°C)**

**415**

**420**

**Milling time (h)**

**Figure 16.** Variation of the glass transition temperature and the amorphous phase proportion of the

**0**

(Fe50Co50)62Nb8B30 powders as a function of milling time.

**20**

**40**

**60**

**Amorphous proportion (%)**

**80**

**100**

3Nb powders milled for 48 h, and (Fe50Co50)62Nb8B30 mixture milled for 100 h [55].

1 198.5 20.56

**2 415.0 35.9**  3 623.5 1.4 4 675.7 3.9

**Sample**

**(Fe50Co50)62Nb8B30**  (100 h)

> **7Nb**  (48 h)

> **3Nb**  (48 h)

160 h [58].

**Figure 13.** DSC scans of 3Nb and 7Nb powder mixtures milled for 48 h [55].

**Figure 14.** DSC scans of the (Fe50Co50)62Nb8B30 powders milled for 100 and 125 h.

Thermal stability of the nanocrystalline phases was investigated by DSC for alloys A, B and C milled for 160 h at a heating rate of 10 K/min (Fig. 15). The broad exothermic process starting at 400420 K is due to early surface crystallization (particle surface) and/or internal stress relaxation [58]. In all alloys, an additional exothermic process was detected with a peak temperature between 713 and 743 K. One observes that the peak temperature increases with increasing Nb content from 5 to 15%. This result agrees with those of the ball-milled 3Nb, 7Nb and (Fe50Co50)62Nb8B30 mixtures.

The endothermic peak at about 286.4, 344.5 and 420°C for 3Nb, 7Nb and (Fe50Co50)62Nb8B30 powders, respectively, that can be attributed to the glass transition temperature, Tg, gives evidence of the amorphous state formation. The glass transition temperature of the (Fe50Co50)62Nb8B30 powders increases rapidly up to 25 h of milling, and then remains nearly constant on further milling time (Fig. 16). The increase of Tg might be correlated to the amorphous phase proportion and/or to the change of its composition. The obtained low values compared to those of the amorphous ribbons with the same composition, can be linked to the heterogeneity of the ball-milled samples. The glass transition is not a first order phase transition but a kinetic event dependent on the rearrangement of the system and experimental time scales. Therefore, the transition would be a purely dynamic phenomenon.

Applications of Calorimetry in a Wide Context –

**100 200 300 400 500 600 700 -0,1**

**Temperature (°C)**

**100 200 300 400 500 600 700**

**Exo. heat flow (a. u.)**

3Nb, 7Nb and (Fe50Co50)62Nb8B30 mixtures.

**310 315 320 325 330**

**T(°C)**

**2**

**260 270 280 290 300 T(°C) 286.4°C**

**410 415 420 425 430**

**T (°C)**

**T g**

**Exo. h eat flow (a.u .)**

**140 145 150 155**

**T(°C)**

**3Nb-48h**

**1**

**Tg**

**0,0**

**Exo. heat flow (a.u.)**

**Exo. heat flow (a. u.)**

**0,1**

**0,2**

**Heat flow (W/g)**

**0,3**

**0,4**

36 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**3**

**Figure 13.** DSC scans of 3Nb and 7Nb powder mixtures milled for 48 h [55].

**Exo. heat flow (a.u.)**

**540 550 560**

**Figure 14.** DSC scans of the (Fe50Co50)62Nb8B30 powders milled for 100 and 125 h.

**T(°C)**

**100 h**

**4**

the onset of crystallization by about 20°C because this atom inhibits atomic movement raising the kinetic barrier for crystallization. The small exothermic peaks centred at ~623.5°C (3) and ~675.7°C (4) in the 3Nb powders can be related to the crystallization of Fe-borides.

> **-3 -2 -1 0 1 2**

**Heat flow (mW)**

**136.8°C**

**Temperature (°C) 100 200 300 400 500 600 700**

**104.3°C**

**Exo. heat flow (a.u.)**

**Exo. heat flow (a.u.)**

Thermal stability of the nanocrystalline phases was investigated by DSC for alloys A, B and C milled for 160 h at a heating rate of 10 K/min (Fig. 15). The broad exothermic process starting at 400420 K is due to early surface crystallization (particle surface) and/or internal stress relaxation [58]. In all alloys, an additional exothermic process was detected with a peak temperature between 713 and 743 K. One observes that the peak temperature increases with increasing Nb content from 5 to 15%. This result agrees with those of the ball-milled

The endothermic peak at about 286.4, 344.5 and 420°C for 3Nb, 7Nb and (Fe50Co50)62Nb8B30 powders, respectively, that can be attributed to the glass transition temperature, Tg, gives evidence of the amorphous state formation. The glass transition temperature of the (Fe50Co50)62Nb8B30 powders increases rapidly up to 25 h of milling, and then remains nearly constant on further milling time (Fig. 16). The increase of Tg might be correlated to the amorphous phase proportion and/or to the change of its composition. The obtained low values compared to those of the amorphous ribbons with the same composition, can be linked to the heterogeneity of the ball-milled samples. The glass transition is not a first order

**154.4°C**

**365.4°C 362.4°C**

**354.85°C**

**350 360 370 380 390 400**

**T(°C)**

**377.7°C**

**-2,92 -2,91 -2,90 -2,89**

**Heat flow (Mw)**

**240 245 250 255 260 265 270 -2,93**

**T(°C)**

**261.8°C**

**Tc 249°C**

**7Nb-48h**

**100 200 300 400 500 600 700 -4**

**Temperature (°C)**

**Temperature (°C)**

**-2,32 -2,30**

**Heat flow (Mw)**

**343 344 345 346**

**T(°C)**

**344.5°C**

**125 h**

**2nd run**

**1st run**

**459.5 °C**


**Table 1.** Peak temperature, Tp, enthalpy release, H, and glass transition temperature, Tg, of 7Nb and 3Nb powders milled for 48 h, and (Fe50Co50)62Nb8B30 mixture milled for 100 h [55].

**Figure 15.** DSC scans at a heating rate of 10 K.min-1 of the ball-milled A, B and C powders for 160 h [58].

**Figure 16.** Variation of the glass transition temperature and the amorphous phase proportion of the (Fe50Co50)62Nb8B30 powders as a function of milling time.

38 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

DSC, which measures heat flow to and from a specimen relative to an inert reference, is the most common thermal analysis method used to measure the glass transition. The heat capacity step change at the glass transition yields three temperature values: onset, midpoint and endset. The midpoint is usually calculated as the peak maximum in the first derivative of heat flow (Fig. 1), although it can be calculated as the midpoint of the extrapolated heat capacities before and after the glass transition. This later is the temperature region where an amorphous material changes from a glassy phase to a rubbery phase upon heating, or *vice versa* if cooling. For example, the glass transition is very important in polymer characterization as the properties of a material are highly dependent on the relationship of the polymer end-use temperature to its Tg. In fact, an elastomer will be brittle if its Tg is too high, and the upper use temperature of a rigid plastic is usually limited by softening at Tg. Therefore, an accurate and precise measure of Tg is a prime concern to many plastics manufacturers and end use designers.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 39

activation energy and the peak temperature variation as a function of Nb content (Fig. 18) reveal that the highest peak temperature and activation energy correspond to the 15%Nb alloy. According to the structural and thermal analysis, it can be concluded that the partial substitution of B by Nb favours the stability of nanocrystalline phase with regard to crystal

**0 10 20 30 40 50**

**Milling time (h)**

**Figure 17.** Variation of the amorphous phase Tc in the (Fe50Co50)62Nb8B30 powders as a function of

T E

**Figure 18.** Apparent activation energy and peak temperature of the crystallization process against Nb

5 10 15 at.% Nb

2.4

2.5

2.6

E / eV

2.7

2.8

Stability of the nanostructured Fe-Co-Nb-B powders can be followed by the variation of the magnetic properties such as saturation magnetization, Ms, and coercivity, Hc. The hysteresis loops of ball milled 3Nb powders for 48 h and 7Nb powders for 96 h and heat treated up to 700°C (Fig. 19) display a sigmoidal shape which is usually observed in nanostructured samples with small magnetic domains. This can be correlated to the presence of structural distortions inside grains. One notes that both Ms and Hc values of 3Nb powders are higher than those of 7Nb powders. The increase of Hc from 71 to 115.5 Oe, after heat treatment of the ball milled 3Nb powders for 96 h, points out that the FeCo-rich ferromagnetic grains

**70**

content for alloys A, B and C milled for 160 h [58].

700

710

720

730

T / K

740

750

**80**

**90**

**TC amorphous (°C)**

**100**

**110**

growth.

milling time.

DSC detects the Curie temperature as a change in heat flow and due to the small amount of energy associated with this transition. An endothermic reaction occurs just below the Curie temperature as energy is being absorbed by the sample to induce randomization of the magnetic dipoles. An exothermic event occurs directly after the Curie temperature since no further energy is needed for randomization. Consequently, the line break at about 237°C and 249°C for 3Nb and 7Nb powders (Fig. 13), respectively, can be assigned to the ferroparamagnetic transition at Curie temperature of the amorphous phase. Those values are comparable to that reported for the amorphous (Fe100-xCox)62Nb8B30 bulk metallic glasses [59], where Tc was found to be 245°C for x=0. Accordingly, one can suppose that the amorphous phase composition is Co-free FeBNb-type. Different Tc values of about (157167)°C and (8797)°C have been reported for the as-quenched Fe52Co10Nb8B30 and Fe22Co40Nb8B30 alloys [60], respectively. Tc of the residual amorphous phase exhibits antagonist behaviour for both alloys. It decreases with increasing crystalline fraction for the Corich Fe22Co40Nb8B30 alloy, and shifts to higher temperature for the Ferich Fe52Co10Nb8B30 alloy. Also, lower Tc values in the temperature range (214230)°C were obtained for the as-cast state and in nanocrystalline Fe77B18Nb4Cu ribbons annealed at different temperatures [61].

Fig. 17 shows the evolution of Curie temperature of the amorphous phase in the (Fe50Co50)62Nb8B30 powders against milling time. Since the amorphous phase Curie temperature is very sensitive to the chemical composition, therefore the progressive decrease of Tc with increasing milling time can be attributed to the increase of B and/or Nb content in the amorphous matrix. It has been reported that the Curie temperature of the FeCoNbB amorphous alloys increases with the B content in the amorphous matrix [62]. Both the first and the second DSC scans of the powders milled for 100 and 125 h, respectively, display many endothermic peaks (see the inset in Fig. 14) that can be attributed to Curie temperatures of different Fe-boride phases and the residual matrix (t=125 h). For example, the endothermic peak at T=579.8°C can be related to the Curie temperature of Fe3B [63].

The apparent activation energy of the crystallization process in the alloys A, B and C was evaluated by the Kissinger method. The obtained values 2.47±0.07, 2.63±0.05 and 2.71±0.08 eV for alloys A, B and C, respectively, can be associated with grain growth process. The activation energy and the peak temperature variation as a function of Nb content (Fig. 18) reveal that the highest peak temperature and activation energy correspond to the 15%Nb alloy. According to the structural and thermal analysis, it can be concluded that the partial substitution of B by Nb favours the stability of nanocrystalline phase with regard to crystal growth.

Applications of Calorimetry in a Wide Context –

manufacturers and end use designers.

38 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

DSC, which measures heat flow to and from a specimen relative to an inert reference, is the most common thermal analysis method used to measure the glass transition. The heat capacity step change at the glass transition yields three temperature values: onset, midpoint and endset. The midpoint is usually calculated as the peak maximum in the first derivative of heat flow (Fig. 1), although it can be calculated as the midpoint of the extrapolated heat capacities before and after the glass transition. This later is the temperature region where an amorphous material changes from a glassy phase to a rubbery phase upon heating, or *vice versa* if cooling. For example, the glass transition is very important in polymer characterization as the properties of a material are highly dependent on the relationship of the polymer end-use temperature to its Tg. In fact, an elastomer will be brittle if its Tg is too high, and the upper use temperature of a rigid plastic is usually limited by softening at Tg. Therefore, an accurate and precise measure of Tg is a prime concern to many plastics

DSC detects the Curie temperature as a change in heat flow and due to the small amount of energy associated with this transition. An endothermic reaction occurs just below the Curie temperature as energy is being absorbed by the sample to induce randomization of the magnetic dipoles. An exothermic event occurs directly after the Curie temperature since no further energy is needed for randomization. Consequently, the line break at about 237°C and 249°C for 3Nb and 7Nb powders (Fig. 13), respectively, can be assigned to the ferroparamagnetic transition at Curie temperature of the amorphous phase. Those values are comparable to that reported for the amorphous (Fe100-xCox)62Nb8B30 bulk metallic glasses [59], where Tc was found to be 245°C for x=0. Accordingly, one can suppose that the amorphous phase composition is Co-free FeBNb-type. Different Tc values of about (157167)°C and (8797)°C have been reported for the as-quenched Fe52Co10Nb8B30 and Fe22Co40Nb8B30 alloys [60], respectively. Tc of the residual amorphous phase exhibits antagonist behaviour for both alloys. It decreases with increasing crystalline fraction for the Corich Fe22Co40Nb8B30 alloy, and shifts to higher temperature for the Ferich Fe52Co10Nb8B30 alloy. Also, lower Tc values in the temperature range (214230)°C were obtained for the as-cast state and in

nanocrystalline Fe77B18Nb4Cu ribbons annealed at different temperatures [61].

Fig. 17 shows the evolution of Curie temperature of the amorphous phase in the (Fe50Co50)62Nb8B30 powders against milling time. Since the amorphous phase Curie temperature is very sensitive to the chemical composition, therefore the progressive decrease of Tc with increasing milling time can be attributed to the increase of B and/or Nb content in the amorphous matrix. It has been reported that the Curie temperature of the FeCoNbB amorphous alloys increases with the B content in the amorphous matrix [62]. Both the first and the second DSC scans of the powders milled for 100 and 125 h, respectively, display many endothermic peaks (see the inset in Fig. 14) that can be attributed to Curie temperatures of different Fe-boride phases and the residual matrix (t=125 h). For example, the endothermic peak at T=579.8°C can be related to the Curie temperature of Fe3B [63].

The apparent activation energy of the crystallization process in the alloys A, B and C was evaluated by the Kissinger method. The obtained values 2.47±0.07, 2.63±0.05 and 2.71±0.08 eV for alloys A, B and C, respectively, can be associated with grain growth process. The

**Figure 17.** Variation of the amorphous phase Tc in the (Fe50Co50)62Nb8B30 powders as a function of milling time.

**Figure 18.** Apparent activation energy and peak temperature of the crystallization process against Nb content for alloys A, B and C milled for 160 h [58].

Stability of the nanostructured Fe-Co-Nb-B powders can be followed by the variation of the magnetic properties such as saturation magnetization, Ms, and coercivity, Hc. The hysteresis loops of ball milled 3Nb powders for 48 h and 7Nb powders for 96 h and heat treated up to 700°C (Fig. 19) display a sigmoidal shape which is usually observed in nanostructured samples with small magnetic domains. This can be correlated to the presence of structural distortions inside grains. One notes that both Ms and Hc values of 3Nb powders are higher than those of 7Nb powders. The increase of Hc from 71 to 115.5 Oe, after heat treatment of the ball milled 3Nb powders for 96 h, points out that the FeCo-rich ferromagnetic grains

#### Applications of Calorimetry in a Wide Context – 40 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

might be separated by Nb and/or B-rich phase with weaker ferromagnetic properties. Another possible origin for this behaviour is the increase of Fe2B boride proportion. Nonetheless, for 7Nb mixture Ms increases slightly while Hc remains nearly constant after heat treatment of the powders milled for 48 h. One can conclude that the nanostructured state is maintained after heat treatment.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 41

**12 h**

**Heat flow (a. u.)**

**Figure 20.** DSC plots of the Ni70P30 powders milled for 3 and 12 h at a heating rate of 10°C/min; first (a)

**Heat flow (a. u.)**

**Figure 21.** Enlargement of the low temperature regions of the DSC scan of the Ni70P30 powders milled

The kinetics of Mo dissolution into the α-Fe matrix of the Fe-6Mo mixture has been deduced from the XRD analysis by following the evolution of the (110) diffraction peak intensity of the unmixed Mo as a function of milling time [26]. Since the milling process occurs at room temperature, one can suppose that the temperature is constant. In addition, the milling time can be considered as the necessary time for phase transformation. Consequently, the mixed fraction of Mo which is considered as the fraction transformed, x, can be described by the Johnson-Mehl-Avrami formalism. The double logarithmic plot ln(-ln(1-x)) versus lnt leads to the Avrami parameter n, and the rate constant k. Two stages have been distinguished according to the kinetics parameter values: (i) a first stage with n1= 0.83 and k1= 0.34; and (ii) a second stage with n2= 0.33 and k2 = 0.73. The former proves that the Mo dissolution is very

**(a)**

**342°C**

**100 200 300 400 500 600**

**Temperature (°C)**

**342 344 346 348**

**344.35°C**

**345.5°C**

**Temperature (°C)**

**344.35°C**

**567.6°C**

**346.7°C**

**(b)**

**236.9°C**

**100 200 300 400 500 600**

**220 230 240 250**

**8. Kinetics of powder mixing** 

**8.1. Fe-Mo mixture** 

**236.9°C**

**Temperature (°C)**

**Temperature (°C)**

**3 h 469.4°C**

**(b)**

**Heat flow (a. u.)**

**Exo.**

**Heat flow (a. u.)**

for 12 h.

**(a)**

and second heating runs (b) [64].

**Figure 19.** Hysteresis loops of 3Nb and 7Nb powders milled for 96 h and 48 h, respectively, and after heat treatment up to 700°C [55].

### **7. Ni-P powders**

Thermal annealing leads, in general, to the relaxation of the introduced stresses during the milling process. The DSC curves of the ball-milled Ni70P30 powders for 3 and 12 h (Fig. 20) display different behaviour on heating at a rate of 10°C.min-1. After the first run up to 700°C (scan a), samples are cooled down to ambient temperature, then reheated in the same conditions. One notes that the DSC signal of the second run (scan b) shows a line without any thermal effect indicating that the phase transformation is achieved during the first run [64]. However, for the first run curve, the enthalpy release spreads over the temperature range (100650)°C. The large exothermic reactions at temperatures below 300°C can be attributed to recovery and strain relaxation. The DSC curve of the powder milled for 3 h shows a single exothermic peak at 496.4°C. While, after 12 h of milling, the DSC curve reveals several endothermic peaks, and one exothermic peak at 567.6°C. According to the Curie temperature of pure Ni (Tc = 350°C), the endothermic peaks (Fig. 21) can be related to the magnetic transition temperature of dilute Ni(P) solid solutions. However, the exothermic peak might be assigned to a growth process of Ni2P nanophase. The depression of Tc compared to that of pure Ni indicates that the nearest-neighbour coordinates are essentially changed in the magnetic nanocrystallites by the P additions. The reason for the existence of several magnetic phase states and therefore, several Curie temperatures can be attributed to inhomogeneities since the Curie temperature is sensitive to the chemical short range order and subsequently, to the local Ni environment.

**Figure 20.** DSC plots of the Ni70P30 powders milled for 3 and 12 h at a heating rate of 10°C/min; first (a) and second heating runs (b) [64].

**Figure 21.** Enlargement of the low temperature regions of the DSC scan of the Ni70P30 powders milled for 12 h.

#### **8. Kinetics of powder mixing**

#### **8.1. Fe-Mo mixture**

Applications of Calorimetry in a Wide Context –

state is maintained after heat treatment.

heat treatment up to 700°C [55].

**7. Ni-P powders** 

40 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

might be separated by Nb and/or B-rich phase with weaker ferromagnetic properties. Another possible origin for this behaviour is the increase of Fe2B boride proportion. Nonetheless, for 7Nb mixture Ms increases slightly while Hc remains nearly constant after heat treatment of the powders milled for 48 h. One can conclude that the nanostructured

 **Figure 19.** Hysteresis loops of 3Nb and 7Nb powders milled for 96 h and 48 h, respectively, and after

Thermal annealing leads, in general, to the relaxation of the introduced stresses during the milling process. The DSC curves of the ball-milled Ni70P30 powders for 3 and 12 h (Fig. 20) display different behaviour on heating at a rate of 10°C.min-1. After the first run up to 700°C (scan a), samples are cooled down to ambient temperature, then reheated in the same conditions. One notes that the DSC signal of the second run (scan b) shows a line without any thermal effect indicating that the phase transformation is achieved during the first run [64]. However, for the first run curve, the enthalpy release spreads over the temperature range (100650)°C. The large exothermic reactions at temperatures below 300°C can be attributed to recovery and strain relaxation. The DSC curve of the powder milled for 3 h shows a single exothermic peak at 496.4°C. While, after 12 h of milling, the DSC curve reveals several endothermic peaks, and one exothermic peak at 567.6°C. According to the Curie temperature of pure Ni (Tc = 350°C), the endothermic peaks (Fig. 21) can be related to the magnetic transition temperature of dilute Ni(P) solid solutions. However, the exothermic peak might be assigned to a growth process of Ni2P nanophase. The depression of Tc compared to that of pure Ni indicates that the nearest-neighbour coordinates are essentially changed in the magnetic nanocrystallites by the P additions. The reason for the existence of several magnetic phase states and therefore, several Curie temperatures can be attributed to inhomogeneities since the Curie temperature is sensitive to the chemical short

range order and subsequently, to the local Ni environment.

The kinetics of Mo dissolution into the α-Fe matrix of the Fe-6Mo mixture has been deduced from the XRD analysis by following the evolution of the (110) diffraction peak intensity of the unmixed Mo as a function of milling time [26]. Since the milling process occurs at room temperature, one can suppose that the temperature is constant. In addition, the milling time can be considered as the necessary time for phase transformation. Consequently, the mixed fraction of Mo which is considered as the fraction transformed, x, can be described by the Johnson-Mehl-Avrami formalism. The double logarithmic plot ln(-ln(1-x)) versus lnt leads to the Avrami parameter n, and the rate constant k. Two stages have been distinguished according to the kinetics parameter values: (i) a first stage with n1= 0.83 and k1= 0.34; and (ii) a second stage with n2= 0.33 and k2 = 0.73. The former proves that the Mo dissolution is very

Applications of Calorimetry in a Wide Context – 42 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

slow even non-existent in the early stage of milling (up to 6 h), while the later can be linked to the increased diffusivity by decreasing crystallite size and increasing the grain boundaries area on further milling time.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 43

**Figure 23.** Johnson-Mehl-Avrami plot of the ball-milled Fe57Co21Nb7B15 versus milling time [27, 66].

The mixing kinetics of the Fe57Co21Nb7B15 powders can be described by two stages [27, 66] with different Avrami parameters n = 1.08 and n' = 0.34 (Fig. 23). The lower values of the Avrami parameter can be ascribed to the presence of both Nb and B which favour the grain size refinement and the formation of a highly disordered state. For the (Fe50Co50)62Nb8B30 mixture, two stages have been obtained with different Avrami parameter values n1 = 1.41 and n2 = 0.34 [2]. The former value is comparable to those obtained for the Finemet and Nanoperm [67]. However, it is higher than that obtained during the crystallization of the amorphous FeCoNbB alloy where α-(Fe,Co) nanocrystals with grain size of 15 nm are distributed in the amorphous matrix [65]. Bigot et al. have obtained a value of n = 1.5 for the nanocrystallization of the Finemet [68]. Comparable kinetics parameters have been obtained in the Ni-15Fe-5Mo (n = 1.049 and k = 0.57) [69]. The important fraction of structural defects which is introduced during the milling process favours the phase formation through the diffusion at the surface which is dominant, at lower temperatures, in comparison to the

diffusion by the grain boundaries and the lattice parameter (vacancy's diffusion).

Thermal analysis is widely used in the reaction study of the mechanically alloyed powder particles because of the obtained metastable disordered structures. Hence, thermal annealing leads to the relaxation of the introduced stresses during the milling process. The heat effects are dependent on the structural and microstructural properties of the ball-milled

**8.3. FeCoNbB powders** 

**9. Conclusion** 

powders.

### **8.2. Fe27.9Nb2.2B69.9 mixture**

Amorphization kinetics of the Fe27.9Nb2.2B69.9 (at. %) powders has been deduced from the Mössbauer spectrometry results by following the variation of the α-Fe transformed fraction as a function of milling time [27]. The amorphization process can be described by one stage with an Avrami parameter of about n~1 (Fig. 22). This value is comparable to those obtained for transformations controlled by the diffusion at the interface and dislocations segregation with 0.45< n < 1.1. This might be correlated to the existence of a high density of dislocations and various types of defects as well as to the crystallite size refinement. Comparable values of the Avrami parameter were obtained for the primary crystallization of the amorphous FeCoNbB alloy prepared by melt spinning [65].

**Figure 22.** Johnson-Mehl-Avrami plot of the ball-milled Fe27.9Nb2.2B69.9 versus milling time [28].

**Figure 23.** Johnson-Mehl-Avrami plot of the ball-milled Fe57Co21Nb7B15 versus milling time [27, 66].

#### **8.3. FeCoNbB powders**

Applications of Calorimetry in a Wide Context –

FeCoNbB alloy prepared by melt spinning [65].

area on further milling time.

**8.2. Fe27.9Nb2.2B69.9 mixture** 

42 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

slow even non-existent in the early stage of milling (up to 6 h), while the later can be linked to the increased diffusivity by decreasing crystallite size and increasing the grain boundaries

Amorphization kinetics of the Fe27.9Nb2.2B69.9 (at. %) powders has been deduced from the Mössbauer spectrometry results by following the variation of the α-Fe transformed fraction as a function of milling time [27]. The amorphization process can be described by one stage with an Avrami parameter of about n~1 (Fig. 22). This value is comparable to those obtained for transformations controlled by the diffusion at the interface and dislocations segregation with 0.45< n < 1.1. This might be correlated to the existence of a high density of dislocations and various types of defects as well as to the crystallite size refinement. Comparable values of the Avrami parameter were obtained for the primary crystallization of the amorphous

**Figure 22.** Johnson-Mehl-Avrami plot of the ball-milled Fe27.9Nb2.2B69.9 versus milling time [28].

The mixing kinetics of the Fe57Co21Nb7B15 powders can be described by two stages [27, 66] with different Avrami parameters n = 1.08 and n' = 0.34 (Fig. 23). The lower values of the Avrami parameter can be ascribed to the presence of both Nb and B which favour the grain size refinement and the formation of a highly disordered state. For the (Fe50Co50)62Nb8B30 mixture, two stages have been obtained with different Avrami parameter values n1 = 1.41 and n2 = 0.34 [2]. The former value is comparable to those obtained for the Finemet and Nanoperm [67]. However, it is higher than that obtained during the crystallization of the amorphous FeCoNbB alloy where α-(Fe,Co) nanocrystals with grain size of 15 nm are distributed in the amorphous matrix [65]. Bigot et al. have obtained a value of n = 1.5 for the nanocrystallization of the Finemet [68]. Comparable kinetics parameters have been obtained in the Ni-15Fe-5Mo (n = 1.049 and k = 0.57) [69]. The important fraction of structural defects which is introduced during the milling process favours the phase formation through the diffusion at the surface which is dominant, at lower temperatures, in comparison to the diffusion by the grain boundaries and the lattice parameter (vacancy's diffusion).

#### **9. Conclusion**

Thermal analysis is widely used in the reaction study of the mechanically alloyed powder particles because of the obtained metastable disordered structures. Hence, thermal annealing leads to the relaxation of the introduced stresses during the milling process. The heat effects are dependent on the structural and microstructural properties of the ball-milled powders.

Applications of Calorimetry in a Wide Context – 44 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

### **Author details**

Safia Alleg \* and Saida Souilah *Badji Mokhtar Annaba University, Department of Physics, Laboratoire de Magnétisme et Spectroscopie des Solides (LM2S) B.P. 12, 23000 Annaba, Algeria* 

Joan Joseph Suñol *Dep. De Fisica, Universitat de Girona, Campus Montilivi, 17071 Girona, Spain* 

### **Acknowledgement**

Prof. Safia Alleg is grateful to the University of Girona-spain for the financial support as invited professor. Financial support from AECID A/016051/08 and AECID A/025066/09 projects is acknowledged. Financial support from WLI Algeria is acknowledged.

Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 45

[9] Alleg Safia, Bentayeb Fatima Zohra, Djebbari Chafia, Bessais Lotfi, Greneche Jean Marc (2008) Effect of the milling conditions on the formation of nanostructured Fe-Co

[10] Alleg S, Ibrir M, Fenineche NE, Azzaza S, Suñol JJ(2010) Magnetic and structural characterization of the mechanically alloyed Fe75Si15B10 powders. J. Alloys Compd. 494:

[11] Bansal C, Gao ZQ, Hong L B, Fultz B (1994) Phases and phase stabilities of Fe3X alloys (X=Al, As, Ge, In, Sb, Si, Sn, Zn) prepared by mechanical alloying. J. Appl. Phys.

[12] Macrí PP, Enzo S, Cowlam N, Frattini R, Principi G, Hu WX (1995) Mechanical alloying of immiscible Cu70TM30 alloys (TM = Fe,Co). Philosophical Magazine Part B 71:249-259. [13] Bentayeb FZ, Alleg S, Greneche J M (2007) Structural and microstructural study of Fe-

[14] Dekhil L, Alleg S, Suñol JJ, Greneche JM (2009) X-rays diffraction and Mössbauer spectrometry studies of the mechanically alloyed Fe-6P-1.7C powders. Adv. Pow.

[16] Sherif El-Eskandarany M, Saida J, Inoue A (2002) Amorphization and crystallization behaviours of glassy Zr70Pd30 alloys prepared by different techniques. Acta Mater.

[17] Kissinger HE (1957) Reaction kinetics in differential thermal analysis. Anal. Chem.

[19] Henderson D W (1979) Thermal analysis of non-isothermal crystallization kinetics in

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[25] Kolmogorov AN (1937) Statistical theory of crystallization of metals. Bull. Acad. Sci.

[26] Moumeni H, Alleg S, Greneche JM (2006), Formation of ball-milled Fe-Mo

[27] Souilah S, Alleg S, Djebbari C, Suñol JJ (2012) Magnetic and microstructural properties of the mechanically alloyed Fe57Co21Nb7B15 powder mixture. Mat. Chem. Phys. 132: 766-

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[22] Avrami M (1939) Kinetics of phase change I. J. Chem. Phys. 7: 1103-1112. [23] Avrami M (1940) Kinetics of phase change II. J. Chem. Phys. 8: 212-224. [24] Avrami M(1941) Kinetics of phase change III. J. Chem. Phys. 9: 177-184.

31Cr-12Co mixture prepared by ball milling. J. Alloys Compd. 434: 435-477*.*

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### **10. References**


<sup>\*</sup> Corresponding Author

[9] Alleg Safia, Bentayeb Fatima Zohra, Djebbari Chafia, Bessais Lotfi, Greneche Jean Marc (2008) Effect of the milling conditions on the formation of nanostructured Fe-Co powders. Phys. Stat. Sol. (a) 205: 1641-1646.

Applications of Calorimetry in a Wide Context –

**Author details** 

Joan Joseph Suñol

**10. References** 

Compd. 482: 86-89.

Compd. 388:41-48.

8:2029-2036.

Corresponding Author

 \*

Condens. Matter 18 : 7257-7272.

**Acknowledgement** 

Safia Alleg \* and Saida Souilah

44 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*Dep. De Fisica, Universitat de Girona, Campus Montilivi, 17071 Girona, Spain* 

*Spectroscopie des Solides (LM2S) B.P. 12, 23000 Annaba, Algeria* 

*Badji Mokhtar Annaba University, Department of Physics, Laboratoire de Magnétisme et* 

projects is acknowledged. Financial support from WLI Algeria is acknowledged.

[1] Suryanarayana C (2004) Mechanical alloying and milling. Marcel Dekker. 457-p

characterization of nanostructured FeCo alloys. J. Mat. Sci. 39: 5441-5443.

alloyed Fe-P powders. Int. J. Nanoparticles 3:237-244.

[2] Alleg S, Azzaza S, Bensalem R, Suñol JJ, Khene S, Fillion G (2009) Magnetic and structural studies of mechanically alloyed (Fe50Co50)62Nb8B30 powder mixtures. J. Alloys

[3] Moumeni H, Alleg S, Djebbari C, Bentayeb FZ, Greneche JM (2004) Synthesis and

[4] Bensebaa N, Alleg S, Bentayeb FZ, Bessais L, Greneche JM (2005) Microstructural characterization of Fe-Cr-P-C powder mixture prepared by ball milling. J. Alloys

[5] Bentayeb FZ, Alleg S, Bouzabata B, Greneche JM (2005) Study of alloying mechanisms of ball milled Fe-Cr and Fe-Cr-Co powders. J. Magn. Magn. Mat. 288: 282-296. [6] Tebib W, Alleg S, Bensalem R, Greneche JM (2010) Structural study of the mechanically

[7] Azzaza S, Alleg S, Moumeni H, Nemamcha AR, Rehspringer J L, Greneche J M (2006) Magnetic properties of nanocrystalline ball milled Fe and Fe50Co50 alloy. J. Phys.:

[8] Tebib W, Alleg S, Bensebaa N, Bentayeb FZ, Suñol JJ, Greneche JM (2008) Structural characterization of nanostructured Fe-8P powder mixture. J. Nanosci. Nanotechnol.

Prof. Safia Alleg is grateful to the University of Girona-spain for the financial support as invited professor. Financial support from AECID A/016051/08 and AECID A/025066/09


46 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

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Thermal Stability of the Nanostructured Powder Mixtures Prepared by Mechanical Alloying 47

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[59] Gercsi Zs, Mazaleyrat F, Kane SN, Varga LK (2004) Magnetic and structural study of (Fe1-xCox)62Nb8B30 bulk amorphous alloys. Mater. Sci. Eng. A 375–377: 1048-1052. [60] Gloriant T, Suriňach S, Baró MD (2004) Stability and crystallization of Fe-Co-Nb-B

[61] Hernando A, Navarro I, Gorría P (1995) Iron exchange-field penetration into the amorphous interphases of nanocrystalline materials. Phys. Rev. B 51:3281-3284. [62] Suzuki K, Cadogan JM, Sahajwalla V, Inoue A, Masumoto T (1996) Fe91Zr7B2 soft

[63] Liebermann HH, Marti J, Martis RJ, Wong CP (1989) The effect of microstructure on properties and behaviours of annealed Fe78B13Si9 amorphous alloy ribbon. Metall. Trans.

[64] Alleg S, Rihia G, Bensalem R, Suñol JJ (2009) Structural evolution of the ball-milled

nanocrystalline Gd and *W/*Gd. NanoStruct. Mater 9:455-460.

1268-1273.

45-52.

J. Appl. Phys. 81: 4039-4041.

Nanoparticles 3: 246-256.

Compd. 536S:S394-S397.

alloys. Appl. Phys. Letters 81:1612-1614.

J. Phys.: Condens. Matter 9:2321-2347.

amorphous alloys. J. Non-Crystal. Sol. 333: 320-326.

magnetic alloy. J Appl. Phys. 79: 5149-5151.

Ni70P30 powders. Ann. Chim. Sci. Mat. 34:267-273.

A 20:63-70.


[48] Host J J, Teng M H, Elliot B R, Hwang J H, Mason T O, Johnson D L (1997) Graphite encapsulated nanocrystals produced using a low carbon:metal ratio. J. Mat. Res. 12: 1268-1273.

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122: 35-40.

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applications, Nova Science Publishers: pp. 81-124.

Pd-Si glassy metals. MRS Proceedings 80:195-201.

mechanical alloying. J. Appl. Phys. 72:2978-2983.

[41] Lutterotti L (2000) MAUD CPD Newsletter (IUCr) 24.

milled iron powders. Mat. Sci. Eng. A226-228: 541-545.

ball milling. *J. Phys.: Condens. Matter. 6:4043*–4052.

[34] Cao M G, Fritsch HU, Bergmann HW (1985). Thermochim. Acta 83:23. [35] Lü L, Lai M (1998) Mechanical alloying. Kluwer Academic Publishers. 273 p. [36] Ibrir M (2011) PhD Thesis. Badji Mokhtar Annaba University, Algeria.

analysis using diffraction. IUCr: Newsletter of the CPD, 21:14-15.

Cr20Co80 alloy. J. Alloys Compd. 493: 110-115.

Phys. Status Solidi A 208:2124-2129.

glasses. J. Mater. Sci. 22:4550-4557.

Phys. 122:439-443.

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[28] Alleg S, Hamouda A, Azzaza S, Suñol JJ, Greneche JM (2010) Solid state amorphization transformation in the mechanically alloyed Fe27.9Nb2.2B69.9 powders. Mat. Chem. Phys.

[29] Alleg S, Bensalem R (2011) Nanostructured Fe-based Mixtures Prepared by Mechanical Alloying. In: Jason M. Barker, editor, Powder Engineering, Technology and

[30] Louidi S, Bentayeb FZ, Suñol JJ, Escoda L (2010) Formation study of the ball-milled

[31] Loudjani Nadia, Bensebaa Nadia, Alleg Safia, Djebbari Chaffia, Greneche Jean Marc (2011) Microstructure characterization of ball-milled Ni50Co50 alloy by Rietveld method.

[32] Calka A, Radlinski AP (1986) The effect of surface on the kinetics of crystallization of

[33] Gibson MA, Delamore GW (1987) Crystallization kinetics of some iron-based metallic

[37] Moumeni H, Alleg S, Greneche JM (2005) Structural properties of Fe50Co50 nanostructured powder prepared by mechanical alloying. J. Alloys Compd. 386: 12-19. [38] Moumeni Hayet, Nemamcha Abderrafik, Alleg Safia, Greneche Jean-Marc (2010) Stacking faults and structure analysis of ball-milled Fe-50%Co powders. Mat. Chem.

[39] Brüning R, Samwer K, Kuhrt C, Schultz L (1992) The mixing of iron and cobalt during

[40] Sorescu M, Grabias A (2002) Structural and magnetic properties of Fe50Co50 system.

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[43] Li S, Wang K, Sun L and Wang Z (1992) Simple model for the refinement of

[44] Börner I, Eckert J (1997) Nanostructure formation and steady-state grain size of ball-

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[46] Zhou GF, Bakker H (1994) Atomically disordered nanocrystalline Co2Si by high-energy

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editors. PV96-10, ECS Symposium Proceedings, Pennington, NJ, p. 703.

nanocrystalline grain size during ball milling. Scr. Metall. Mater. 27: 437-442


	- [65] Blazquez JS, Conde CF, Conde A (2001) Crystallization process in (FeCo)78Nb6(BCu)16 alloys. J. Non-Cryst. Solids 287:187-192.

**Chapter 3** 

© 2013 Dhanaraj and Rajesh, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

and reproduction in any medium, provided the original work is properly cited.

**Studies on Growth, Crystal Structure and** 

**Trifluoroacetate Single Crystals** 

Additional information is available at the end of the chapter

P.V. Dhanaraj and N.P. Rajesh

http://dx.doi.org/10.5772/53795

**1. Introduction** 

computing circuits.

**Characterization of Novel Organic Nicotinium** 

Single crystal growth has a prominent role in the present era of rapid scientific and technical advancement, whereas the application of crystals has unbounded limits. New materials are the lifeblood of solid state research and device technology. Nonlinear optical (NLO) crystals have come upon the materials science scene and are being studied by many research groups around the world. These materials operate on light in a way very analogous to the way of semiconductors which operate on electrons to produce very fast electronic switching and

Organic crystals have compounds with carbon atoms as their essential structural elements. The design and synthesis of organic molecules exhibiting NLO properties have been motivated by the tremendous potential for their applications in the fast developing domains of optoelectronics and photonic technologies. The relevance of the organic materials in the present context is, the delocalized electronic structure of π–conjugated organic compound offers a number of tantalizing opportunities in the applications as NLO materials. Extensive research in the last decades has shown that organic crystals often possess a higher degree of optical nonlinearity than their inorganic counterparts [1, 2]. Some of the advantages of organic materials include inherently high nonlinearity, high electronic susceptibility through high molecular polarizability, fast response time, the ease of varied synthesis, scope for altering the properties by functional substitutions, high damage resistance, relative ease of device processing, etc. Organic materials have another advantage over inorganic materials, in that the properties of organic materials can be optimized by modifying the molecular structure using molecular engineering and chemical synthesis [3]. A very large operating bandwidth modulation in organic electro-optic devices can be obtained through


## **Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals**

P.V. Dhanaraj and N.P. Rajesh

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53795

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

alloys. J. Non-Cryst. Solids 287:187-192.

48 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[66] Souilah S (2012) PhD thesis. Badji Mokhtar Annaba University, Algeria.

materials for applications as soft magnets. Prog. Mat. Sci. 44:291-433.

Fe73.5Cu1Nb3Si13.5B9 alloy. J. Magn. Magn. Mater. 133: 299-302.

[69] Shen SY, Hng HH, Oh JT (2004). Mater. Letter 58:2824.

[65] Blazquez JS, Conde CF, Conde A (2001) Crystallization process in (FeCo)78Nb6(BCu)16

[67] McHenry ME, Willard MA, Laughlin DE (1999), Amorphous and nanocrystalline

[68] Bigot J, Lecaude N, Perron JC, Milan C, Ramiarinjaona C, Rialland JF (1994) Influence of annealing conditions on nanocrystallization and magnetic properties in

> Single crystal growth has a prominent role in the present era of rapid scientific and technical advancement, whereas the application of crystals has unbounded limits. New materials are the lifeblood of solid state research and device technology. Nonlinear optical (NLO) crystals have come upon the materials science scene and are being studied by many research groups around the world. These materials operate on light in a way very analogous to the way of semiconductors which operate on electrons to produce very fast electronic switching and computing circuits.

> Organic crystals have compounds with carbon atoms as their essential structural elements. The design and synthesis of organic molecules exhibiting NLO properties have been motivated by the tremendous potential for their applications in the fast developing domains of optoelectronics and photonic technologies. The relevance of the organic materials in the present context is, the delocalized electronic structure of π–conjugated organic compound offers a number of tantalizing opportunities in the applications as NLO materials. Extensive research in the last decades has shown that organic crystals often possess a higher degree of optical nonlinearity than their inorganic counterparts [1, 2]. Some of the advantages of organic materials include inherently high nonlinearity, high electronic susceptibility through high molecular polarizability, fast response time, the ease of varied synthesis, scope for altering the properties by functional substitutions, high damage resistance, relative ease of device processing, etc. Organic materials have another advantage over inorganic materials, in that the properties of organic materials can be optimized by modifying the molecular structure using molecular engineering and chemical synthesis [3]. A very large operating bandwidth modulation in organic electro-optic devices can be obtained through

© 2013 Dhanaraj and Rajesh, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

50 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

its low dielectric constant at low frequencies. Hence they are projected as forefront candidates for fundamental and applied investigations.

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 51

antitumor activity than the well-known cis-platin or doxorubicin [15]. Many of its pharmacological properties are detailed in literature [16-18]. The reported structures of complexes reveal that nicotinic acid and its derivatives acting as bridging ligands through the carboxylate group and pyridyl N atom [19]. We have synthesized the crystalline salt of nicotinium trifluoroacetate and their crystals in monoclinic system were grown by using solution growth technique for the first time. The crystal structure of nicotinium trifluoroacetate in triclinic system has reported by S. Athimoolam and S. Natarajan [20]. Here we report monoclinic polymorph of nicotinium trifluoroacetate, its asymmetric unit contains a protonated nicotinium cation and a trifluroacetate anion. This chapter discusses synthesis, solubility, crystal growth, structural, dielectric and mechanical properties of nicotinium trifluoroacetate (NTF). Thermal properties of NTF were analyzed and compared with that of two nicotinium derivative crystals nicotinium oxalate and nicotinium nitrate

NTF was synthesized by the reaction between nicotinic acid (SRL, India) and trifluoroacetic acid (Merck) taken in equimolar ratio. The growth solution was prepared by adding calculated amount of trifluoroacetic acid slowly in saturated aqueous solution of equimolar nicotinic acid at 50 oC. The continuous stirring of the solution for 6 h at constant temperature using a temperature controlled magnetic stirrer yielded the precipitate of crystalline substance of NTF. Repeated crystallization and filtration processes were applied for the

The nucleation studies were carried out in a constant temperature bath (CTB) with cooling facility of accuracy of 0.01 oC. The solubility at 30 C was determined by dissolving the recrystallized salt of NTF in 100 ml Millipore water of resistivity 18.2 Mcm taken in an air tight container. The solution was stirred continuously for 6 h to achieve stabilization using an immersible magnetic stirrer. After attaining the saturation, the concentration of the solute was estimated gravimetrically. The same procedure is repeated for different temperatures

Metastable zone width is an essential parameter for the growth of large size crystals from solution, since it is the direct measure of the stability of the solution in its supersaturated region. The metastable zone width was measured by adopting the conventional polythermal method [21]. The saturated solution (100 ml) at 30 C was prepared according to the presently determined solubility data. After attaining the saturation, the solution was filtered by the filtration pump and Whatman filter paper of pore size 11 μm. The solution was preheated to 5 C above the saturated temperature for homogenization and left at the superheated temperature for about 1 h before cooling. Then it was slowly cooled at a

monohydrate.

**2. Experimental studies** 

purification of the synthesized compound.

**2.2. Determination of solubility and metastable zone width** 

**2.1. Synthesis of NTF** 

(35, 40, 45 and 50 C).

In organic materials, there is a strong correlation between structure and nonlinear properties. Thus, in the case of second order nonlinear effects, it has been established that the macroscopic susceptibility of the materials χ(2), is related to both the magnitude of the molecular nonlinearities, i.e. the first hyperpolarizability β, and the relative orientation of the molecules in the medium. Therefore, a fundamental limitation for second-order effects to be observed is the non-centrosymmetry requirement, both at the microscopic molecular level and at the macroscopic bulk level. On the other hand, the third order effects described by χ(3) can be present in any medium. The χ(3) coefficients are thus essential in centrosymmetric compounds where the second order coefficients equal zero. They are also important in the non-centrosymmetric molecules. Moreover, these χ(3) coefficients play a part in some experimental determination of χ(2) coefficients. It is for example the case in electric field induced second harmonic generation [4-6] (EFISHG) experiment or in hyper-Rayleigh technique [7-10] where the two-photon absorption (TPA), which is third order effect, can induce fluorescence thus making imprecise the determination of the β coefficient. An ultimate goal for designing the molecules with large third order nonlinearities is to incorporate them into devices used in all optical signals processing [11, 12]. Nonlinear optical absorption (NOA) has shown its potential application in optical information storage, all optical logic gates, laser radiation protection, and locked laser mode. Interest in searching for NOA materials has been gradually increased. Organic molecules have been the subjects of great attention due to their potential applications in nonlinear optics, optical switching, and light emitting diodes. Indeed, the potential use of organic device materials in optoelectronics is now a very serious matter.

In order to achieve good macroscopic nonlinear response in organic crystals, one requires an increase in the number of π electrons and π delocalization length, so as to lead to high molecular hyperpolarizability and also proper orientation of the molecule in the solid-state structure to facilitate high-frequency conversion efficiency. Effective materials generally contain donor and acceptor groups positioned at either end of suitable conjugation path. The increased effective conjugation and the large π delocalization length have been recognized as the factors leading to the large third order nonlinearities. While the engineering for enhancing second order NLO efficiency is relatively well understood, the need for efficient third order molecules and materials still exists. The design of organic polar crystals for the quadratic NLO applications is supported by the observation that organic molecules containing π electron systems asymmetrized by electron donor and acceptor groups are highly polarizable entities [13]. Donor/acceptor benzene derivatives are sure to produce high molecular nonlinearity. So far, many organic Donor–π–Acceptor (D–π–A) type compounds have been studied theoretically and also experimentally [14]. The studies indicate that the organic D–π–A compounds are highly promising candidates for NLO applications.

Nicotinic acid, a B vitamin also known as niacin, and its derivatives have been studied extensively over the last decade due to their biological and chemical importance. Niacin forms coordination complexes with tin (Sn), which have been found to have better antitumor activity than the well-known cis-platin or doxorubicin [15]. Many of its pharmacological properties are detailed in literature [16-18]. The reported structures of complexes reveal that nicotinic acid and its derivatives acting as bridging ligands through the carboxylate group and pyridyl N atom [19]. We have synthesized the crystalline salt of nicotinium trifluoroacetate and their crystals in monoclinic system were grown by using solution growth technique for the first time. The crystal structure of nicotinium trifluoroacetate in triclinic system has reported by S. Athimoolam and S. Natarajan [20]. Here we report monoclinic polymorph of nicotinium trifluoroacetate, its asymmetric unit contains a protonated nicotinium cation and a trifluroacetate anion. This chapter discusses synthesis, solubility, crystal growth, structural, dielectric and mechanical properties of nicotinium trifluoroacetate (NTF). Thermal properties of NTF were analyzed and compared with that of two nicotinium derivative crystals nicotinium oxalate and nicotinium nitrate monohydrate.

### **2. Experimental studies**

### **2.1. Synthesis of NTF**

Applications of Calorimetry in a Wide Context –

optoelectronics is now a very serious matter.

50 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

candidates for fundamental and applied investigations.

its low dielectric constant at low frequencies. Hence they are projected as forefront

In organic materials, there is a strong correlation between structure and nonlinear properties. Thus, in the case of second order nonlinear effects, it has been established that the macroscopic susceptibility of the materials χ(2), is related to both the magnitude of the molecular nonlinearities, i.e. the first hyperpolarizability β, and the relative orientation of the molecules in the medium. Therefore, a fundamental limitation for second-order effects to be observed is the non-centrosymmetry requirement, both at the microscopic molecular level and at the macroscopic bulk level. On the other hand, the third order effects described by χ(3) can be present in any medium. The χ(3) coefficients are thus essential in centrosymmetric compounds where the second order coefficients equal zero. They are also important in the non-centrosymmetric molecules. Moreover, these χ(3) coefficients play a part in some experimental determination of χ(2) coefficients. It is for example the case in electric field induced second harmonic generation [4-6] (EFISHG) experiment or in hyper-Rayleigh technique [7-10] where the two-photon absorption (TPA), which is third order effect, can induce fluorescence thus making imprecise the determination of the β coefficient. An ultimate goal for designing the molecules with large third order nonlinearities is to incorporate them into devices used in all optical signals processing [11, 12]. Nonlinear optical absorption (NOA) has shown its potential application in optical information storage, all optical logic gates, laser radiation protection, and locked laser mode. Interest in searching for NOA materials has been gradually increased. Organic molecules have been the subjects of great attention due to their potential applications in nonlinear optics, optical switching, and light emitting diodes. Indeed, the potential use of organic device materials in

In order to achieve good macroscopic nonlinear response in organic crystals, one requires an increase in the number of π electrons and π delocalization length, so as to lead to high molecular hyperpolarizability and also proper orientation of the molecule in the solid-state structure to facilitate high-frequency conversion efficiency. Effective materials generally contain donor and acceptor groups positioned at either end of suitable conjugation path. The increased effective conjugation and the large π delocalization length have been recognized as the factors leading to the large third order nonlinearities. While the engineering for enhancing second order NLO efficiency is relatively well understood, the need for efficient third order molecules and materials still exists. The design of organic polar crystals for the quadratic NLO applications is supported by the observation that organic molecules containing π electron systems asymmetrized by electron donor and acceptor groups are highly polarizable entities [13]. Donor/acceptor benzene derivatives are sure to produce high molecular nonlinearity. So far, many organic Donor–π–Acceptor (D–π–A) type compounds have been studied theoretically and also experimentally [14]. The studies indicate that the

organic D–π–A compounds are highly promising candidates for NLO applications.

Nicotinic acid, a B vitamin also known as niacin, and its derivatives have been studied extensively over the last decade due to their biological and chemical importance. Niacin forms coordination complexes with tin (Sn), which have been found to have better NTF was synthesized by the reaction between nicotinic acid (SRL, India) and trifluoroacetic acid (Merck) taken in equimolar ratio. The growth solution was prepared by adding calculated amount of trifluoroacetic acid slowly in saturated aqueous solution of equimolar nicotinic acid at 50 oC. The continuous stirring of the solution for 6 h at constant temperature using a temperature controlled magnetic stirrer yielded the precipitate of crystalline substance of NTF. Repeated crystallization and filtration processes were applied for the purification of the synthesized compound.

### **2.2. Determination of solubility and metastable zone width**

The nucleation studies were carried out in a constant temperature bath (CTB) with cooling facility of accuracy of 0.01 oC. The solubility at 30 C was determined by dissolving the recrystallized salt of NTF in 100 ml Millipore water of resistivity 18.2 Mcm taken in an air tight container. The solution was stirred continuously for 6 h to achieve stabilization using an immersible magnetic stirrer. After attaining the saturation, the concentration of the solute was estimated gravimetrically. The same procedure is repeated for different temperatures (35, 40, 45 and 50 C).

Metastable zone width is an essential parameter for the growth of large size crystals from solution, since it is the direct measure of the stability of the solution in its supersaturated region. The metastable zone width was measured by adopting the conventional polythermal method [21]. The saturated solution (100 ml) at 30 C was prepared according to the presently determined solubility data. After attaining the saturation, the solution was filtered by the filtration pump and Whatman filter paper of pore size 11 μm. The solution was preheated to 5 C above the saturated temperature for homogenization and left at the superheated temperature for about 1 h before cooling. Then it was slowly cooled at a

52 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

desired cooling rate of 4 C/h, until the first crystal appeared. The temperature was instantly recorded. The difference between the saturation temperature and nucleation temperature gives the metastable zone width of the system. Then experiment was repeated for different saturation temperatures 35, 40, 45 and 50 C and the corresponding metastable zone widths were measured. Several runs (3–5 times) were carried out under controlled conditions for the confirmation of the saturation and nucleation points. The measured values of solubility and metastable zone width of NTF are shown in Figure 1. It shows that NTF has good solubility in water and it increases almost linearly with temperature. Hence solution growth could be a better method to grow good quality single crystals of NTF. The value of the metastable zone width depends not only on the temperature but also on the type of the crystal and its physicochemical properties [22]. One can observe that the metastable zone width decreases with increasing temperature.

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 53

Morphology of the grown crystals was identified by the single crystal X-ray diffraction studies (Bruker Kappa APEXII). It establishes that the crystal has eight developed faces, out of which (112) and (112) planes are more prominent. For each face, its parallel Friedal plane

is also present in the grown crystal and shown diagrammatically in Figure 3.

**Figure 2.** Photograph of as-grown NTF crystal

**Figure 3.** Morphology representation of NTF crystal

**3. Analysis of physicochemical studies** 

The unit cell parameters and crystal structure of NTF were determined from single crystal X-ray diffraction data obtained with a four-circle Nonius CAD4 MACH3 diffractometer (graphite monochromated, MoKα = 0.71073 Å) at room temperature (293 K). The data reduction was done by using XCAD4 [23] and absorption correction was done by the

**3.1. X-ray diffraction analysis** 

**Figure 1.** Solubility and metastablity curves of NTF

#### **2.3. Crystal growth**

Slow evaporation method was employed for growing the single crystals of NTF. The recrystallized salt was used for the preparation of saturated solution at room temperature (35 oC). The solution was filtered by filtration pump and Whatman filter paper of pore size 11 μm. Then the filtered solution was transferred to a petridish with a perforated lid in order to control the evaporation rate and kept undisturbed in a dust free environment. The single crystal of NTF of size 27 x 12 x 7 mm3 was harvested from mother solution after a growth period of 22 days. The grown single crystal of NTF is shown in the Figure 2.

Morphology of the grown crystals was identified by the single crystal X-ray diffraction studies (Bruker Kappa APEXII). It establishes that the crystal has eight developed faces, out of which (112) and (112) planes are more prominent. For each face, its parallel Friedal plane is also present in the grown crystal and shown diagrammatically in Figure 3.

**Figure 2.** Photograph of as-grown NTF crystal

Applications of Calorimetry in a Wide Context –

width decreases with increasing temperature.

**Figure 1.** Solubility and metastablity curves of NTF

**2.3. Crystal growth** 

52 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

desired cooling rate of 4 C/h, until the first crystal appeared. The temperature was instantly recorded. The difference between the saturation temperature and nucleation temperature gives the metastable zone width of the system. Then experiment was repeated for different saturation temperatures 35, 40, 45 and 50 C and the corresponding metastable zone widths were measured. Several runs (3–5 times) were carried out under controlled conditions for the confirmation of the saturation and nucleation points. The measured values of solubility and metastable zone width of NTF are shown in Figure 1. It shows that NTF has good solubility in water and it increases almost linearly with temperature. Hence solution growth could be a better method to grow good quality single crystals of NTF. The value of the metastable zone width depends not only on the temperature but also on the type of the crystal and its physicochemical properties [22]. One can observe that the metastable zone

Slow evaporation method was employed for growing the single crystals of NTF. The recrystallized salt was used for the preparation of saturated solution at room temperature (35 oC). The solution was filtered by filtration pump and Whatman filter paper of pore size 11 μm. Then the filtered solution was transferred to a petridish with a perforated lid in order to control the evaporation rate and kept undisturbed in a dust free environment. The single crystal of NTF of size 27 x 12 x 7 mm3 was harvested from mother solution after a

growth period of 22 days. The grown single crystal of NTF is shown in the Figure 2.

**Figure 3.** Morphology representation of NTF crystal

### **3. Analysis of physicochemical studies**

### **3.1. X-ray diffraction analysis**

The unit cell parameters and crystal structure of NTF were determined from single crystal X-ray diffraction data obtained with a four-circle Nonius CAD4 MACH3 diffractometer (graphite monochromated, MoKα = 0.71073 Å) at room temperature (293 K). The data reduction was done by using XCAD4 [23] and absorption correction was done by the

54 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

method of ψ–scan [24]. The structure solution and refinement were performed using SHELXTL 6.10 [25]. The crystal structure of NTF was solved by direct methods, and fullmatrix least-squares refinements were performed on F2 using all the unique reflections. All the non-hydrogen atoms were refined with anisotropic atomic displacement parameters, and hydrogen atoms were refined with isotropic displacement factors. The crystallographic data and structure refinement parameters of NTF crystal are presented in Table 1. The crystal structure and packing diagram of NTF are shown in Figures 4 and 5 respectively. The H atom participating in the N–H bond was located from the difference Fourier map and all other H atoms were positioned geometrically and refined using a riding model with C–H = 0.93 Å and O–H = 0.82 Å with Uiso(H) = 1.2 – 1.5 Ueq (parent atom). The absolute configuration is assigned from the starting materials taken for reaction.

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 55

This monoclinic polymorph of NTF crystallized in *I*2/a space group and the asymmetric unit contains a protonated nicotinium cation and a trifluroacetate anion. The angle between the mean plane of the pyridine ring and the mean plane of the acetate group is 48.93o where as in the triclinic form [20], it is 14o and the distance between the anion to cation is 3.134 Å which is 0.463 Å longer than the triclinic form. The structure is stabilized by N–H···O, O– H···O and C–H···O hydrogen bonds and hydrogen bond geometry is given in Table 2.

**Figure 4.** Structure of NTF showing 50% probability displacement ellipsoids with atom numbering

scheme (for clarity, only major components of the disordered fluorine atoms are shown)


**Table 1.** Crystallographic data and structure refinement parameters for NTF

This monoclinic polymorph of NTF crystallized in *I*2/a space group and the asymmetric unit contains a protonated nicotinium cation and a trifluroacetate anion. The angle between the mean plane of the pyridine ring and the mean plane of the acetate group is 48.93o where as in the triclinic form [20], it is 14o and the distance between the anion to cation is 3.134 Å which is 0.463 Å longer than the triclinic form. The structure is stabilized by N–H···O, O– H···O and C–H···O hydrogen bonds and hydrogen bond geometry is given in Table 2.

Applications of Calorimetry in a Wide Context –

54 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

configuration is assigned from the starting materials taken for reaction.

Empirical formula C8H6F3NO4 Formula weight 237.14 Temperature 293(2) K Wavelength 0.71073 Å

Crystal system, space group Monoclinic, *I*2/a

Volume 1911.6 Ǻ<sup>3</sup> Z, Calculated density 8, 1.648 g/cm3 Absorption coefficient 0.167 mm-1

Theta range for data collection 2.48 - 24.96o

Data / restraints / parameters 1680 / 0 / 194

Completeness to theta = 24.96 99.6% Absorption correction ψ– scan

Goodness-of-fit on F2 1.095

Extinction coefficient 0.0040(7)

F(000) 960

Unit cell dimensions a = 15.616(5) Ǻ, α = 90o

Crystal size 0.18 mm x 0.15 mm x 0.13 mm

Limiting indices -18 ≤ h ≤ 18, -8 ≤ k ≤ 1, -19 ≤ l ≤ 19 Reflections collected / unique 3929 / 1680 [R(int) = 0.0204]

Refinement method Full-matrix least-squares on F2

Final R indices [I>2σ(I)] R1 = 0.0353, wR2 = 0.0905 R indices (all data) R1 = 0.0495, wR2 = 0.0976

Largest diff. peak and hole 0.210 and -0.201 e.Å-3

**Table 1.** Crystallographic data and structure refinement parameters for NTF

method of ψ–scan [24]. The structure solution and refinement were performed using SHELXTL 6.10 [25]. The crystal structure of NTF was solved by direct methods, and fullmatrix least-squares refinements were performed on F2 using all the unique reflections. All the non-hydrogen atoms were refined with anisotropic atomic displacement parameters, and hydrogen atoms were refined with isotropic displacement factors. The crystallographic data and structure refinement parameters of NTF crystal are presented in Table 1. The crystal structure and packing diagram of NTF are shown in Figures 4 and 5 respectively. The H atom participating in the N–H bond was located from the difference Fourier map and all other H atoms were positioned geometrically and refined using a riding model with C–H = 0.93 Å and O–H = 0.82 Å with Uiso(H) = 1.2 – 1.5 Ueq (parent atom). The absolute

> b = 7.455(5) Ǻ, β = 95.74o c = 16.503(5) Ǻ, γ = 90o

**Figure 4.** Structure of NTF showing 50% probability displacement ellipsoids with atom numbering scheme (for clarity, only major components of the disordered fluorine atoms are shown)

56 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 57

**Figure 6.** Powder XRD pattern of NTF

**3.2. High-resolution x-ray diffraction (HRXRD) analysis** 

The crystalline perfection of the grown NTF single crystals was characterized by HRXRD analysis by employing a multicrystal X-ray diffractometer designed and developed at National Physical Laboratory [26]. The schematic diagram of this multicrystal X-ray diffractometer is shown in figure 7. The divergence of the X-ray beam emerging from a fine focus X-ray tube (Philips X-ray Generator; 0.4 mm × 8 mm; 2kWMo) is first reduced by a long collimator fitted with a pair of fine slit assemblies. This collimated beam is diffracted twice by two Bonse-Hart [27] type of monochromator crystals and the thus diffracted beam contains well resolved MoK1 and MoK2 components. The MoK1 beam is isolated with the help of fine slit arrangement and allowed to further diffract from a third (111) Si monochromator crystal set in dispersive geometry (+, –, –). Due to dispersive configuration, though the lattice constant of the monochromator crystal and the specimen are different, the dispersion broadening in the diffraction curve of the specimen does not arise. Such an arrangement disperses the divergent part of the MoKα1 beam away from the Bragg diffraction peak and thereby gives a good collimated and monochromatic MoK1 beam at the Bragg diffraction angle, which is used as incident or exploring beam for the specimen crystal. The dispersion phenomenon is well described by comparing the diffraction curves recorded in dispersive (+, –, –) and non-dispersive (+, –, +) configurations [28]. This arrangement improves the spectral purity (λ/ 10-5) of the MoK1 beam. The divergence of the exploring beam in the horizontal plane (plane of diffraction) was estimated to be 3 arc s. The specimen occupies the fourth crystal stage in symmetrical Bragg geometry for diffraction in (+, –, –, +) configuration. The specimen can be rotated about a vertical axis, which is perpendicular to the plane of diffraction, with minimum angular interval of 0.4 arc

**Figure 5.** Molecular packing diagram of NTF viewed down the b-axis


Symmetry codes: (i) 1/2-x,y,-z, (ii) x,1/2-y,1/2+z and (iii) 1-x,-1/2+y,1/2-z.

**Table 2.** Hydrogen bonds geometry of NTF

CCDC No. 779179 contains the supplementary crystallographic data for this paper. These data can be obtained free of charge via www.ccdc.cam.ac.uk/data-request/cif, by e-mailing data-request@ccdc.com.ac.uk or by contacting the Cambridge crystallographic data centre, 12 Union Road, Cambridge CB21 EZ, U.K.; Fax: +44 1223 336033.

Powder X-ray diffraction study was carried out by employing SEIFERT, 2002 (DLX model) diffractometer with CuK (λ = 1.5405 Å) radiation using a tube voltage and current of 40 kV and 30 mA respectively. The grown crystals were finely powdered and have been subjected to powder XRD analysis. The sample was scanned over the range 10–60o at the rate of 1o/min. The indexed powder X-ray diffraction pattern of NTF is given in Figure 6. The well defined Bragg's peaks at specific 2θ angles confirmed the crystallinity of NTF.

**Figure 6.** Powder XRD pattern of NTF

56 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 5.** Molecular packing diagram of NTF viewed down the b-axis

Symmetry codes: (i) 1/2-x,y,-z, (ii) x,1/2-y,1/2+z and (iii) 1-x,-1/2+y,1/2-z.

12 Union Road, Cambridge CB21 EZ, U.K.; Fax: +44 1223 336033.

**Table 2.** Hydrogen bonds geometry of NTF

O(2)–H(2O)···O(4)i

D–H···A d(D–H) d(H···A) d(D···A) <(DHA) N(1)–H(1N)···O(3) 0.97 1.69 2.6468 167

CCDC No. 779179 contains the supplementary crystallographic data for this paper. These data can be obtained free of charge via www.ccdc.cam.ac.uk/data-request/cif, by e-mailing data-request@ccdc.com.ac.uk or by contacting the Cambridge crystallographic data centre,

Powder X-ray diffraction study was carried out by employing SEIFERT, 2002 (DLX model) diffractometer with CuK (λ = 1.5405 Å) radiation using a tube voltage and current of 40 kV and 30 mA respectively. The grown crystals were finely powdered and have been subjected to powder XRD analysis. The sample was scanned over the range 10–60o at the rate of 1o/min. The indexed powder X-ray diffraction pattern of NTF is given in Figure 6. The well

defined Bragg's peaks at specific 2θ angles confirmed the crystallinity of NTF.

C(3)–H(3)···O(1)ii 0.93 2.44 3.3397 163 C(4)–H(4)···O(3)iii 0.93 2.37 3.2929 174

0.82 1.74 2.5460 167

### **3.2. High-resolution x-ray diffraction (HRXRD) analysis**

The crystalline perfection of the grown NTF single crystals was characterized by HRXRD analysis by employing a multicrystal X-ray diffractometer designed and developed at National Physical Laboratory [26]. The schematic diagram of this multicrystal X-ray diffractometer is shown in figure 7. The divergence of the X-ray beam emerging from a fine focus X-ray tube (Philips X-ray Generator; 0.4 mm × 8 mm; 2kWMo) is first reduced by a long collimator fitted with a pair of fine slit assemblies. This collimated beam is diffracted twice by two Bonse-Hart [27] type of monochromator crystals and the thus diffracted beam contains well resolved MoK1 and MoK2 components. The MoK1 beam is isolated with the help of fine slit arrangement and allowed to further diffract from a third (111) Si monochromator crystal set in dispersive geometry (+, –, –). Due to dispersive configuration, though the lattice constant of the monochromator crystal and the specimen are different, the dispersion broadening in the diffraction curve of the specimen does not arise. Such an arrangement disperses the divergent part of the MoKα1 beam away from the Bragg diffraction peak and thereby gives a good collimated and monochromatic MoK1 beam at the Bragg diffraction angle, which is used as incident or exploring beam for the specimen crystal. The dispersion phenomenon is well described by comparing the diffraction curves recorded in dispersive (+, –, –) and non-dispersive (+, –, +) configurations [28]. This arrangement improves the spectral purity (λ/ 10-5) of the MoK1 beam. The divergence of the exploring beam in the horizontal plane (plane of diffraction) was estimated to be 3 arc s. The specimen occupies the fourth crystal stage in symmetrical Bragg geometry for diffraction in (+, –, –, +) configuration. The specimen can be rotated about a vertical axis, which is perpendicular to the plane of diffraction, with minimum angular interval of 0.4 arc

58 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

s. The diffracted intensity is measured by using an in-house developed scintillation counter. To provide two-theta (2B) angular rotation to the detector (scintillation counter) corresponding to the Bragg diffraction angle (B), it is coupled to the radial arm of the goniometer of the specimen stage. The rocking or diffraction curves were recorded by changing the glancing angle (angle between the incident X-ray beam and the surface of the specimen) around the Bragg diffraction peak position B (taken as zero for the sake of convenience) starting from a suitable arbitrary glancing angle. The detector was kept at the same angular position 2B with wide opening for its slit, the so-called scan. This arrangement is very appropriate to record the short range order scattering caused by the defects or by the scattering from local Bragg diffractions from agglomerated point defects or due to low angle and very low angle structural grain boundaries [29].

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 59

min) boundaries [30] whose tilt angles (Tilt angle may be defined as the misorientation angle between the two crystalline regions on both sides of the structural grain boundary) are 18 and 28 arc s from their adjoining regions. The FWHM (full width at half maximum) of the main peak and the very low angle boundaries are respectively 22, 27 and 40 arc s. The low FWHM values and relatively low angular spread of around 200 arc s of the diffraction curve show that the crystalline perfection of the specimen is reasonably good. Thermal fluctuations or mechanical disturbances or segregation of solvent molecules during the growth process could be responsible for the observed very low angle boundaries. It may be mentioned here that such very low angle boundaries could be detected with well resolved peaks in the diffraction curve only because of the high-resolution of the multicrystal X-ray

**Figure 8.** High-resolution X-ray diffraction curve recorded for a typical NTF single crystal specimen

Thermal properties of NTF were analyzed and compared with that of two nicotinium derivative crystals nicotinium oxalate (NOX) and nicotinium nitrate monohydrate (NNM). All these crystals had grown in our laboratory and belong to monoclinic system. Differential thermal analysis (DTA) and thermogravimetric analysis (TGA) of crystals were carried out simultaneously by employing TA instrument Model Q600 SDT thermal analyzer. The sample was heated at a rate of 10 oC/min in inert nitrogen atmosphere. Thermal stability of crystals was further tested using differential scanning calorimetry (DSC). DSC study was performed by using TA instrument Model Q20 in the temperature range 50–300 oC at a

diffractometer used in the present studies.

using 112 diffracting planes

**3.3. Thermal analysis** 

**Figure 7.** Schematic line diagram of multicrystal X-ray diffractometer designed, developed and fabricated at National Physical Laboratory

Before recording the diffraction curve, to remove the non-crystallized solute atoms remained on the surface of the crystal and also to ensure the surface planarity, the specimen was first lapped and chemically etched in a non preferential etchant of water and acetone mixture in 1:2 ratio.

Figure 8 shows the high-resolution X-ray diffraction curve recorded for NTF specimen crystal using 112 diffraction planes using MoKα1 radiation. The solid line (convoluted curve) is well fitted with the experimental points represented by the filled circles. On deconvolution of the diffraction curve, it is clear that the curve contains two additional peaks, which are 18 and 28 arc s away from the main peak (at zero glancing angle). These two additional peaks correspond to two internal structural very low angle (tilt angle ≤ 1 arc min) boundaries [30] whose tilt angles (Tilt angle may be defined as the misorientation angle between the two crystalline regions on both sides of the structural grain boundary) are 18 and 28 arc s from their adjoining regions. The FWHM (full width at half maximum) of the main peak and the very low angle boundaries are respectively 22, 27 and 40 arc s. The low FWHM values and relatively low angular spread of around 200 arc s of the diffraction curve show that the crystalline perfection of the specimen is reasonably good. Thermal fluctuations or mechanical disturbances or segregation of solvent molecules during the growth process could be responsible for the observed very low angle boundaries. It may be mentioned here that such very low angle boundaries could be detected with well resolved peaks in the diffraction curve only because of the high-resolution of the multicrystal X-ray diffractometer used in the present studies.

**Figure 8.** High-resolution X-ray diffraction curve recorded for a typical NTF single crystal specimen using 112 diffracting planes

#### **3.3. Thermal analysis**

Applications of Calorimetry in a Wide Context –

fabricated at National Physical Laboratory

mixture in 1:2 ratio.

58 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

due to low angle and very low angle structural grain boundaries [29].

**Figure 7.** Schematic line diagram of multicrystal X-ray diffractometer designed, developed and

Before recording the diffraction curve, to remove the non-crystallized solute atoms remained on the surface of the crystal and also to ensure the surface planarity, the specimen was first lapped and chemically etched in a non preferential etchant of water and acetone

Figure 8 shows the high-resolution X-ray diffraction curve recorded for NTF specimen crystal using 112 diffraction planes using MoKα1 radiation. The solid line (convoluted curve) is well fitted with the experimental points represented by the filled circles. On deconvolution of the diffraction curve, it is clear that the curve contains two additional peaks, which are 18 and 28 arc s away from the main peak (at zero glancing angle). These two additional peaks correspond to two internal structural very low angle (tilt angle ≤ 1 arc

s. The diffracted intensity is measured by using an in-house developed scintillation counter. To provide two-theta (2B) angular rotation to the detector (scintillation counter) corresponding to the Bragg diffraction angle (B), it is coupled to the radial arm of the goniometer of the specimen stage. The rocking or diffraction curves were recorded by changing the glancing angle (angle between the incident X-ray beam and the surface of the specimen) around the Bragg diffraction peak position B (taken as zero for the sake of convenience) starting from a suitable arbitrary glancing angle. The detector was kept at the same angular position 2B with wide opening for its slit, the so-called scan. This arrangement is very appropriate to record the short range order scattering caused by the defects or by the scattering from local Bragg diffractions from agglomerated point defects or

> Thermal properties of NTF were analyzed and compared with that of two nicotinium derivative crystals nicotinium oxalate (NOX) and nicotinium nitrate monohydrate (NNM). All these crystals had grown in our laboratory and belong to monoclinic system. Differential thermal analysis (DTA) and thermogravimetric analysis (TGA) of crystals were carried out simultaneously by employing TA instrument Model Q600 SDT thermal analyzer. The sample was heated at a rate of 10 oC/min in inert nitrogen atmosphere. Thermal stability of crystals was further tested using differential scanning calorimetry (DSC). DSC study was performed by using TA instrument Model Q20 in the temperature range 50–300 oC at a

60 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

heating rate of 10 oC/min in inert nitrogen atmosphere and sample was placed in the Alumina crucible.

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 61

the crystal for NLO applications. The absence of water of crystallization in the molecular structure is indicated by the absence of the weight loss near 100 oC. Further there is no decomposition near the melting point [31]. This ensures the suitability of the material for possible application in lasers, where the crystals are required to withstand high temperatures. The weight loss starts around 110 oC and weight loss corresponding to decomposition of NTF was observed at 223 oC, which takes place over large temperature range (110–252 oC) where almost all the gaseous fragments like carbon dioxide and ammonia might be liberated. The TGA reveals exactly the same changes shown by DTA. The second endothermic peak in the DTA curve shows that the material is fully decomposed at 223 oC as confirmed by DSC. The small difference in the shape of the second peak may be due to the presence of impurities. The sharpness of the endothermic peaks shows good

In TG-DTA trace of NOX (Figure 11), endothermic peak in DTA trace at 203 oC represents the melting point of the sample. The absence of water of crystallization in the molecular structure is indicated by the absence of the weight loss around 100 oC. TGA trace reveals that weight loss of the sample starts from this region and at 223 oC it shows complete weight loss. The shoulder peaks in DTA after the main peak corresponds to the decomposition of the material. There is no phase transition till the material melts and this enhances the temperature range for the utility of the crystal for applications. Under these conditions, phase transition means common phase transition (e.g., solid-to-liquid, liquid-to-gas etc.).

Figure 12 shows the thermogram for DTA and TGA of NNM. The compound starts to lose single molecule of water of crystallization at about 90 oC and the loss continues up to 102 oC. The weight loss in this temperature range is consistent with the weight of single molecules

degree of crystallinity of the grown sample.

**Figure 11.** TGA-DTA curves of NOX

**Figure 9.** TGA-DTA curves of NTF

**Figure 10.** DSC trace of NTF

TG-DTA and DSC curves of NTF were depicted in Figures 9 and 10 respectively. In DTA curve, first endothermic peak at 152 oC is attributed to meting point of the sample, which is also evident in the DSC curve. Another important observation is that, there is no phase transition till the material melts and this enhances the temperature range for the utility of the crystal for NLO applications. The absence of water of crystallization in the molecular structure is indicated by the absence of the weight loss near 100 oC. Further there is no decomposition near the melting point [31]. This ensures the suitability of the material for possible application in lasers, where the crystals are required to withstand high temperatures. The weight loss starts around 110 oC and weight loss corresponding to decomposition of NTF was observed at 223 oC, which takes place over large temperature range (110–252 oC) where almost all the gaseous fragments like carbon dioxide and ammonia might be liberated. The TGA reveals exactly the same changes shown by DTA. The second endothermic peak in the DTA curve shows that the material is fully decomposed at 223 oC as confirmed by DSC. The small difference in the shape of the second peak may be due to the presence of impurities. The sharpness of the endothermic peaks shows good degree of crystallinity of the grown sample.

**Figure 11.** TGA-DTA curves of NOX

Applications of Calorimetry in a Wide Context –

**Figure 9.** TGA-DTA curves of NTF

**Figure 10.** DSC trace of NTF

Alumina crucible.

60 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

heating rate of 10 oC/min in inert nitrogen atmosphere and sample was placed in the

TG-DTA and DSC curves of NTF were depicted in Figures 9 and 10 respectively. In DTA curve, first endothermic peak at 152 oC is attributed to meting point of the sample, which is also evident in the DSC curve. Another important observation is that, there is no phase transition till the material melts and this enhances the temperature range for the utility of In TG-DTA trace of NOX (Figure 11), endothermic peak in DTA trace at 203 oC represents the melting point of the sample. The absence of water of crystallization in the molecular structure is indicated by the absence of the weight loss around 100 oC. TGA trace reveals that weight loss of the sample starts from this region and at 223 oC it shows complete weight loss. The shoulder peaks in DTA after the main peak corresponds to the decomposition of the material. There is no phase transition till the material melts and this enhances the temperature range for the utility of the crystal for applications. Under these conditions, phase transition means common phase transition (e.g., solid-to-liquid, liquid-to-gas etc.).

Figure 12 shows the thermogram for DTA and TGA of NNM. The compound starts to lose single molecule of water of crystallization at about 90 oC and the loss continues up to 102 oC. The weight loss in this temperature range is consistent with the weight of single molecules

62 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

of water present in the crystal. The DTA curve shows a major endothermic peak, which corresponds to the melting point of NNM at 189 oC. The second weight loss take place over the temperature range 135–235 oC and almost all the compounds decomposed as its gaseous products. The second endothermic peak in the DTA curve at 230 oC attributed to the decomposition temperature of NNM. Summarized results of thermal analysis of NNM are given in Table 3.

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 63

**Figure 13.** DSC curves of NNM, NTF and NO

The FTIR spectrum was recorded using Perkin–Elmer FTIR spectrum RXI spectrometer by KBr pellet technique in the range 400–4000 cm-1 at room temperature (35 oC). In the FTIR spectrum of NTF (Figure 14), the strong band at 3439 cm-1 is attributed to stretching vibrations of O–H groups. The peak at 3086 cm-1 corresponds to the aromatic C–H stretching vibrations in the ring. O–H and C–C stretching vibrations are observed at 2809 cm-1 and 1907 cm-1 respectively. The existence of COO– or COOH groups in the studied crystal was deduced on the basis of vibrational spectra. It is clearly seen that the existence of COOH is illustrated by the very strong infrared band located at 1708 cm-1. Asymmetric stretching vibration of COO– is observed at 1597 cm-1. The peak at 1420 cm-1 is due to symmetric stretching vibration of COO–. The C–H vibrations are occurred at 1369 cm-1. C–H in plane bending vibrational modes in nicotinic acid is assigned to the frequency at 1322 cm-1. It should be noted that the next band at 1194 cm-1 in IR spectrum is assigned to C–F stretching, which is the characteristic vibration peak of CF3 group [32, 33]. The absorption at 1140 cm-1 is also due to the stretching type of vibrations of C–F bonds. The band at 517 cm-1 is assigned to C–C=O wagging. The characteristics bands, one at 836 cm-1 (COO– rocking), one at 746 cm-1 (COO–

scissoring) and the third at 622 cm-1 (COO– wagging) are observed in the IR spectrum.

The dielectric constant is one of the basic electrical properties of solids. Dielectric properties are correlated with the electro-optic property of the crystals [34]. The capacitance (Ccrys) and dielectric loss (tan δ) of NTF crystal were measured using the conventional parallel plate

**3.4. FTIR studies** 

**3.5. Dielectric studies** 

**Figure 12.** TGA-DTA curves of NNM


**Table 3.** Summarized TGA and DTA results of NNM

The figure 13 shows the comparison of DSC curves of NTF with other nicotinium derivative crystals. The calculated values of enthalpy for vapourisation, melting reaction and decomposition reaction for these three materials show that enthalpy value for NTF is less than that of NNM and NOX. As the temperature increases, initially NNM loses its single molecule of water of crystallization in the range 90-102 oC. NTF melts at 152 oC, NNM at 189 oC and NOX at 203 oC respectively. Thus thermal stability of NTF is higher than that of NNM but low when compared to NOX. The low thermal stability of NNM is due to vapourisation of its water molecule.

**Figure 13.** DSC curves of NNM, NTF and NO

#### **3.4. FTIR studies**

Applications of Calorimetry in a Wide Context –

**Figure 12.** TGA-DTA curves of NNM

vapourisation of its water molecule.

**Table 3.** Summarized TGA and DTA results of NNM

given in Table 3.

62 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

of water present in the crystal. The DTA curve shows a major endothermic peak, which corresponds to the melting point of NNM at 189 oC. The second weight loss take place over the temperature range 135–235 oC and almost all the compounds decomposed as its gaseous products. The second endothermic peak in the DTA curve at 230 oC attributed to the decomposition temperature of NNM. Summarized results of thermal analysis of NNM are

The figure 13 shows the comparison of DSC curves of NTF with other nicotinium derivative crystals. The calculated values of enthalpy for vapourisation, melting reaction and decomposition reaction for these three materials show that enthalpy value for NTF is less than that of NNM and NOX. As the temperature increases, initially NNM loses its single molecule of water of crystallization in the range 90-102 oC. NTF melts at 152 oC, NNM at 189 oC and NOX at 203 oC respectively. Thus thermal stability of NTF is higher than that of NNM but low when compared to NOX. The low thermal stability of NNM is due to The FTIR spectrum was recorded using Perkin–Elmer FTIR spectrum RXI spectrometer by KBr pellet technique in the range 400–4000 cm-1 at room temperature (35 oC). In the FTIR spectrum of NTF (Figure 14), the strong band at 3439 cm-1 is attributed to stretching vibrations of O–H groups. The peak at 3086 cm-1 corresponds to the aromatic C–H stretching vibrations in the ring. O–H and C–C stretching vibrations are observed at 2809 cm-1 and 1907 cm-1 respectively. The existence of COO– or COOH groups in the studied crystal was deduced on the basis of vibrational spectra. It is clearly seen that the existence of COOH is illustrated by the very strong infrared band located at 1708 cm-1. Asymmetric stretching vibration of COO– is observed at 1597 cm-1. The peak at 1420 cm-1 is due to symmetric stretching vibration of COO–. The C–H vibrations are occurred at 1369 cm-1. C–H in plane bending vibrational modes in nicotinic acid is assigned to the frequency at 1322 cm-1. It should be noted that the next band at 1194 cm-1 in IR spectrum is assigned to C–F stretching, which is the characteristic vibration peak of CF3 group [32, 33]. The absorption at 1140 cm-1 is also due to the stretching type of vibrations of C–F bonds. The band at 517 cm-1 is assigned to C–C=O wagging. The characteristics bands, one at 836 cm-1 (COO– rocking), one at 746 cm-1 (COO– scissoring) and the third at 622 cm-1 (COO– wagging) are observed in the IR spectrum.

#### **3.5. Dielectric studies**

The dielectric constant is one of the basic electrical properties of solids. Dielectric properties are correlated with the electro-optic property of the crystals [34]. The capacitance (Ccrys) and dielectric loss (tan δ) of NTF crystal were measured using the conventional parallel plate

Applications of Calorimetry in a Wide Context – 64 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

capacitor method with the frequency range 100 Hz to 1 MHz using the Agilent 4284A LCR meter at various temperatures ranging from 40 to 80 oC. A good quality crystal of size 5 × 5 × 2 mm3 was electroded on either side with graphite coating to make it behave like a parallel plate capacitor. The observations were made during cooling of the sample. The air capacitance (Cair) was also measured.

**Figure 14.** FTIR spectrum of NTF

The dielectric constant (εr) of the crystal was calculated using the following relation

$$
\omega\_{\mathbf{r}} = \frac{\mathbf{C\_{crys}}}{\mathbf{C\_{air}}} \tag{1}
$$

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 65

almost a constant at higher frequencies for all temperatures. It is also indicates that dielectric constant increases with increase in temperature. The measurements of dielectric loss at different frequencies and temperatures show the same trend. This dielectric behavior [35] can be understood on the basis that the mechanism of polarization is similar to that of conduction process. The electronic exchange of the number of ions in the crystals gives local displacement of electrons in the direction of the applied field, which in turn gives rise to polarization namely, electronic, ionic, dipolar and space charge polarization. Space charge polarization is generally active at lower frequencies and high temperatures and indicates the perfection of the crystal. As the frequency increases, a point will be reached where the space charge cannot sustain and comply with the external field and hence the polarization decreases, giving rise to decrease in values of εr. At 80 oC, the dielectric constant of NTF crystal at 100 Hz is 10.851, and this value decreases to 1.955 at 1 MHz. Lowering the value of dielectric constant of the interlayer dielectric (ILD) decreases the RC delay, lowers the power consumption and reduces the crosstalk between nearby interconnects [36]. Also the materials with quite low dielectric constant lead to a small RC constant, thus permitting a higher bandwidth in the range of 1012 Hz for light modulation. Thus materials with low

**Figure 15.** Plot of dielectric constant versus applied frequency. Plot of dielectric loss versus applied

Mechanical strength of the materials plays a key role in the device fabrication. Vickers hardness is one of the important deciding factors in selecting the processing (cutting, grinding and polishing) steps of bulk crystal in fabrication of devices based on crystals.

dielectric constant have considerable advantages in this context.

frequency is in inset

**3.6. Mechanical hardness studies** 

As the crystal area was smaller than the plate area of the cell, parallel capacitance of the portion of the cell not filled with the crystal was taken into account and, consequently the above equation becomes

$$\mathcal{E}\_{\mathbf{r}} = \left( \frac{\mathbf{C}\_{\text{cryst}} - \mathbf{C}\_{\text{air}} \left( 1 - \frac{\mathbf{A}\_{\text{cryst}}}{\mathbf{A}\_{\text{air}}} \right)}{\mathbf{C}\_{\text{air}}} \right) \left( \frac{\mathbf{A}\_{\text{air}}}{\mathbf{A}\_{\text{cryst}}} \right) \tag{2}$$

where Acrys is the area of the crystal touching the electrode and Aair is the area of the electrode.

The variation of dielectric constant with frequency at different temperatures (Figure 15) shows that dielectric constant decreases with increasing frequency and finally it becomes almost a constant at higher frequencies for all temperatures. It is also indicates that dielectric constant increases with increase in temperature. The measurements of dielectric loss at different frequencies and temperatures show the same trend. This dielectric behavior [35] can be understood on the basis that the mechanism of polarization is similar to that of conduction process. The electronic exchange of the number of ions in the crystals gives local displacement of electrons in the direction of the applied field, which in turn gives rise to polarization namely, electronic, ionic, dipolar and space charge polarization. Space charge polarization is generally active at lower frequencies and high temperatures and indicates the perfection of the crystal. As the frequency increases, a point will be reached where the space charge cannot sustain and comply with the external field and hence the polarization decreases, giving rise to decrease in values of εr. At 80 oC, the dielectric constant of NTF crystal at 100 Hz is 10.851, and this value decreases to 1.955 at 1 MHz. Lowering the value of dielectric constant of the interlayer dielectric (ILD) decreases the RC delay, lowers the power consumption and reduces the crosstalk between nearby interconnects [36]. Also the materials with quite low dielectric constant lead to a small RC constant, thus permitting a higher bandwidth in the range of 1012 Hz for light modulation. Thus materials with low dielectric constant have considerable advantages in this context.

**Figure 15.** Plot of dielectric constant versus applied frequency. Plot of dielectric loss versus applied frequency is in inset

#### **3.6. Mechanical hardness studies**

Applications of Calorimetry in a Wide Context –

capacitance (Cair) was also measured.

**Figure 14.** FTIR spectrum of NTF

above equation becomes

electrode.

64 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

capacitor method with the frequency range 100 Hz to 1 MHz using the Agilent 4284A LCR meter at various temperatures ranging from 40 to 80 oC. A good quality crystal of size 5 × 5 × 2 mm3 was electroded on either side with graphite coating to make it behave like a parallel plate capacitor. The observations were made during cooling of the sample. The air

The dielectric constant (εr) of the crystal was calculated using the following relation

r

crys air

C C1

where Acrys is the area of the crystal touching the electrode and Aair is the area of the

The variation of dielectric constant with frequency at different temperatures (Figure 15) shows that dielectric constant decreases with increasing frequency and finally it becomes

r

crys

(1)

(2)

C C

As the crystal area was smaller than the plate area of the cell, parallel capacitance of the portion of the cell not filled with the crystal was taken into account and, consequently the

air

crys

C A

A

air crys

air air

 

A A

Mechanical strength of the materials plays a key role in the device fabrication. Vickers hardness is one of the important deciding factors in selecting the processing (cutting, grinding and polishing) steps of bulk crystal in fabrication of devices based on crystals. 66 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Microhardness measurements were done on (112) face of NTF crystal using Leitz-Wetzlar hardness tester fitted with a Vickers diamond indenter at room temperature. The Vickers microhardness number, HV was calculated using the relation [37]:

$$\text{H}\_{\text{V}} = 1.8544 \left( \text{p} / \text{d}^2 \right) \text{kg} / \text{mm}^2 \tag{3}$$

Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 67

Hanneman [42], n should be between 1 and 1.6 for hard materials and above 1.6 for softer ones. Thus NTF crystal belongs to soft material category. Meyer number is a measure of the indentation size effect (ISE). For the normal ISE behaviour, the exponent n < 2. When n > 2,

Single crystals of NTF in monoclinic system were grown by solution growth technique for the first time and its solubility and metastable zone width were determined. X-ray diffraction analysis reveals that NTF crystallizes in monoclinic system with space group *I*2/a and unit cell parameters are a = 15.616(5) Å, b = 7.455(5) Å, c = 16.503(5) Å, and β = 95.74o. HRXRD analysis substantiates the good quality of the crystals. TG-DTA and DSC studies show that NTF melts at 152 oC. It is observed that thermal stability of NTF is in between that of other nicotinium derivative crystals. The FTIR analysis confirms the presence of functional groups constituting NTF. Dielectric measurements indicate that NTF crystal has

[1] Zyss J, Dhenaut C, Van T C, Ledoux I (1993) Quadratic Nonlinear Susceptibility of

[2] Russell V A, Evans C C, Li W, Ward M D (1997) Nanoporous Molecular Sandwiches: Pillared Two-Dimensional Hydrogen-bonded Networks with Adjustable Porosity.

[3] Matos Gomes E D, Venkataramanan V, Nogueira E, Belsley M, Proenca F, Criado A, Dianez M J, Estrada M D,Perez-Garrido S (2000) Synthesis, Crystal Growth and Characterization of a Nonlinear Optical Material–Urea L- Malic Acid. Synth. Met. 115:

[4] Levine B F, Bethea C G (1975) Conjugated Electron Contributions to the Second Order Hyperpolarizability of Substituted Benzene Molecules. J. Chem. Phys. 63: 6-10. [5] Bosshard Ch, Knopfle G, Pretre P, Gunter J P (1992) Second-order Polarizabilities of Nitropyridine DerivativesDetermined with Electric-Field-Induced Second-Harmonic Generation and a Solvatochromic Method: A Comparative Study. J. Appl. Phys. 71:

there is the RISE behaviour [39].

low values of dielectric constant and dielectric loss.

*Department of Physics, Malabar Christian College, Kozhikode, India* 

Octupolar Chiral Ions. Chem. Phys. Lett. 206: 409-414.

*Centre for Crystal Growth, SSN College of Engineering, Kalavakkam, India* 

**4. Conclusions** 

**Author details** 

P.V. Dhanaraj

N.P. Rajesh

**5. References** 

225-228.

1594-1599.

Science 276: 575-579.

where p is the applied load (g) and d is the diagonal length (μm) of the indentation. The indentation time was kept at 10 s and microhardness value was taken as the average of the several impressions made. Figure 16 shows the variation of HV as function of applied load in the range 10–100 g on (112) face of NTF crystal.

**Figure 16.** Variation of Vickers microhardness values versus applied load

It reveals that hardness number increases with increasing applied load. This phenomenon is known as reverse indentation size effect (RISE). When the material is deformed by the indenter, dislocations are generated near the indentation site. The major contribution to the increase in hardness is attributed to the high stress required for homogenous nucleation of dislocations in the small dislocation-free region indented [38]. The RISE can be caused by the relative predominance of nucleation and multiplication of dislocations. The other reason for RISE is that the relative predominance of the activity of either two sets of slip planes of a particular slip system or two slip systems below and above a particular load [39]. The RISE phenomenon essentially takes place in crystals which readily undergo plastic deformation [40]. The relation between load and the size of indentation can be interpreted using Meyer's law, P = k1dn, where k1 is a constant and n is the Meyer's number (or index). The slope of log P versus log d gives the n value and it is estimated to be 2.73. According to Onitsch [41] and Hanneman [42], n should be between 1 and 1.6 for hard materials and above 1.6 for softer ones. Thus NTF crystal belongs to soft material category. Meyer number is a measure of the indentation size effect (ISE). For the normal ISE behaviour, the exponent n < 2. When n > 2, there is the RISE behaviour [39].

### **4. Conclusions**

Applications of Calorimetry in a Wide Context –

the range 10–100 g on (112) face of NTF crystal.

66 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

microhardness number, HV was calculated using the relation [37]:

**Figure 16.** Variation of Vickers microhardness values versus applied load

It reveals that hardness number increases with increasing applied load. This phenomenon is known as reverse indentation size effect (RISE). When the material is deformed by the indenter, dislocations are generated near the indentation site. The major contribution to the increase in hardness is attributed to the high stress required for homogenous nucleation of dislocations in the small dislocation-free region indented [38]. The RISE can be caused by the relative predominance of nucleation and multiplication of dislocations. The other reason for RISE is that the relative predominance of the activity of either two sets of slip planes of a particular slip system or two slip systems below and above a particular load [39]. The RISE phenomenon essentially takes place in crystals which readily undergo plastic deformation [40]. The relation between load and the size of indentation can be interpreted using Meyer's law, P = k1dn, where k1 is a constant and n is the Meyer's number (or index). The slope of log P versus log d gives the n value and it is estimated to be 2.73. According to Onitsch [41] and

Microhardness measurements were done on (112) face of NTF crystal using Leitz-Wetzlar hardness tester fitted with a Vickers diamond indenter at room temperature. The Vickers

where p is the applied load (g) and d is the diagonal length (μm) of the indentation. The indentation time was kept at 10 s and microhardness value was taken as the average of the several impressions made. Figure 16 shows the variation of HV as function of applied load in

2 2 H 1.8544 p / d kg / mm <sup>V</sup> (3)

Single crystals of NTF in monoclinic system were grown by solution growth technique for the first time and its solubility and metastable zone width were determined. X-ray diffraction analysis reveals that NTF crystallizes in monoclinic system with space group *I*2/a and unit cell parameters are a = 15.616(5) Å, b = 7.455(5) Å, c = 16.503(5) Å, and β = 95.74o. HRXRD analysis substantiates the good quality of the crystals. TG-DTA and DSC studies show that NTF melts at 152 oC. It is observed that thermal stability of NTF is in between that of other nicotinium derivative crystals. The FTIR analysis confirms the presence of functional groups constituting NTF. Dielectric measurements indicate that NTF crystal has low values of dielectric constant and dielectric loss.

### **Author details**

P.V. Dhanaraj *Department of Physics, Malabar Christian College, Kozhikode, India* 

N.P. Rajesh *Centre for Crystal Growth, SSN College of Engineering, Kalavakkam, India* 

### **5. References**


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Studies on Growth, Crystal Structure and Characterization of Novel Organic Nicotinium Trifluoroacetate Single Crystals 69

[22] Sangwal K (1989) On The Estimation of Surface Entropy Factor, Interfacial Tension, Dissolution Enthalpy and Metastable Zone-Width for Substances Crystallizing from

[24] North A C T, Phillips D C, Mathews F S (1968) A semi-empirical method of absorption

[26] Lal K, Bhagavannarayana G (1989) A High-Resolution Diffuse X-Ray Scattering Study of Defects in Dislocation-Free Silicon Crystals Grown by the Float-Zone Method and

[27] Bonse U, Hart M (1965) Tailless X–ray Single Crystal Reflection Curves Obtained by

[28] Bhagavannarayana G (1994) High Resolution X-Ray Diffraction Study of As-Grown and BF2+ Implanted Silicon Single Crystals, Ph. D. Thesis, University of Delhi, Delhi, India. [29] Bhagavannarayana G, Kushwaha S K (2010) Enhancement of SHG Efficiency by Urea Doping in ZTS Single Crystals and its Correlation with Crystalline Perfection as Revealed by Kurtz Powder and High-Resolution X-Ray Diffraction Methods. J. Appl.

[30] Bhagavannarayana G, Ananthamurthy R V, Budakoti G C, Kumar B, Bartwal K S (2005) A Study of the Effect of Annealing on Fe-Doped LiNbO3 by HRXRD, XRT and FT-IR. J.

[31] Willard, Merritt, Dean, Settle (1986) Instrumental Methods of Analyses, First Indian

[32] Fuson N, Josien M L, Jones E A, Lawson J R (1952) Infrared and Raman Spectroscopy Studies of Light and Heavy Trifluoroacetic Acids. J. Chem. Phys. 20: 1627-1635. [33] Takeda Y, Suzuki H, Notsu K, Sugimoto W, Sugahara Y (2006) Preparation of a Novel Organic Derivative of the Layered Perovskite Bearing HLaNb2O7·nH2O Interlayer

[34] Aithal P S, Nagaraja H S, Mohan Rao P, Avasti D K, Sarma A (1997) Effect of high energy ion irradiation on electrical and optical properties of organic nonlinear optical

[36] Hatton B D, Landskron K, Hunks W J, Bennett M R, Shukaris D, Pervoic D D, Ozin G A

[38] Kunjomana A G, Chandrasekharan K A (2005) Microhardness Studies of GaTe

[39] Sangwal K (2000) On the Reverse Indentation Size Effect and Microhardness

[40] Li H, Han Y H, Bradt R C (1994) Knoop Microhardness of Single Crystal Sulphur. J.

(2006) Materials Chemistry for Low k-Materials. Mater. Today. 9: 22-31. [37] Mott B W (1956) Microindentation Hardness Testing, Butterworths, London.

Comparison with Czochralski-Grown Crystals. J. Appl. Cryst. 22: 209-215.

[23] Harms K, Wocadlo S, XCAD4, University of Marburg, Germany, 1995.

[25] SHELXTL/PC Version 6.10 Madison, WI: Bruker AXS Inc., 2000.

Surface Trifluoroacetate Groups. Mat. Res. Bull. 41: 834-841.

[35] Anderson J C (1964) Dielectrics, Chapman and Hall.

Whiskers. Cryst. Res. Technol. 40: 782-785.

Measurement of Solids. Mater. Chem. Phys. 63: 145-152.

Multiple Reflection. Appl. Phys. Lett. 7: 238-240.

Solution. J. Cryst. Growth 97: 393-405.

correction. Acta Cryst. A24: 351-359.

Cryst. 43: 154-162.

Appl. Cryst. 38: 768-771.

crystals. Vacuum 48: 991-994.

Mater. Sci. 29: 5641-5645.

Edition: CBS, Delhi.


Phys. Lett. 293: 337-342.

Studies. Opt. Mater. 21: 485–488.

phite. Acta Cryst. C49: 834-837.

Cryst.E61: o2553–o2555.

Aqueous Solutions. J. Cryst. Growth 6: 151-162.

E61:o2674–o2676.

m363-m365.

2657.

2980-2983.

288.

68 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Optical Properties of Chiral Thiolates. Synth. Met. 102: 1548-1549.

Liquid Crystals. J. Nonlinear Opt. Phys. Mater. 5: 89- 98.

[6] Clays K, Persoons A (1991) Hyper-Rayleigh Scattering in Solution. Phys. Rev. Lett. 66:

[7] Clays K, Olbrechts G, Munters T, Persoons A, Kim O K, Choi L S (1998) Enhancement of the Molecular Hyperpolarizability by a Supramolecular Amylose–Dye Inclusion Complex, Studied by Hyper-Rayleigh Scatteringwith Fluorescence Suppression. Chem.

[8] Dhenaut C, Ledoux I, Samuel I D W, Zyss J, Bourgault M, Bozec H L (1995) Chiral Metal Complexes with Large Octupolar Optical Nonlinearities. Nature 374: 339-342. [9] Sylla M, Giffard M, Boucher V, Illien B, Mercier N, Nguyen Phu X (1999) Nonlinear

[10] Ferrier J L, Gazengel J, Nguyen Phu X, Rivoire G (1984) Backscattering in the Picosecond Range: an Optical Triggered Switching Effect. Opt. Commun. 51 (4): 285-

[11] Somac M, Somac A, Davies B L, Humphery M G, Wong M S (2002) Third-Order Optical Nonlinearities of Oligomers, Dendrimers and Polymers Derived from Solution Z-Scan

[12] Natarajan L V, Sutherland R L, Tondiaglia V P, Bunning T J, Adams W W (1996) Electro-Optical Switching Characteristics of Volume Holograms in Polymer Dispersed

[13] Pecaut J, Bagieu-Beucher M (1993) 2–Amino–5–nitropyridiniummonohydrogenphos

[14] Ravindra H J, John Kiran A, Dharmaprakash S M, Satheesh Rai N, Chandrasekharan K, Kalluraya B, Rotermund F (2008) Growth and characterization of an efficient nonlinear

optical D–π–A–π–D type chalcone single crystal. J. Cryst. Growth 310: 4169-4176. [15] Gielen M, Kholufi A E, Biesemans M, Willem R (1992) (2-Methylthio-3- Pyridinecarboxylato)-diethyltin and -di- n-butyltin Compounds: Synthesis, Spectroscopic Characterization and in vitro Antitumour Activity. X-ray Crystal Structure of bis[diethyl(2-methylthio-3-Pyridinecarboxylato)tin] oxide and of diethyltin

[16] Athimoolam S, Anitha K, Rajaram R K (2005) Nicotinium dihydrogenphosphate. Acta

[17] Athimoolam S, Rajaram R K (2005) Bis(nicotinic acid) hydrogen perchlorate. Acta Cryst.

[18] Athimoolam S, Rajaram R K (2005) Dinicotinium sulfate. Acta Cryst. E61: o2764–o2767. [19] Gao S, Liu J W, Huo L H, Sun Z Z, Gao J S, Ng S W (2004) Catena-Poly[[diaquabis(2 chloronicotinato-κ 2O,O')cadmium(II)]- -2-chloronicotinato-κ3O,O':N]. Acta Cryst. C 60:

[20] Athimoolam S, Natarajan, S (2007) Nicotinium trifluoroacetate. Acta Cryst. E 63: 2656-

[21] Nyvlt J, Rychly R, Gottfried J, Wurzelova J (1970) Metastable Zone-Width of Some

bis(2-methylthio-3- pyridinecarboxylate), Polyhedron. 11: 1861-1868.


Applications of Calorimetry in a Wide Context – 70 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Section 2** 

**Application of Isothermal Titration Calorimetry** 

**for Analysis of Proteins and DNA** 

[41] Onitsch E M (1947) Mikroscopia 2: 131-134.

[42] Hanneman M (1941) Metall. Manch. 23: 135-139.

**Application of Isothermal Titration Calorimetry for Analysis of Proteins and DNA** 

Applications of Calorimetry in a Wide Context –

[41] Onitsch E M (1947) Mikroscopia 2: 131-134. [42] Hanneman M (1941) Metall. Manch. 23: 135-139.

70 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Chapter 4** 

© 2013 Martinez et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Isothermal Titration Calorimetry:** 

Jose C. Martinez, Javier Murciano-Calles, Eva S. Cobos, Manuel Iglesias-Bexiga, Irene Luque and Javier Ruiz-Sanz

**by Using Equilibrium Models** 

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53311

drugs to alter their functionalities.

**1. Introduction** 

**Thermodynamic Analysis of the Binding** 

**Thermograms of Molecular Recognition Events** 

The revolution achieved during the last decade in the fields of genomics and proteomics has shown the need of going in-depth into the structural, dynamic, energetic and functional knowledge of biological macromolecules, mainly proteins and nucleic acids. Of special interest is the study of the molecular recognition between such kind of molecules or between them and other biological molecules, for example, natural metabolites or designed

Isothermal titration calorimetry (ITC) is a technique that directly measures the heat exchange accompanying a chemical or biochemical reaction. It is the ideal technique for the investigation of the energetics of ligand binding to biological macromolecules because it provides a complete thermodynamic characterization of the macromolecule-ligand interactions, allowing for the measurement of the binding affinity as well as of the changes in enthalpy and entropy of the process. The nature (enthalpic or entropic) and magnitude of the forces directing the interaction are very important factors to be considered in the design of ligands with specific characteristics. Additionally, the heat capacity of binding can be

From the diverse methodologies that can be applied in the research of binding processes, ITC presents a series of advantages and possibilities, and as such it is considered a very powerful tool. Precluding the structural interpretation, the direct determination of binding thermodynamic parameters becomes necessary to describe the energetic aspects of the

and reproduction in any medium, provided the original work is properly cited.

determined by carrying out titration experiments at different temperatures.

## **Isothermal Titration Calorimetry: Thermodynamic Analysis of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models**

Jose C. Martinez, Javier Murciano-Calles, Eva S. Cobos, Manuel Iglesias-Bexiga, Irene Luque and Javier Ruiz-Sanz

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53311

### **1. Introduction**

The revolution achieved during the last decade in the fields of genomics and proteomics has shown the need of going in-depth into the structural, dynamic, energetic and functional knowledge of biological macromolecules, mainly proteins and nucleic acids. Of special interest is the study of the molecular recognition between such kind of molecules or between them and other biological molecules, for example, natural metabolites or designed drugs to alter their functionalities.

Isothermal titration calorimetry (ITC) is a technique that directly measures the heat exchange accompanying a chemical or biochemical reaction. It is the ideal technique for the investigation of the energetics of ligand binding to biological macromolecules because it provides a complete thermodynamic characterization of the macromolecule-ligand interactions, allowing for the measurement of the binding affinity as well as of the changes in enthalpy and entropy of the process. The nature (enthalpic or entropic) and magnitude of the forces directing the interaction are very important factors to be considered in the design of ligands with specific characteristics. Additionally, the heat capacity of binding can be determined by carrying out titration experiments at different temperatures.

From the diverse methodologies that can be applied in the research of binding processes, ITC presents a series of advantages and possibilities, and as such it is considered a very powerful tool. Precluding the structural interpretation, the direct determination of binding thermodynamic parameters becomes necessary to describe the energetic aspects of the

© 2013 Martinez et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Applications of Calorimetry in a Wide Context – 74 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

binding and, thus, to define and to rationalize macromolecular recognition. Nevertheless, although calorimetry has been widely used as an experimental resource, it has not always been interpreted correctly, mainly due to the difficulty found in extracting thermodynamic information from experimental data. Thus, the rigorous analysis of ITC thermograms should be done under the assumption of theoretical models, able to describe the most significant stages present during the binding process and which application would give rise to valuable thermodynamic information for each of such stages.

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 75

**.** Represents the moles of bound ligand by each mole of

**) and empty (n-**

**) sites** in the

**,**

 Binding of the ligand involves a non-covalent *reversible* interaction to a specific region of the macromolecule, called the *binding site*, usually situated at its surface or close to it. The ligand binding process may induce conformational changes that modify the activity

 When the macromolecule has more than one binding site, the binding of one ligand to one of the sites may change the affinity of the ligand for the rest of binding sites; this feature is known as *co-operativity* and is closely related to the alosterism phenomenon. In some cases, the binding process can result in a change in the aggregation state of the molecules (*polisterism*) or, even, give rise to a new phase in the system (*poliphasic*

The correct characterization of the binding process requires some experimental work in

 **Number of binding sites** per macromolecule for a defined ligand*, n***.** The numeric value can be one or higher, sites can be identical or different in terms of affinity into the same

 **Saturation fraction, θ.** The fraction of the total number of sites of the macromolecule occupied by ligand molecules, which ranges from zero (no occupancy) to one (all sites

 *=n·θ.*  **Binding affinity** of the ligand to the macromolecule, expressed by means of the equilibrium binding constant, *Kb*, or the corresponding Gibbs energy change, *ΔGb=- RT·lnKb*. As mentioned above, ITC experiments provide a complete thermodynamic characterization of the macromolecule-ligand interactions, allowing the determination of the binding affinity as well as the changes in enthalpy, *ΔHb*, and entropy, *ΔSb*, of the

Thus, binding studies can provide the answer to some fundamental questions related to the functional aspects of biological macromolecules, such as, for example: How many binding sites in the macromolecule for a defined ligand exist? What is the affinity of the ligand for each binding site? Is there any dependency or inter-connection among the sites? Can affinity

The experimental data is ideally expressed in terms of changes in the binding parameter,

as a function of the free ligand concentration in solution, *[L]*. In practice, it is necessary to move along the whole equilibrium process, starting usually from a solution containing the free macromolecule where the ligand solution is added progressively until the saturation of all sites is achieved. During this titration process, we should measure the binding parameter, generally by using spectroscopic or calorimetric probes. This kind of approach allows us to know the total concentration of both macromolecule, *[M]T*, and ligand, *[L]T*, in

macromolecule. It ranges between zero and the number of binding sites, *n*.

All these ML interactions present some common features:

order to determine a variety of parameters such as:

occupied). It can be easily deduced that

binding process, where *ΔGb= ΔHb –T· ΔSb*.

**)** is the **relationship between occupied (**

be modulated by the proper ligand molecule or by any other metabolites?

macromolecule. **Binding parameter,** 

macromolecule.

 **/(n-**

the solution.

of the macromolecule; this phenomenon is known as *alosterism*.

processes). These two aspects are not within the scope of this Chapter.

### **2. General aspects of binding equilibrium**

Through this Chapter we are going to scrutinise the use of ITC in the study of binding equilibrium processes, as well as how to design and perform the experiments and the correct way to handle the data and achieve the corresponding fit to the proper equilibrium models. Nevertheless, prior to focusing on the different ITC aspects, we will describe briefly some basic features of binding equilibrium, for which it is crucial to introduce some basic concepts and equilibrium formulas.

### **2.1. Basic concepts**

Apart from the capacity of self-copying, biomolecules are characterized by their ability to specifically interact with other molecules within the cell, which defines their biological functionality. Many of the biochemical processes occurring in living systems are based on, or regulated by, binding interactions between biological macromolecules or with other small molecules. Examples of interactions between macromolecules can be found out in interactions between polypeptide chains to form the quaternary structure of multi-subunit proteins, in the close association of protein and RNA molecules in the ribosome, in the binding of transcription regulators to DNA, protein-protein interactions in many signalling cascades, etc. Besides, many biological macromolecules bind small molecules, for example, enzymes that bind substrates and effector molecules, or proteins that bind metabolites in order to transport or store them. Signalling transmission is also based on interactions, as those of hormones with membrane receptors. Additionally, some of the regulation pathways of the transcription and replication of nucleic acids involve the change of their conformations induced by binding of metallic ions.

The interactions that can take place under different backgrounds and contexts from a physico-chemical point of view, can be summarized into three different types: i) at *equilibrium*, ii) at *steady-state conditions*, and iii) at the *transition between different steady-state conditions*. In this Chapter, we will direct attention to the first case, the binding equilibrium process between a biological macromolecule (such as a protein or a nucleic acid) and a small molecule, called a *ligand*, occurring by *specific* interactions, that is, the ligand (L) binds at specific sites of the macromolecule (M). The establishment of such specific interactions is crucial for the correct functioning of the cell, as happens in the most of biological processes, where one or more macromolecule-ligand (ML) interactions are involved, determining and regulating the biological function.

All these ML interactions present some common features:

Applications of Calorimetry in a Wide Context –

thermodynamic information for each of such stages.

**2. General aspects of binding equilibrium** 

conformations induced by binding of metallic ions.

regulating the biological function.

concepts and equilibrium formulas.

**2.1. Basic concepts** 

74 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

binding and, thus, to define and to rationalize macromolecular recognition. Nevertheless, although calorimetry has been widely used as an experimental resource, it has not always been interpreted correctly, mainly due to the difficulty found in extracting thermodynamic information from experimental data. Thus, the rigorous analysis of ITC thermograms should be done under the assumption of theoretical models, able to describe the most significant stages present during the binding process and which application would give rise to valuable

Through this Chapter we are going to scrutinise the use of ITC in the study of binding equilibrium processes, as well as how to design and perform the experiments and the correct way to handle the data and achieve the corresponding fit to the proper equilibrium models. Nevertheless, prior to focusing on the different ITC aspects, we will describe briefly some basic features of binding equilibrium, for which it is crucial to introduce some basic

Apart from the capacity of self-copying, biomolecules are characterized by their ability to specifically interact with other molecules within the cell, which defines their biological functionality. Many of the biochemical processes occurring in living systems are based on, or regulated by, binding interactions between biological macromolecules or with other small molecules. Examples of interactions between macromolecules can be found out in interactions between polypeptide chains to form the quaternary structure of multi-subunit proteins, in the close association of protein and RNA molecules in the ribosome, in the binding of transcription regulators to DNA, protein-protein interactions in many signalling cascades, etc. Besides, many biological macromolecules bind small molecules, for example, enzymes that bind substrates and effector molecules, or proteins that bind metabolites in order to transport or store them. Signalling transmission is also based on interactions, as those of hormones with membrane receptors. Additionally, some of the regulation pathways of the transcription and replication of nucleic acids involve the change of their

The interactions that can take place under different backgrounds and contexts from a physico-chemical point of view, can be summarized into three different types: i) at *equilibrium*, ii) at *steady-state conditions*, and iii) at the *transition between different steady-state conditions*. In this Chapter, we will direct attention to the first case, the binding equilibrium process between a biological macromolecule (such as a protein or a nucleic acid) and a small molecule, called a *ligand*, occurring by *specific* interactions, that is, the ligand (L) binds at specific sites of the macromolecule (M). The establishment of such specific interactions is crucial for the correct functioning of the cell, as happens in the most of biological processes, where one or more macromolecule-ligand (ML) interactions are involved, determining and


The correct characterization of the binding process requires some experimental work in order to determine a variety of parameters such as:


Thus, binding studies can provide the answer to some fundamental questions related to the functional aspects of biological macromolecules, such as, for example: How many binding sites in the macromolecule for a defined ligand exist? What is the affinity of the ligand for each binding site? Is there any dependency or inter-connection among the sites? Can affinity be modulated by the proper ligand molecule or by any other metabolites?

The experimental data is ideally expressed in terms of changes in the binding parameter, **,** as a function of the free ligand concentration in solution, *[L]*. In practice, it is necessary to move along the whole equilibrium process, starting usually from a solution containing the free macromolecule where the ligand solution is added progressively until the saturation of all sites is achieved. During this titration process, we should measure the binding parameter, generally by using spectroscopic or calorimetric probes. This kind of approach allows us to know the total concentration of both macromolecule, *[M]T*, and ligand, *[L]T*, in the solution.

76 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

#### **2.2. The Adair's equation**

This equation defines the type of equilibrium that can be established between a macromolecule and its ligand upon binding.

#### *2.2.1. Binding to one site*

In order to establish how the equilibrium constants can be determined from experimental data we are going to develop the simplest binding process, described by the binding of a ligand to a macromolecule which has only one binding site. It can be expressed as following:

$$M + L \xleftarrow{K\_b} ML \tag{1} \tag{1}$$

$$K\_b = \frac{\left\lceil ML \right\rceil}{\left\lceil M \right\rceil \left\lceil L \right\rceil} \tag{1}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

(5)

*<sup>M</sup> K·n <sup>b</sup>* **1 2**

**<sup>15</sup> 105** *<sup>b</sup> M·K*

, or the

*n* **1**

is ITC [1, 2]. It can also be achieved by

**0.0 0.2 0.4 0.6 0.8 1.0**

**0.0 0.5 1.0 1.5**

**<sup>15</sup> 105** *<sup>b</sup> M·K·n*

(4)

**A B**

**C D**

**<sup>1</sup> <sup>1</sup>** *<sup>n</sup>*

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 77

*K L <sup>b</sup>*

**1**

log log <sup>1</sup>

*K K b b <sup>L</sup>*

Different representations of simulated data for the binding equilibrium of a ligand to a macromolecule with a single binding site with Kb = 5·105 M-1. (A) Binding curve. (B) Double reciprocal representation.

**0.0 0.1 0.2 0.3 0.4 0.5**

**1**

*[L]* (M) *1/[L]* (M-1)

*L* (μM-1) **2**

**3**

**4**

Another accessible parameter from binding experiments is the *saturation fraction*, *θ*, defined as the fraction of binding sites occupied by ligand. It is related to the binding parameter by

Depending on the techniques used to obtain the experimental data of the binding

saturation fraction, *θ*, and then, to develop the subsequent analysis to determine the rest of

equilibrium dialysis, which allows the calculation of the concentrations of the free ligand in equilibrium with the different species of the macromolecule (free and bound), in order to construct directly the binding curve. Although this technique provides the complete set of experimental data required, it requires extensive work and also needs large amounts of sample.

equilibrium processes, it is possible to determine either the binding parameter,

Scatchard representation:

*n* **1**

**Figure 1.** Binding to one site

**-0.5**

**0.0**

**0.5**

 

*<sup>n</sup> log*

**1.0**

**0.0 0.2 0.4 0.6 0.8 1.0**

> / *n*

the expression:

parameters of interest.

(C) Hill representation. (D) Scatchard representation.

**-6.0 -5.5 -5.0 -4.5**

*)Klog( <sup>b</sup>*

**0 20 40 60 80**

*log [L]*

The most appropriate technique to determine

Although the thermodynamic equilibrium constant that characterizes the binding process, *Kb*, must be expressed as a function of the activities of the different species present at equilibrium, it is usual to use concentrations instead of this, as experimental data contains larger errors than the ones derived from this approximation.

As we have stated previously, a very useful parameter obtained by experimental data is the *binding parameter*, , defined as the average of ligand molecules that are bound per macromolecule, its range from 0 to *n* (number of binding sites per macromolecule). Mathematically it can be defined as:

$$\overline{\mathcal{V}} = \frac{\left[\overline{L}\right]\_b}{\left[\overline{M}\right]\_T} = \frac{\left[ML\right]}{\left[\overline{M}\right] + \left[ML\right]} = \frac{K\_b\left[\overline{L}\right]}{1 + K\_b\left[\overline{L}\right]}\tag{2}$$

The representation of  *versus [L]* (free ligand concentration) gives the so called *binding curve*. As shown in Figure 1, our simple example corresponds to a hyperbolic curve trending asymptotically to the number of sites *n* (*n=1* in this case), because saturation conditions are reached as the free ligand concentration increases.

The value of the equilibrium constant, *Kb*, can be determined from the non-linear fitting of the experimental data, represented in the binding curve, to equation 2. In the case of a single binding site, it is also possible to convert equation 2 into a variety of linear equations to obtain the *Kb* value from the corresponding linear regression.

Such linear representations (Figure 1) can be easily deduced from the previous equations and are named as follows:

Double reciprocal representation:

$$\frac{1}{\overline{\nu}} = 1 + \frac{1}{K\_b \left\lceil \overline{L} \right\rceil} \tag{3}$$

Hill representation:

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 77

$$\log\left(\frac{\overline{\nu}}{1-\overline{\nu}}\right) = \log\left(K\_b\left\lceil L\right\rceil\right) \tag{4}$$

Scatchard representation:

Applications of Calorimetry in a Wide Context –

macromolecule and its ligand upon binding.

**2.2. The Adair's equation** 

*2.2.1. Binding to one site* 

*binding parameter*,

The representation of

and are named as follows:

Hill representation:

Double reciprocal representation:

Mathematically it can be defined as:

76 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*Kb*

larger errors than the ones derived from this approximation.

reached as the free ligand concentration increases.

1 1 <sup>1</sup>

obtain the *Kb* value from the corresponding linear regression.

*M L ML K*

This equation defines the type of equilibrium that can be established between a

In order to establish how the equilibrium constants can be determined from experimental data we are going to develop the simplest binding process, described by the binding of a ligand to a macromolecule which has only one binding site. It can be expressed as following:

Although the thermodynamic equilibrium constant that characterizes the binding process, *Kb*, must be expressed as a function of the activities of the different species present at equilibrium, it is usual to use concentrations instead of this, as experimental data contains

As we have stated previously, a very useful parameter obtained by experimental data is the

macromolecule, its range from 0 to *n* (number of binding sites per macromolecule).

*b b T b*

*curve*. As shown in Figure 1, our simple example corresponds to a hyperbolic curve trending asymptotically to the number of sites *n* (*n=1* in this case), because saturation conditions are

The value of the equilibrium constant, *Kb*, can be determined from the non-linear fitting of the experimental data, represented in the binding curve, to equation 2. In the case of a single binding site, it is also possible to convert equation 2 into a variety of linear equations to

Such linear representations (Figure 1) can be easily deduced from the previous equations

*K L <sup>b</sup>*

*L ML KL M M ML K L*

*b*

, defined as the average of ligand molecules that are bound per

1

 *versus [L]* (free ligand concentration) gives the so called *binding* 

*ML*

(1)

(2)

(3)

*M L*

**Figure 1.** Binding to one site

Different representations of simulated data for the binding equilibrium of a ligand to a macromolecule with a single binding site with Kb = 5·105 M-1. (A) Binding curve. (B) Double reciprocal representation. (C) Hill representation. (D) Scatchard representation.

Another accessible parameter from binding experiments is the *saturation fraction*, *θ*, defined as the fraction of binding sites occupied by ligand. It is related to the binding parameter by the expression: / *n*

Depending on the techniques used to obtain the experimental data of the binding equilibrium processes, it is possible to determine either the binding parameter, , or the saturation fraction, *θ*, and then, to develop the subsequent analysis to determine the rest of parameters of interest.

The most appropriate technique to determine is ITC [1, 2]. It can also be achieved by equilibrium dialysis, which allows the calculation of the concentrations of the free ligand in equilibrium with the different species of the macromolecule (free and bound), in order to construct directly the binding curve. Although this technique provides the complete set of experimental data required, it requires extensive work and also needs large amounts of sample.

#### 78 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The techniques that allow the determination of *θ* values are based on detecting physical change occurring in the macromolecule or in the ligand during the binding process. Such physical change has to be a linear function, as the ligand is bound to the macromolecule. Furthermore, if the macromolecule presents several binding sites, the change must be the same for all of them or, at least, the change relationship between the binding sites must be known. Depending on the nature of the physical change, different techniques may be used: UV-visible spectroscopy, fluorescence, circular dicroism, nuclear magnetic resonance spectroscopy, etc [1, 2].

Isothermal Titration Calorimetry: Thermodynamic Analysis

2 2

2 2

 

> 

> > L

L

*k4*

*k3*

(8)

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 79

2 1 12 1 2

1 1

22 2

*ML ML K L K K L L L M ML ML K L KK L L L*

*b bb b bb*

When more than one binding site exists , the binding process can be described using a **microscopic formulae**, that is, distinguishing each binding site. Thus, as it is shown in Figure 2, the first ligand molecule can bind to binding site 1 of M, being the equilibrium process characterized by the microscopic binding constant *k1*; or to the binding site 2 and then, characterized by *k2*. The second ligand molecule will bind to the free binding site, and the equilibrium will be characterized by *k3* if the free site is the number 2 or *k4* if it is the

Schematic representation to distinguish between the macroscopic and microscopic formulae for the binding

1

L

**+** L

**ML** *Kb***<sup>1</sup>** *Kb***<sup>2</sup>**

**+**

L

For the case we are explaining, the meaning of having equivalent binding sites is that *k1* = *k2* and *k3* = *k4*. Also, independent binding sites imply that *k1* = *k4* and *k2* = *k3*. So, in binding processes where all binding sites are equivalent and independent, all microscopic equilibrium constants will be identical. The relations between macroscopic, *Kb*, and

L

2

equilibriums of a general ligand L to a macromolecule with two binding sites.

*k2*

*k1*

**Figure 2.** Binding to two sites

**+**

**+** L

L

1

2

<sup>2</sup> 1 12 1 2

The binding equilibrium constants *Kb* and *β* are named as *macroscopic constants*.

, can be calculated as:

the binding parameter,

number 1.

*2.2.2.2. Microscopic formulae*

In this case, where the macromolecule has two equivalent and independent binding sites,

#### *2.2.2. Binding to two equivalent and independent sites*

#### *2.2.2.1. Macroscopic formulae*

Here, we are going to describe the formulae of the equilibrium processes corresponding to the binding of a ligand to a macromolecule with two binding sites. In this stage, we will focus on the simplest situation, where both sites are equal in affinity and independent, *i.e.*, not influencing each other upon ligand binding. Binding schemes where these basic assumptions do not occur can be useful to describe cooperative interactions and will be described later on in this Chapter. To obtain the binding parameters we can use elementary thermodynamics for the simplest non-cooperative cases, but as the cases turn more complex, this formulae becomes very laborious and a more general formulae is needed.

In order to strengthen the binding concepts, we will start by applying the classical formulae to this simple case, before the description of the general formulae introduced in the biochemical field by Wyman [3], which is useful for the formulae of more complicated binding schemes. Thus, in the case of a macromolecule with two equivalent and independent binding sites, the description of the formulae from a **macroscopic** point of view can be developed in two different but equivalent ways:

 Stage formulae: A first equilibrium stage is considered, where M binds to one ligand molecule, L, followed by a second stage where a second L molecule binds to M, achieving saturation. These two stages are characterized by their corresponding equilibrium constants as follows:

$$\begin{array}{ll} M + L \leftarrow \xrightarrow{K\_{b1}} ML & \begin{array}{c} \text{ML} \end{array} \\\\ \text{ML} + L \leftarrow \xrightarrow{K\_{b2}} ML\_2 \end{array} \\\\ \text{ML} + L \leftarrow \xrightarrow{K\_{b2}} ML\_2$$

 Global formulae: The equilibriums take place between both the free and the bound M species to either one or two ligand molecules. The equilibrium constants for this formulae are related with the ones of the previous formulae as follows:

$$\begin{aligned} \text{ML} + \text{L} & \xleftarrow{\beta\_1} \text{ML} & \qquad \beta\_1 = \frac{\left[\text{ML}\right]}{\left[\text{M}\right]\left[\text{L}\right]} = \text{K}\_{b1} & \quad \beta\_2 = \frac{\left[\text{ML}\_2\right]}{\left[\text{M}\right]\left[\text{L}\right]^2} = \text{K}\_{b1} \cdot \text{K}\_{b2} \\ & \quad \text{ML} + 2\text{L} \leftarrow \frac{\beta\_2}{\left[\text{M}\right]} \cdot \text{ML}\_2 \end{aligned} \tag{7}$$

The binding equilibrium constants *Kb* and *β* are named as *macroscopic constants*.

In this case, where the macromolecule has two equivalent and independent binding sites, the binding parameter,, can be calculated as:

$$\overline{\rho} = \frac{\left[ML\right] + 2\left[ML\_2\right]}{\left[M\right] + \left[ML\right] + \left[ML\_2\right]} = \frac{K\_{b1}\left[L\right] + 2K\_{b1}K\_{b2}\left[L\right]^2}{1 + K\_{b1}\left[L\right] + K\_{b1}K\_{b2}\left[L\right]^2} = \frac{\beta\_1\left[L\right] + 2\beta\_2\left[L\right]^2}{1 + \beta\_1\left[L\right] + \beta\_2\left[L\right]^2} \tag{8}$$

#### *2.2.2.2. Microscopic formulae*

Applications of Calorimetry in a Wide Context –

spectroscopy, etc [1, 2].

*2.2.2.1. Macroscopic formulae* 

78 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*2.2.2. Binding to two equivalent and independent sites* 

can be developed in two different but equivalent ways:

equilibrium constants as follows:

1

*b*

*K*

2

*b*

*K*

*ML L ML*

1

2

*M L ML*

2

2

2

The techniques that allow the determination of *θ* values are based on detecting physical change occurring in the macromolecule or in the ligand during the binding process. Such physical change has to be a linear function, as the ligand is bound to the macromolecule. Furthermore, if the macromolecule presents several binding sites, the change must be the same for all of them or, at least, the change relationship between the binding sites must be known. Depending on the nature of the physical change, different techniques may be used: UV-visible spectroscopy, fluorescence, circular dicroism, nuclear magnetic resonance

Here, we are going to describe the formulae of the equilibrium processes corresponding to the binding of a ligand to a macromolecule with two binding sites. In this stage, we will focus on the simplest situation, where both sites are equal in affinity and independent, *i.e.*, not influencing each other upon ligand binding. Binding schemes where these basic assumptions do not occur can be useful to describe cooperative interactions and will be described later on in this Chapter. To obtain the binding parameters we can use elementary thermodynamics for the simplest non-cooperative cases, but as the cases turn more complex,

In order to strengthen the binding concepts, we will start by applying the classical formulae to this simple case, before the description of the general formulae introduced in the biochemical field by Wyman [3], which is useful for the formulae of more complicated binding schemes. Thus, in the case of a macromolecule with two equivalent and independent binding sites, the description of the formulae from a **macroscopic** point of view

 Stage formulae: A first equilibrium stage is considered, where M binds to one ligand molecule, L, followed by a second stage where a second L molecule binds to M, achieving saturation. These two stages are characterized by their corresponding

 Global formulae: The equilibriums take place between both the free and the bound M species to either one or two ligand molecules. The equilibrium constants for this

*M L ML K K K*

1 2

1 1 2 2 1 2

 

*ML ML*

*M L M L*

*ML ML*

*M L ML L*

2

*b b b*

*b b*

2

·

(6)

(7)

this formulae becomes very laborious and a more general formulae is needed.

*M L ML K K*

formulae are related with the ones of the previous formulae as follows:

When more than one binding site exists , the binding process can be described using a **microscopic formulae**, that is, distinguishing each binding site. Thus, as it is shown in Figure 2, the first ligand molecule can bind to binding site 1 of M, being the equilibrium process characterized by the microscopic binding constant *k1*; or to the binding site 2 and then, characterized by *k2*. The second ligand molecule will bind to the free binding site, and the equilibrium will be characterized by *k3* if the free site is the number 2 or *k4* if it is the number 1.

Schematic representation to distinguish between the macroscopic and microscopic formulae for the binding equilibriums of a general ligand L to a macromolecule with two binding sites.

#### **Figure 2.** Binding to two sites

For the case we are explaining, the meaning of having equivalent binding sites is that *k1* = *k2* and *k3* = *k4*. Also, independent binding sites imply that *k1* = *k4* and *k2* = *k3*. So, in binding processes where all binding sites are equivalent and independent, all microscopic equilibrium constants will be identical. The relations between macroscopic, *Kb*, and

#### 80 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

microscopic, *k*, equilibrium constants are: 1 <sup>2</sup> *K k <sup>b</sup>* and <sup>2</sup> <sup>2</sup> *<sup>b</sup> <sup>K</sup> <sup>k</sup>* . Thus, although microscopic constants are identical, the macroscopic ones are different due to statistical factors. By using the microscopic constants instead of the macroscopic ones, a simpler expression for the binding parameter than that given in equation 8 is obtained:

$$
\overline{\mathcal{V}} = \frac{2k\left\lceil L \right\rceil}{1 + k\left\lceil L \right\rceil} \tag{9}
$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

` (13)

(14)

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 81

2 <sup>1</sup> 1 2 1 1 · · · · · · ·....· · · *<sup>i</sup> <sup>M</sup> iii ii i i i L K ML L K K ML L K K K M L* (12)

1

` (15)

(17)

*bi*

(16)

*j*

*i*

1 1

*KK K K*

····

*i i i j i*

Taking into account the equation 11, the binding parameter, expressed in terms of the

· ·

*<sup>n</sup> <sup>i</sup> i*

*i L*

·

This equation is known as *Adair's general equation*, being the denominator the so called

As equation 14 presents a very high number of macroscopic constants, it is interesting to deduce the relation between microscopic and macroscopic equilibrium constants, to obtain a more simple expression for the binding parameter. Firstly, it is necessary to know the number of possible microscopic states of each macroscopic species. Thus, for MLi species it will be the number of different ways to arrange *i* ligands into *n* binding sites, which corresponds to the combinatorial of *n* elements taken in groups of *i*. Since all binding sites are equivalent and independent, all the possible microscopic forms for any macroscopic species are equally probable and, therefore, they will be at the same concentration; then, the concentration of the macroscopic MLi species expressed as the concentration of its

> ! ! ! *i i micro*

> > ( )! !

*ML n i i ML <sup>i</sup> k K ML L n i i ML L n i* 

> ! ! ! *i*

The binding parameter expressed in terms of microscopic constants can be obtained from

*<sup>n</sup> <sup>k</sup> n ii*

( 1)!( 1)! 1

1 1

*i micro i*

*i i micro*

*i*

The macroscopic constant *βi* is obtained from equations 13 and 16 as

*<sup>n</sup> ML ML n ii*

*L*

*<sup>n</sup> <sup>i</sup> i i*

1

*i*

0

*i*

*ML*

*M L*

So:

macroscopic constants, is:

*binding polynomial*.

microscopic forms is:

equations 14 and 17 as

So the microscopic equilibrium constant, k, will be:

Therefore, it is interesting to know the relationships between the equilibrium constants obtained using the different formulae; such relationships between microscopic and macroscopic constants may allow it to be deduced whether the binding sites are independent or not. Meanwhile, the use of microscopic constants will simplify the equation of the binding parameter which, as mentioned above, is the experimentally accessible parameter, besides the fraction saturation.

#### *2.2.3. Binding to n equivalent and independent sites*

We can obtain the relationship between the different types of binding constants for the general case of a macromolecule having *n* equivalent and independent binding sites. Firstly, we proceed to apply the macroscopic formulae in its two ways, which are summarized in the next scheme:

$$\begin{array}{cccc}\text{Stage formulation} & & \text{Global formulation} \\ \hline \text{M+L} & \xleftarrow{\text{K}\_{\text{th}}} & \text{ML} & \xleftarrow{\beta\_{1}} \text{ML} \\ \text{ML+L} & \xleftarrow{\text{K}\_{\text{th}}} & \text{ML} & \xleftarrow{\beta\_{1}} \text{ML} \\ \vdots & & & \vdots \\ \text{ML}\_{i\_{1}} & \xleftarrow{\text{K}\_{\text{th}}} & \text{ML}\_{i} & \xleftarrow{\beta\_{1}} \text{ML} & \xleftarrow{\beta\_{1}} \text{ML}\_{i} \\ \vdots & & & \vdots \\ \vdots & & & \vdots \\ \text{ML}\_{n-1} & \xleftarrow{\text{K}\_{\text{th}}} & \text{ML}\_{n} & \xleftarrow{\beta\_{1}} \text{ML}\_{\text{min}} \end{array} \tag{10}$$

Looking at the equations defining the macroscopic binding parameter (equations 2 and 8) we can easily deduce that, in the case of having *n* equivalent and independent binding sites, this variable can be written in general as

$$\overline{\nabla} = \frac{\left[\begin{array}{c} \underline{L} \end{array}\right]\_b}{\left[\begin{array}{c} \underline{M} \end{array}\right]\_T} = \frac{\sum\_{i=1}^n i \left[\begin{array}{c} ML\_i \end{array}\right]}{\sum\_{i=0}^n \left[ML\_i \right]} \tag{11}$$

where MLi refers to the macromolecule with *i* bound ligand molecules. For a general stage *i* we can obtain the relation between both macroscopic constants, considering that the concentration of MLi may be expressed as:

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 81

$$\mathbb{E}\left[\left.ML\_{i}\right\|\right] = K\_{i}\left\{\left.ML\_{i-1}\right\|\right\}\left[L\right] = K\_{i}\cdot K\_{i-1}\cdot\left\{\left.ML\_{i-2}\right\|\right\}\left[L\right]^{2} = K\_{i}\cdot K\_{i-1}\cdot... \cdot K\_{1}\cdot\left\{\left.M\right\|\right\}L\right]^{i} \tag{12}$$

So:

Applications of Calorimetry in a Wide Context –

parameter, besides the fraction saturation.

the next scheme:

*2.2.3. Binding to n equivalent and independent sites* 

bi

K

K K

bn

K

this variable can be written in general as

concentration of MLi may be expressed as:

80 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

expression for the binding parameter than that given in equation 8 is obtained:

microscopic, *k*, equilibrium constants are: 1 <sup>2</sup> *K k <sup>b</sup>* and <sup>2</sup> <sup>2</sup> *<sup>b</sup> <sup>K</sup> <sup>k</sup>* . Thus, although microscopic constants are identical, the macroscopic ones are different due to statistical factors. By using the microscopic constants instead of the macroscopic ones, a simpler

> 2 1

*k L k L*

(9)

Therefore, it is interesting to know the relationships between the equilibrium constants obtained using the different formulae; such relationships between microscopic and macroscopic constants may allow it to be deduced whether the binding sites are independent or not. Meanwhile, the use of microscopic constants will simplify the equation of the binding parameter which, as mentioned above, is the experimentally accessible

We can obtain the relationship between the different types of binding constants for the general case of a macromolecule having *n* equivalent and independent binding sites. Firstly, we proceed to apply the macroscopic formulae in its two ways, which are summarized in

> b1 1 b2 2

 

M+L ML M+L ML ML+L M+2L ML

*Stage formulation Global formulation*

*ML*

 

 

i-1 i i

*i*

(10)

(11)

*n*

ML ML M+iL ML

ML M+nL ML

Looking at the equations defining the macroscopic binding parameter (equations 2 and 8) we can easily deduce that, in the case of having *n* equivalent and independent binding sites,

*n*

*ML*

n-1 n

1

*b i n*

*T*

*M*

*i*

*i*

*ML*

*n*

*i ML <sup>L</sup>*

0

*i*

where MLi refers to the macromolecule with *i* bound ligand molecules. For a general stage *i* we can obtain the relation between both macroscopic constants, considering that the

$$\mathcal{J}\_{i}\mathcal{J}\_{i} = \frac{\left[\overline{\,\,M\boldsymbol{L}\_{i}}\right]}{\left[\overline{\,\,M}\right]\left[\overline{\,\,L}\right]^{i}} = K\_{i}\boldsymbol{K}\_{i-1}\cdots\boldsymbol{K}\_{1} = \prod\_{j=1}^{i}\boldsymbol{K}\_{j} \tag{13}$$

Taking into account the equation 11, the binding parameter, expressed in terms of the macroscopic constants, is:

$$\overline{\mathcal{V}} = \frac{\sum\_{i=1}^{n} i \cdot \mathcal{O}\_{i} \left\lceil \overline{\mathcal{L}} \right\rceil^{i}}{\sum\_{i=0}^{n} \mathcal{O}\_{i} \left\lceil \overline{\mathcal{L}} \right\rceil^{i}} \tag{14}$$

This equation is known as *Adair's general equation*, being the denominator the so called *binding polynomial*.

As equation 14 presents a very high number of macroscopic constants, it is interesting to deduce the relation between microscopic and macroscopic equilibrium constants, to obtain a more simple expression for the binding parameter. Firstly, it is necessary to know the number of possible microscopic states of each macroscopic species. Thus, for MLi species it will be the number of different ways to arrange *i* ligands into *n* binding sites, which corresponds to the combinatorial of *n* elements taken in groups of *i*. Since all binding sites are equivalent and independent, all the possible microscopic forms for any macroscopic species are equally probable and, therefore, they will be at the same concentration; then, the concentration of the macroscopic MLi species expressed as the concentration of its microscopic forms is:

$$
\left[\begin{array}{c} ML\_{i} \\ \end{array}\right] = \frac{n!}{\left(n-i\right)!i!} \left[\begin{array}{c} ML\_{i} \\ \end{array}\right]\_{micro} \text{ \textquotedblleft} \tag{15}
$$

So the microscopic equilibrium constant, k, will be:

$$k = \frac{\left[ML\_i\right]\_{micro}}{\left[ML\_{i-1}\right]\_{micro}\left[L\right]} = \frac{(n-i)!i!\left[ML\_i\right]}{(n-i+1)!(i-1)!\left[ML\_{i-1}\right]\left[L\right]} = \frac{i}{n-i+1}K\_{bi} \tag{16}$$

The macroscopic constant *βi* is obtained from equations 13 and 16 as

$$\beta\_i = \frac{n!}{\left(n-i\right)!i!}k^i \tag{17}$$

The binding parameter expressed in terms of microscopic constants can be obtained from equations 14 and 17 as

82 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

$$\overline{\nabla} = \frac{\sum\_{i=1}^{n} \frac{n!}{(n-i)!i!} k^i \left\lceil \overline{L} \right\rceil^i}{\sum\_{i=0}^{n} \frac{n!}{(n-i)!i!} k^i \left\lceil \overline{L} \right\rceil^i} = \frac{nk \left\lceil \overline{L} \right\rceil \left(1 + k \left\lceil \overline{L} \right\rceil \right)^{n-1}}{\left(1 + k \left\lceil \overline{L} \right\rceil \right)^n} = \frac{nk \left\lceil \overline{L} \right\rceil}{1 + k \left\lceil \overline{L} \right\rceil} \tag{18}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

(20)

(21)

(22)

(24)

(23)

, corresponds to the average of ligand bound to the

0

*L L*

·

 

*<sup>n</sup> <sup>i</sup>*

*i L*

0 0

*i i*

*<sup>n</sup> <sup>n</sup> <sup>i</sup> <sup>i</sup> i i*

<sup>0</sup> ,

*<sup>i</sup> P T*

*<sup>n</sup> <sup>i</sup>*

*L*

(25)

0 0

*i i i i*

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 83

*Z W* . For binding processes the partition function is expressed as

*i*

*i*

*L*

/ *<sup>i</sup> W ML M L ii i*

Construct the partition function, *Z*, as the sum of the statistical weights of all accessible

0 0

Probability of each accessible state, *Pi*, which is the fraction of each species at equilibrium in

*i i <sup>i</sup> <sup>n</sup> <sup>i</sup>*

*W L*

0

Average quantities of interest for the system, that is, measured values of any

0 · *n*

*<sup>i</sup> n n <sup>i</sup> i i i n n i i i i*

Of course, the expression obtained is the Adair´s equation (equation 14) and the denominator, which corresponds to the binding polynomial, can be identified with the partition function.

There is also a direct way to calculate the binding parameter, based on the calculation of the

· ln

*P T P T <sup>i</sup>*

*<sup>L</sup> i L <sup>Z</sup> L L <sup>Z</sup>*

*i a aP* 

*i i*

*i i*

*i i ML Z L M*

Based on this formalism it is possible to easily obtain interesting expressions such as

*Z*

*P*

where *ai* corresponds to the value of the magnitude *a* for the state *i* (specie *i*).

0 0

*ii i Z*

· ·

partial derivative of lnZ in respect to ln[L] at constant P and T, as is shown below:

*L Z Z L L*

, ,

*W L*

macromolecule and can be calculated as follows

 

ln

*n n <sup>i</sup> <sup>i</sup>*

states (or species): *<sup>i</sup>*

the binding process

*i*

magnitude. For a magnitude *a*

Thus, the binding parameter,

where the resulting expression has been obtained by taking into account the binomial theorem. Once again, the binding parameter, expressed in terms of microscopic constants, gives a quite simple expression with a reduced number of fitting parameters, since a single *k* value is always expected for all microscopic binding constants in the case of a binding process where binding sites are equivalent and independent.

#### **2.3. A general formulae for non-cooperative binding. The binding polynomial**

At this point, we have explained the simplest cases of binding equilibrium, where binding sites are equivalent and independent. When more complex schemes are considered, the use of classical thermodynamic formulae to obtain the binding parameter turns complicated and laborious, as was mentioned previously. Thus, it is more convenient to use a general formulae which will allow obtaining *([L])* expressions, systematically and independently of the complexity of the case in study. This general formulae is based on the construction of a function, which may be described as the macroscopic analogue of the grand canonical partition function from statistical thermodynamics. This function was introduced in the biochemical field by Wyman [3] and then, applied to ligand binding [4-7].

In order to apply this general formulae to ligand binding systems, firstly, it is necessary to construct the *partition function*, and then, apply it to the system under study. Let us explain briefly the steps to obtain the partition function:


$$\mathcal{W}\_i = D^\* \exp\left(\begin{matrix} -\Delta E\_i \\ \hline \\ \end{matrix} \bigg| \mathbf{R} \mathbf{T} \right) \tag{19}$$

where *D* is the degeneration of each state, and *i i ref EEE*

For a binding process the statistical weight of the specie MLi is

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 83

$$\mathcal{W}\_{i} = \left[ \begin{array}{c} ML\_{i} \\ \end{array} \right] / \left[ \begin{array}{c} M \\ \end{array} \right] = \mathcal{J}\_{i} \left[ \begin{array}{c} L \\ \end{array} \right]^{i} \tag{20}$$

Construct the partition function, *Z*, as the sum of the statistical weights of all accessible states (or species): *<sup>i</sup> i Z W* . For binding processes the partition function is expressed as

$$Z = \sum\_{i=0}^{n} \frac{\left\lfloor \begin{array}{c} ML\_i \\ \hline M \end{array} \right\rfloor}{\left\lceil \begin{array}{c} M \\ \hline \end{array} \right\rfloor} = \sum\_{i=0}^{n} \beta\_i \left\lceil \begin{array}{c} L \\ \hline \end{array} \right\rceil^i \tag{21}$$

Based on this formalism it is possible to easily obtain interesting expressions such as

Applications of Calorimetry in a Wide Context –

formulae which will allow obtaining

with the ligand.

briefly the steps to obtain the partition function:

equilibrium constants given by the mass action law.

binding process is the free macromolecule (M).

where *D* is the degeneration of each state, and *i i ref EEE*

For a binding process the statistical weight of the specie MLi is

The statistical weight for a state *i*, *Wi*, is

82 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

! ! 1

*n n <sup>i</sup> <sup>i</sup>*

*<sup>n</sup> <sup>i</sup> <sup>i</sup> <sup>n</sup>*

1

*([L])* expressions, systematically and independently

(19)

(18)

*<sup>n</sup> k L k L k L*

! 1 1

where the resulting expression has been obtained by taking into account the binomial theorem. Once again, the binding parameter, expressed in terms of microscopic constants, gives a quite simple expression with a reduced number of fitting parameters, since a single *k* value is always expected for all microscopic binding constants in the case of a binding

**2.3. A general formulae for non-cooperative binding. The binding polynomial** 

biochemical field by Wyman [3] and then, applied to ligand binding [4-7].

At this point, we have explained the simplest cases of binding equilibrium, where binding sites are equivalent and independent. When more complex schemes are considered, the use of classical thermodynamic formulae to obtain the binding parameter turns complicated and laborious, as was mentioned previously. Thus, it is more convenient to use a general

of the complexity of the case in study. This general formulae is based on the construction of a function, which may be described as the macroscopic analogue of the grand canonical partition function from statistical thermodynamics. This function was introduced in the

In order to apply this general formulae to ligand binding systems, firstly, it is necessary to construct the *partition function*, and then, apply it to the system under study. Let us explain

 Identify the different energetic accessible states of the system: in a binding process it would be the different species of the macromolecule (free and bound) in equilibrium

Determine the energy of each accessible state: it would be equivalent to specify the

 Choose a reference state, that is, a reference specie: it can be chosen any of the identified ones, though is preferable to choose the state (species) with the lowest energy; for a

Calculate the statistical weight of each state (species) with respect to the reference one.

\* exp *<sup>i</sup>*

*<sup>E</sup> W D RT* 

*i*

*n ii nk L k L nk L*

!

*<sup>n</sup> i kL*

! !

1

*i*

0

*i*

*n ii*

process where binding sites are equivalent and independent.

Probability of each accessible state, *Pi*, which is the fraction of each species at equilibrium in the binding process

$$P\_i = \frac{W\_i}{Z} = \frac{\mathcal{B}\_i \left\lceil \boldsymbol{L} \right\rceil^i}{\sum\_{i=0}^n \mathcal{B}\_i \left\lceil \boldsymbol{L} \right\rceil^i} \tag{22}$$

 Average quantities of interest for the system, that is, measured values of any magnitude. For a magnitude *a*

$$\left\langle a \right\rangle = \sum\_{i=0}^{n} a\_i \cdot P\_i \tag{23}$$

where *ai* corresponds to the value of the magnitude *a* for the state *i* (specie *i*).

Thus, the binding parameter, , corresponds to the average of ligand bound to the macromolecule and can be calculated as follows

$$\overline{\boldsymbol{\nabla}} = \left\{ \overline{\boldsymbol{i}} \right\} = \sum\_{i=0}^{n} \overline{\boldsymbol{i}} \cdot \frac{\boldsymbol{\mathcal{W}}\_{i}}{\boldsymbol{Z}} = \sum\_{i=0}^{n} \overline{\boldsymbol{i}} \cdot \frac{\boldsymbol{\mathcal{B}}\_{i} \left\llbracket \boldsymbol{L} \right\rrbracket^{i}}{\sum\_{i=0}^{n} \boldsymbol{\mathcal{B}}\_{i} \left\llbracket \boldsymbol{L} \right\rrbracket^{i}} = \frac{\sum\_{i=0}^{n} \boldsymbol{i} \cdot \boldsymbol{\mathcal{B}}\_{i} \left\llbracket \boldsymbol{L} \right\rrbracket^{i}}{\sum\_{i=0}^{n} \boldsymbol{\mathcal{B}}\_{i} \left\llbracket \boldsymbol{L} \right\rrbracket^{i}} \tag{24}$$

Of course, the expression obtained is the Adair´s equation (equation 14) and the denominator, which corresponds to the binding polynomial, can be identified with the partition function.

There is also a direct way to calculate the binding parameter, based on the calculation of the partial derivative of lnZ in respect to ln[L] at constant P and T, as is shown below:

$$\overline{\nabla} = \left( \frac{\partial \left( \ln Z \right)}{\partial \left( \ln \left[ \underline{L} \right] \right)} \right)\_{P,T} = \frac{\left\lbrack \underline{L} \right\rbrack}{Z} \left( \frac{\partial Z}{\partial \left[ \underline{L} \right]} \right)\_{P,T} = \frac{\left\lbrack \underline{L} \right\rbrack}{Z} \left[ \frac{\partial \left( \sum\_{i=0}^{n} \beta\_{i} \left\lbrack \underline{L} \right\rbrack^{i} \right)}{\partial \left[ \underline{L} \right]} \right]\_{P,T} = \frac{\sum\_{i=0}^{n} i \cdot \beta\_{i} \left\lbrack \underline{L} \right\rbrack^{i}}{\sum\_{i=0}^{n} \beta\_{i} \left\lbrack \underline{L} \right\rbrack^{i}} \tag{25}$$

Applications of Calorimetry in a Wide Context – 84 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

If we apply this general formulae to the case of the binding of a ligand to a macromolecule with *n* equivalent and independent binding sites, we can obtain the same expression than that given in equation 18. It is interesting to note that, since the binding sites are independent, the partition function corresponds to the product of the partition sub-function for each binding site. Therefore, the binding parameter can also be expressed as the sum of the binding parameter for each binding site. Additionally, if the sites are equivalent, such parameters will be equal to *n* times the value of the binding parameter obtained for one of the sites.

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 85

independent sites, being *n* estimated from the asymptotic value of the graph (curve A). When the macromolecule displays different kinds of sites, characterized by different values of microscopic constants, the shape of the curve changes, becoming more difficult to distinguish from the former simpler case when such values become similar (curves B and C). The shape will be the equivalent to the sum of two or more hyperbolic binding curves

The Scatchard representation would be more helpful to distinguish between equal or different kinds of independent sites (Figure 3). From the intersection with the X-axis the number of binding sites can be easily determined when sites are equal (curve A). In the case of different kind of sites *n* estimation is difficult, although we can obtain the number of sites of the highest affinity and the respective *k* value from the extrapolation of the initial linear

The Hill representation is fundamentally informative to distinguish between independent (non-cooperative) and dependent (cooperative) sites in the macromolecule, and will be

Up to now we have referred only to binding processes where all binding sites are independent. It is time to introduce the effect of binding cooperativity, which means that the interaction of the ligand with one of the sites of the macromolecule produces an alteration of the affinity that the other sites have for such ligand. We can distinguish between *positive cooperativity*, when the binding of a ligand increases the affinity of the rest of binding sites, and *negative cooperativity*, when such affinity is decreased. These changes in affinity are usually related to conformational changes in the macromolecule, that is, what was referred to at the beginning of the chapter as *alosterism*. From a practical point of view, cooperativity can be viewed as a way to regulate the biological activity as a function of ligand

Although the Adair equation is still a valid approach, as we described in Section 2.4, it could be difficult to distinguish among the different equilibriums and, in addition, it may contain an excessive number of equilibrium constants to be estimated from fitting. Thus, different strategies have been described to analyze cooperativity, as will be explained into the next Section. Prior to this description, let us first describe how to determine cooperativity from

The binding curve reveals an S-shape when cooperativity is positive. From the Scatchard representation positive cooperativity can also be easily discernible from any scheme of independent binding sites, since a concave shape of the experimental data is revealed (Figure 4). However, negative cooperativity can be confused with the scheme of different and independent sites (compared to Figures 3 and 4). The Hill representation is the most useful to distinguish between dependent and independent types of binding sites. In Figure 4 both situations have been simulated. When a non-cooperative behaviour is revealed, a

**2.5. Experimental analysis of binding cooperativity (non-independent sites)** 

with two or more different *k* values.

analyzed in detail into the next Section.

tendency (see figure).

concentration.

analysis of experimental data.

In the case of a macromolecule with *n* different and independent binding sites, the partition function can also be expressed as the product of the partition sub-functions for each binding site, though as the sites are different these partition sub-functions will not be equivalent. Consequently, the binding parameter will be the sum of the binding parameter corresponding to each site.

### **2.4. Experimental analysis of binding equilibriums to independent sites**

Prior to describing cooperative phenomena, in this Section we will describe how the analysis of the different graphical representations mentioned in Section 2.2.1 may help to rationalize the experimental data to get information about, for example, the existence of different kinds of binding sites for the ligand and how the equilibrium constants describing ligand binding can be estimated.

Simulation examples for the binding equilibrium of a ligand to a macromolecule with one or two different classes of sites, to show the differences in the binding curves (left panel) and in the Scatchard representation (right panel). Curve A corresponds to the ligand binding to six equivalent and independent sites, with a microscopic constant of 5·105 M-1. Curves B and C correspond to the binding to two different kinds of sites, each class with 3 sites: for curve B the ratio between microscopic constants of the two binding site classes is *k1*=10*k2*; for curve C the ratio is *k1*=100*k2*.

#### **Figure 3.** Binding to independent sites

The easiest representation of experimental data is the binding curve (Figures 1 and 3). Simulations carried out with the equations described above, by using the different *([L])* expressions obtained in the earlier sections indicate that a hyperbolic shape of this curve will represent a binding process corresponding to a macromolecule with equivalent and independent sites, being *n* estimated from the asymptotic value of the graph (curve A). When the macromolecule displays different kinds of sites, characterized by different values of microscopic constants, the shape of the curve changes, becoming more difficult to distinguish from the former simpler case when such values become similar (curves B and C). The shape will be the equivalent to the sum of two or more hyperbolic binding curves with two or more different *k* values.

Applications of Calorimetry in a Wide Context –

the sites.

corresponding to each site.

can be estimated.

*n***<sup>1</sup>** *n***<sup>2</sup>**

**(A)**

**0**

**2**

**4**

**6**

**Figure 3.** Binding to independent sites

**0 10 20 30 40 50 60 70 80**

*k1* **=***k2* **= 5·105 M-1**

**(C)**

**(B)**

*k1* **= 5·105 M-1 ;** *k2* **= 5·104 M-1**

*k1* **= 5·105 M-1 ;** *k2* **= 5·103 M-1**

*[L]* (M)

*n1*  **=** *n2*  **= 3**

84 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

If we apply this general formulae to the case of the binding of a ligand to a macromolecule with *n* equivalent and independent binding sites, we can obtain the same expression than that given in equation 18. It is interesting to note that, since the binding sites are independent, the partition function corresponds to the product of the partition sub-function for each binding site. Therefore, the binding parameter can also be expressed as the sum of the binding parameter for each binding site. Additionally, if the sites are equivalent, such parameters will be equal to *n* times the value of the binding parameter obtained for one of

In the case of a macromolecule with *n* different and independent binding sites, the partition function can also be expressed as the product of the partition sub-functions for each binding site, though as the sites are different these partition sub-functions will not be equivalent. Consequently, the binding parameter will be the sum of the binding parameter

Prior to describing cooperative phenomena, in this Section we will describe how the analysis of the different graphical representations mentioned in Section 2.2.1 may help to rationalize the experimental data to get information about, for example, the existence of different kinds of binding sites for the ligand and how the equilibrium constants describing ligand binding

Simulation examples for the binding equilibrium of a ligand to a macromolecule with one or two different classes of sites, to show the differences in the binding curves (left panel) and in the Scatchard representation (right panel). Curve A corresponds to the ligand binding to six equivalent and independent sites, with a microscopic constant of 5·105 M-1. Curves B and C correspond to the binding to two different kinds of sites, each class with 3 sites: for curve B the ratio

**0**

**1**

**2**

**(μM-1)** *L* 

**3**

**<sup>1</sup> <sup>1</sup> <sup>2</sup> <sup>2</sup>** *n ·k n ·k*

**(C) (B) (A)**

The easiest representation of experimental data is the binding curve (Figures 1 and 3).

expressions obtained in the earlier sections indicate that a hyperbolic shape of this curve will represent a binding process corresponding to a macromolecule with equivalent and

*([L])*

*n***<sup>1</sup>** *n***<sup>2</sup>**

**0123456**

*n***1**

*k1* **=***k2* **= 5·105 M-1**

*k1* **= 5·105 M-1 ;** *k2* **= 5·104 M-1**

*k1* **= 5·105 M-1 ;** *k2* **= 5·103 M-1**

*n1*  **=** *n2*  **= 3**

Simulations carried out with the equations described above, by using the different

between microscopic constants of the two binding site classes is *k1*=10*k2*; for curve C the ratio is *k1*=100*k2*.

**2.4. Experimental analysis of binding equilibriums to independent sites** 

The Scatchard representation would be more helpful to distinguish between equal or different kinds of independent sites (Figure 3). From the intersection with the X-axis the number of binding sites can be easily determined when sites are equal (curve A). In the case of different kind of sites *n* estimation is difficult, although we can obtain the number of sites of the highest affinity and the respective *k* value from the extrapolation of the initial linear tendency (see figure).

The Hill representation is fundamentally informative to distinguish between independent (non-cooperative) and dependent (cooperative) sites in the macromolecule, and will be analyzed in detail into the next Section.

### **2.5. Experimental analysis of binding cooperativity (non-independent sites)**

Up to now we have referred only to binding processes where all binding sites are independent. It is time to introduce the effect of binding cooperativity, which means that the interaction of the ligand with one of the sites of the macromolecule produces an alteration of the affinity that the other sites have for such ligand. We can distinguish between *positive cooperativity*, when the binding of a ligand increases the affinity of the rest of binding sites, and *negative cooperativity*, when such affinity is decreased. These changes in affinity are usually related to conformational changes in the macromolecule, that is, what was referred to at the beginning of the chapter as *alosterism*. From a practical point of view, cooperativity can be viewed as a way to regulate the biological activity as a function of ligand concentration.

Although the Adair equation is still a valid approach, as we described in Section 2.4, it could be difficult to distinguish among the different equilibriums and, in addition, it may contain an excessive number of equilibrium constants to be estimated from fitting. Thus, different strategies have been described to analyze cooperativity, as will be explained into the next Section. Prior to this description, let us first describe how to determine cooperativity from analysis of experimental data.

The binding curve reveals an S-shape when cooperativity is positive. From the Scatchard representation positive cooperativity can also be easily discernible from any scheme of independent binding sites, since a concave shape of the experimental data is revealed (Figure 4). However, negative cooperativity can be confused with the scheme of different and independent sites (compared to Figures 3 and 4). The Hill representation is the most useful to distinguish between dependent and independent types of binding sites. In Figure 4 both situations have been simulated. When a non-cooperative behaviour is revealed, a single straight line with a slope equal to one is obtained, while when a positive cooperative behaviour occurs, the Hill analysis shows an increase of the slope at the central region (Sshape). The decrease of this region will indicate negative cooperativity. The slope of this region is known as the *Hill coefficient, nH*. The explanation is as follows:

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 87

*n*

 (27)

*nK L*

23 4 1 12 123 1234 *Z K L KK L KKK L KKKK L* <sup>1</sup> ... (29)

> 1 *i*

(30)

*i*

(28)

maximum experimental value around half of saturation. The maximum theoretical value in this zone will be hypothetically reached in the case of infinite cooperativity, where only the free and fully saturated M species are significantly populated. In this case, it can be demonstrated that this slope can be equal to *n*. In the real cases where cooperativity is finite,

 At very high ligand concentrations, reaching saturation of the macromolecule, for almost the totality of macromolecules all sites are occupied by ligand molecules except one of them and the binding to this last site does not influence binding affinity. Therefore, the slope returns again to be equal to 1 (Figure 4) and it can be deduced from the mathematical expression of the Hill equation in the limit of strong binding that

log log · log *<sup>n</sup>*

This approach does not imply the assumption of any structural model for the MLi species. For a situation where sites are independent it is assumed that only one microscopic binding constant, *k*, exists, but there are different macroscopic constants, *Ki*, for the different

In general, we can also assume that the relationship between macroscopic and microscopic

*Isoforms of ML K k Isoforms of ML*

By replacing this equation in the binding polynomial, we obtain the phenomenological expression for this function, and then, by using equation 25 the binding parameter can be estimated. In the case of cooperative sites, this description assumes that the microscopic binding constant changes upon binding, increasing when positive cooperativity happens, and decreasing for negative cooperativity. This approach does not explain the molecular reasons of such a change, as do the following schemes, but it represents an easy way to

*L*

*n* 

**2.6. Physico-chemical description of binding cooperativity** 

equilibriums, according to the scheme shown in Figure 5.

estimate the equilibrium constants in these cases.

Therefore, the binding polynomial can be generally described as

*i*

log log ·log *<sup>n</sup> M n n nL ML Kn L*

the value will range between 1< nH < *n*

*2.6.1. Phenomenological description* 

binding constants can be

At very low ligand concentrations, the binding occurs statistically at different sites allocated in different macromolecule units, all of them free of ligand. Thus, at this stage cooperativity phenomena are not revealed experimentally. This "non-cooperative" initiation of the binding process results in a straight line with slope equal to one. Thus, equation 4 converts into

Graph A shows some simulations of the binding curve for the ligand binding to a macromolecule with two binding sites, with a microscopic constant of *k*=5·105 M-1: solid line curve corresponds to equal and independent binding sites, and dashed line curve to equal sites showing positive cooperativity (the binding of a ligand increases fifty times the affinity for the second ligand molecule). Graphs B and C show the Scatchard and Hill representations respectively. In both panels simulated curves correspond to *k*=5·105 M-1 and the affinity for the second site is increased (for positive cooperativity) or decreased (negative cooperativity) five times.

**Figure 4.** Binding to cooperative sites

$$\log\left(\frac{\overline{\nu}}{n-\overline{\nu}}\right)\_{\left[L\right]\to 0} = \log\frac{K\_1}{n} + \log\left[L\right] \tag{26}$$

At moderate saturation of the macromolecule, the ligand binds to sites where affinity has changed (second and subsequent sites of the macromolecule). As a result, the slope of this region of the Hill curve will change to values higher than one in the case of positive cooperativity, or lower than one for negative cooperativity. Thus, the slope will achieve its maximum experimental value around half of saturation. The maximum theoretical value in this zone will be hypothetically reached in the case of infinite cooperativity, where only the free and fully saturated M species are significantly populated. In this case, it can be demonstrated that this slope can be equal to *n*. In the real cases where cooperativity is finite, the value will range between 1< nH < *n*

$$M + nL \leftarrow \xrightarrow{\beta\_n} ML\_n \tag{27} \\ \tag{28} \\ \tag{28} \\ \tag{29}$$

 At very high ligand concentrations, reaching saturation of the macromolecule, for almost the totality of macromolecules all sites are occupied by ligand molecules except one of them and the binding to this last site does not influence binding affinity. Therefore, the slope returns again to be equal to 1 (Figure 4) and it can be deduced from the mathematical expression of the Hill equation in the limit of strong binding that

$$\log\left(\frac{\overline{\nu}}{n-\overline{\nu}}\right)\_{\left[\frac{L}{L}\right]\to\ast} = \log\left(n \cdot K\_n\right) + \log\left[L\right] \tag{28}$$

#### **2.6. Physico-chemical description of binding cooperativity**

#### *2.6.1. Phenomenological description*

Applications of Calorimetry in a Wide Context –

into

86 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

region is known as the *Hill coefficient, nH*. The explanation is as follows:

single straight line with a slope equal to one is obtained, while when a positive cooperative behaviour occurs, the Hill analysis shows an increase of the slope at the central region (Sshape). The decrease of this region will indicate negative cooperativity. The slope of this

At very low ligand concentrations, the binding occurs statistically at different sites allocated in different macromolecule units, all of them free of ligand. Thus, at this stage cooperativity phenomena are not revealed experimentally. This "non-cooperative" initiation of the binding process results in a straight line with slope equal to one. Thus, equation 4 converts

Graph A shows some simulations of the binding curve for the ligand binding to a macromolecule with two binding sites, with a microscopic constant of *k*=5·105 M-1: solid line curve corresponds to equal and independent binding sites, and dashed line curve to equal sites showing positive cooperativity (the binding of a ligand increases fifty times the affinity for the second ligand molecule). Graphs B and C show the Scatchard and Hill representations respectively. In both panels simulated curves correspond to *k*=5·105 M-1 and the affinity for the second site is increased (for positive

> 0 log log log *L*

At moderate saturation of the macromolecule, the ligand binds to sites where affinity has changed (second and subsequent sites of the macromolecule). As a result, the slope of this region of the Hill curve will change to values higher than one in the case of positive cooperativity, or lower than one for negative cooperativity. Thus, the slope will achieve its

*n n*

 1

**-2**

**-1**

**0**

**1**

 

**<sup>M</sup>-1 ;** *Kb2***= 2.5·10<sup>5</sup>**

**<sup>M</sup>-1 ;** *Kb2***= 2.5·10<sup>5</sup>**

**M-1**

**M-1**

*<sup>n</sup> log*

*[L]* **(M)**

**0 20 40 60 80**

*Kb1***=10<sup>6</sup>**

**A**

*Kb1***=2·10<sup>4</sup>**

*<sup>K</sup> <sup>L</sup>*

(26)

**-7 -6 -5 -4**

 log(nu/n-nu) (n=2, k=0.5microM, coop=5) log(nu/n-nu) (n=2, k=0.5microM, coop=1) log(nu/n-nu) (n=2, k=0.5microM, coop=0.2)

**C**

*log [L]*

cooperativity) or decreased (negative cooperativity) five times.

**0.0 0.5 1.0 1.5 2.0**

**1.2 B**

**0.0**

**0.5**

**1.0**

**1.5**

**2.0**

*n*

**Figure 4.** Binding to cooperative sites

**0.0**

**0.4**

**0.8**

**(μM-1)**

*L* 

This approach does not imply the assumption of any structural model for the MLi species. For a situation where sites are independent it is assumed that only one microscopic binding constant, *k*, exists, but there are different macroscopic constants, *Ki*, for the different equilibriums, according to the scheme shown in Figure 5.

Therefore, the binding polynomial can be generally described as

$$\text{V.Z.} = 1 + K\_1 \left[ L \right] + K\_1 K\_2 \left[ L \right]^2 + K\_1 K\_2 K\_3 \left[ L \right]^3 + K\_1 K\_2 K\_3 K\_4 \left[ L \right]^4 + \dots \tag{29}$$

In general, we can also assume that the relationship between macroscopic and microscopic binding constants can be

$$K\_i = \frac{\text{Isoforms} \quad \text{of} \quad ML\_i}{\text{Isoforms} \quad \text{of} \quad ML\_{i-1}} k \tag{30}$$

By replacing this equation in the binding polynomial, we obtain the phenomenological expression for this function, and then, by using equation 25 the binding parameter can be estimated. In the case of cooperative sites, this description assumes that the microscopic binding constant changes upon binding, increasing when positive cooperativity happens, and decreasing for negative cooperativity. This approach does not explain the molecular reasons of such a change, as do the following schemes, but it represents an easy way to estimate the equilibrium constants in these cases.

88 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Left side shows the matrix of the model, where columns represent ligand binding equilibriums and rows the conformational changes associated to a hypothetical macromolecule displaying four cooperative binding sites for the ligand. Right side shows the relationship between macroscopic and microscopic constants, where *Ωi* represents the number of isoforms of MLi.

**Figure 5.** Phenomenological description of binding cooperativity

#### *2.6.2. The Koshland-Nemety-Filmer model*

The basics of this model were initially proposed by Pauling to study the cooperative binding of oxygen to haemoglobin [8]. It can explain both, positive and negative cooperative behaviours. More interesting, this model assumes that the different binding sites of the macromolecule are influencing each other through their mutual interconnection by means of a molecular ligature, σ. In Figure 6 we have represented this situation for a macromolecule with four binding sites for the ligand L. It must be considered that when every site is occupied by L, it breaks the ligature with the others, resulting in a modification of their binding affinities. Then, the mathematical expression for the binding polynomial is:

$$Z = \sum\_{i=0}^{n} I\_i \frac{k^i}{\sigma^{Bi}} \left\lbrack L \right\rbrack^i \tag{31}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 89

exists in at least two different conformations, which are under mutual equilibriums, and differ in their affinities for the ligand. Within every conformation, the binding sites behave

The upper scheme represents the so-called square version of this model for a hypothetical macromolecule displaying fou cooperative binding sites for the ligand and only one kind of ligature. The lower panel shows the rectangular version, with two kinds of ligatures. In both cases we also show the corresponding formulae of the partition function,

In Figure 7 a schematic diagram is shown for the case of a macromolecule with four binding sites and two (left side) distinct conformations under equilibrium. In this situation, it is usually assumed that the allosteric equilibrium constant, *Λ*, is initially big enough to move

**Figure 6.** The Koshland-Nemety-Filmer model of binding cooperativity

Z, below each one.

as if they were equivalent and independent for the binding of L.

where Ii are the number of possibilities of allocating i ligands into the macromolecule, and Bi is the number of broken ligatures for each configuration. The results for the case of a macromolecule with four binding sites are collected into Figure 6 as an example.

This description can be modified as a function of the experimental behaviour of every macromolecule-ligand example. It might be easily developed for the case of different microscopic constants or, even, of different contribution of the ligatures. The main advantage with respect to the phenomenological description is that it can reveal molecular aspects of cooperative phenomena when applied.

#### *2.6.3. The Monod-Wyman-Changeux model*

Although this model has been widely used in the literature [4, 9], it can only be used to describe positive cooperativity, which is expressed by assuming that the macromolecule can exists in at least two different conformations, which are under mutual equilibriums, and differ in their affinities for the ligand. Within every conformation, the binding sites behave as if they were equivalent and independent for the binding of L.

Applications of Calorimetry in a Wide Context –

number of isoforms of MLi.

88 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Left side shows the matrix of the model, where columns represent ligand binding equilibriums and rows the conformational changes associated to a hypothetical macromolecule displaying four cooperative binding sites for the ligand. Right side shows the relationship between macroscopic and microscopic constants, where *Ωi* represents the

The basics of this model were initially proposed by Pauling to study the cooperative binding of oxygen to haemoglobin [8]. It can explain both, positive and negative cooperative behaviours. More interesting, this model assumes that the different binding sites of the macromolecule are influencing each other through their mutual interconnection by means of a molecular ligature, σ. In Figure 6 we have represented this situation for a macromolecule with four binding sites for the ligand L. It must be considered that when every site is occupied by L, it breaks the ligature with the others, resulting in a modification of their

binding affinities. Then, the mathematical expression for the binding polynomial is:

0

where Ii are the number of possibilities of allocating i ligands into the macromolecule, and Bi is the number of broken ligatures for each configuration. The results for the case of a

This description can be modified as a function of the experimental behaviour of every macromolecule-ligand example. It might be easily developed for the case of different microscopic constants or, even, of different contribution of the ligatures. The main advantage with respect to the phenomenological description is that it can reveal molecular

Although this model has been widely used in the literature [4, 9], it can only be used to describe positive cooperativity, which is expressed by assuming that the macromolecule can

*i <sup>k</sup> ZI L* 

macromolecule with four binding sites are collected into Figure 6 as an example.

*<sup>n</sup> <sup>i</sup> <sup>i</sup> i Bi*

(31)

**Figure 5.** Phenomenological description of binding cooperativity

*2.6.2. The Koshland-Nemety-Filmer model* 

aspects of cooperative phenomena when applied.

*2.6.3. The Monod-Wyman-Changeux model* 

The upper scheme represents the so-called square version of this model for a hypothetical macromolecule displaying fou cooperative binding sites for the ligand and only one kind of ligature. The lower panel shows the rectangular version, with two kinds of ligatures. In both cases we also show the corresponding formulae of the partition function, Z, below each one.

**Figure 6.** The Koshland-Nemety-Filmer model of binding cooperativity

In Figure 7 a schematic diagram is shown for the case of a macromolecule with four binding sites and two (left side) distinct conformations under equilibrium. In this situation, it is usually assumed that the allosteric equilibrium constant, *Λ*, is initially big enough to move the equilibrium towards the T-state, considered as the low affinity state. Upon addition of the ligand, the equilibrium moves towards the R-state, of higher affinity than the former. Therefore, this displacement will allow the rest of sites to bind the ligand with higher affinity than the first one. This progressive displacement to the R-state may, thus, explain an increase in affinity (positive cooperative), but not the opposite.

The binding polynomial can be mathematically expressed as

$$Z = \frac{1}{1 + \mathcal{L}} \left( 1 + k\_{\mathcal{R}} \lceil L \rceil \right)^{n} + \frac{\mathcal{L}}{1 + \mathcal{L}} \left( 1 + k\_{T} \lceil L \rceil \right)^{n} \tag{32}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

*kT*

*kT*

*kT*

*kT*

**L L L**

**L L**

**L L**

*kS*

*kS*

*kS*

*kS*

**L L L**

**L**

**L L L**

**L L L**

**L L L L**

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 91

The two schemes show the equilibriums for a hypothetical macromolecule displaying four cooperative binding sites

**L L L**

**L**

**L**

**L L**

**L L**

*kR*

*kR*

*kR*

*kR*

As we stated above, a typical ITC experiment consists of a series of injections of determined ligand solution volumes, which can be equal or variable each time, into a macromolecule solution. Such injections have to be separated in between by a time interval, large enough to be sure that the system has reached the equilibrium and all heat absorbed or emitted has been transferred. The titration process is continued until saturation of the macromolecule by the ligand into the cell is reached. In this way, the last additions will not give a significant heat exchange, as shown in Figure 8. The final thermogram is obtained by the individual integration of each peak, setting the integration limits in the baseline that precedes and

> *tf Q W(t)·dt ti*

As we have mentioned previously, this technique allows us to directly evaluate the heat exchange generated upon binding of two molecules. The correct performance of a titration

(34)

for the ligand and one (left) or two (right) different conformational changes. **Figure 7.** The Monod-Wyman-Changeux model of binding cooperativity

continues such peak with the equation:

R T

*kT*

*kT*

*kT*

*kT*

RL TL

*+L +L*

*kR*

*+L +L*

*kR*

*+L +L*

*kR*

*+L +L*

*kR*

RL2 TL2

RL3 TL3

RL4 TL4

**3.1. Procedures for ITC experiments** 

This model can be easily generalized to more than two conformations of the macromolecule by adding additional terms to this general equation. For example, for the case of three conformations (right side of Figure 7):

$$Z = \frac{1}{1 + \lambda + \varpi} \left( 1 + k\_R \lceil L \rceil \right)^n + \frac{\lambda}{1 + \lambda + \varpi} \left( 1 + k\_T \lceil L \rceil \right)^n + \frac{\varpi}{1 + \lambda + \varpi} \left( 1 + k\_S \lceil L \rceil \right)^n \tag{33}$$

and so on.

### **3. Notes on ITC performance and general experimental procedures**

As was mentioned in the Introduction, ITC is a thermodynamic technique that directly measures the heat released or absorbed in an intermolecular interaction, such as ligandprotein interactions, protein-protein interactions, etc [10]. An ITC experiment consists of a calorimetric titration of a specific volume of one of the reagents, usually the macromolecule, with controlled quantities of the other reagent, usually the ligand, at constant temperature and pressure. Thus, the measured heat during the titration corresponds to the enthalpy of such interactions [11]. This relatively easy experiment allows a complete and precise thermodynamic characterization of the binding event. Subsequently, if the thermal effect is high enough, and the value of the binding constant is moderately good, a single ITC experiment can establish the equilibrium binding constant, *Kb*, the apparent enthalpy change, *ΔHapp*, and the stoichiometry of the reaction, *n*. Additionally, if the experiments are made at different temperatures, the change of heat capacity of the process, *ΔCpb*, can also be measured.

The most common titration calorimeters are adiabatic and are based on the compensation of the thermal effect generated by the addition of the ligand into the sample cell, which is placed in an adiabatic environment [11]. In the left side of Figure 8 we show a schematic representation of one of these instruments. A thermoelectric device measures the temperature difference between the sample and the reference cells (T-1) and also between each cell and the adiabatic jacket (T-2). As long as the reaction is being developed, T-1 value decreases to zero with the heating of the sample cell (if the reaction is endothermic) or the reference cell (if exothermic). This heating generates a spike over the baseline of the stationary power, and the integration of this potential required to get T-1 to zero in the time to recover the equilibrium is the heat of each injection (right panel in Figure 8).

Isothermal Titration Calorimetry: Thermodynamic Analysis of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 91

The two schemes show the equilibriums for a hypothetical macromolecule displaying four cooperative binding sites for the ligand and one (left) or two (right) different conformational changes.

**Figure 7.** The Monod-Wyman-Changeux model of binding cooperativity

As we stated above, a typical ITC experiment consists of a series of injections of determined ligand solution volumes, which can be equal or variable each time, into a macromolecule solution. Such injections have to be separated in between by a time interval, large enough to be sure that the system has reached the equilibrium and all heat absorbed or emitted has been transferred. The titration process is continued until saturation of the macromolecule by the ligand into the cell is reached. In this way, the last additions will not give a significant heat exchange, as shown in Figure 8. The final thermogram is obtained by the individual integration of each peak, setting the integration limits in the baseline that precedes and continues such peak with the equation:

$$Q = \begin{cases} t \\ W(t) \cdot dt \\ \text{if} \end{cases} \tag{34}$$

#### **3.1. Procedures for ITC experiments**

Applications of Calorimetry in a Wide Context –

conformations (right side of Figure 7):

 

and so on.

90 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

increase in affinity (positive cooperative), but not the opposite.

The binding polynomial can be mathematically expressed as

the equilibrium towards the T-state, considered as the low affinity state. Upon addition of the ligand, the equilibrium moves towards the R-state, of higher affinity than the former. Therefore, this displacement will allow the rest of sites to bind the ligand with higher affinity than the first one. This progressive displacement to the R-state may, thus, explain an

<sup>1</sup> 1 1

 

*Z kL R Tk L*

This model can be easily generalized to more than two conformations of the macromolecule by adding additional terms to this general equation. For example, for the case of three

*n n*

*nnn*

 

  (33)

(32)

1 1

. <sup>1</sup> <sup>111</sup> 111

 

**3. Notes on ITC performance and general experimental procedures** 

*Z kRTS L k L k L* 

As was mentioned in the Introduction, ITC is a thermodynamic technique that directly measures the heat released or absorbed in an intermolecular interaction, such as ligandprotein interactions, protein-protein interactions, etc [10]. An ITC experiment consists of a calorimetric titration of a specific volume of one of the reagents, usually the macromolecule, with controlled quantities of the other reagent, usually the ligand, at constant temperature and pressure. Thus, the measured heat during the titration corresponds to the enthalpy of such interactions [11]. This relatively easy experiment allows a complete and precise thermodynamic characterization of the binding event. Subsequently, if the thermal effect is high enough, and the value of the binding constant is moderately good, a single ITC experiment can establish the equilibrium binding constant, *Kb*, the apparent enthalpy change, *ΔHapp*, and the stoichiometry of the reaction, *n*. Additionally, if the experiments are made at different temperatures, the change of heat capacity of the process, *ΔCpb*, can also be measured.

The most common titration calorimeters are adiabatic and are based on the compensation of the thermal effect generated by the addition of the ligand into the sample cell, which is placed in an adiabatic environment [11]. In the left side of Figure 8 we show a schematic representation of one of these instruments. A thermoelectric device measures the temperature difference between the sample and the reference cells (T-1) and also between each cell and the adiabatic jacket (T-2). As long as the reaction is being developed, T-1 value decreases to zero with the heating of the sample cell (if the reaction is endothermic) or the reference cell (if exothermic). This heating generates a spike over the baseline of the stationary power, and the integration of this potential required to get T-1 to zero in the time

to recover the equilibrium is the heat of each injection (right panel in Figure 8).

As we have mentioned previously, this technique allows us to directly evaluate the heat exchange generated upon binding of two molecules. The correct performance of a titration

Applications of Calorimetry in a Wide Context – 92 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

experiment has to consider two main aspects, first, the samples preparation and, second, the proper measurement of reaction heats in the calorimeter. In this Section we are going to describe both experimental aspects.

Isothermal Titration Calorimetry: Thermodynamic Analysis

, 2.5x105, 2.5x104 and 2.5x103 M -1.

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 93

in the experiment (2x buffer). The experimental solutions of protein, ligand and reference buffer (1x buffer) are prepared by adding to the protein and ligand solutions in the necessary amounts (1:1 dilution) of 2x buffer from the last change of dialysis and Milli-Q

The three solutions (buffer, protein and ligand) have to be centrifuged and/or filtered prior to filling the calorimetric cells in order to avoid insoluble particles, it is also recommended to degas them in order to avoid bubbles. The exact protein concentration of the solution has to be determined just before filling the calorimetric sample cell. One of the most accurate and used methods is the spectrophotometric one using protein extinction coefficients

Once the protein solution is in the calorimetric cell and the ligand solution in the ITC syringe (where no air bubbles are present), it is very important to wait enough time to be sure that everything is properly thermostated; a way to control such thermal equilibration is controlling the signal of the ITC instrument. Once the signal of the ITC is stable, the

Simulation of heat per added mole of ligand associated to each injection for an ITC experiment with the following experimental parameters: Vc = 1.347 mL; [M]T = 1.8x10-4M-1 in the cell; 20 injections of 5µL; [L]T = 5mM in the syringe;

**0.5 1.0 1.5 2.0 [L]T/[M]T**

**Kb·[M]T** 450 45 4.5 0.45

The limits of a correct determination of the binding thermodynamic parameters using this technique are given by the product of the binding constant, *Kb*, and the total concentration of the macromolecule, *[M]T*, being *1< Kb·[M]T <1000* [11]. Different simulations of a conventional ITC experiment with additions of equal volumes in which four different binding constants have been considered, 2.5·106, 2.5·105, 2.5·104 and 2.5·103 M-1, are shown in Figure 9. These values are in the range that includes both high and low affinity (the product

water respectively, following the subsequent pH correction of both solutions.

(described by Gill & von Hippel [12]).

*3.1.2. Modeling and performance of an ITC experiment* 

experiment is ready to start with the series of ligand injections.

one binding site and four different values of the association constant, 2.5x106

**Figure 9.** Simulations in isothermal titration calorimetry

**5**

**10**

**dQi / d[L]T**

**15**

**20**

Left side: a schematic diagram of the main components of a titration calorimeter. Right side: a titration calorimetry experiment of a protein with a ligand. In panel A) the titration thermogram is represented as heat per unit of time released after each injection of the ligand into the protein (black), as well as the dilution of ligand into buffer (red). In panel B) the dependence of released heat in each injection *versus* the ratio between total ligand concentration and total protein concentration is represented. Circles represent experimental data and the line corresponds to the best fitting to a model considering *n* identical and independent sites.

**Figure 8.** Isothermal titration calorimetry instrumentation

### *3.1.1. Sample preparation*

To carry out ITC binding studies the protein must be of higher purity than 95%, and dialyzed against a selected buffer. Moreover, it is recommended to use the buffer solution of the last dialysis change as the reference solution. The process and precautions to prepare the ligand solution are the same as those described for the protein solution. Nevertheless, when ligands are small as is not possible to dialyze them, the lyophilized (solid) ligand can be directly dissolved with the last dialysis change buffer used for protein sample preparation. As an alternative way, and in order to minimize the differences in the composition of solutions of protein and ligand, lyophilized and solid samples (usually the low molecular weight ligands) can be dissolved in Milli-Q water at a double concentration than that required in the experiment, as well as the protein solution. Accordingly, the dialysis buffer and the protein solution may also contain twice the concentration of buffering salts desired in the experiment (2x buffer). The experimental solutions of protein, ligand and reference buffer (1x buffer) are prepared by adding to the protein and ligand solutions in the necessary amounts (1:1 dilution) of 2x buffer from the last change of dialysis and Milli-Q water respectively, following the subsequent pH correction of both solutions.

The three solutions (buffer, protein and ligand) have to be centrifuged and/or filtered prior to filling the calorimetric cells in order to avoid insoluble particles, it is also recommended to degas them in order to avoid bubbles. The exact protein concentration of the solution has to be determined just before filling the calorimetric sample cell. One of the most accurate and used methods is the spectrophotometric one using protein extinction coefficients (described by Gill & von Hippel [12]).

### *3.1.2. Modeling and performance of an ITC experiment*

Applications of Calorimetry in a Wide Context –

describe both experimental aspects.

a model considering *n* identical and independent sites.

*3.1.1. Sample preparation* 

**Figure 8.** Isothermal titration calorimetry instrumentation

92 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

experiment has to consider two main aspects, first, the samples preparation and, second, the proper measurement of reaction heats in the calorimeter. In this Section we are going to

Left side: a schematic diagram of the main components of a titration calorimeter. Right side: a titration calorimetry experiment of a protein with a ligand. In panel A) the titration thermogram is represented as heat per unit of time released after each injection of the ligand into the protein (black), as well as the dilution of ligand into buffer (red). In panel B) the dependence of released heat in each injection *versus* the ratio between total ligand concentration and total protein concentration is represented. Circles represent experimental data and the line corresponds to the best fitting to

To carry out ITC binding studies the protein must be of higher purity than 95%, and dialyzed against a selected buffer. Moreover, it is recommended to use the buffer solution of the last dialysis change as the reference solution. The process and precautions to prepare the ligand solution are the same as those described for the protein solution. Nevertheless, when ligands are small as is not possible to dialyze them, the lyophilized (solid) ligand can be directly dissolved with the last dialysis change buffer used for protein sample preparation. As an alternative way, and in order to minimize the differences in the composition of solutions of protein and ligand, lyophilized and solid samples (usually the low molecular weight ligands) can be dissolved in Milli-Q water at a double concentration than that required in the experiment, as well as the protein solution. Accordingly, the dialysis buffer and the protein solution may also contain twice the concentration of buffering salts desired Once the protein solution is in the calorimetric cell and the ligand solution in the ITC syringe (where no air bubbles are present), it is very important to wait enough time to be sure that everything is properly thermostated; a way to control such thermal equilibration is controlling the signal of the ITC instrument. Once the signal of the ITC is stable, the experiment is ready to start with the series of ligand injections.

Simulation of heat per added mole of ligand associated to each injection for an ITC experiment with the following experimental parameters: Vc = 1.347 mL; [M]T = 1.8x10-4M-1 in the cell; 20 injections of 5µL; [L]T = 5mM in the syringe; one binding site and four different values of the association constant, 2.5x106 , 2.5x105, 2.5x104 and 2.5x103 M -1.

**Figure 9.** Simulations in isothermal titration calorimetry

The limits of a correct determination of the binding thermodynamic parameters using this technique are given by the product of the binding constant, *Kb*, and the total concentration of the macromolecule, *[M]T*, being *1< Kb·[M]T <1000* [11]. Different simulations of a conventional ITC experiment with additions of equal volumes in which four different binding constants have been considered, 2.5·106, 2.5·105, 2.5·104 and 2.5·103 M-1, are shown in Figure 9. These values are in the range that includes both high and low affinity (the product

94 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*Kb·[M]T* ranges from 450 to 0.45). As it can be observed, when the product *Kb·[M]T* is within the appropriate range, the sigmoid curve is obtained, which is needed to perform an analysis with acceptable standard errors. When the product *Kb·[M]T* is close to the limits, the isotherm can be optimized with some variations of the experimental design, such as the concentration of total macromolecule in the cell or ligand in the syringe, or also by designing profiles of different injected volumes of ligand. Such profiles usually start with lower ligand volumes for the first injections, which increase progressively in a nonlinear way. Another advantage of using an optimal injection volume profile is the increase of the signal/noise ratio at the end of the thermogram, where the heats of binding are quite small. When the product *Kb·[M]T* is over the range, titration experiments by displacement can be performed, in which the target ligand competes for the same binding site with another ligand whose interaction has been previously characterized [13-15].

Isothermal Titration Calorimetry: Thermodynamic Analysis

int · *H H nH app P ion* (35)

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 95

where *np* is the number of protons accepted or liberated due to the ligand binding to the protein and *ΔHion* is the ionization enthalpy of the buffer used in the experiment. As *ΔHapp* depends on the buffer used and the working pH, the easiest way to determine *ΔHint* is to perform several ITC experiments under the same conditions (mainly at the same pH and ionic strength), but using buffers of different *ΔHion*, which permits the determination of the net binding enthalpy from the ordinate of the corresponding linear correlation of *ΔHapp*

*versus ΔHion*, i.e., the enthalpy value without buffer ionization contributions *ΔHint*.

**4. Thermodynamic analysis of ITC experiments by using different** 

The analysis of the isotherms is done by the non-linear fitting of the experimental data using different equations, depending on the way the ligand binds to the macromolecule. In this Section we are going to describe, as an example, the four most common models in the literature. The fittings can be done with the appropriate software, as Origin 7.0 (Microcal

**4.1. Ligand binding to one macromolecule with** *n* **identical and independent** 

Although the mathematical formulae corresponding to this binding model has been described in Section 2.2.3, we will start defining several functions and parameters. Thus, the

*[L]b*, and the total macromolecule concentration, *[M]T*, can be the one given in equation 18:

1 *nk L k L*

The heat released or absorbed in any ITC injection, *qi*, is related to the binding process as

 *app <sup>b</sup> b*

<sup>1</sup> , , 1 , ,. 1 *<sup>i</sup>* ) *app C b i b i app C T i T i <sup>q</sup> <sup>Δ</sup>H ·V ·( [L] [L] ) <sup>Δ</sup>H ·V ·(<sup>ν</sup> ·[M] <sup>ν</sup> ·[M] <sup>i</sup> <sup>i</sup>* (38)

molar amount of ligand bounded in the injection *i*. If we express the moles of ligand bound

*kJ <sup>q</sup> <sup>Δ</sup>H( )<sup>Δ</sup> molesL <sup>i</sup> molL* (37)

where *k* is the microscopic equilibrium constant, which is unique since all binding sites are independent, *[L]* is the concentration of non-bounded ligand and *n* is the number of binding

where *ΔHapp* is the apparent enthalpy change per mole of bound ligand, and

in terms of concentrations, the above equation can be written as:

, being the relationship between the concentration of bound ligand,

(36)

*(molesLb)* is the

**equilibrium models** 

**sites** 

binding parameter,

sites in the macromolecule.

Software Inc.) or SigmaPlot 2000 (Jandel Co.).

### **3.2. Previous treatment of ITC experimental data for thermodynamic analysis**

Once the ITC experiment has been performed (black titration in panel A of Figure 8), the thermogram can be integrated to obtain the corresponding heats of each injection. Nevertheless, in order to correct the dilution heat effect of the ligand it is necessary to make a baseline ITC experiment (red titration in panel A of Figure 8), which consist of performing an identical ITC experiment of the ligand binding but with buffer instead of protein into the calorimetric cell. Then, the heats for each injection obtained in this baseline experiment are subtracted to the corresponding ones to the ligand binding experiment. Afterwards, we have to normalize the obtained net heats by the total concentration of ligand in the cell after each injection. The binding isotherm can be obtained by the representation of transferred heat per added mole of ligand (*dQi/dLT,i*) versus the molar fraction (*[L]T/[M]T*) (panel B in Figure 8).

### **3.3. Corrections to possible additional heat contributions to the binding experiment**

The fitting of the experimental data to the equations explained in the next Section, will allow us to obtain, besides the binding constant or the Gibbs energy, the binding enthalpy. Sometimes this enthalpy change obtained from the fittings of experimental data is the result of additional events occurring during the ligand binding process. So it is important to distinguish between the apparent binding enthalpy, *ΔHapp*, and the real or intrinsic binding enthalpy, *ΔHint*.

One of the possible events associated to the ligand binding process can be a conformational change of the protein and/or the ligand not associated uniquely to the interaction. A typical example is when the free protein is partially denatured at the experimental temperature, so it is important to check the folding of the protein using other techniques, as circular dichroism or differential scanning calorimetry.

Another possibility is that the ligand binding to the protein can be associated to a change in the pKa of ionisable groups of the protein or/and the ligand [16-18], in such a way that:

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 95

$$
\Delta H\_{app} = \Delta H\_{\text{int}} + \mathfrak{n}\_P \cdot \Delta H\_{\text{ion}} \tag{35}
$$

where *np* is the number of protons accepted or liberated due to the ligand binding to the protein and *ΔHion* is the ionization enthalpy of the buffer used in the experiment. As *ΔHapp* depends on the buffer used and the working pH, the easiest way to determine *ΔHint* is to perform several ITC experiments under the same conditions (mainly at the same pH and ionic strength), but using buffers of different *ΔHion*, which permits the determination of the net binding enthalpy from the ordinate of the corresponding linear correlation of *ΔHapp versus ΔHion*, i.e., the enthalpy value without buffer ionization contributions *ΔHint*.

### **4. Thermodynamic analysis of ITC experiments by using different equilibrium models**

Applications of Calorimetry in a Wide Context –

**experiment** 

enthalpy, *ΔHint*.

dichroism or differential scanning calorimetry.

94 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

ligand whose interaction has been previously characterized [13-15].

*Kb·[M]T* ranges from 450 to 0.45). As it can be observed, when the product *Kb·[M]T* is within the appropriate range, the sigmoid curve is obtained, which is needed to perform an analysis with acceptable standard errors. When the product *Kb·[M]T* is close to the limits, the isotherm can be optimized with some variations of the experimental design, such as the concentration of total macromolecule in the cell or ligand in the syringe, or also by designing profiles of different injected volumes of ligand. Such profiles usually start with lower ligand volumes for the first injections, which increase progressively in a nonlinear way. Another advantage of using an optimal injection volume profile is the increase of the signal/noise ratio at the end of the thermogram, where the heats of binding are quite small. When the product *Kb·[M]T* is over the range, titration experiments by displacement can be performed, in which the target ligand competes for the same binding site with another

**3.2. Previous treatment of ITC experimental data for thermodynamic analysis** 

**3.3. Corrections to possible additional heat contributions to the binding** 

The fitting of the experimental data to the equations explained in the next Section, will allow us to obtain, besides the binding constant or the Gibbs energy, the binding enthalpy. Sometimes this enthalpy change obtained from the fittings of experimental data is the result of additional events occurring during the ligand binding process. So it is important to distinguish between the apparent binding enthalpy, *ΔHapp*, and the real or intrinsic binding

One of the possible events associated to the ligand binding process can be a conformational change of the protein and/or the ligand not associated uniquely to the interaction. A typical example is when the free protein is partially denatured at the experimental temperature, so it is important to check the folding of the protein using other techniques, as circular

Another possibility is that the ligand binding to the protein can be associated to a change in the pKa of ionisable groups of the protein or/and the ligand [16-18], in such a way that:

Once the ITC experiment has been performed (black titration in panel A of Figure 8), the thermogram can be integrated to obtain the corresponding heats of each injection. Nevertheless, in order to correct the dilution heat effect of the ligand it is necessary to make a baseline ITC experiment (red titration in panel A of Figure 8), which consist of performing an identical ITC experiment of the ligand binding but with buffer instead of protein into the calorimetric cell. Then, the heats for each injection obtained in this baseline experiment are subtracted to the corresponding ones to the ligand binding experiment. Afterwards, we have to normalize the obtained net heats by the total concentration of ligand in the cell after each injection. The binding isotherm can be obtained by the representation of transferred heat per added mole of ligand (*dQi/dLT,i*) versus the molar fraction (*[L]T/[M]T*) (panel B in Figure 8).

The analysis of the isotherms is done by the non-linear fitting of the experimental data using different equations, depending on the way the ligand binds to the macromolecule. In this Section we are going to describe, as an example, the four most common models in the literature. The fittings can be done with the appropriate software, as Origin 7.0 (Microcal Software Inc.) or SigmaPlot 2000 (Jandel Co.).

### **4.1. Ligand binding to one macromolecule with** *n* **identical and independent sites**

Although the mathematical formulae corresponding to this binding model has been described in Section 2.2.3, we will start defining several functions and parameters. Thus, the binding parameter, , being the relationship between the concentration of bound ligand, *[L]b*, and the total macromolecule concentration, *[M]T*, can be the one given in equation 18:

$$
\overline{\nu} = \frac{nk\left\lceil L\right\rceil}{1 + k\left\lceil L\right\rceil}\tag{36}
$$

where *k* is the microscopic equilibrium constant, which is unique since all binding sites are independent, *[L]* is the concentration of non-bounded ligand and *n* is the number of binding sites in the macromolecule.

The heat released or absorbed in any ITC injection, *qi*, is related to the binding process as

$$q\_{\circ} = \Delta H\_{app} (\frac{k \text{J}}{mol \text{L}\_{b}}) \Delta \text{(moles} \text{L}\_{b}) \tag{37}$$

where *ΔHapp* is the apparent enthalpy change per mole of bound ligand, and *(molesLb)* is the molar amount of ligand bounded in the injection *i*. If we express the moles of ligand bound in terms of concentrations, the above equation can be written as:

$$\boldsymbol{\eta}\_{\mathbf{j}} = \boldsymbol{\Delta} \boldsymbol{H}\_{\mathrm{app}} \cdot \boldsymbol{V}\_{\mathbf{C}} \cdot (\left[ \boldsymbol{\mathcal{L}} \right]\_{b,i} - \left[ \boldsymbol{\mathcal{L}} \right]\_{b,i-1}) = \boldsymbol{\Delta} \boldsymbol{H}\_{\mathrm{app}} \cdot \boldsymbol{V}\_{\mathbf{C}} \cdot (\bar{\boldsymbol{\nu}}\_{\mathbf{I}} \cdot \left[ \boldsymbol{M} \right]\_{T,i} - \bar{\boldsymbol{\nu}}\_{i-1} \cdot \left[ \boldsymbol{M} \right]\_{T,i-1}) \tag{38}$$

96 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

where *Vc* represents the effective volume of the ITC cell and *[M]T* is the total concentration of the protein in the cell at injection *i*.

Furthermore, as known parameters the effective volume of the ITC cell, *Vc*, the injection volume, *Vinj*, and the ligand concentration in the syringe, *[L]0*, we can express the concentrations of macromolecule, *[M]T,i*, and ligand, *[L]T,i*, at each injection using the equations

$$\begin{aligned} \text{[[M]}\!]\_{T,i} = \text{[M]}\!]\_{T,i-1} \frac{V\_{\subset} - V\_{in\text{j}}}{V\_{\subset}} \end{aligned} \qquad \qquad \qquad \begin{aligned} \text{[L]}\!\!)\_{T,i} = \frac{(V\_{\subset} - V\_{in\text{j}}) \cdot \text{[L]}\_{T,i-1} + V\_{in\text{j}} \cdot \text{[L]}\_{0}}{V\_{\subset}} \end{aligned} \tag{39}$$

Thus, the total heat accumulated after N injections could be described as

$$\mathbf{Q} = \sum\_{i=1}^{N} \mathbf{q}\_{i} = \mathbf{V}\_{\mathbf{C}} \cdot \begin{bmatrix} \mathbf{M} \end{bmatrix}\_{\mathbf{T}} \cdot \Delta \mathbf{H}\_{app} \cdot \overline{\mathbf{v}} = \mathbf{V}\_{\mathbf{C}} \cdot \begin{bmatrix} \mathbf{M} \end{bmatrix}\_{\mathbf{T}} \cdot \Delta \mathbf{H}\_{app} \cdot \frac{\mathbf{n} \cdot \mathbf{K} \cdot \{\mathbf{L}\}}{\mathbf{1} + \mathbf{K} \cdot \{\mathbf{L}\}} \tag{40}$$

During the ITC experiment the value of the non-bounded ligand concentration, *[L]*, is an unknown variable and for this reason, it is operationally required to estimate it from the experimental variables *[L]T* and *Q* as

$$\text{L}\{\text{L}\} = \text{[L]}\_{T} - \text{[L]}\_{b} = \text{[L]}\_{T} - \frac{\text{Q}}{V\_{\text{C}} \cdot \Delta H\_{app}} \tag{41}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 97

**4.2. Ligand binding to one macromolecule with** *m* **different and independent** 

1· 2

1 2 1 2

[ ] · ·[ ] [ ] 1 ·[ ]

*L nK L M K L*

, ,

1 , ,, ,, 1 , , , 1

(47)

· ·([ ] [ ] ) · ·( ·[ ] ·[ ] )

, , ,

1 2

*kL kL*

(48)

The binding parameter, defined as the ratio of the concentration of ligand bound at any of the two classes of sites, *[L]b,i*, and the total concentration of macromolecule, *[M]T*, can be

> 2 2 , 1 1

1 ,

*i b i kJ q H molesL molL*

Thus, the heat released or absorbed in any injection, qj, would be

*m*

2

2 2

*m m*

*i i*

accumulated in N injections can be re-written as

1 1

 

*m m b i i i <sup>i</sup> <sup>T</sup> i i <sup>i</sup>*

( )·

*j app i b i*

where *ΔHapp,i* is the apparent enthalpy change per mole of ligand bound to any of the two classes of sites. If we express the moles of ligand bound in terms of concentrations, then the

*j i j app i c b i j b i j app i c T j T j*

where Vc represents the effective volume of the ITC cell and [*M*]T,j is the concentration of

2 2

Solving the summation for two classes of sites, m=2, the expression of the total heat

· ·[ ] [ ] [ ]· 1 ·[ ] *i N <sup>j</sup> app i app i N m <sup>m</sup> i i c c T T j i i i nk L Q q VM H VM H k L* 

> ,1 ,2 1 1 2 2 ·· ·

· ·[ ] · ·[ ] [ ] 1 ·[ ] 1 ·[ ] *app app <sup>c</sup> <sup>T</sup> nk L nk L QVM H <sup>H</sup>*

*q H VL L H V M M*

Thus, if we substitute equations 39 in the above expression, we obtain the following:

·· · · 1 1 1

 

*K K M n n L MLn n* (44)

(45)

(46)

 

(49)

In this model, each binding site is defined as an independent site, with different affinity to the other binding sites. The expression "different sites" implies a microscopic equilibrium constant for each binding site, and the term "independent" site means that the binding affinity does not change with the binding of any other ligand to the other sites of the macromolecule. The mathematical formulae that we describe here correspond to a macromolecule with only two different classes of sites (m = 2) with *n1* and *n2* sites for each

**classes of sites** 

expressed now as

type, as represented in the following scheme:

above equation can be re-formulated as:

protein in the cell after injection j.

Substituting the above equation in equation 40 we obtain a quadratic equation with Q as unknown variable, whose solution is

$$Q = \frac{Vc \cdot \Delta H\_{app}}{2 \cdot k} \left[ 1 + k \cdot [\mathrm{L}]\_{\mathrm{T}} + n \cdot k \cdot [\mathrm{M}]\_{\mathrm{T}} - \sqrt{(1 + k \cdot [\mathrm{L}]\_{\mathrm{T}} + n \cdot k \cdot [\mathrm{M}]\_{\mathrm{T}})^2 - 4 \cdot n \cdot k^2 \langle \mathrm{M} \rangle\_{\mathrm{T}} \cdot [\mathrm{L}]\_{\mathrm{T}}} \right] \tag{42}$$

Finally, deriving this expression with respect to *[L]T* we obtain an expression for the heat per mole of ligand added in each injection

$$\frac{1}{V\_c} \cdot \frac{d\underline{Q}}{d\llbracket L \rrbracket\_\Gamma} \approx \frac{1}{V\_c} \cdot \frac{\Delta \underline{Q}}{\Delta \llbracket L \rrbracket\_\Gamma} = \frac{\Delta H\_{app}}{2} \left[ 1 - \frac{1 + [L]\_\Gamma - \eta \cdot k \cdot [M]\_\Gamma}{\sqrt{\left(1 + k \left\{ L \rrbracket\_\Gamma + \eta \cdot k \cdot [M]\_\Gamma \right\}^2 - 4 \cdot \eta \cdot k^2 \cdot [M]\_\Gamma \cdot [L]\_\Gamma}} \right] \tag{43}$$

According to these equations, there are two possible ways to analyze the experimental heats from an ITC experiment: one by using equation 43 which considers the heat per mole of added ligand associated with each injection; the second by using equation 42 and considering the total heat accumulated from the beginning to each injection of the ITC experiment. The first approach has the advantage of avoiding experimental errors, since in such analysis is possible to eliminate individual experimental points from the curve (Figure 8), while the second approach imply the sum of all the heats of each injection which accumulates errors.

### **4.2. Ligand binding to one macromolecule with** *m* **different and independent classes of sites**

Applications of Calorimetry in a Wide Context –

the protein in the cell at injection *i*.

equations

96 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

, ,1 ,

Thus, the total heat accumulated after N injections could be described as

*[M] [M] [L] V V*

*Ti Ti T i*

1

*i*

experimental variables *[L]T* and *Q* as

unknown variable, whose solution is

*app*

mole of ligand added in each injection

2

accumulates errors.

*Vc · H*

*N*

where *Vc* represents the effective volume of the ITC cell and *[M]T* is the total concentration of

Furthermore, as known parameters the effective volume of the ITC cell, *Vc*, the injection volume, *Vinj*, and the ligand concentration in the syringe, *[L]0*, we can express the concentrations of macromolecule, *[M]T,i*, and ligand, *[L]T,i*, at each injection using the

*C inj C inj T i inj*

*V V (V V )·[L] V ·[L]*

(39)

(40)

*C app*

*T T T T T T*

*V ·H* (41)

2 2

(43)

*C C*

· · <sup>1</sup>

*i C T app C T app*

*n·K·[L] Q q V [M] · H ·<sup>ν</sup> V [M] · H · K·[L]*

During the ITC experiment the value of the non-bounded ligand concentration, *[L]*, is an unknown variable and for this reason, it is operationally required to estimate it from the

*TbT*

Substituting the above equation in equation 40 we obtain a quadratic equation with Q as

2 2 1 14

(42)

*app T T*

 

*<sup>Q</sup> k·[L] n·k·[M] ( k·[L] n·k·[M] ) ·n·k [M] ·[L] ·k*

1 1 1 [ ] · ·[ ] ·· 1

*dQ Q H L nk M*

Finally, deriving this expression with respect to *[L]T* we obtain an expression for the heat per

[] [] 2 (1 ·[ ] · ·[ ] ) 4· · ·[ ] ·[ ]

*c Tc T T T T T*

According to these equations, there are two possible ways to analyze the experimental heats from an ITC experiment: one by using equation 43 which considers the heat per mole of added ligand associated with each injection; the second by using equation 42 and considering the total heat accumulated from the beginning to each injection of the ITC experiment. The first approach has the advantage of avoiding experimental errors, since in such analysis is possible to eliminate individual experimental points from the curve (Figure 8), while the second approach imply the sum of all the heats of each injection which

*V dL V L k L nk M nk M L*

*<sup>Q</sup> [L] [L] [L] [L]*

, 1 0

In this model, each binding site is defined as an independent site, with different affinity to the other binding sites. The expression "different sites" implies a microscopic equilibrium constant for each binding site, and the term "independent" site means that the binding affinity does not change with the binding of any other ligand to the other sites of the macromolecule. The mathematical formulae that we describe here correspond to a macromolecule with only two different classes of sites (m = 2) with *n1* and *n2* sites for each type, as represented in the following scheme:

$$M + \left(n\_1 + n\_2\right)L \leftarrow \xrightarrow{K1 \cdot K2} ML\_{n1+n2} \tag{44}$$

The binding parameter, defined as the ratio of the concentration of ligand bound at any of the two classes of sites, *[L]b,i*, and the total concentration of macromolecule, *[M]T*, can be expressed now as

$$\overline{\nu} = \sum\_{i=1}^{m=2} \overline{\nu}\_i = \frac{\llbracket L \rrbracket\_{\mathbb{H}} i}{\llbracket M \rrbracket^r} = \sum\_{i=1}^{m=2} \frac{n\_i \cdot K\_i \cdot \llbracket L \rrbracket}{1 + K\_i \cdot \llbracket L \rrbracket} \tag{45}$$

Thus, the heat released or absorbed in any injection, qj, would be

$$q\_{j} = \sum\_{i=1}^{m=2} \Delta H\_{app,i}(\frac{kJ}{molL\_{b,i}}) \cdot \Delta \left(molesL\_{b,i}\right) \tag{46}$$

where *ΔHapp,i* is the apparent enthalpy change per mole of ligand bound to any of the two classes of sites. If we express the moles of ligand bound in terms of concentrations, then the above equation can be re-formulated as:

$$q\_{j} = \sum\_{i=1}^{m=2} \Delta H\_{app,i} \cdot V\_{c} \cdot (\![L]\_{b,i,j} - \![L]\_{b,i,j-1}) = \sum\_{i=1}^{m=2} \Delta H\_{app,i} \cdot V\_{c} \cdot (\![\nu] \cdot \![M]\_{\Gamma,j} - \![\nu] \cdot \![M]\_{\Gamma,j-1}) \tag{47}$$

where Vc represents the effective volume of the ITC cell and [*M*]T,j is the concentration of protein in the cell after injection j.

Thus, if we substitute equations 39 in the above expression, we obtain the following:

$$\mathbf{Q} = \sum\_{j=1}^{N} q\_j = V\_{\mathbf{c}} \cdot \begin{bmatrix} M \end{bmatrix}\_{\Gamma} \cdot \sum\_{i=1}^{m=2} \Delta H\_{\mathbf{s}\mathbf{p},i} \cdot \overline{\mathbf{v}}\_{i,\mathbf{N}} = V\_{\mathbf{c}} \cdot \begin{bmatrix} M \end{bmatrix}\_{\Gamma} \cdot \sum\_{i=1}^{m=2} \Delta H\_{\mathbf{s}\mathbf{p},i} \frac{n\_i \cdot k\_i \cdot \llbracket L \rrbracket}{\mathbf{1} + k\_i \cdot \llbracket L \rrbracket} \tag{48}$$

Solving the summation for two classes of sites, m=2, the expression of the total heat accumulated in N injections can be re-written as

$$\mathcal{Q} = V\_c \cdot \left[ M \right]\_{\Gamma} \left[ \Delta H\_{\text{\tiny app.1}} \frac{n\_1 \cdot k\_1 \cdot \text{[L]}}{1 + k\_1 \cdot \text{[L]}} + \Delta H\_{\text{\tiny app.2}} \frac{n\_2 \cdot k\_2 \cdot \text{[L]}}{1 + k\_2 \cdot \text{[L]}} \right] \tag{49}$$

98 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Since the value of [L] is unknown, we should express it in terms of total bound ligand ( , 12 [ ] [ ]·[ ] *b T <sup>T</sup> L M* ), as we show in the following equation

$$\begin{aligned} [L] = [L]\_{\Gamma} - [L]\_{b,\Gamma} = [L]\_{\Gamma} - [M]\_{\Gamma} \left[ \frac{n\_1 \cdot k\_1 \left\lceil L \right\rceil}{1 + k\_1 \left\lceil L \right\rceil} + \frac{n\_2 \cdot k\_2 \left\lceil L \right\rceil}{1 + k\_2 \left\lceil L \right\rceil} \right] \end{aligned} \tag{50}$$

Substituting the previous expression in the equation 49 and re-organizing it, we obtain the following cubic equation:

$$a\_1 \left[ L \right]^3 + a\_2 \left[ L \right]^2 + a\_1 \left[ L \right] + a\_0 = 0 \tag{51}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

(57)

(59)

(56)

· ·

*M A MB*

0 0 [ ] [ ] [ ] [] [ ] [] *A MA A B MB B* (58)

*MA MB*

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 99

*A B*

*A*

*M A MA K K*

Because the binding of two ligands takes place in the same binding site of the macromolecule, and having the ligand *A* tighter affinity than ligand *B*, *KA >> KB*, we should

> *B A*

*MB A MA B*

According to the schemes 56 and 57 we can express the initial concentration of the ligands A

Substituting these expressions in equations 56, the association constants can be re-written as

1 / 1 / *<sup>A</sup> <sup>B</sup>*

It is important to consider that in the case we propose for this binding model, it is usual that the binding of the high-affinity ligand *A* has been previously analyzed in a simple titration experiment. The displacement titration experiment will allow us to analyze the interaction of the low affinity ligand *B*, which cannot be determined by direct titration experiments. Thus, initially, the macromolecule *M* is bounded to ligand *B* forming the *MB* complex and during the titration of the ligand *A* we will shift partially the *MB* complex formation to the

For the mathematical formulae of this model, we first define the molar fractions of all

If we also write the molar ratios between the initial amounts of A and B relative to the total

we can write the concentrations of *A* and *B* bounded ligands during the interaction as

Then, substituting these expressions in equations 59, we obtain the following equations for all the species that form the macromolecule, expressed in terms of the molar ratios of

*<sup>M</sup>* [ ]/[ ] [ ]/[ ] [ ]/[ ] *T MA <sup>T</sup> MB <sup>T</sup> x M M x MA M x MB M* (60)

0 0 [ ] /[ ] [ ] /[ ] *<sup>A</sup> TB T r AM rBM* (61)

·[ ] ·[ ] *<sup>A</sup> A T BB T c KM c KM* (62)

*MA MB*

0 0 · ·

*K M K M*

*M A M B*

*K K M B MB*

*K*

*B*

*K*

*M B MB*

consider the following scheme

formation of the *MA* complex.

macromolecule concentration as

products of the association constants

macromolecule:

species containing the macromolecule. Such fractions are

where [M]T is the total concentration of macromolecule.

and B as

where the coefficients *a0*, *a1* and *a2* are defined as

$$\begin{aligned} a\_0 &= -\frac{\left[\boldsymbol{L}\_T\right]}{k\_1 k\_2} \\ a\_1 &= \left(\frac{n\_1}{k\_2} + \frac{n\_2}{k\_1}\right) \left[\boldsymbol{M}\_T\right] - \left(\frac{1}{k\_1} + \frac{1}{k\_2}\right) \left[\boldsymbol{L}\_T\right] + \frac{1}{k\_1 k\_2} \\ a\_2 &= \frac{1}{k\_1} + \frac{1}{k\_2} + \left(n\_1 + n\_2\right) \left[\boldsymbol{M}\_T\right] - \left[\boldsymbol{L}\_T\right] \end{aligned} \tag{52}$$

The only valid solution to the cubic equation 51 can be simply written by just grouping the coefficients *a0*, *a1* and *a2* in three new coefficients *A*, *B* and *C* as

$$
\begin{bmatrix} L \ \end{bmatrix} = \sqrt[3]{A + \sqrt{A^2 + B^3}} + \sqrt[3]{A - \sqrt{A^2 + B^3}} + \text{C} \tag{53}
$$

where *A*, *B* and *C* are

$$A = \frac{-a\_2^3}{27} + \frac{a\_1 a\_2}{6} - \frac{a\_0}{2} \qquad \qquad \qquad B = \left(\frac{a\_1}{3} - \frac{a\_2^2}{9}\right) \qquad \qquad C = -\frac{a\_2}{3} \tag{54}$$

The solution of the cubic equation (using equations 52 to 54) allows us to calculate the nonbounded ligand concentration for a given number of injections. Substituting in equation 49, we can determine the heat associated to each injection using the following expression:

$$dQ \approx \Lambda Q(j) = Q\_T(j) - Q\_T(j-1) + \frac{V\_{in}}{V\_C} \left(\frac{Q\_T(j) + Q\_T(j-1)}{2}\right) \tag{55}$$

### **4.3. Ligand binding by the displacement of another ligand in the single binding site of a macromolecule**

To formulate this binding model of displacement, we assume two ligands, A and B, which can bind to the same binding site of a protein, M, with different affinity constants. Then, we can describe the equilibrium binding for each ligand as:

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 99

$$M + A \leftarrow \xrightarrow{K\_A} MA \qquad \qquad \qquad K\_A = \begin{bmatrix} \left[ MA \right] \\ \left[ \left[ M \right] \right] \left[ A \right] \end{bmatrix} \qquad K\_B = \begin{bmatrix} \left[ MB \right] \\ \left[ M \right] \left[ \left[ B \right] \right] \end{bmatrix} \tag{56}$$
  $M + B \leftarrow \xrightarrow{K\_B} MB$ 

Because the binding of two ligands takes place in the same binding site of the macromolecule, and having the ligand *A* tighter affinity than ligand *B*, *KA >> KB*, we should consider the following scheme

$$\begin{aligned} \text{MB} + \text{B} &\xleftarrow{K\_{\text{B}}} \text{MB} \\ \text{MB} + \text{A} &\xleftarrow{K\_{\text{A}}} \text{MA} + \text{B} \end{aligned} \tag{57}$$

According to the schemes 56 and 57 we can express the initial concentration of the ligands A and B as

$$[A]\_0 = [MA] + [A] \qquad \qquad [B]\_0 = [MB] + [B] \tag{58}$$

Substituting these expressions in equations 56, the association constants can be re-written as

$$
\begin{bmatrix}
\begin{bmatrix}
\boldsymbol{MA} \end{bmatrix}
\end{bmatrix} = \frac{\begin{bmatrix}
\boldsymbol{M} \ \boldsymbol{\bar{J}}
\end{bmatrix}
\begin{bmatrix}
\boldsymbol{A} \ \boldsymbol{\bar{J}}
\end{bmatrix}\_{0}}{\begin{bmatrix}
\boldsymbol{M} \ \boldsymbol{K}\_{A}
\end{bmatrix}
\begin{bmatrix}
\boldsymbol{A}
\end{bmatrix}}
\tag{59}
$$

$$
\begin{bmatrix}
\boldsymbol{M} \ \boldsymbol{B}
\end{bmatrix} = \begin{bmatrix}
\boldsymbol{M} \ \boldsymbol{\bar{J}}
\end{bmatrix} \begin{bmatrix}
\boldsymbol{B} \\
\boldsymbol{0}
\end{bmatrix}
\tag{50}
$$

It is important to consider that in the case we propose for this binding model, it is usual that the binding of the high-affinity ligand *A* has been previously analyzed in a simple titration experiment. The displacement titration experiment will allow us to analyze the interaction of the low affinity ligand *B*, which cannot be determined by direct titration experiments. Thus, initially, the macromolecule *M* is bounded to ligand *B* forming the *MB* complex and during the titration of the ligand *A* we will shift partially the *MB* complex formation to the formation of the *MA* complex.

For the mathematical formulae of this model, we first define the molar fractions of all species containing the macromolecule. Such fractions are

$$\mathbf{x}\_{M} = \text{[} \text{M]} / \text{[} \text{[} \text{M]} \mathbf{}\_{\Gamma} \qquad \mathbf{x}\_{\text{MA}} = \text{[} \text{MA} \text{]} / \text{[} \text{[} \text{M]} \text{]} \mathbf{}\_{\Gamma} \qquad \qquad \qquad \mathbf{x}\_{\text{MB}} = \text{[} \text{MB} \text{]} / \text{[} \text{[} \text{M]} \text{]} \mathbf{}\_{\Gamma} \tag{60}$$

where [M]T is the total concentration of macromolecule.

Applications of Calorimetry in a Wide Context –

where the coefficients *a0*, *a1* and *a2* are defined as

0

*a*

1

1 2 1 2

*T*

*L*

*k k*

1 1

*k k*

coefficients *a0*, *a1* and *a2* in three new coefficients *A*, *B* and *C* as

2 1 2 1 2

( , 12 [ ] [ ]·[ ] *b T <sup>T</sup> L M* 

following cubic equation:

where *A*, *B* and *C* are

**site of a macromolecule** 

98 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

 11 22 ,

*LL L L M*

), as we show in the following equation

Since the value of [L] is unknown, we should express it in terms of total bound ligand

Substituting the previous expression in the equation 49 and re-organizing it, we obtain the

·· ·· [ ] [ ] [ ] [ ] [ ]· 1· 1· *T bT T T*

3 2

3 2

*T T*

can describe the equilibrium binding for each ligand as:

*<sup>V</sup> Qj Qj dQ Q j Q j Q j <sup>V</sup>*

*a nnM L*

*n n aM L*

 

2 1 1 2 1 2

*k k k k kk*

The only valid solution to the cubic equation 51 can be simply written by just grouping the

2 12 0 1 2 2 27 6 2 3 9 3 *a aa <sup>a</sup> a a <sup>a</sup> A BC*

( ) ( 1) ( ) ( ) ( 1) <sup>2</sup>

**4.3. Ligand binding by the displacement of another ligand in the single binding** 

To formulate this binding model of displacement, we assume two ligands, A and B, which can bind to the same binding site of a protein, M, with different affinity constants. Then, we

*C*

The solution of the cubic equation (using equations 52 to 54) allows us to calculate the nonbounded ligand concentration for a given number of injections. Substituting in equation 49, we can determine the heat associated to each injection using the following expression:

*in T T*

*T T*

*T T*

11 1

3 3 23 23 *L A AB A ABC* (53)

1 2

*kL kL*

2 10 *L aL aL a* 0 (51)

(50)

(52)

(54)

(55)

*nk L nk L*

If we also write the molar ratios between the initial amounts of A and B relative to the total macromolecule concentration as

$$r\_A = [A]\_0 / \,\text{[}M\text{]}\_T \qquad r\_B = [B]\_0 / \,\text{[}M\text{]}\_T \tag{61}$$

we can write the concentrations of *A* and *B* bounded ligands during the interaction as products of the association constants

$$\mathbf{c}\_A = \mathbf{K}\_A \cdot \mathbf{[M]}\_\mathbf{I} \qquad \qquad \mathbf{c}\_B = \mathbf{K}\_B \cdot \mathbf{[M]}\_\mathbf{I} \tag{62}$$

Then, substituting these expressions in equations 59, we obtain the following equations for all the species that form the macromolecule, expressed in terms of the molar ratios of macromolecule:

100 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

$$\mathbf{x}\_{M} + \mathbf{x}\_{MA} + \mathbf{x}\_{MB} = \mathbf{1} \qquad \qquad \qquad \mathbf{x}\_{MA} = \frac{r\_A \cdot \mathbf{x}\_M}{1/\left\langle \mathbf{c}\_A + \mathbf{x}\_M \right\rangle} \qquad \qquad \qquad \mathbf{x}\_{MB} = \frac{r\_B \cdot \mathbf{x}\_M}{1/\left\langle \mathbf{c}\_B + \mathbf{x}\_M \right\rangle} \tag{63}$$

Substituting the above equations of *xMA* and *xMB* into the first one and rearranging, we obtain the following cubic equation:

$$
\boldsymbol{\alpha}\_M^3 + \boldsymbol{a} \cdot \boldsymbol{\alpha}\_M^2 + \boldsymbol{b} \cdot \boldsymbol{\alpha}\_M + \boldsymbol{c} = \boldsymbol{0} \tag{64}
$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

2

(73)

2

<sup>2</sup>

*A*

*A B*

*A AB*

*A AB*

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 101

<sup>1</sup> 1 1 (1 )*i ii i i i ii i A A f M fM B fB* (71)

*<sup>c</sup>*· · ·( · ) ( · ) *A B MA i i MA i* , , 1 · *MB i i MB i* , ,1 *<sup>T</sup> dQ Q V M H x f x H x f x* (72)

where fi is the dilution factor that allow us to define the molar ratios after each injection as

Consequently, the heat absorbed or released after each injection can be expressed as

**4.4. Ligand binding to a macromolecule with two dependent (cooperative)** 

The scheme described in Figure 2 for a macromolecule with two binding sites was used in Section 2.2.2 to describe the correlation between macroscopic and microscopic equilibrium constants and the binding parameter was obtained for the case of independent sites, characterized by the same microscopic constant. Nevertheless, when cooperativity exists among sites, this simple assumption cannot be considered, and more than one value for such constants must be taken into account. Thus, positive cooperativity would be revealed when *k3 > k1* and *k4 > k2*, and the opposite is true for negative cooperativity. In any case, it can

The most simplified version of this model could be attained for equivalent binding sites, that is, when microscopic binding to the first site is identical, independently if the ligand binds to either site 1 or 2. The occupancy of the first site will drive to the modification of the affinity of the second one, in a similar way in both branches of the scheme. Therefore, *k1 = k2* and *k3 = k4*. In parallel, the enthalpy changes associated can be also grouped in only two different values, the changes for the formation of ML and ML2 species respectively. From here, any other version should be much more complicated from a mathematical point of view. Overcoming these calculation matters, the solution can be achieved in a similar way to the described here for the

simplest version, which is also inspired in the models described previously.

The molar fractions of all species containing the macromolecule are in this case

2

2

2 1 2

2 1 2

2 2 2

Taking into account the equation 40, the total heat accumulated after N injections could be

*ML k L*

*M ML ML k L kk L*

*ML kk L*

*M ML ML k L kk L*

*i C T app C T ML A B ML A B*

*Q q V [M] · H · <sup>ν</sup> V [M] · x H H x H H* (74)

**binding sites** 

be easily deduced that *k3·k1 = k4·k2*.

*ML*

*x*

*x*

described as

\_1

*i*

*N*

*ML*

where we have assumed that *k1 = k2= kA* and *k3 = k4= kB*.

· ·

in which we have defined the *a*, *b* and *c* coefficients as:

$$a = \frac{1}{c\_A} + \frac{1}{c\_B} + r\_A + r\_B - 1 \qquad b = \frac{r\_A - 1}{c\_A} + \frac{r\_B - 1}{c\_B} + \frac{1}{c\_A \cdot c\_B} \qquad c = -\frac{1}{c\_A \cdot c\_B} \tag{65}$$

Solving such cubic equation, we obtain the following real solution for the molar fraction of macromolecule:

$$\propto x\_M = \frac{2 \cdot (\sqrt{a^2 - 3b}) \cdot \cos(\phi/3) - a}{3} \tag{66}$$

in which the coefficient can be written as:

$$\phi = \arccos \frac{-2 \cdot a^3 - 9 \cdot a \cdot b - 27 \cdot c}{2 \cdot (\sqrt{a^2 - 3 \cdot b})^3} \tag{67}$$

Once the molar fraction of free macromolecule, *xM*, is determined, we can also know the molar fractions of the other species in which the macromolecule is present (*xMA* and *xMB*) by solving the equations 63.

The heat released or absorbed after each injection is proportional to the changes in concentration of MA and MB, [MA] and [MB], and their molar enthalpies of binding. Therefore, the heat after each injection can be written according to the following expression

$$
\Delta Q = V\_{\hat{c}} \cdot \left( \Delta H\_{\hat{A}} \cdot \Delta \left[ MA \right] + \Delta H\_{\hat{s}} \cdot \Delta \left[ MB \right] \right) = V\_{\hat{c}} \cdot \left[ M \right]\_{T} \cdot \left( \Delta H\_{\hat{A}} \cdot \Delta \mathbf{x}\_{MA} + \Delta H\_{\hat{s}} \cdot \Delta \mathbf{x}\_{MB} \right) \tag{68}
$$

where Vc is the effective volume of the ITC cell. To correct the concentrations of macromolecule and ligand, we define the following infinitesimal change for their concentrations

$$d\left[\left.X\right] = -\frac{dV\_i}{V\_0}\right[X] \tag{69}$$

where *[X]* represents the concentration of any species. Integrating the above expression between the limits from *[X]i* to *[X]i-1* and from zero to Vi. The resulting equation is

$$\mathbb{E}\left[\left.X\right]\_i\right] = \left[\left.X\right]\_{i-1}\right] \exp\left(-\frac{V\_i}{V\_0}\right) = \left[\left.X\right]\_{i-1} f\_i\right] \tag{70}$$

where fi is the dilution factor that allow us to define the molar ratios after each injection as

$$
\begin{bmatrix} A \\ \end{bmatrix}\_i = \begin{bmatrix} A \\ \end{bmatrix}\_{i-1} (1 - f\_i) \qquad \qquad \begin{bmatrix} M \\ \end{bmatrix}\_i = f\_i \begin{bmatrix} M \\ \end{bmatrix}\_{i-1} \quad \begin{bmatrix} B \\ \end{bmatrix}\_i = f\_i \begin{bmatrix} B \\ \end{bmatrix}\_{i-1} \tag{71}
$$

Consequently, the heat absorbed or released after each injection can be expressed as

Applications of Calorimetry in a Wide Context –

the following cubic equation:

macromolecule:

solving the equations 63.

concentrations

100 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

in which we have defined the *a*, *b* and *c* coefficients as:

in which the coefficient can be written as:

*A B*

*M MA MB MA MB*

Substituting the above equations of *xMA* and *xMB* into the first one and rearranging, we obtain

1 1 1 1 1 1 <sup>1</sup> · · *A B*

*c c c c cc cc*

Solving such cubic equation, we obtain the following real solution for the molar fraction of

<sup>2</sup> 2·( 3 )·cos( / 3)

3

Once the molar fraction of free macromolecule, *xM*, is determined, we can also know the molar fractions of the other species in which the macromolecule is present (*xMA* and *xMB*) by

The heat released or absorbed after each injection is proportional to the changes in concentration of MA and MB, [MA] and [MB], and their molar enthalpies of binding. Therefore, the heat after each injection can be written according to the following expression

· · ( · ·· · ) ·( ) *A B A B Q V H MA H MB V M H x H x c c <sup>T</sup> MA MB*

where Vc is the effective volume of the ITC cell. To correct the concentrations of macromolecule and ligand, we define the following infinitesimal change for their

> *<sup>i</sup> dV dX X V*

where *[X]* represents the concentration of any species. Integrating the above expression

exp *<sup>i</sup> i i i i V X X X f <sup>V</sup>* 

between the limits from *[X]i* to *[X]i-1* and from zero to Vi. The resulting equation is

0 ·

1 1 0

*ab a*

2 3 2· 9· · 27·

(68)

(69)

2·( 3· ) *a ab c a b*

*r r a rr b <sup>c</sup>*

3 *<sup>M</sup>*

*<sup>x</sup>*

arccos

*A B A B AB A B*

(65)

*xx x x x*

· · <sup>1</sup>

1 / 1 /

*A M B M*

*c x c x*

3 2 *x ax bx c MMM* ·· 0 (64)

(66)

(67)

(70)

*r x r x*

*A M B M*

(63)

$$d\mathcal{Q} \approx \Delta \mathcal{Q} = V\_{\mathbb{C}} \Big[ \boldsymbol{M} \Big]\_{\mathcal{I}} \Big[ \Delta \boldsymbol{H}\_{\boldsymbol{A}} \cdot \{ \Delta \mathbf{x}\_{\text{MA},i} - \boldsymbol{f}\_{i} \cdot \mathbf{x}\_{\text{MA},i-1} \} + \Delta \boldsymbol{H}\_{\boldsymbol{a}} \cdot \{ \Delta \mathbf{x}\_{\text{MB},i} - \boldsymbol{f}\_{i} \cdot \mathbf{x}\_{\text{MB},i-1} \} \Big] \tag{72}$$

### **4.4. Ligand binding to a macromolecule with two dependent (cooperative) binding sites**

The scheme described in Figure 2 for a macromolecule with two binding sites was used in Section 2.2.2 to describe the correlation between macroscopic and microscopic equilibrium constants and the binding parameter was obtained for the case of independent sites, characterized by the same microscopic constant. Nevertheless, when cooperativity exists among sites, this simple assumption cannot be considered, and more than one value for such constants must be taken into account. Thus, positive cooperativity would be revealed when *k3 > k1* and *k4 > k2*, and the opposite is true for negative cooperativity. In any case, it can be easily deduced that *k3·k1 = k4·k2*.

The most simplified version of this model could be attained for equivalent binding sites, that is, when microscopic binding to the first site is identical, independently if the ligand binds to either site 1 or 2. The occupancy of the first site will drive to the modification of the affinity of the second one, in a similar way in both branches of the scheme. Therefore, *k1 = k2* and *k3 = k4*. In parallel, the enthalpy changes associated can be also grouped in only two different values, the changes for the formation of ML and ML2 species respectively. From here, any other version should be much more complicated from a mathematical point of view. Overcoming these calculation matters, the solution can be achieved in a similar way to the described here for the simplest version, which is also inspired in the models described previously.

The molar fractions of all species containing the macromolecule are in this case

$$\begin{aligned} \text{tr}\_{ML} &= \frac{\left[\begin{array}{c} ML \\ \hline \end{array}\right]}{\left[\begin{array}{c} ML \end{array}\right] + 2\left[\begin{array}{c} ML \end{array}\right] + \left[\begin{array}{c} ML\_{2} \end{array}\right]} = \frac{k\_{A}\left[\begin{array}{c} L \end{array}\right]}{1 + 2k\_{A}\left[\begin{array}{c} L \end{array}\right] + k\_{A}k\_{B}\left[\begin{array}{c} L \end{array}\right]^{2}} \\ \text{tr}\_{ML,2} &= \frac{\left[\begin{array}{c} ML\_{2} \end{array}\right]}{\left[\begin{array}{c} M \end{array}\right] + 2\left[\begin{array}{c} ML \end{array}\right] + \left[\begin{array}{c} ML\_{2} \end{array}\right]} = \frac{k\_{A}k\_{B}\left[L \right]^{2}}{1 + 2k\_{A}\left[\begin{array}{c} L \end{array}\right] + k\_{A}k\_{B}\left[L \right]^{2}} \end{aligned} \tag{73}$$

where we have assumed that *k1 = k2= kA* and *k3 = k4= kB*.

Taking into account the equation 40, the total heat accumulated after N injections could be described as

$$\mathbf{Q} = \sum\_{i=1}^{N} q\_i = V\_{\mathbb{C}} \cdot \{\mathbf{M}\}\_{\mathbb{T}} \cdot \Delta H\_{\text{app}} \cdot \overline{\boldsymbol{\nu}} = V\_{\mathbb{C}} \cdot \{\mathbf{M}\}\_{\mathbb{T}} \cdot \left\{ \mathbf{x}\_{\text{ML}} \left( \Delta H\_A + \Delta H\_B \right) + \mathbf{x}\_{\text{ML2}} \left( \Delta H\_A + \Delta H\_B \right) \right\} \tag{74}$$

where HA and HB are the enthalpy changes associated to equilibriums characterized by kA and kB respectively. Since the value of [L] is unknown, we should express it in terms of total ligand ( <sup>2</sup> [] 2 2 *<sup>T</sup> L L ML ML* ), as we show in the following equation

$$\mathbb{E}\left[L\right] = \left[L\right]\_{\Gamma} - 2 \cdot \mathbb{x}\_{ML} \left[M\right]\_{\Gamma} - 2 \cdot \mathbb{x}\_{ML2} \left[M\right]\_{\Gamma} \tag{75}$$

Isothermal Titration Calorimetry: Thermodynamic Analysis

of the Binding Thermograms of Molecular Recognition Events by Using Equilibrium Models 103

mathematical point of view. That is, the total heat accumulated after N injections as a function of the binding parameter (equation 40) and the concentration of free ligand as a function of the well-known total concentrations of macromolecule and ligand. Both solutions can be replaced into an equation such as 80 to determine the heat associated to

These heats divided by the number of moles of ligand added represent the dependent variable of the curve fitting analysis (*dQi/dLi*), where the ratio between the total concentrations of ligand and macromolecule *[L]T/[M]T* represents the independent variable of the fitting function. The results of this non-linear regression analysis provide the values of the equilibrium constants and the respective enthalpy changes involved in such

This work was financed by grant CVI-5915 from the Andalucian Regional Goverment (Spain), grant BIO2009-13261-C02-01 from the Spanish Ministry of Science and Technology,

[1] Langerman N & Biltonen RL (1979) Microcalorimeters for biological chemistry: applications, instrumentation and experimental design. Methods Enzymol 61: 261-286. [2] Biltonen RL & Langerman N (1979) Microcalorimetry for biological chemistry: experimental design, data analysis, and interpretation. Methods Enzymol 61: 287-318. [3] Wyman J (1965) Binding Potential a Neglected Linkage Concept. Journal of Molecular

[4] Hess VL & Szabo A (1979) Ligand-Binding to Macromolecules - Allosteric and Sequential Models of Cooperativity. Journal of Chemical Education 56: 289-293. [5] Szabo A & Karplus M (1972) Mathematical-Model for Structure-Function Relations in

[6] Szabo A & Karplus M (1975) Analysis of cooperativity in hemoglobin. Valency hybrids, oxidation, and methemoglobin replacement reactions. Biochemistry 14: 931-940. [7] Szabo A & Karplus M (1976) Analysis of Interaction of Organic-Phosphates with

[8] Pauling L (1935) The Oxygen Equilibrium of Hemoglobin and Its Structural

Hemoglobin. Journal of Molecular Biology 72: 163-&.

Interpretation. Proc Natl Acad Sci U S A 21: 186-191.

Hemoglobin. Biochemistry 15: 2869-2877.

equilibriums, according to the proposed model. An example is illustrated in Figure 8.

Jose C. Martinez, Javier Murciano-Calles, Eva S. Cobos, Manuel Iglesias-Bexiga,

*Department of Physical Chemistry and Institute of Biotechnology, Faculty of Sciences,* 

each injection.

**Author details** 

**Acknowledgement** 

Biology 11: 631-&.

FEDER and Plan E.

**5. References** 

Irene Luque and Javier Ruiz-Sanz

*University of Granada, Granada, Spain* 

This can be expressed as the following third-order equation:

$$a\_1 \left[\boldsymbol{L}\right]^3 + a\_2 \left[\boldsymbol{L}\right]^2 + a\_1 \left[\boldsymbol{L}\right] + a\_0 = 0\tag{76}$$

where the coefficients *a0*, *a1* and *a2* are defined as

$$a\_0 = -\frac{\lfloor L \rfloor\_\Gamma}{k\_A k\_B} \qquad \qquad a\_1 = \frac{2}{k\_B} \lceil M \rceil\_\Gamma - \frac{2}{k\_B} \lceil L \rceil\_\Gamma + \frac{1}{k\_A k\_B} \qquad \qquad a\_2 = \frac{2}{k\_B} + 2 \lceil M \rceil\_\Gamma - \lceil L \rceil\_\Gamma \tag{77}$$

The only valid solution to the cubic equation above can be simply written by grouping the coefficients *a0*, *a1* and *a2* in three new coefficients *A*, *B* and *C* as follows:

$$
\left[\begin{array}{c}
\mathbb{L}\end{array}\right] = \sqrt[3]{A + \sqrt{A^2 + B^3}} + \sqrt[3]{A - \sqrt{A^2 + B^3}} + \mathbb{C} \tag{78}
$$

where *A*, *B* and *C* are

$$A = \frac{-a\_2^3}{27} + \frac{a\_1 a\_2}{6} - \frac{a\_0}{2} \qquad \qquad \qquad B = \left(\frac{a\_1}{3} - \frac{a\_2^2}{9}\right) \qquad \qquad C = -\frac{a\_2}{3} \tag{79}$$

The solution of the cubic equation (using equations 77 to 79) allows us to calculate the non bounded ligand concentration for a given number of injections. Substituting in equation 74, we can determine the heat associated to each injection using the following expression:

$$d\mathbb{Q} \approx \Lambda \mathbb{Q}(j) = \mathbb{Q}\_{\Gamma}(j) - \mathbb{Q}\_{\Gamma}(j-1) + \frac{V\_{in}}{V\_{\mathbb{C}}} \left( \frac{\mathbb{Q}\_{\Gamma}(j) + \mathbb{Q}\_{\Gamma}(j-1)}{2} \right) \tag{80}$$

#### **4.5. Guidelines for the development of ITC equilibrium models**

Following the reasoning given in this Chapter, it is easy to discern the basic rules to build any ITC model. The main point would be to collect any experimental and structural evidence (number of sites in the macromolecule M for ligand L, their dependent or independent character, etc) to develop the basic interaction scheme. This scheme will drive to the construction of the binding polynomial, *Z*, which derives into the binding parameter, , as it has been described in detail into Section 2.

The examples given into Section 4 for the most common ITC models used reveal that, once the model is described in terms of the binding parameter or by the molar fractions of all species containing the macromolecule, two basic points have to be solved from a mathematical point of view. That is, the total heat accumulated after N injections as a function of the binding parameter (equation 40) and the concentration of free ligand as a function of the well-known total concentrations of macromolecule and ligand. Both solutions can be replaced into an equation such as 80 to determine the heat associated to each injection.

These heats divided by the number of moles of ligand added represent the dependent variable of the curve fitting analysis (*dQi/dLi*), where the ratio between the total concentrations of ligand and macromolecule *[L]T/[M]T* represents the independent variable of the fitting function. The results of this non-linear regression analysis provide the values of the equilibrium constants and the respective enthalpy changes involved in such equilibriums, according to the proposed model. An example is illustrated in Figure 8.

### **Author details**

Applications of Calorimetry in a Wide Context –

102 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

This can be expressed as the following third-order equation:

where the coefficients *a0*, *a1* and *a2* are defined as

*L*

where *A*, *B* and *C* are

where HA and HB are the enthalpy changes associated to equilibriums characterized by kA and kB respectively. Since the value of [L] is unknown, we should express it in terms of

<sup>2</sup> [ ] [ ] 2· [ ] 2· [ ] *T ML T ML T LL xM x M* (75)

2 10 *L aL aL a* 0 (76)

*T T T T*

3 3 23 23 *L A AB A ABC* (78)

(79)

(80)

total ligand ( <sup>2</sup> [] 2 2 *<sup>T</sup> L L ML ML* ), as we show in the following equation

3 2

221 2 <sup>2</sup> *<sup>T</sup>*

*a a M L a ML*

The only valid solution to the cubic equation above can be simply written by grouping the

2 12 0 1 2 2 27 6 2 3 9 3 *a aa <sup>a</sup> a a <sup>a</sup> A BC*

( ) ( 1) ( ) ( ) ( 1) <sup>2</sup>

*C*

The solution of the cubic equation (using equations 77 to 79) allows us to calculate the non bounded ligand concentration for a given number of injections. Substituting in equation 74, we can determine the heat associated to each injection using the following expression:

Following the reasoning given in this Chapter, it is easy to discern the basic rules to build any ITC model. The main point would be to collect any experimental and structural evidence (number of sites in the macromolecule M for ligand L, their dependent or independent character, etc) to develop the basic interaction scheme. This scheme will drive to the construction of the binding polynomial, *Z*, which derives into the binding parameter,

The examples given into Section 4 for the most common ITC models used reveal that, once the model is described in terms of the binding parameter or by the molar fractions of all species containing the macromolecule, two basic points have to be solved from a

*in T T*

(77)

*A B B B AB B*

3 2

*T T*

**4.5. Guidelines for the development of ITC equilibrium models** 

, as it has been described in detail into Section 2.

*<sup>V</sup> Qj Qj dQ Q j Q j Q j <sup>V</sup>* 

*k k k k kk k*

0 1 2

coefficients *a0*, *a1* and *a2* in three new coefficients *A*, *B* and *C* as follows:

Jose C. Martinez, Javier Murciano-Calles, Eva S. Cobos, Manuel Iglesias-Bexiga, Irene Luque and Javier Ruiz-Sanz *Department of Physical Chemistry and Institute of Biotechnology, Faculty of Sciences, University of Granada, Granada, Spain* 

### **Acknowledgement**

This work was financed by grant CVI-5915 from the Andalucian Regional Goverment (Spain), grant BIO2009-13261-C02-01 from the Spanish Ministry of Science and Technology, FEDER and Plan E.

### **5. References**


	- [9] Cuadri-Tome C, Baron C, Jara-Perez V, Parody-Morreale A, Martinez JC & Camara-Artigas A (2006) Kinetic analysis and modelling of the allosteric behaviour of liver and muscle glycogen phosphorylases. J Mol Recognit 19: 451-457, doi: 10.1002/jmr.772.

**Chapter 5** 

© 2013 Romanini et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Applications of Calorimetric Techniques in the** 

Diana Romanini, Mauricio Javier Braia and María Cecilia Porfiri

Additional information is available at the end of the chapter

**1.1. Formation of the protein-polyelectrolyte complex** 

**Figure 1.** Formation of the protein- polyelectrolyte complex (binary complex).

start to interact with each other to form the macroscopic insoluble complex.

http://dx.doi.org/10.5772/54260

**1. Introduction** 

electrical charge.

figure 1.

**Formation of Protein-Polyelectrolytes Complexes** 

Polyelectrolytes are flexible-chain polymers containing subunits with negative or positive charges. These compounds form soluble or insoluble complexes with proteins with opposite

The different equilibriums present in a solution of protein and polyelectrolyte are shown in

As can be seen, when a protein interacts with a polyelectrolyte, a soluble complex is formed containing few molecules of the protein. As more molecules of protein interact with the polyelectrolyte, the complex becomes insoluble. Finally, the particles of insoluble complex

and reproduction in any medium, provided the original work is properly cited.


## **Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes**

Diana Romanini, Mauricio Javier Braia and María Cecilia Porfiri

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54260

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

[pii]10.1038/nprot.2006.28.

[pii]10.1006/abio.1998.2738.

10.1002/Prot.21657.

3: 791-801.

131-137.

2055.

104 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

amino acid sequence data. Anal Biochem 182: 319-326.

10.1006/abio.1999.4402S0003-2697(99)94402-0 [pii].

[9] Cuadri-Tome C, Baron C, Jara-Perez V, Parody-Morreale A, Martinez JC & Camara-Artigas A (2006) Kinetic analysis and modelling of the allosteric behaviour of liver and muscle glycogen phosphorylases. J Mol Recognit 19: 451-457, doi: 10.1002/jmr.772. [10] Ladbury JE & Chowdhry BZ (1996) Sensing the heat: the application of isothermal titration calorimetry to thermodynamic studies of biomolecular interactions. Chem Biol

[11] Wiseman T, Williston S, Brandts JF & Lin LN (1989) Rapid measurement of binding constants and heats of binding using a new titration calorimeter. Anal Biochem 179:

[12] Gill SC & von Hippel PH (1989) Calculation of protein extinction coefficients from

[13] Sigurskjold BW (2000) Exact analysis of competition ligand binding by displacement isothermal titration calorimetry. Anal Biochem 277: 260-266, doi:

[14] Velazquez-Campoy A & Freire E (2006) Isothermal titration calorimetry to determine association constants for high-affinity ligands. Nat Protoc 1: 186-191, doi: nprot.2006.28

[15] Zhang YL & Zhang ZY (1998) Low-affinity binding determined by titration calorimetry using a high-affinity coupling ligand: a thermodynamic study of ligand binding to protein tyrosine phosphatase 1B. Anal Biochem 261: 139-148, doi: S0003-2697(98)92738-5

[16] Baker BM & Murphy KP (1996) Evaluation of linked protonation effects in protein binding reactions using isothermal titration calorimetry. Biophysical Journal 71: 2049-

[17] Mason AC & Jensen JH (2008) Protein-protein binding is often associated with changes in protonation state. Proteins-Structure Function and Bioinformatics 71: 81-91, doi: Doi

[18] Velazquez-Campoy A, Luque I, Todd MJ, Milutinovich M, Kiso Y & Freire E (2000) Thermodynamic dissection of the binding energetics of KNI-272, a potent HIV-1

protease inhibitor. Protein Sci 9: 1801-1809, doi: 10.1110/ps.9.9.1801.

### **1.1. Formation of the protein-polyelectrolyte complex**

Polyelectrolytes are flexible-chain polymers containing subunits with negative or positive charges. These compounds form soluble or insoluble complexes with proteins with opposite electrical charge.

The different equilibriums present in a solution of protein and polyelectrolyte are shown in figure 1.

As can be seen, when a protein interacts with a polyelectrolyte, a soluble complex is formed containing few molecules of the protein. As more molecules of protein interact with the polyelectrolyte, the complex becomes insoluble. Finally, the particles of insoluble complex start to interact with each other to form the macroscopic insoluble complex.

106 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Besides this model of formation of the insoluble complex, there is another model in which the formation of the insoluble complex requires the presence of an inorganic polyion (figure 2).

**Figure 2.** Formation of polyelectrolyte-ion-protein complex (ternary complex).

First, the polyelectrolyte interacts with the polyion and forms a soluble complex with charges oppose to those in the protein. Then, the protein interacts with the complex to form the insoluble complex.

In both cases, the formation and solubility of the complex depends on the pH and the ionic strength of the medium [1], the density of charges in the protein and the polyelectrolyte, the molecular weight and the concentration of the polyelectrolyte [2,3]. Various studies have been directed to understand the formation of these complexes in aqueous medium [4-6]. Equation 1 shows how the density of charges *(σ)* on the surface of the protein and the polyelectrolyte is affected by the pH and the ionic strength of the medium.

$$
\sigma = \frac{\partial \sigma}{\partial \mathbf{p} \mathbf{H}} (\mathbf{p} \mathbf{H} - \mathbf{p} \mathbf{I}) \tag{1}
$$

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 107

represented as the moles of polyelectrolyte per mol of protein, mass of polyelectrolyte per

The stoichiometry of a protein-polyelectrolyte complex might be over or below 1 as shown

A complex with a stoichiometry below 1 contains more protein molecules than polyelectrolyte molecules. Usually, this kind of complex is insoluble, while a complex with a stoichiometry over 1 might be soluble or insoluble. As can be seen in figure 3, a complex with a stoichiometry below 1 can be turned into one with stoichiometry over 1 by adding polyelectrolyte to the medium. Of course, the effect can be reverted by adding protein.

**Figure 3.** Stoichiometry (*e*) of a protein-polyelectrolyte complex.

immobilized enzymes in bioreactors or scarefolds.

applied it to any industrial process.

expected to yield a high purification factor.

*1.3.1. Bioseparation of proteins from a complex mixture* 

**1.3. Biotechnological applications of the protein-polyelectrolyte complex** 

In biotechnology, it is interesting to use insoluble protein-polyelectrolyte complexes with e < 1 since they can be used to purificate and concentrate industrial-interest enzymes [8], to

The development of Biotechnology has allowed the used of enzymes in the production of food, drugs and in many others industries. At the same time, Genetic Engineering and Molecular Biology has allowed the expression of proteins in bacteria and superior microorganisms; however, some proteins must still being isolated from its natural sources due to complex post-traductional modifications that occur during the synthesis of the proteins. In both cases, the protein of interest is in a media containing many other biomolecules and inorganic compounds that need to be separated from the protein before

Most purification protocols consist on many steps: the first ones have the aim to concentrate the protein of interest and to obtain a high recovery; while the last steps of the protocol are

mass unit of protein, etc.

in figure 3.

Mattison *et. al*. postulated an equation that correlates the density of charges in the protein *(σ)* and the polyelectrolyte *(ξ)* with the Debye-Hückel constant *(κ*) that is highly dependent on ionic strength (*a* is a constant that depends on the protein-polyelectrolyte system) [7].

$$
\xi \sigma \cong a \cdot \kappa \tag{2}
$$

The conditions of the medium determine whether the soluble or the insoluble complex is formed, or if the complex is dissociated.

#### **1.2. Stoichiometry of the protein-polyelectrolyte formation**

When studying the interaction of a protein and a polyelectrolyte, it is interesting to know the minimum quantity of protein requires forming the maximum quantity of complex per polyelectrolyte unit. This value is called stoichiometry of the complex *(e)* and it is usually represented as the moles of polyelectrolyte per mol of protein, mass of polyelectrolyte per mass unit of protein, etc.

The stoichiometry of a protein-polyelectrolyte complex might be over or below 1 as shown in figure 3.

A complex with a stoichiometry below 1 contains more protein molecules than polyelectrolyte molecules. Usually, this kind of complex is insoluble, while a complex with a stoichiometry over 1 might be soluble or insoluble. As can be seen in figure 3, a complex with a stoichiometry below 1 can be turned into one with stoichiometry over 1 by adding polyelectrolyte to the medium. Of course, the effect can be reverted by adding protein.

**Figure 3.** Stoichiometry (*e*) of a protein-polyelectrolyte complex.

Applications of Calorimetry in a Wide Context –

the insoluble complex.

formed, or if the complex is dissociated.

106 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 2.** Formation of polyelectrolyte-ion-protein complex (ternary complex).

polyelectrolyte is affected by the pH and the ionic strength of the medium.

**1.2. Stoichiometry of the protein-polyelectrolyte formation** 

Besides this model of formation of the insoluble complex, there is another model in which the formation of the insoluble complex requires the presence of an inorganic polyion (figure 2).

First, the polyelectrolyte interacts with the polyion and forms a soluble complex with charges oppose to those in the protein. Then, the protein interacts with the complex to form

In both cases, the formation and solubility of the complex depends on the pH and the ionic strength of the medium [1], the density of charges in the protein and the polyelectrolyte, the molecular weight and the concentration of the polyelectrolyte [2,3]. Various studies have been directed to understand the formation of these complexes in aqueous medium [4-6]. Equation 1 shows how the density of charges *(σ)* on the surface of the protein and the

> <sup>σ</sup> <sup>σ</sup> pH pI pH

> >

The conditions of the medium determine whether the soluble or the insoluble complex is

When studying the interaction of a protein and a polyelectrolyte, it is interesting to know the minimum quantity of protein requires forming the maximum quantity of complex per polyelectrolyte unit. This value is called stoichiometry of the complex *(e)* and it is usually

Mattison *et. al*. postulated an equation that correlates the density of charges in the protein *(σ)* and the polyelectrolyte *(ξ)* with the Debye-Hückel constant *(κ*) that is highly dependent on

ionic strength (*a* is a constant that depends on the protein-polyelectrolyte system) [7].

(1)

*a* (2)

### **1.3. Biotechnological applications of the protein-polyelectrolyte complex**

In biotechnology, it is interesting to use insoluble protein-polyelectrolyte complexes with e < 1 since they can be used to purificate and concentrate industrial-interest enzymes [8], to immobilized enzymes in bioreactors or scarefolds.

#### *1.3.1. Bioseparation of proteins from a complex mixture*

The development of Biotechnology has allowed the used of enzymes in the production of food, drugs and in many others industries. At the same time, Genetic Engineering and Molecular Biology has allowed the expression of proteins in bacteria and superior microorganisms; however, some proteins must still being isolated from its natural sources due to complex post-traductional modifications that occur during the synthesis of the proteins. In both cases, the protein of interest is in a media containing many other biomolecules and inorganic compounds that need to be separated from the protein before applied it to any industrial process.

Most purification protocols consist on many steps: the first ones have the aim to concentrate the protein of interest and to obtain a high recovery; while the last steps of the protocol are expected to yield a high purification factor.

Applications of Calorimetry in a Wide Context – 108 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Precipitation of enzyme-polyelectrolyte insoluble complexes is a very useful technique to apply at the beginning of purification protocols since it requires simple equipment and so is very easy to scale up; needs low concentrations of the polyelectrolyte since it interacts with high affinity with the proteins; and can be based on a wide variety of polyelectrolytes, both natural and synthetic, positively or negatively charged. An important aspect of this technique is that the enzyme usually retains its tertiary structure and its catalytic activity. Even more, usually it is more stable in the presence of the polyelectrolyte [9,10].

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 109

enzyme in an industrial process. Fluorescence, UV-visible and circular dichroism spectroscopy are very useful techniques to analyze the structure of the protein but also must

Although these techniques are helpful, they do not give an idea of the nature of the interaction between the protein and the polyelectrolyte. Calorimetric techniques such as differential scanning calorimetry and isothermal titration calorimetry allow studying the thermal stability of the enzyme in the presence of the polyelectrolyte and the nature of the

In order to study the formation of insoluble complexes between proteins and polyelectrolytes it is necessary to carry out different methodologies in a sequential way.

The formation of the insoluble polyelectrolyte-protein complexes can be followed by means of turbidimetric titration of the protein with the polyelectrolyte, or vice versa. Taking into account the isoelectric point of the protein and the pK value of the polyelectrolyte, the pH of

Figure 4. shows the turbidimetric titration curve obtained for two systems with different behavior: hyperbolic and sigmoid. Turbidity is usually measured as the absorbance (Abs) at

**Figure 4.** Determination of the polyelectrolyter/protein mass ratio when saturation is reached in a **A**-

These graphs demonstrate a saturation behavior with different mechanism of complex formation, and allow us to determine the *stoichiometric polyelectrolyte/protein ratio "e*", which

be performed experiments to study the enzymatic activity.

interaction between the enzyme and polyelectrolyte, respectively.

**2.1. Titration curves at different pH in binary systems** 

the medium should be selected so that they have opposite net charge.

**2. Research course and methodology** 

420 nm.

sigmoid and **B**- hyperbolic graph

### *1.3.2. Enzyme immobilization*

The immobilization of enzymes is a process by which the protein is attached to a solid matrix, synthesized using a polyelectrolyte, in order to enhance the stability of the structure of the protein and to reuse enzyme [11]. Enzymes immobilized, in comparison with enzymes in solution, are more robust and resistant to environmental changes.

Immobilization can be performed by physical or chemical methods. The first results in weak interactions between the enzyme and the solid support and includes adsorption on a waterinsoluble matrix and gel entrapment or micelles [12,13]. Chemical methods generate covalent bonds or electrostatic interactions between the enzyme and a water-insoluble support forming reticulated or single-chain particles. Insoluble complexes allow to immobilized enzymes by entrapment in polyelectrolyte solid particles, micelles or by covalent linkage to the support using carboimide as coupling.

The protein-matrix systems are widely used in bio-reactors for industrial process mainly because of the possibility of recycle the enzyme. Bio-reactors are very useful for the synthesis of organic compounds; since immobilized enzymes reduced the steps of the process, enhance the purity of the final products and allow stereo-selective synthesis. These systems also can be applied on the production of micro/nanocapsules for the delivery of proteins (or drugs). In this case, the use of polyelectrolytes sensitive to environmental conditions allows the releasing of the enzyme (or drug) molecules in different parts of the body [14].

### **1.4. Characterization of the protein-polyelectrolyte complex**

The formation of the protein-polyelectrolyte complex can be studied by spectroscopic and calorimetric techniques.

Spectroscopy assays based on turbidimetric measurements allow knowing the effect of pH, ionic strength, time and temperature on the amount of insoluble complex formed. Phase diagrams, turbidimetric titrations and kinetic assays must be performed in order to evaluate the best conditions to obtain the maximum quantity of insoluble protein-polyelectrolyte complex [15;16].

Study the stability of the enzyme when it is part of the complex is also important to understand how the polyelectrolyte affects its catalytic activity since it is expected to use the enzyme in an industrial process. Fluorescence, UV-visible and circular dichroism spectroscopy are very useful techniques to analyze the structure of the protein but also must be performed experiments to study the enzymatic activity.

Although these techniques are helpful, they do not give an idea of the nature of the interaction between the protein and the polyelectrolyte. Calorimetric techniques such as differential scanning calorimetry and isothermal titration calorimetry allow studying the thermal stability of the enzyme in the presence of the polyelectrolyte and the nature of the interaction between the enzyme and polyelectrolyte, respectively.

### **2. Research course and methodology**

Applications of Calorimetry in a Wide Context –

*1.3.2. Enzyme immobilization* 

body [14].

calorimetric techniques.

complex [15;16].

108 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Precipitation of enzyme-polyelectrolyte insoluble complexes is a very useful technique to apply at the beginning of purification protocols since it requires simple equipment and so is very easy to scale up; needs low concentrations of the polyelectrolyte since it interacts with high affinity with the proteins; and can be based on a wide variety of polyelectrolytes, both natural and synthetic, positively or negatively charged. An important aspect of this technique is that the enzyme usually retains its tertiary structure and its catalytic activity.

The immobilization of enzymes is a process by which the protein is attached to a solid matrix, synthesized using a polyelectrolyte, in order to enhance the stability of the structure of the protein and to reuse enzyme [11]. Enzymes immobilized, in comparison with

Immobilization can be performed by physical or chemical methods. The first results in weak interactions between the enzyme and the solid support and includes adsorption on a waterinsoluble matrix and gel entrapment or micelles [12,13]. Chemical methods generate covalent bonds or electrostatic interactions between the enzyme and a water-insoluble support forming reticulated or single-chain particles. Insoluble complexes allow to immobilized enzymes by entrapment in polyelectrolyte solid particles, micelles or by

The protein-matrix systems are widely used in bio-reactors for industrial process mainly because of the possibility of recycle the enzyme. Bio-reactors are very useful for the synthesis of organic compounds; since immobilized enzymes reduced the steps of the process, enhance the purity of the final products and allow stereo-selective synthesis. These systems also can be applied on the production of micro/nanocapsules for the delivery of proteins (or drugs). In this case, the use of polyelectrolytes sensitive to environmental conditions allows the releasing of the enzyme (or drug) molecules in different parts of the

The formation of the protein-polyelectrolyte complex can be studied by spectroscopic and

Spectroscopy assays based on turbidimetric measurements allow knowing the effect of pH, ionic strength, time and temperature on the amount of insoluble complex formed. Phase diagrams, turbidimetric titrations and kinetic assays must be performed in order to evaluate the best conditions to obtain the maximum quantity of insoluble protein-polyelectrolyte

Study the stability of the enzyme when it is part of the complex is also important to understand how the polyelectrolyte affects its catalytic activity since it is expected to use the

Even more, usually it is more stable in the presence of the polyelectrolyte [9,10].

enzymes in solution, are more robust and resistant to environmental changes.

covalent linkage to the support using carboimide as coupling.

**1.4. Characterization of the protein-polyelectrolyte complex** 

In order to study the formation of insoluble complexes between proteins and polyelectrolytes it is necessary to carry out different methodologies in a sequential way.

### **2.1. Titration curves at different pH in binary systems**

The formation of the insoluble polyelectrolyte-protein complexes can be followed by means of turbidimetric titration of the protein with the polyelectrolyte, or vice versa. Taking into account the isoelectric point of the protein and the pK value of the polyelectrolyte, the pH of the medium should be selected so that they have opposite net charge.

Figure 4. shows the turbidimetric titration curve obtained for two systems with different behavior: hyperbolic and sigmoid. Turbidity is usually measured as the absorbance (Abs) at 420 nm.

**Figure 4.** Determination of the polyelectrolyter/protein mass ratio when saturation is reached in a **A**sigmoid and **B**- hyperbolic graph

These graphs demonstrate a saturation behavior with different mechanism of complex formation, and allow us to determine the *stoichiometric polyelectrolyte/protein ratio "e*", which

Applications of Calorimetry in a Wide Context – 110 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

is defined as the minimal ratio in which the protein precipitates as an insoluble complex. The value *"e"* is calculated from the plot at the lowest concentration of polyelectrolyte necessary to get the saturation. This value is important because it allows us to determine the minimal amount of polymer needed to fully precipitate the protein, and can be expressed as the number of moles of protein bounded per mol of polyelectrolyte.

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 111

**Figure 5.** Phase diagram, turbidity vs. pH, for protein (—), polyelectrolyte (—) and binary system (—).

Figure 6 shows a schematic phase diagram between a cationic polyelectrolyte and an anion, in different polymer/anion ratios. Figure 6 A shows a pH range where the turbidity of the medium drastically increases. Each curve has a trapezoidal shape with a plateau, and the height of the trapezium depends on the polyelectrolyte concentration. The pHs that correspond to the edges of the trapezium are the critical pH values, at which the transition from complete dissolution to precipitation occurs. The lower critical pH is usually called acidic, and the higher one is called basic. It is remarkable that the transitions from complete solubility to precipitation occur at the same critical pHs independently of the polyelectrolyte

Also, phase diagrams can be represented as in figure 6.B. This diagram represents the behavior of the polyelectrolyte-anion complex by filled and open circles: filled circles are drawn at the pH of non-zero absorbance whereas the open circles at the zero absorbance

As mentioned above, insoluble polyelectrolyte-anion complexes behave as an ampholyte. This can be used to precipitate cationic or anionic proteins depending on the pH of work, as

The coulombic component in the interaction between proteins and polyelectrolytes is closely related with the presence of charges. So, the ionic strength of the medium can alter the forces involved in the interaction and eventually leads to dissociation of the complexes.

Whatever the system, this inhibition of the formation of the precipitates may be directly proportional to salt concentration. So, the effect of the presence of salt in the systems can be evaluated by turbidimetric titration in the presence of different concentrations of NaCl in

In ternary systems, high ionic strength can also inhibit polymer-anion interaction.

concentration.

values of the solution.

indicated in figure 6.B.

the medium.

**2.5. Effect of ionic strength** 

### **2.2. Titration curves at different pH in ternary systems**

In ternary systems, the polyelectrolyte forms an insoluble complex with an anion, which associates proteins with opposite net charge. The mixture polyelectrolyte-anion behaves as a pseudo polyampholyte with a characteristic isoelectric point.

The formation of insoluble complexes between the polymer and the anion can be examined by turbidimetric titration of the anion with the polyelectrolyte. When these curves reach the saturation it suggests a complete precipitation of the complex.

The precipitation of polyampholyte -protein complexes is driven by coulombic forces, which are highly dependent on protein and polyampholitic isoelectric pH values [5;17;18]. So, precipitation begins at a critical pH where the attractive forces have just overcome electrostatic repulsion.

### **2.3. Phase diagrams in binary systems**

Phase diagrams, also called solubility curves, show the range of pH in which the complexes are soluble or insoluble. It means that they provide information about the pH of higher interaction between the components and the optimum pH for precipitation and dissolution of the complexes.

To obtain these diagrams, a polyelectrolyte/protein mixture at a ratio close to *"e"* is titrated with acid or alkali and the turbidity of the medium is measured after pH variation.

Figure 5. shows an schematic phase diagram in a binary system.

### **2.4. Phase diagrams in ternary systems**

Classical polyampholytes have both anionic and cationic groups in their molecules. However, the aqueous solution of any polyelectrolyte may behave as a polyampholyte provided there is a small ion with multiple electrical charges (two or more) in the medium which interacts with the opposite charge of the polyelectrolyte to form a pseudo polyampholyte. Under these conditions, it is possible to find a pH interval where the pseudo complex behaves as an ampholyte.

To obtain the phase diagrams, a mixture with fixed polyelectrolyte/anion ratio is titrated with alkali or acid, and the turbidity of the medium is measured as the absorbance at 420 nm after pH variation.

**Figure 5.** Phase diagram, turbidity vs. pH, for protein (—), polyelectrolyte (—) and binary system (—).

Figure 6 shows a schematic phase diagram between a cationic polyelectrolyte and an anion, in different polymer/anion ratios. Figure 6 A shows a pH range where the turbidity of the medium drastically increases. Each curve has a trapezoidal shape with a plateau, and the height of the trapezium depends on the polyelectrolyte concentration. The pHs that correspond to the edges of the trapezium are the critical pH values, at which the transition from complete dissolution to precipitation occurs. The lower critical pH is usually called acidic, and the higher one is called basic. It is remarkable that the transitions from complete solubility to precipitation occur at the same critical pHs independently of the polyelectrolyte concentration.

Also, phase diagrams can be represented as in figure 6.B. This diagram represents the behavior of the polyelectrolyte-anion complex by filled and open circles: filled circles are drawn at the pH of non-zero absorbance whereas the open circles at the zero absorbance values of the solution.

As mentioned above, insoluble polyelectrolyte-anion complexes behave as an ampholyte. This can be used to precipitate cationic or anionic proteins depending on the pH of work, as indicated in figure 6.B.

### **2.5. Effect of ionic strength**

Applications of Calorimetry in a Wide Context –

electrostatic repulsion.

of the complexes.

**2.3. Phase diagrams in binary systems** 

**2.4. Phase diagrams in ternary systems** 

complex behaves as an ampholyte.

nm after pH variation.

110 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

the number of moles of protein bounded per mol of polyelectrolyte.

**2.2. Titration curves at different pH in ternary systems** 

pseudo polyampholyte with a characteristic isoelectric point.

saturation it suggests a complete precipitation of the complex.

is defined as the minimal ratio in which the protein precipitates as an insoluble complex. The value *"e"* is calculated from the plot at the lowest concentration of polyelectrolyte necessary to get the saturation. This value is important because it allows us to determine the minimal amount of polymer needed to fully precipitate the protein, and can be expressed as

In ternary systems, the polyelectrolyte forms an insoluble complex with an anion, which associates proteins with opposite net charge. The mixture polyelectrolyte-anion behaves as a

The formation of insoluble complexes between the polymer and the anion can be examined by turbidimetric titration of the anion with the polyelectrolyte. When these curves reach the

The precipitation of polyampholyte -protein complexes is driven by coulombic forces, which are highly dependent on protein and polyampholitic isoelectric pH values [5;17;18]. So, precipitation begins at a critical pH where the attractive forces have just overcome

Phase diagrams, also called solubility curves, show the range of pH in which the complexes are soluble or insoluble. It means that they provide information about the pH of higher interaction between the components and the optimum pH for precipitation and dissolution

To obtain these diagrams, a polyelectrolyte/protein mixture at a ratio close to *"e"* is titrated

Classical polyampholytes have both anionic and cationic groups in their molecules. However, the aqueous solution of any polyelectrolyte may behave as a polyampholyte provided there is a small ion with multiple electrical charges (two or more) in the medium which interacts with the opposite charge of the polyelectrolyte to form a pseudo polyampholyte. Under these conditions, it is possible to find a pH interval where the pseudo

To obtain the phase diagrams, a mixture with fixed polyelectrolyte/anion ratio is titrated with alkali or acid, and the turbidity of the medium is measured as the absorbance at 420

with acid or alkali and the turbidity of the medium is measured after pH variation.

Figure 5. shows an schematic phase diagram in a binary system.

The coulombic component in the interaction between proteins and polyelectrolytes is closely related with the presence of charges. So, the ionic strength of the medium can alter the forces involved in the interaction and eventually leads to dissociation of the complexes.

In ternary systems, high ionic strength can also inhibit polymer-anion interaction.

Whatever the system, this inhibition of the formation of the precipitates may be directly proportional to salt concentration. So, the effect of the presence of salt in the systems can be evaluated by turbidimetric titration in the presence of different concentrations of NaCl in the medium.

112 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 113

In the far-UV region (between 180 and 250 nm) the circular dichroism spectrum provides information one the secondary structure of proteins, due to asymmetrical packing of

The effect of polymers on the structure of proteins can be analyzed in terms of its secondary elements. So, far-UV circular dichroism spectra of proteins are recorded in different polymer/protein ratios, with a fixed concentration of protein and varying the amount of polymer. The pH of the medium must be the pH of higher interaction between the protein

In order to evaluate the effect of the polyelectrolyte on the enzymatic activity of the protein, enzyme assays are performed at constant protein concentration in the presence of different amounts of polymer. Polyelectrolyte/protein ratios are usually close to the stoichiometry of

The stability of the enzyme in the presence of the polyelectrolyte can also be monitored by incubating the mixture polyelectrolyte/enzyme and recording the enzymatic activity over time.

After analyzing the conditions of complex formation or dissolution and evaluating the effects of the different variables, we are able to design a methodology of precipitation of the

According to this precipitation scheme, an aliquot of the polyelectrolyte is mixed with a solution of the protein, both prepared at the pH of precipitation, to reach a proper polymer/protein ratio. This mixture is incubated the time necessary to form the maximum quantity of insoluble complex and centrifuged to obtain a solid precipitate. Then, the supernatant is separated and the precipitate redissolved in buffer at the pH of dissolution of the complex. Finally, in order to evaluate the effectiveness of the total process, enzymatic

This scheme is successfully applied in many systems [15-20] and allows to obtain a protein

Thermal desnaturation of proteins was monitored with a high sensitivity differential scanning calorimeter model VP-DSC from MicroCal Inc. Thermograms were obtained between 20-85°C, at scan rate 25-30ºC/h and at constant pressure of 28 psi. All result were averages of, at least, three independent measurements. Buffer versus buffer baseline scans were determined and subtracted from transition scans prior to normalization and analysis of

*2.7.2. Effect of the polyelectrolytes on the enzymatic activity of proteins* 

protein with the polyelectrolyte by following the steps shown in figure 7.:

**2.9. Calorimetric measurements for polymer-protein complex** 

the complex (*"e"*) or in excess of polymer respect this value.

**2.8. Precipitation and redissolution of the complexes** 

activity is measured in both fractions.

*2.9.1. Differential scanning calorimetry* 

with a high recovery and catalytically conserved.

intrinsically achiral (planar) peptide groups [22].

and the polyelectrolyte.

**Figure 6.** Phase diagram in polyelectrolyte-anion systems. Each color represents a different polyelectrolyte/anion ratio.

### **2.6. Complex formation kinetics**

The interaction between polyelectrolytes and proteins requires time to achieve the maximum quantity of complex (maximum turbidity). Thus, it is necessary a kinetic study by which the turbidity of a mixture polyelectrolyte-protein is measured over time. So, a solution of the polyelectrolyte is added to a solution of the protein, at the pH of precipitation and in an appropriate ratio, and absorbance at 420 nm is measured over time. Finally, a plot of turbidity vs. time is made and the time required to reach the maximum quantity of turbidity is obtained [19].

### **2.7. Conformational and enzymatic evaluation of the protein in the complex**

Several investigations have reported that polymers stabilize the catalytic activity in a variety of enzymes. Besides, it has been suggested that electrostatic interactions between the enzyme and polyelectrolytes play a primary role, also in conformational stabilization [20;21].

### *2.7.1. Effect of the polyelectrolytes on the far-UV circular dichroism (CD) of proteins*

Circular dichroism spectroscopy is a very frequently used technique to evaluate protein conformation in solution. This method is sufficiently simple and allows a rapid determination of protein structure or conformational changes.

In the far-UV region (between 180 and 250 nm) the circular dichroism spectrum provides information one the secondary structure of proteins, due to asymmetrical packing of intrinsically achiral (planar) peptide groups [22].

The effect of polymers on the structure of proteins can be analyzed in terms of its secondary elements. So, far-UV circular dichroism spectra of proteins are recorded in different polymer/protein ratios, with a fixed concentration of protein and varying the amount of polymer. The pH of the medium must be the pH of higher interaction between the protein and the polyelectrolyte.

### *2.7.2. Effect of the polyelectrolytes on the enzymatic activity of proteins*

In order to evaluate the effect of the polyelectrolyte on the enzymatic activity of the protein, enzyme assays are performed at constant protein concentration in the presence of different amounts of polymer. Polyelectrolyte/protein ratios are usually close to the stoichiometry of the complex (*"e"*) or in excess of polymer respect this value.

The stability of the enzyme in the presence of the polyelectrolyte can also be monitored by incubating the mixture polyelectrolyte/enzyme and recording the enzymatic activity over time.

### **2.8. Precipitation and redissolution of the complexes**

Applications of Calorimetry in a Wide Context –

polyelectrolyte/anion ratio.

turbidity is obtained [19].

[20;21].

**2.6. Complex formation kinetics** 

112 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 6.** Phase diagram in polyelectrolyte-anion systems. Each color represents a different

The interaction between polyelectrolytes and proteins requires time to achieve the maximum quantity of complex (maximum turbidity). Thus, it is necessary a kinetic study by which the turbidity of a mixture polyelectrolyte-protein is measured over time. So, a solution of the polyelectrolyte is added to a solution of the protein, at the pH of precipitation and in an appropriate ratio, and absorbance at 420 nm is measured over time. Finally, a plot of turbidity vs. time is made and the time required to reach the maximum quantity of

**2.7. Conformational and enzymatic evaluation of the protein in the complex** 

*2.7.1. Effect of the polyelectrolytes on the far-UV circular dichroism (CD) of proteins* 

determination of protein structure or conformational changes.

Several investigations have reported that polymers stabilize the catalytic activity in a variety of enzymes. Besides, it has been suggested that electrostatic interactions between the enzyme and polyelectrolytes play a primary role, also in conformational stabilization

Circular dichroism spectroscopy is a very frequently used technique to evaluate protein conformation in solution. This method is sufficiently simple and allows a rapid After analyzing the conditions of complex formation or dissolution and evaluating the effects of the different variables, we are able to design a methodology of precipitation of the protein with the polyelectrolyte by following the steps shown in figure 7.:

According to this precipitation scheme, an aliquot of the polyelectrolyte is mixed with a solution of the protein, both prepared at the pH of precipitation, to reach a proper polymer/protein ratio. This mixture is incubated the time necessary to form the maximum quantity of insoluble complex and centrifuged to obtain a solid precipitate. Then, the supernatant is separated and the precipitate redissolved in buffer at the pH of dissolution of the complex. Finally, in order to evaluate the effectiveness of the total process, enzymatic activity is measured in both fractions.

This scheme is successfully applied in many systems [15-20] and allows to obtain a protein with a high recovery and catalytically conserved.

#### **2.9. Calorimetric measurements for polymer-protein complex**

#### *2.9.1. Differential scanning calorimetry*

Thermal desnaturation of proteins was monitored with a high sensitivity differential scanning calorimeter model VP-DSC from MicroCal Inc. Thermograms were obtained between 20-85°C, at scan rate 25-30ºC/h and at constant pressure of 28 psi. All result were averages of, at least, three independent measurements. Buffer versus buffer baseline scans were determined and subtracted from transition scans prior to normalization and analysis of

114 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

protein denaturation. Finally, the values of the excess heat capacity were obtained after subtraction of the baseline. The calorimetric data were analysed by using the software ORIGIN 7.0, MicroCal Inc., following the methodology recommended by IUPAC. The parameters obtained from this analysis were: temperature at which maximum heat exchange occurs (*Tm*), the area under the peak, which represents the enthalpy of transition for reversible process (*ΔHcal*) and the van´t Hoff enthalpy (*ΔHVH*).

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 115

Where ΔHt is the total heat associated to each polymer addition, ΔHd is the heat of dilution of the polyelectrolyte in the buffer in the absence of the protein and ΔHdissol is the heat of polymer dissolution. The heat associated to the dilution of the protein in buffer was negligible. Then ΔHb was plotted vs polyelectrolyte/protein molar ratio and, by non-linear fitting of these calorimetric curve, the affinity constant (K) for the polyelectrolyte binding to the protein and the number of polymer molecules (n) bound per protein molecule was

The resulting data set was fitted using MicroCal ORIGIN 7.0 software supplied with the instrument and the intrinsic molar enthalpy change for the binding, ΔHb, the binding stoichiometry, n, and the intrinsic binding constant, K, were thus obtained. The equation for

calculated using the software provided by the instrument.

� �� + �

����

<sup>+</sup> �� ���

��� � ���� ���

where Vo is the active volume cell, Xt is the bulk concentration of ligand and Mt is the bulk

The intrinsic molar free energy change, ΔGº, and the intrinsic molar entropy change, ΔSº, for the binding reaction were calculated by the fundamental thermodynamic equations 5 and 6:

Figure 8 shows typical hyperbolic titration curves of a protein with a polyelectrolyte. In this case, trypsin (TRP) with poly vinyl sulfonate (PVS) [26]. As can be seen, two important characteristics were observed: at low polymer/protein ratios, absorbance increases with an increase in the polyelectrolyte total concentration and, at high polyelectrolyte/protein ratio,

The protein/polyelectrolyte molar ratio which corresponds to the situation where the protein has been precipitated as an insoluble complex was calculated from the intersection of a straight line which corresponds to the prolongation of the linear zone of the curve (at low

Trypsin is a serin-protease found in the digestive system. It is used for numerous biotechnological processes. Its isoelectric point is between 11.0 and 11.4 [27]. The pHs selected in the curves were chosen in the range where TRP and PVS have opposite charges.

<sup>−</sup> ��� + �

����

<sup>+</sup> �� ��� � � <sup>−</sup> ��� ���

��� � −� � �� � (5)

� (6)

� (4)

determining the heat associated to each injection is:

� � � �� ��� ��

concentration of the macromolecule in V0 [25].

**3.1. Turbidimetric titration curves** 

there is a plateau which depends on the medium pH.

polymer concentration) with a line which gives a plateau.

**3. Results** 

*H HHH b t d dissol* (3)

**Figure 7.** Scheme of precipitation of polyelectrolyte/protein complexes

The evaluation of *ΔHVH* gives an idea of the mechanism of the unfolding process [23]:


However, in some cases this calorimetric criterion may lead to erroneous conclusion.

### *2.9.2. Isothermal titration calorimetry*

Measurements of the examples presented were performed at 20-25 ºC by using a VP-ITC titration calorimeter (MicroCal Inc. USA). The sample cell was loaded with 1.436 mL of protein solution and the reference cell contained Milli-Q grade water. Titration was carried out using a 300 µL syringe filled with polyelectrolyte solutions. The experiments were performed by adding aliquots of 3-5µL of polyelectrolyte solutions 0.175 % (w/w) to the cell containing the protein solution.

The mathematical model equation selected to fit the ITC data was derived from a model that assumes the polyelectrolyte molecule binding to several protein molecules, all with the same intensity; in other words, the polyelectrolyte was considered as a macromolecule having **n** independent and equivalent sites, all of which have the same affinity constant, K, for the ligand (protein) [24].

The heat associated with the interaction polyelectrolyte-protein (ΔHb) was calculated by subtraction using the equation 3:

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 115

$$
\Delta H\_b = \Delta H\_t - \Delta H\_d - \Delta H\_{dissol} \tag{3}
$$

Where ΔHt is the total heat associated to each polymer addition, ΔHd is the heat of dilution of the polyelectrolyte in the buffer in the absence of the protein and ΔHdissol is the heat of polymer dissolution. The heat associated to the dilution of the protein in buffer was negligible. Then ΔHb was plotted vs polyelectrolyte/protein molar ratio and, by non-linear fitting of these calorimetric curve, the affinity constant (K) for the polyelectrolyte binding to the protein and the number of polymer molecules (n) bound per protein molecule was calculated using the software provided by the instrument.

The resulting data set was fitted using MicroCal ORIGIN 7.0 software supplied with the instrument and the intrinsic molar enthalpy change for the binding, ΔHb, the binding stoichiometry, n, and the intrinsic binding constant, K, were thus obtained. The equation for determining the heat associated to each injection is:

$$Q = \frac{n \, M\_t \, \Delta H\_b \, V\_o}{2} \left( 1 + \frac{1}{n k \, M\_t} + \frac{X\_t}{n \, M\_t} - \sqrt{\left( 1 + \frac{1}{n k \, M\_t} + \frac{X\_t}{n \, M\_t} \right)^2 - \frac{4X\_t}{n \, M\_t}} \right) \tag{4}$$

where Vo is the active volume cell, Xt is the bulk concentration of ligand and Mt is the bulk concentration of the macromolecule in V0 [25].

The intrinsic molar free energy change, ΔGº, and the intrinsic molar entropy change, ΔSº, for the binding reaction were calculated by the fundamental thermodynamic equations 5 and 6:

$$
\Delta G^\circ = -R \, T \ln K \tag{5}
$$

$$
\Delta \mathbf{S}^{\diamond} = \frac{\Delta H^{\diamond} - \Delta G^{\diamond}}{\tau} \tag{6}
$$

#### **3. Results**

Applications of Calorimetry in a Wide Context –

114 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

for reversible process (*ΔHcal*) and the van´t Hoff enthalpy (*ΔHVH*).

**Figure 7.** Scheme of precipitation of polyelectrolyte/protein complexes

degree of molecular association.

*2.9.2. Isothermal titration calorimetry* 

containing the protein solution.

subtraction using the equation 3:

ligand (protein) [24].

The evaluation of *ΔHVH* gives an idea of the mechanism of the unfolding process [23]:


Measurements of the examples presented were performed at 20-25 ºC by using a VP-ITC titration calorimeter (MicroCal Inc. USA). The sample cell was loaded with 1.436 mL of protein solution and the reference cell contained Milli-Q grade water. Titration was carried out using a 300 µL syringe filled with polyelectrolyte solutions. The experiments were performed by adding aliquots of 3-5µL of polyelectrolyte solutions 0.175 % (w/w) to the cell

The mathematical model equation selected to fit the ITC data was derived from a model that assumes the polyelectrolyte molecule binding to several protein molecules, all with the same intensity; in other words, the polyelectrolyte was considered as a macromolecule having **n** independent and equivalent sites, all of which have the same affinity constant, K, for the

The heat associated with the interaction polyelectrolyte-protein (ΔHb) was calculated by


However, in some cases this calorimetric criterion may lead to erroneous conclusion.


protein denaturation. Finally, the values of the excess heat capacity were obtained after subtraction of the baseline. The calorimetric data were analysed by using the software ORIGIN 7.0, MicroCal Inc., following the methodology recommended by IUPAC. The parameters obtained from this analysis were: temperature at which maximum heat exchange occurs (*Tm*), the area under the peak, which represents the enthalpy of transition

#### **3.1. Turbidimetric titration curves**

Figure 8 shows typical hyperbolic titration curves of a protein with a polyelectrolyte. In this case, trypsin (TRP) with poly vinyl sulfonate (PVS) [26]. As can be seen, two important characteristics were observed: at low polymer/protein ratios, absorbance increases with an increase in the polyelectrolyte total concentration and, at high polyelectrolyte/protein ratio, there is a plateau which depends on the medium pH.

The protein/polyelectrolyte molar ratio which corresponds to the situation where the protein has been precipitated as an insoluble complex was calculated from the intersection of a straight line which corresponds to the prolongation of the linear zone of the curve (at low polymer concentration) with a line which gives a plateau.

Trypsin is a serin-protease found in the digestive system. It is used for numerous biotechnological processes. Its isoelectric point is between 11.0 and 11.4 [27]. The pHs selected in the curves were chosen in the range where TRP and PVS have opposite charges.

116 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 117

n polymer/n protein ratio 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07

**LYZ- PVS Protein/polyelectrolyte molar ratio**

**Figure 9.** Turbidimetric titration curves of LYZ (0.3mg/mL) solution with PVS in a medium with 50 mM

pH 3.1 66 pH 5.5 47 pH 7.0 23

Figure 10 shows turbidimetric titration curves when phosphate (500mM) or citrate (50mM) was titrated by adding a concentrated solution of the polyelectrolyte poly ethylene imine (PEI). Both curves reached a plateau at high polyelectrolyte anion ratios, which suggests a complete precipitation of the complex. It could be seen that the plateau was obtained at a polymer/anion ratio 10 times higher for citrate than for phosphate, suggesting that citrate has a greater precipitation capacity than phosphate. These ternary systems have the capability to precipitate in the absence of protein. Only is required the presence in the medium of the

Figures 11 show the absorbance dependence (at 420 nm) vs. the pH change by the system LYS with poly acrylate (PAA). These complexes were soluble at basic pH values. At pH lower than 6.50 a significant increase in the turbidity was observed that corresponding to the insoluble complex formation. Similar behavior was reported for the serum albumin

The relevance of these phase diagrams are in the possibility to know the insolubility and

phosphate buffer. pH 5.5 (▲ ), 7.0 (●), and acetic acid/acetate buffer pH 3.1 (■ ). T= 20 ºC.

cationic polyelectrolyte (PEI) and a polyanion like phosphate (Pi) or citrate (Cit).

Absorbance a 420nm

0.0

**Table 2.** Lys/PVS molar ratios at different pHs.

**3.3. Phase diagrams of binary systems** 

titration with anionic polyelectrolyte [7].

solubility complex conditions.

**3.2. Turbidimetric titration of ternary complex:** 

0.2

0.4

0.6

0.8

**Figure 8.** Turbidimetric titration curves of TRP (70µM) solution with PVS (0.25 % w/w) in a medium with phosphate buffer 50mM, pH 3.0 (●), 5.5 (▲ ) and 7.0 (■ ). T=20 ºC, [21].

Table 1 shows the molar protein-polyelectrolyte ratio which corresponds to the stoichiometry of the complex formation calculated from the titration curves for the different experiments. These values are important because they allow us to calculate the minimal polymer amount necessary to precipitate the protein in a complete form. The data have been expressed as the number of TRP moles bound per polyelectrolyte mol. Despite the fact that these values were similar, turbidity is much higher at pH 3.00 which suggest a major size of the precipitate particle.


**Table 1.** TRP/PVS molar ratios at different pHs.

Figure 9 shows titration curves of lysozyme (LYZ) with the polyelectrolyte PVS. LYZ is a basic protein with 19 amino residues, an isoelectrical pH between 11.0 and 11.4 and a molecular mass of 14.3 kDa [28], therefore at the pHs where the turbidimetry titration were assayed the protein has a net positive electrical charge. Formation of LYZ-PVS complex was observed to be influenced by the medium pH, however, at pH 3.1, a minor absorbance maximum value was observed than at pH 5.5, which can be assigned to the loss of the native structure of this protein by influence of the acid medium [26].

Table 2 shows the molar protein-polymer ratios which correspond to the stoichiometry of the complex formation calculate from the titration curves for the different experiments. These values are important because allow to estimate the minimal polyelectrolyte amount needed to precipitate the protein, the data have been expressed as the number of LYZ molecules bound per polyelectrolyte molecule.

**Figure 9.** Turbidimetric titration curves of LYZ (0.3mg/mL) solution with PVS in a medium with 50 mM phosphate buffer. pH 5.5 (▲ ), 7.0 (●), and acetic acid/acetate buffer pH 3.1 (■ ). T= 20 ºC.


**Table 2.** Lys/PVS molar ratios at different pHs.

Applications of Calorimetry in a Wide Context –

Absorbance 420 nm

the precipitate particle.

0.0

**Table 1.** TRP/PVS molar ratios at different pHs.

molecules bound per polyelectrolyte molecule.

structure of this protein by influence of the acid medium [26].

0.5

1.0

1.5

2.0

2.5

116 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

with phosphate buffer 50mM, pH 3.0 (●), 5.5 (▲ ) and 7.0 (■ ). T=20 ºC, [21].

n polymer/n protein ratio 0.000 0.005 0.010 0.015 0.020 0.025

Table 1 shows the molar protein-polyelectrolyte ratio which corresponds to the stoichiometry of the complex formation calculated from the titration curves for the different experiments. These values are important because they allow us to calculate the minimal polymer amount necessary to precipitate the protein in a complete form. The data have been expressed as the number of TRP moles bound per polyelectrolyte mol. Despite the fact that these values were similar, turbidity is much higher at pH 3.00 which suggest a major size of

**pH Protein/polyelectrolyte molar ratio**

3.00 136 ± 3 5.50 228 ± 21 7.00 147 ± 12

Figure 9 shows titration curves of lysozyme (LYZ) with the polyelectrolyte PVS. LYZ is a basic protein with 19 amino residues, an isoelectrical pH between 11.0 and 11.4 and a molecular mass of 14.3 kDa [28], therefore at the pHs where the turbidimetry titration were assayed the protein has a net positive electrical charge. Formation of LYZ-PVS complex was observed to be influenced by the medium pH, however, at pH 3.1, a minor absorbance maximum value was observed than at pH 5.5, which can be assigned to the loss of the native

Table 2 shows the molar protein-polymer ratios which correspond to the stoichiometry of the complex formation calculate from the titration curves for the different experiments. These values are important because allow to estimate the minimal polyelectrolyte amount needed to precipitate the protein, the data have been expressed as the number of LYZ

**Figure 8.** Turbidimetric titration curves of TRP (70µM) solution with PVS (0.25 % w/w) in a medium

#### **3.2. Turbidimetric titration of ternary complex:**

Figure 10 shows turbidimetric titration curves when phosphate (500mM) or citrate (50mM) was titrated by adding a concentrated solution of the polyelectrolyte poly ethylene imine (PEI). Both curves reached a plateau at high polyelectrolyte anion ratios, which suggests a complete precipitation of the complex. It could be seen that the plateau was obtained at a polymer/anion ratio 10 times higher for citrate than for phosphate, suggesting that citrate has a greater precipitation capacity than phosphate. These ternary systems have the capability to precipitate in the absence of protein. Only is required the presence in the medium of the cationic polyelectrolyte (PEI) and a polyanion like phosphate (Pi) or citrate (Cit).

#### **3.3. Phase diagrams of binary systems**

Figures 11 show the absorbance dependence (at 420 nm) vs. the pH change by the system LYS with poly acrylate (PAA). These complexes were soluble at basic pH values. At pH lower than 6.50 a significant increase in the turbidity was observed that corresponding to the insoluble complex formation. Similar behavior was reported for the serum albumin titration with anionic polyelectrolyte [7].

The relevance of these phase diagrams are in the possibility to know the insolubility and solubility complex conditions.

118 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 119

In this figure it can be identify both critical pHs: 3.5 and 7. At pH=3.5 the net charge of the complex is positive whereas at pH= 7 is negative. On the other hand, transitions from complete solubility of the insoluble complex are independent of the polyelectrolyte

> pH 3456789

In general, protein/polyelectrolyte insoluble complexes are greatly affected by ionic strength because the molecular mechanism of the interaction is mainly electrostatic in nature. Turbidimetric titrations at pH 7.00 were performed in medium of different ionic strength such as shown Figure. 13. In this case, only 0.1 M of NaCl is enough to avoid formation the insoluble protein-polyelectrolyte complex [26]. This finding may be interesting in the design of an isolation method of protein, allowing in a first step the precipitation by the polyelectrolyte and then the precipitate may be dissolved by NaCl solution addition at low

Ternary systems like PEI-citrate was dramatically affected by 0.5 for higher ionic strength; in this case, no formation of the insoluble complex was found while the PEI-phosphate system showed to be slightly affected by the NaCl increased concentration. The inhibition of the precipitate formation in both systems was directly proportional to the salt concentration, in agreement with the presence of an important coulombic component in the insoluble

In general, the kinetics of complex formation is fast (around 2-10 minutes) [15;17;19]. Figure 14 shows the kinetic studies of different molar ratios of the systems TRP/Eudragit®L100 (EL100). It required less than 2 minutes of incubation to achieve the maximum quantity of complexes. In addition, by increasing the polyelectrolyte concentration increases the

concentration.

Absorbance 420nm

0.0

**3.5. Effect of ionic strength** 

concentration.

complex formation [19].

**3.6. Kinetics of the complex formation** 

**Figure 12.** Phase diagram of PEI/Pi systems at different molar ratios.

0.5

1.0

1.5

2.0

**Figure 10.** Turbidimetric titration of phosphate (▲ ) and citrate (●) with PEI. pH 5.5. T= 20º C [6].

**Figure 11.** Dependence of the absorbance at 420 nm vs the medium pH at a constant proteinpolyelectrolyte molar ratio of LYZ-PAA: (●) 0.0027, (■ ) 0.0065, (▲ ) 0.0010. T= 20ºC [25].

#### **3.4. Phase diagrams of ternary systems**

Figure 12 shows the pH variation effect on the insoluble complex formation obtained for ternary systems PEI/Pi at different PEI/Pi molar ratios [6]. As can be seen, in all curves there is an increase in the turbidity of the medium, reaching a maximum value and then decreasing in the pH interval 3.5-7. Each curve has a trapezoidal shape and the pH values corresponding to the edges of the trapezium are the critical pHs at which the transition from complete dissolution to precipitation occurs.

In this figure it can be identify both critical pHs: 3.5 and 7. At pH=3.5 the net charge of the complex is positive whereas at pH= 7 is negative. On the other hand, transitions from complete solubility of the insoluble complex are independent of the polyelectrolyte concentration.

**Figure 12.** Phase diagram of PEI/Pi systems at different molar ratios.

### **3.5. Effect of ionic strength**

Applications of Calorimetry in a Wide Context –

Absorbance 420nm

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Absorbance 420nm


**3.4. Phase diagrams of ternary systems** 

complete dissolution to precipitation occurs.

118 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

n PEI/n Pi ratio 0 1e-5 2e-5 3e-5 4e-5 5e-5

pH 2 3 4 5 6 7 8 9 10 11 12

Figure 12 shows the pH variation effect on the insoluble complex formation obtained for ternary systems PEI/Pi at different PEI/Pi molar ratios [6]. As can be seen, in all curves there is an increase in the turbidity of the medium, reaching a maximum value and then decreasing in the pH interval 3.5-7. Each curve has a trapezoidal shape and the pH values corresponding to the edges of the trapezium are the critical pHs at which the transition from

**Figure 11.** Dependence of the absorbance at 420 nm vs the medium pH at a constant proteinpolyelectrolyte molar ratio of LYZ-PAA: (●) 0.0027, (■ ) 0.0065, (▲ ) 0.0010. T= 20ºC [25].

**Figure 10.** Turbidimetric titration of phosphate (▲ ) and citrate (●) with PEI. pH 5.5. T= 20º C [6].

n PEI/n Cit ratio 0.0000 0.0002 0.0004 0.0006 0.0008 0.0010 0.0012

> In general, protein/polyelectrolyte insoluble complexes are greatly affected by ionic strength because the molecular mechanism of the interaction is mainly electrostatic in nature. Turbidimetric titrations at pH 7.00 were performed in medium of different ionic strength such as shown Figure. 13. In this case, only 0.1 M of NaCl is enough to avoid formation the insoluble protein-polyelectrolyte complex [26]. This finding may be interesting in the design of an isolation method of protein, allowing in a first step the precipitation by the polyelectrolyte and then the precipitate may be dissolved by NaCl solution addition at low concentration.

> Ternary systems like PEI-citrate was dramatically affected by 0.5 for higher ionic strength; in this case, no formation of the insoluble complex was found while the PEI-phosphate system showed to be slightly affected by the NaCl increased concentration. The inhibition of the precipitate formation in both systems was directly proportional to the salt concentration, in agreement with the presence of an important coulombic component in the insoluble complex formation [19].

### **3.6. Kinetics of the complex formation**

In general, the kinetics of complex formation is fast (around 2-10 minutes) [15;17;19]. Figure 14 shows the kinetic studies of different molar ratios of the systems TRP/Eudragit®L100 (EL100). It required less than 2 minutes of incubation to achieve the maximum quantity of complexes. In addition, by increasing the polyelectrolyte concentration increases the

120 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

turbidity of the system, however the time required achieving the maximum turbidity is independent of the concentration of the molar ratio**.** 

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 121

Lysozyme is a basic protein with 19 amino residues, an isoelectrical pH between 11.0 to 11.4 and a molecular mass of 14.3 kDa. Because LYZ is one of the four proteins whose thermal denaturation is thermodynamically reversible, the equations for systems in thermodynamic equilibrium can be applied to obtain the thermodynamic functions (entropy and enthalpy of

Thermograms of LYS enzyme with PAA and PVS are presented as examples in figure 15 and Table 3 shows the thermodynamics functions and Tm obtained in each case. In these systems DSC measurements demonstrated that the Tm of LYS was not modified by the polyelectrolytes presence only a decrease in the denaturalization heat (ΔHcal) was observed.

> Temperature (ºC) 60 65 70 75 80 85 90

> > **LYZ LYZ-PVS LYZ -PAA**

**Figure 15.** DSC Thermograms of the LYZ in the absence (—) and presence of: PVS (----) and PAA (….)

**ΔHcal (kcal/ mol)** 89.4 ± 0.3 72.0 ± 0.3 66.7 ± 0.4 **ΔHVH (kcal/ mol)** 139.0 ± 0.6 141 ± 0.8 151 ± 1.0 **ΔH VH / ΔH cal** 1.55 ± 0.05 1.96 ± 0.01 2.26 ± 0.03 **Tm (ºC)** 75.01 ± 0.01 75.33 ± 0.02 75.2 ± 0.1 **ΔS (e.u.)** 399 ± 3 405 ± 4 405 ± 5 **Table 3.** Thermodynamic functions obtained for the thermal LYZ unfolding determined by DSC in the

A Tm constant value is a proof that the protein retains its thermodynamic stability in the presence of both polyelectrolytes. However the polymer presence induced a decrease in the area under the curves, in agreement with a diminution of the heat associated to the denaturation process. The unfolding entropic change showed to be not affected by the polyelectrolyte presence, in accordance with the protein retaining its tertiary structure and

unfolding) directly from the thermograms, as described by Privalov [29].

Cp (Kcal/mol ºC)

absence and presence of the studied polyelectrolytes.

no important conformational protein change is occurring.

pH 7.00.

**Figure 13.** NaCl concentration effect on the turbidity of LYZ-PAA, pH 7.0, NaCl concentration: (O) 0M, (■ ) 0.1 M and (▲ ) 0.5M. T= 20ºC.

**Figure 14.** Formation of complex TRP-EL100 through time at three protein/polyelectrolyte molar ratio of TRP/EL100: (── ) 32.41, ( ─ ─ ) 16.18, (····) 8.08. [15].

### **4. Calorimetric techniques of protein-polyelectrolyte complex**

#### **4.1. Differential scanning calorimetry by polymer-protein complex**

DSC is a useful tool for studying the protein unfolding in which values of excess specific heat capacity (Cp) are obtained as a function of temperature. Two enzymes having different behavior towards charged flexible chain polyelectrolytes are analyzed below.

Lysozyme is a basic protein with 19 amino residues, an isoelectrical pH between 11.0 to 11.4 and a molecular mass of 14.3 kDa. Because LYZ is one of the four proteins whose thermal denaturation is thermodynamically reversible, the equations for systems in thermodynamic equilibrium can be applied to obtain the thermodynamic functions (entropy and enthalpy of unfolding) directly from the thermograms, as described by Privalov [29].

Applications of Calorimetry in a Wide Context –

Absorbance 420nm

(■ ) 0.1 M and (▲ ) 0.5M. T= 20ºC.

Abs 420 nm

0.0

of TRP/EL100: (── ) 32.41, ( ─ ─ ) 16.18, (····) 8.08. [15].

0.5

1.0

1.5

2.0

2.5

3.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

independent of the concentration of the molar ratio**.** 

120 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

turbidity of the system, however the time required achieving the maximum turbidity is

n polymer /n protein ratio 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 0.016

time (sec) 0 50 100 150 200 250 300 350

**Figure 14.** Formation of complex TRP-EL100 through time at three protein/polyelectrolyte molar ratio

DSC is a useful tool for studying the protein unfolding in which values of excess specific heat capacity (Cp) are obtained as a function of temperature. Two enzymes having different

**4. Calorimetric techniques of protein-polyelectrolyte complex** 

**4.1. Differential scanning calorimetry by polymer-protein complex** 

behavior towards charged flexible chain polyelectrolytes are analyzed below.

**Figure 13.** NaCl concentration effect on the turbidity of LYZ-PAA, pH 7.0, NaCl concentration: (O) 0M,

Thermograms of LYS enzyme with PAA and PVS are presented as examples in figure 15 and Table 3 shows the thermodynamics functions and Tm obtained in each case. In these systems DSC measurements demonstrated that the Tm of LYS was not modified by the polyelectrolytes presence only a decrease in the denaturalization heat (ΔHcal) was observed.

**Figure 15.** DSC Thermograms of the LYZ in the absence (—) and presence of: PVS (----) and PAA (….) pH 7.00.


**Table 3.** Thermodynamic functions obtained for the thermal LYZ unfolding determined by DSC in the absence and presence of the studied polyelectrolytes.

A Tm constant value is a proof that the protein retains its thermodynamic stability in the presence of both polyelectrolytes. However the polymer presence induced a decrease in the area under the curves, in agreement with a diminution of the heat associated to the denaturation process. The unfolding entropic change showed to be not affected by the polyelectrolyte presence, in accordance with the protein retaining its tertiary structure and no important conformational protein change is occurring.

LYZ is a protein which has only one domain with low molecular mass, its thermal unfolding have been describe as reversible, however the capacity of LYZ to associate in aqueous solution it is well known. ΔHVH/ΔHcal ratio greater than 1 is an indication of the intermolecular cooperation presence during the thermal unfolding. The increase of this ratio in the polyelectrolytes presence, suggests more cooperative intermolecular process.

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 123

The comparison of the two figures and table evidences two main differences

and in the presence of polymer (two-state model)

turbidimetric titration because is a good estimation of **n**.

**Figure 17.** ITC measurements of LYZ with PVS [26].

\*The enthalpic change is expressed per mol of protein bound.

experiments.

**4.2. Isothermal titration calorimetry** 

denaturation.



ITC technique gives the direct heat associated to the complex formation (**ΔH**), a number of protein molecules bounded to polyelectrolyte molecule (**n**), the affinity constant (**K**). Before performed ITC experiment is important to known which is the number "*e*" obtained by

Figure 17 shows the ITC measurements of the LYS titration with PVS and Table 5 summarizes the parameters obtained by two anionic polyelectrolytes (PVS and PAA).

**System LYZ-PVS LYZ -PAA** 

**K (M-1)** 2.7 103 5.1 104 **ΔHº (kcal/mol)** - 15.2 - 10.0 **ΔSº (e.u.)** -1103 -1033

**n (protein /polyelectrolyte)** 21.2 ± 0.2 294 ± 8

**Table 5.** Thermodynamic and binding parameters of the interaction LYZ-polyelectrolyte from ITC

The interaction LYZ-PVS and LYZ-PAA is exothermic. The mechanism of bond is carried out between the electrically charged groups of both. The differences found between

Furthermore, the unfolding entropy was not affected in the protein-polymer complexes (LYZ-PVS and LYS-PAA). It indicates that LYZ in complex follows in the same conformational state that LYZ alone.

Trypsin is a serin-protease found in the digestive system. It is used for numerous biotechnological processes. It is a globular protein which has two domains with similar structures [27]. DSC experimental results for enzyme trypsin are demonstrated a two-state transition model at pH 3.00 [30]. Figure 16.A shows DSC thermograms of TRP. Although the ratio ΔHVH/ ΔHcal is close to 1, however the thermogram clearly shows 3 transitions.

TRP-EL100 complex has a very interesting behavior. As can be seen in Figure 16.B protein thermogram was significantly modified by the polyelectrolyte presence.

**Figure 16.** (A) DSC Thermogram of the TRP: (—) experimental data; (---) fit data; (··─ ) first transition; (- - -) second transition; (─ ─ ) third transition. (B) DSC Thermogram of the TRP in the presence of EL100: (—) experimental data; (---) fit data.


**Table 4.** Thermodynamics functions obtained for the thermal TRP unfolding determined by DSC in the absence and presence of the EL100.

The comparison of the two figures and table evidences two main differences


### **4.2. Isothermal titration calorimetry**

Applications of Calorimetry in a Wide Context –

conformational state that LYZ alone.

EL100: (—) experimental data; (---) fit data.

**TRP (transitions)** 316.1 ± 0.1

absence and presence of the EL100.

122 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

LYZ is a protein which has only one domain with low molecular mass, its thermal unfolding have been describe as reversible, however the capacity of LYZ to associate in aqueous solution it is well known. ΔHVH/ΔHcal ratio greater than 1 is an indication of the intermolecular cooperation presence during the thermal unfolding. The increase of this ratio

Furthermore, the unfolding entropy was not affected in the protein-polymer complexes (LYZ-PVS and LYS-PAA). It indicates that LYZ in complex follows in the same

Trypsin is a serin-protease found in the digestive system. It is used for numerous biotechnological processes. It is a globular protein which has two domains with similar structures [27]. DSC experimental results for enzyme trypsin are demonstrated a two-state transition model at pH 3.00 [30]. Figure 16.A shows DSC thermograms of TRP. Although the

TRP-EL100 complex has a very interesting behavior. As can be seen in Figure 16.B protein

**Figure 16.** (A) DSC Thermogram of the TRP: (—) experimental data; (---) fit data; (··─ ) first transition; (- - -) second transition; (─ ─ ) third transition. (B) DSC Thermogram of the TRP in the presence of

> **ΔHcal (kcal/mol)**

13.9 ± 0.1 22.2 ± 0.2 1.8 ± 0.5

**TRP** 320.6 ± 0.1 38.7 ± 0.6 42.2 ± 0.8 1.09

**TRP-EL100** 327.8 ± 0.1 82.0 ± 0.1 81.6 ± 0.1 0.99 **Table 4.** Thermodynamics functions obtained for the thermal TRP unfolding determined by DSC in the

**ΔHVH**

8.3 ± 3 53.1 ± 3

**(kcal/mol) ΔHVH/ ΔHcal**


in the polyelectrolytes presence, suggests more cooperative intermolecular process.

ratio ΔHVH/ ΔHcal is close to 1, however the thermogram clearly shows 3 transitions.

thermogram was significantly modified by the polyelectrolyte presence.

**Tm (K)** 

324.4 ± 0.3 336.4 ± 0.3 ITC technique gives the direct heat associated to the complex formation (**ΔH**), a number of protein molecules bounded to polyelectrolyte molecule (**n**), the affinity constant (**K**). Before performed ITC experiment is important to known which is the number "*e*" obtained by turbidimetric titration because is a good estimation of **n**.

Figure 17 shows the ITC measurements of the LYS titration with PVS and Table 5 summarizes the parameters obtained by two anionic polyelectrolytes (PVS and PAA).

**Figure 17.** ITC measurements of LYZ with PVS [26].


\*The enthalpic change is expressed per mol of protein bound.

**Table 5.** Thermodynamic and binding parameters of the interaction LYZ-polyelectrolyte from ITC experiments.

The interaction LYZ-PVS and LYZ-PAA is exothermic. The mechanism of bond is carried out between the electrically charged groups of both. The differences found between complexes were the affinity (K) and the number of molecules of protein bonded to polymer molecule. Because the size of the polyelectrolytes are 10-fold larger than the protein, the number of protein molecules bound per polymer molecule is high.

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 125

A value of 15 mol of protein per mol of polyelectrolyte was found for the complex EL100- TRP formation. The high value of the affinity constant demonstrated that both molecules interact strongly with each other. The ΔH was normalized per mol of protein; therefore, heat value of 62.14 Kcal/mol of protein is yielded. The positive value of ΔH indicates that the interaction between EL100 and TRP requires consuming of heat form de medium. The ΔS° value obtained was positive as a result of the increase of the disorder of the system due to

EL100 is a charged polymer which also contains a hydrophobic framework in its linear chain. For such a complicated system it is not clear to what extent non-electrostatic forces contribute to the observed complexation behavior. Besides, the value of ΔS° was positive

ITC experiment performed in presence of NaCl confirmed the results obtained by turbidimetry (data not shown). The values of heat measured during the experiment of titration are similar that obtained when studying the dilution of the polyelectrolyte. This result is indicating that the TRP and the EL100 are not interacting when NaCl 1.00 M is

Thermodynamic parameters were according to hydrophobic interactions between TRP and EL100. However, ITC and turbidimetric titrations experiments were altered in salt presence. It would demonstrate that the mechanism of interaction between these two molecules

Experimental conditions of charged polyelectrolyte-protein complex formation may be determined by turbidimetric measurements, but are necessary to complement it for

DSC measurements show that the Tm and denaturalization heat of some proteins may increase or not change in the polymer presence and the complex unfolded according to a

In general, ΔH° and ΔS° of complex formation obtained by ITC have negative when protein and polyelectrolyte are oppositely charged (electrostatic interaction). Nevertheless, the thermodynamic functions can be positive as a result of the interaction between hydrophobic backbone of polymers and aromatic amino acids. Moreover, if ionic strength modifies this insoluble complex formation, a mechanism of interaction may involve both hydrophobic

The calorimetric techniques (ITC and DSC), turbidimetry and enzymatic activity studies provide useful quantitative information about the interaction of proteins and charged polyelectrolytes in aqueous solution. The knowledge of the nature of this interaction is essential for the application of the complex formation in protocols as proteins isolation

release of structured water molecules.

added to the buffer.

**5. Conclusions** 

two-state model.

calorimetric techniques.

and electrostatic interactions.

indicating that the disorder of the system increased.

involves both hydrophobic and electrostatic interactions.

strategy, immobilization or in purification of a target protein.

The heat associated to the complex formation were extremely high, but when they are normalized per protein molecule bound to the polyelectrolyte the heat associate yielded 10- 15 kcal/mol which is a normal heat amount for a coulombic interaction between two charge groups in solution. These low interaction heats are in agreement with the low NaCl concentration needed to induces the dissolution of the insoluble complex (around 0.1 M) Other important parameters to know are the thermodynamically stability of the protein in the polyelectrolyte presence. It is desirable that the protein retains its tertiary structure.

TRP- EL100 complex is an interesting example. Although the polymer and protein present opposite electrical charge, however the interaction is endothermic.

Figure 18 shows the binding isotherm obtained when consecutive aliquots of EL100 were added to a solution of trypsin [15]. The parameters calculated are summarized in Table 6.

**Figure 18.** ITC measurements of TRP with EL100.


**Table 6.** Binding parameters of the TRP- EL100 interaction from ITC experiments.T= 25°C.

A value of 15 mol of protein per mol of polyelectrolyte was found for the complex EL100- TRP formation. The high value of the affinity constant demonstrated that both molecules interact strongly with each other. The ΔH was normalized per mol of protein; therefore, heat value of 62.14 Kcal/mol of protein is yielded. The positive value of ΔH indicates that the interaction between EL100 and TRP requires consuming of heat form de medium. The ΔS° value obtained was positive as a result of the increase of the disorder of the system due to release of structured water molecules.

EL100 is a charged polymer which also contains a hydrophobic framework in its linear chain. For such a complicated system it is not clear to what extent non-electrostatic forces contribute to the observed complexation behavior. Besides, the value of ΔS° was positive indicating that the disorder of the system increased.

ITC experiment performed in presence of NaCl confirmed the results obtained by turbidimetry (data not shown). The values of heat measured during the experiment of titration are similar that obtained when studying the dilution of the polyelectrolyte. This result is indicating that the TRP and the EL100 are not interacting when NaCl 1.00 M is added to the buffer.

Thermodynamic parameters were according to hydrophobic interactions between TRP and EL100. However, ITC and turbidimetric titrations experiments were altered in salt presence. It would demonstrate that the mechanism of interaction between these two molecules involves both hydrophobic and electrostatic interactions.

### **5. Conclusions**

Applications of Calorimetry in a Wide Context –

cal/mol of inyectant

0

10000

**Figure 18.** ITC measurements of TRP with EL100.

20000

30000

40000

50000

60000

124 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

number of protein molecules bound per polymer molecule is high.

opposite electrical charge, however the interaction is endothermic.

complexes were the affinity (K) and the number of molecules of protein bonded to polymer molecule. Because the size of the polyelectrolytes are 10-fold larger than the protein, the

The heat associated to the complex formation were extremely high, but when they are normalized per protein molecule bound to the polyelectrolyte the heat associate yielded 10- 15 kcal/mol which is a normal heat amount for a coulombic interaction between two charge groups in solution. These low interaction heats are in agreement with the low NaCl concentration needed to induces the dissolution of the insoluble complex (around 0.1 M) Other important parameters to know are the thermodynamically stability of the protein in the polyelectrolyte presence. It is desirable that the protein retains its tertiary structure.

TRP- EL100 complex is an interesting example. Although the polymer and protein present

Figure 18 shows the binding isotherm obtained when consecutive aliquots of EL100 were added to a solution of trypsin [15]. The parameters calculated are summarized in Table 6.

> mol EL100/mol TRP 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09

**Binding parameter Value** *n ( molar ratio) [mol TRP/mol EL-100]* 15.22 ± 0.05 *K (affinity constant) [M-1]* 9.8 106 ± 7. 105 *ΔH° (kcal/mol)* 62.1 ± 0.3 *ΔS°(e.u.)* 240 ± 10 *ΔG° (kcal/mol)* - 9.59 ± 0.05

**Table 6.** Binding parameters of the TRP- EL100 interaction from ITC experiments.T= 25°C.

Experimental conditions of charged polyelectrolyte-protein complex formation may be determined by turbidimetric measurements, but are necessary to complement it for calorimetric techniques.

DSC measurements show that the Tm and denaturalization heat of some proteins may increase or not change in the polymer presence and the complex unfolded according to a two-state model.

In general, ΔH° and ΔS° of complex formation obtained by ITC have negative when protein and polyelectrolyte are oppositely charged (electrostatic interaction). Nevertheless, the thermodynamic functions can be positive as a result of the interaction between hydrophobic backbone of polymers and aromatic amino acids. Moreover, if ionic strength modifies this insoluble complex formation, a mechanism of interaction may involve both hydrophobic and electrostatic interactions.

The calorimetric techniques (ITC and DSC), turbidimetry and enzymatic activity studies provide useful quantitative information about the interaction of proteins and charged polyelectrolytes in aqueous solution. The knowledge of the nature of this interaction is essential for the application of the complex formation in protocols as proteins isolation strategy, immobilization or in purification of a target protein.

Applications of Calorimetry in a Wide Context – 126 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

### **Author details**

Diana Romanini, Mauricio Javier Braia and María Cecilia Porfiri *Laboratory of Physical Chemistry Applied to Bioseparation. College of Biochemical and Pharmaceutical Sciences, National University of Rosario (UNR), Rosario, Argentina* 

### **Acknowledgement**

We thank Prof Watson Loh, Institute of Chemistry, State University of Campinas (UNICAMP), Campinas, SP, BRAZIL for performing DSC and ITC measurements. We also thank Prof. G. Picó, Prof. B. Nerli and Prof. B. Farruggia for useful discussions.

Applications of Calorimetric Techniques in the Formation of Protein-Polyelectrolytes Complexes 127

[14] Esposito E., Cervellati F., Menegatti E., Nastruzzi C., Cortesi R., (2002) Spray dried Eudragit microparticles as encapsulation devices for vitamin C, Int J Pharm 242: 329–

[15] Braia, M Tubio, G Nerli, B Loh W, Romanini, D., (2012) Analysis of the interactions between eudragit® l100 and porcine pancreatic trypsin by calorimetric techniques. Int J

[16] Porfiri M. C., Picó G., Farruggia B., Romanini D., (2010) Insoluble complex formation between alpha-amylase from Aspergillus oryzae and polyacrylic acid of different

[17] Tsuboi A., Izumi T., Hirata M., J. Xia, P. Dublin E. Kokufuta, (1999) Complexation of Proteins with a Strong Polyanion in an Aqueous Salt-free System Langmuir 12: 6295-

[18] Fornasiero F., Ulrich J., Prausnitz J.,(1999) Molecular thermodynamics of precipitation.

[19] Patrickios, C, Sharma, L, Armes, S, Billingham, N. (1999) Precipitation of a Water-Soluble ABC Triblock Methacrylic Polyampholyte: Effects of Time, pH, Polymer Concentration, Salt Type and Concentration, and Presence of a Protein. Langmuir 15:

[20] Foreman T, Khalil M, Meier P, Brainard J, Vanderberg L, Sauer N (2001). Effects of charged water-soluble polymers on the stability and activity of yeast alcohol

[21] Braia, M. , Porfiri, M.C., Farruggia, B., Picó G., Romanini, D. (2008) Complex formation between protein and poly vinyl sulfonate as a strategy of proteins isolation. Journal of

[22] Fasman G. D. (1996) Circular dichroism and the conformational analysis of

[23] Sturtevant J, (2001) Biochemical applications of differential scanning calorimetry. Annu.

[24] Jha N, Kishore N., (2009) Binding of streptomycin with bovine serum albumin:

[25] Kim W., Yamasaki Y., Kataoka K., (2006) Development of a Fitting Model Suitable for the Isothermal Titration Calorimetric Curve of DNA with Cationic Ligands. J. Phys.

[26] Romanini D, Braia M, Giatte Angarten R, Loh W, Picó G, (2007) Interaction of lysozyme

[27] Beynon R, Bond J.S., Proteolytic Enzymes, Practical Approach, Oxford University

[28] Aschaffenburg R., Blake C., Dickie H., Gayen, S., Keegan R., Sen A. (1980). The crystal structure of tortoise egg-white lysozyme at 6 Å resolution .Biochim Biophys Acta 625:

dehydrogenase and subtilisin carlsberg. Biotechnol Bioeng 76: 241–246.

Energetics and conformational aspects.Thermochim. Acta 482: 21-29.

with negatively charged flexible chain polymers. J Chrom B, 857: 25-31.

334.

6303.

1613-1620.

Biol Macromol 50: 180-186.

Chem. Eng. Process 38: 463-475.

Chromatography B, 873: 139-143.

biomolecules. Plenum press 738p.

Rev. Phys. Chem. 38 463-488.

Chem. B 110: 10919-10925.

Press, 2001.

64-71.

molecular weight. Proc. Biochem. 45: 1753-1756.

### **6. References**


[14] Esposito E., Cervellati F., Menegatti E., Nastruzzi C., Cortesi R., (2002) Spray dried Eudragit microparticles as encapsulation devices for vitamin C, Int J Pharm 242: 329– 334.

Applications of Calorimetry in a Wide Context –

**Author details** 

**Acknowledgement** 

**6. References** 

126 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*Laboratory of Physical Chemistry Applied to Bioseparation. College of Biochemical and Pharmaceutical Sciences, National University of Rosario (UNR), Rosario, Argentina* 

thank Prof. G. Picó, Prof. B. Nerli and Prof. B. Farruggia for useful discussions.

Selectivity and Efficiency, Biotechnology Progress, 12: 356-362.

proteins on carboxymethyl cellulose, Poocess Biochemistry 35: 777-785.

of Whey Proteins and Gum Arabic, Biomacromolecules, 4: 293-303.

polyethylenimine. Biotechnol. Lett., 22: 927.

of Physical Chemistry B, 102: 3830-3836.

Ltda., cap. 2. (2005).

Ars Pharmaceutica, 39: 23-39.

79–90.

Tesis, 206 p.

isolate pepsin. Journal of Chromatography B. 860: 63-68.

complexes Opinion in Colloid & Interface Science 10: 52–78.

immobilizations: a review Enzyme Microb Tech 35: 126–139.

We thank Prof Watson Loh, Institute of Chemistry, State University of Campinas (UNICAMP), Campinas, SP, BRAZIL for performing DSC and ITC measurements. We also

[1] Kumara, A Srivastavaa A, Yu Galaevb I, Mattiasson B, (2007) Smart polymers: Physical forms and bioengineering applications. Progress in Polymer Science 32: 1205-1237. [2] Wang, Y.; Gao, Y.; Dubin, P., (1999) Protein Separation via Polyelectrolyte Coacervation:

[3] Arvind, L.; Aruna, N.; Roshnnie, J.; Devika, T. (2000) Reversible precipitation of

[4] Weinbreck, F.; De Vries, R.; Schrooyen, P.; De Kruif, C.G. (2003) Complex Coacervation

[5] Gupta V., Nath S., Chand S., (2002) Estimation of proteins in the presence of

[6] Manzur A, Spelzini D, Farruggia B, Romanini D, Picó G (2007) Polyethyleneimine phosphate and citrate systems act like pseudo polyampholytes as a starting method to

[7] Mattison, K.W.; Dubin, P.L.; Brittain, I.J., (1998) Complex Formation between Bovine Serum Albumin and Strong Polielectrolytes: Effect of Polymer Charge Density, Journal

[8] Cooper C, Dubin P , Kayitmazer A, Turksen S,Current, (2005) Polyelectrolyte–protein

[9] Pessoa Jr., A.; Vahan Kilikian, B.;Purificação de Produtos Biotecnológicos, Ed. Manole

[10] Hilbrig F, Freitag R, (2003) Protein purification by affinity precipitation, J Chrom B 790:

[11] Arroyo M., (1998) Inmobilized enzymes: Theory, methods of study and applications.

[12] Krajewska B., (2004) Application of chitin- and chitosan-based materials for enzyme

[13] Saskia Lindhoud. (2009) Polyelectrolyte Complex Micelles as Wrapping for enzymes –

Diana Romanini, Mauricio Javier Braia and María Cecilia Porfiri


	- [29] Privalov P.L..(1979) Stability of Proteins Small Globular Proteins. Adv. Protein Chem. 33: 167-241.

**Chapter 6** 

© 2013 McKnight, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Insights into the Relative DNA Binding** 

**Affinity and Preferred Binding Mode** 

**Isothermal Titration Calorimetry (ITC)** 

Many biologically significant compounds have been known, for several decades now, to bind non-covalently to nucleic acids.[1-7] Ever since the discovery of the structure of DNA in the 1950s, DNA has been a target for many therapeutic compounds. Several of these compounds have been found to bind to DNA while interfering with the activity of many vital enzymes and protein factors involved in DNA metabolism. Others cleave DNA or cause DNA cross-linking (for example, cisplatin) interfering with cell division and leading to apoptosis. As a result, several DNA-binding compounds have been identified as therapeutic agents in especially the anti-cancer and anti-pathogenic classes. Some of the most notable members of these classes include the Streptomyces derived anthracyclins e.g., daunomycin (daunorubicin) and doxorubicin, have been used for decades, initially as antibiotics, then mainly as antitumor agents.[8] Other known DNA binding agent include mitoxantrone, which has been particularly useful in the treatment of breast cancers, the glycopeptide antibiotic bleomycin which has been used in the treatment of Hodgkin's lymphoma and testicular cancer, amsacrine, bisantrene and various porphyrin derivatives. Even though many of these compounds have exhibited therapeutic potency, there still exist the accompanying unwanted side-effects, due mainly to the lack of selectivity and DNA targeting. Now, even after decades of studies of drug-DNA interactions, the existence of deleterious side-effects remains a huge area of concern and presents the main barrier for progress within the field. So, the question of whether a certain molecule will bind to a specific DNA sequence is currently being probed by several research groups. If we are to

**of Homologous Compounds Using** 

Additional information is available at the end of the chapter

Ruel E. McKnight

**1. Introduction** 

http://dx.doi.org/10.5772/54061

**1.1. Drug-DNA interactions** 

[30] Santos A. Santana M., Gomidea, F. Miranda A, Oliveira, J., Vilas Boas F., Vasconcelos, A., Bemquerer M. ,Santoro M., (2008) Physical-chemical characterization and stability study of α-trypsin at pH 3.0 by by differential scanning calorimetry Int. J. Biol.Macromol. 42: 278–284.

### **Chapter 6**

## **Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC)**

Ruel E. McKnight

Applications of Calorimetry in a Wide Context –

Biol.Macromol. 42: 278–284.

33: 167-241.

128 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[29] Privalov P.L..(1979) Stability of Proteins Small Globular Proteins. Adv. Protein Chem.

[30] Santos A. Santana M., Gomidea, F. Miranda A, Oliveira, J., Vilas Boas F., Vasconcelos, A., Bemquerer M. ,Santoro M., (2008) Physical-chemical characterization and stability study of α-trypsin at pH 3.0 by by differential scanning calorimetry Int. J.

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54061

### **1. Introduction**

### **1.1. Drug-DNA interactions**

Many biologically significant compounds have been known, for several decades now, to bind non-covalently to nucleic acids.[1-7] Ever since the discovery of the structure of DNA in the 1950s, DNA has been a target for many therapeutic compounds. Several of these compounds have been found to bind to DNA while interfering with the activity of many vital enzymes and protein factors involved in DNA metabolism. Others cleave DNA or cause DNA cross-linking (for example, cisplatin) interfering with cell division and leading to apoptosis. As a result, several DNA-binding compounds have been identified as therapeutic agents in especially the anti-cancer and anti-pathogenic classes. Some of the most notable members of these classes include the Streptomyces derived anthracyclins e.g., daunomycin (daunorubicin) and doxorubicin, have been used for decades, initially as antibiotics, then mainly as antitumor agents.[8] Other known DNA binding agent include mitoxantrone, which has been particularly useful in the treatment of breast cancers, the glycopeptide antibiotic bleomycin which has been used in the treatment of Hodgkin's lymphoma and testicular cancer, amsacrine, bisantrene and various porphyrin derivatives. Even though many of these compounds have exhibited therapeutic potency, there still exist the accompanying unwanted side-effects, due mainly to the lack of selectivity and DNA targeting. Now, even after decades of studies of drug-DNA interactions, the existence of deleterious side-effects remains a huge area of concern and presents the main barrier for progress within the field. So, the question of whether a certain molecule will bind to a specific DNA sequence is currently being probed by several research groups. If we are to

© 2013 McKnight, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### 130 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

approach the problem from a fundamental level, such efforts must rely heavily on a fundamental understanding of the predominant contributions to drug-DNA interactions. Although ligand-DNA interactions have been studied, so far there have only been a handful of studies that have probed the factors that govern DNA-binding using homologous series of compounds. This information is especially relevant to the rationale design of novel therapeutics with improved efficacy and specificity. The proposed chapter is designed to yield an understanding of how various features of small molecules govern their binding to DNA and will provide insights into ligand-DNA interactions by studying binding trends within homologous series of compounds. Several studies have suggested that some DNA binding molecules exhibit more than one binding mode while binding in a sequence specific manner. In fact, some researchers have proposed that the therapeutic efficiency of these drugs may be linked to their ability to exhibit mixed binding modes.[9,10] These modes primarily involve intercalation, where planar aromatic molecules slide between adjacent DNA base pairs resulting in significant perturbation of the DNA, and/or minor-groove binding, where molecules with the requisite flexibility and isohelicity with the DNA minor groove are able to fit into the DNA groove, usually with no significant change in the structure of the DNA.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 131

(**Figure1**).[13,14,17-19] In this geometry, one side chain occupies the minor groove, while the other lies in the major groove. According to some researchers, a threading intercalator has a number of potential advantages since the contact with both DNA grooves provide additional potential sites for recognition and targeting.[12-20] The NDI scaffold has

Some NDI derivatives have also been found to selectively bind non-standard structural forms of DNA such as triplexes and G-quadruplexes, which are normally transient and unstable.[21-25] Stabilization of DNA triplexes formed when oligonucleotides (normally referred to as triplex formation oligonucleotide or TFO) bind to DNA duplexes, have been explored in anti-gene therapeutics where expression of deleterious DNA sequences are suppressed by the binding and stabilization of complimentary TFO sequences.[15,21] Formation of transient G-quadruplexes in G-rich sequences have been found to be prominent in telomeres, G-rich ends on chromosomes that protects indispensable genes from being depleted, as well as preventing unwanted chromosomal fusions.[23-25] As a result, some compounds (e.g., certain NDI derivatives) can bind to and stabilize these telomeric G-quadruplexes can block access to these sequences by telomerase enzymes, which are responsible for extending and protecting telomeres and have been found to be over-expressed in 80% of cancers cells.[24,25] G-quadruplexes have also been found to be prominent in promoter regions, especially in the promoters of oncogenes such as the *c-myc and Ras genes, were*, found to be directly linked to the formation of certain cancers.[24,25] Stabilization of these G-quadruplexes in oncogene promoter regions can block access by RNA polymerase, and ultimately blocking expression of these deleterious genes. It is therefore important that we continue to probe ligands systems in order to increase our understanding of the driving force behind ligand–DNA interactions, and to use this

The NDI compounds were synthesized as previously described.[26] As mentioned above, the NDI scaffold has been used by several groups to design biologically significant compounds.[12-20] In the current series, the quaternary amino group in each side chains is close enough (ethyl- and propyl-amino linker) to the naphthalene core group to allow electrostatic contact with the DNA. Therefore, the cationic quaternary amino groups are close to the DNA when the core ring system intercalates between DNA base pairs. As a result, there is a greater probability for electrostatic interaction with the phosphates in the DNA backbone. The NDI molecules of this study have two substituents on either side of the central naphthalene moiety and differ mainly in substituent size and hydrophobicity. That means, each compound should adopt a threading molecular geometry when bound to DNA via intercalation. Threading NDI compounds analogous to the ones in this study have been

provided a versatile template for the design of many promising derivatives.[12-20]

**Figure 1.** General structure of the naphthalene diimides in this study.

knowledge to control their preferred binding mode and sequence.

(R = ethyl- or propyl-amino side chain)

For many years now, microcalorimetry has been utilized to decipher the complete thermodynamic profiles for a number of drug-DNA complexes.[11] Isothermal titration calorimetry (ITC) has been successfully used to parse the thermodynamics of the interactions between drug molecules and DNA.[2,3,11] ITC is regarded as the "gold standard" approach for the determination of binding affinity data in biomolecular interactions. ITC has been used to determine the comprehensive thermodynamic profile of these interactions, by determining enthalpy change (H) directly (usually in the presence of an excess of the macromolecular binding sites), while determining equilibrium binding constant (K), and number of binding sites (n) by model-fitting routines. Free energy change (G) and ultimately entropy change (S) are determined from the known thermodynamic relationships (G = -RTlnK) and (G = H-TS), respectively. Furthermore, heat capacity change (Cp) may be determined from ITC measurements of H over a range of different temperatures (Cp = dH/dT).[11]

In this chapter, we show how isothermal titration calorimetry can be successfully utilized to determine relative DNA binding efficacy, as well as the preferred DNA binding mode for a selection of homologous series of compounds. By comparing the DNA binding characteristics of homologous compounds under identical conditions, we can make robust conclusions as to the most important driving force governing the interaction of ligands to DNA. The chapter will describe two classes of homologous compounds; the naphthalene diimides and chalcogenoxanthyliums. However, the chapter will mainly focus on the naphthalene diimide series. The NDI scaffold has been used by several researchers to design therapeutically significant candidates [12-20] and are used in our studies as model systems to gain additional insight into the binding of "threading" intercalators to DNA. These symmetrical molecules have two substituents on either side of the intercalating moiety, thus necessitating the threading through or involvement of the side chain during binding (**Figure1**).[13,14,17-19] In this geometry, one side chain occupies the minor groove, while the other lies in the major groove. According to some researchers, a threading intercalator has a number of potential advantages since the contact with both DNA grooves provide additional potential sites for recognition and targeting.[12-20] The NDI scaffold has provided a versatile template for the design of many promising derivatives.[12-20]

(R = ethyl- or propyl-amino side chain)

Applications of Calorimetry in a Wide Context –

structure of the DNA.

temperatures (Cp = dH/dT).[11]

130 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

approach the problem from a fundamental level, such efforts must rely heavily on a fundamental understanding of the predominant contributions to drug-DNA interactions. Although ligand-DNA interactions have been studied, so far there have only been a handful of studies that have probed the factors that govern DNA-binding using homologous series of compounds. This information is especially relevant to the rationale design of novel therapeutics with improved efficacy and specificity. The proposed chapter is designed to yield an understanding of how various features of small molecules govern their binding to DNA and will provide insights into ligand-DNA interactions by studying binding trends within homologous series of compounds. Several studies have suggested that some DNA binding molecules exhibit more than one binding mode while binding in a sequence specific manner. In fact, some researchers have proposed that the therapeutic efficiency of these drugs may be linked to their ability to exhibit mixed binding modes.[9,10] These modes primarily involve intercalation, where planar aromatic molecules slide between adjacent DNA base pairs resulting in significant perturbation of the DNA, and/or minor-groove binding, where molecules with the requisite flexibility and isohelicity with the DNA minor groove are able to fit into the DNA groove, usually with no significant change in the

For many years now, microcalorimetry has been utilized to decipher the complete thermodynamic profiles for a number of drug-DNA complexes.[11] Isothermal titration calorimetry (ITC) has been successfully used to parse the thermodynamics of the interactions between drug molecules and DNA.[2,3,11] ITC is regarded as the "gold standard" approach for the determination of binding affinity data in biomolecular interactions. ITC has been used to determine the comprehensive thermodynamic profile of these interactions, by determining enthalpy change (H) directly (usually in the presence of an excess of the macromolecular binding sites), while determining equilibrium binding constant (K), and number of binding sites (n) by model-fitting routines. Free energy change (G) and ultimately entropy change (S) are determined from the known thermodynamic relationships (G = -RTlnK) and (G = H-TS), respectively. Furthermore, heat capacity change (Cp) may be determined from ITC measurements of H over a range of different

In this chapter, we show how isothermal titration calorimetry can be successfully utilized to determine relative DNA binding efficacy, as well as the preferred DNA binding mode for a selection of homologous series of compounds. By comparing the DNA binding characteristics of homologous compounds under identical conditions, we can make robust conclusions as to the most important driving force governing the interaction of ligands to DNA. The chapter will describe two classes of homologous compounds; the naphthalene diimides and chalcogenoxanthyliums. However, the chapter will mainly focus on the naphthalene diimide series. The NDI scaffold has been used by several researchers to design therapeutically significant candidates [12-20] and are used in our studies as model systems to gain additional insight into the binding of "threading" intercalators to DNA. These symmetrical molecules have two substituents on either side of the intercalating moiety, thus necessitating the threading through or involvement of the side chain during binding **Figure 1.** General structure of the naphthalene diimides in this study.

Some NDI derivatives have also been found to selectively bind non-standard structural forms of DNA such as triplexes and G-quadruplexes, which are normally transient and unstable.[21-25] Stabilization of DNA triplexes formed when oligonucleotides (normally referred to as triplex formation oligonucleotide or TFO) bind to DNA duplexes, have been explored in anti-gene therapeutics where expression of deleterious DNA sequences are suppressed by the binding and stabilization of complimentary TFO sequences.[15,21] Formation of transient G-quadruplexes in G-rich sequences have been found to be prominent in telomeres, G-rich ends on chromosomes that protects indispensable genes from being depleted, as well as preventing unwanted chromosomal fusions.[23-25] As a result, some compounds (e.g., certain NDI derivatives) can bind to and stabilize these telomeric G-quadruplexes can block access to these sequences by telomerase enzymes, which are responsible for extending and protecting telomeres and have been found to be over-expressed in 80% of cancers cells.[24,25] G-quadruplexes have also been found to be prominent in promoter regions, especially in the promoters of oncogenes such as the *c-myc and Ras genes, were*, found to be directly linked to the formation of certain cancers.[24,25] Stabilization of these G-quadruplexes in oncogene promoter regions can block access by RNA polymerase, and ultimately blocking expression of these deleterious genes. It is therefore important that we continue to probe ligands systems in order to increase our understanding of the driving force behind ligand–DNA interactions, and to use this knowledge to control their preferred binding mode and sequence.

The NDI compounds were synthesized as previously described.[26] As mentioned above, the NDI scaffold has been used by several groups to design biologically significant compounds.[12-20] In the current series, the quaternary amino group in each side chains is close enough (ethyl- and propyl-amino linker) to the naphthalene core group to allow electrostatic contact with the DNA. Therefore, the cationic quaternary amino groups are close to the DNA when the core ring system intercalates between DNA base pairs. As a result, there is a greater probability for electrostatic interaction with the phosphates in the DNA backbone. The NDI molecules of this study have two substituents on either side of the central naphthalene moiety and differ mainly in substituent size and hydrophobicity. That means, each compound should adopt a threading molecular geometry when bound to DNA via intercalation. Threading NDI compounds analogous to the ones in this study have been

Applications of Calorimetry in a Wide Context – 132 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

under investigation for several years as potential therapeutic (especially anticancer) compounds that bind to DNA with improved sequence-selectivity due to their interactions with both DNA grooves.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 133

These chalcogenoxanthylium derivatives represent an improvement over the parent rhodamine and rosamine since the inclusion of the heavier chalcogen (e.g.,S and Se instead of O) provides the known "heavy atom effect" which increases the production of long-lived excited triplet states.[33] Furthermore, the substituents (for example, a 2-thienyl instead of a phenyl) in the 9-position can be "tuned" such that they absorb light at wavelength that

To date, PACT has been mostly unsuccessful due largely to 1) low efficacy against pathogens, and 2) unwanted background hemolysis of red blood cells.[32] Both these shortcomings are mostly due to the non-specific actions of the photosensitizers when exposed to the requisite light. To circumvent these problems, photosensitizers that are able to target the pathogenic DNA relative to the red blood cells are currently being explored.[32,35] One approach to target these pathogens in the presence of red blood cells is to use photosensitizers that bind strongly to the pathogenic DNA, since mature red blood cells do not contain organelles or genomic nucleic acids.[32,35] The chalcogenoxanthylium derivatives are advantageous to use since their substituents can be tuned such that 1) they absorb light in a spectral region where light attenuation by hemoglobin absorption is avoided, 2) increased yield of singlet excited state that are responsible for destruction of pathogens, and 3) their planarity and hydrophobicity can be altered to monitor the effects on their interaction with DNA. Thus, offering greater opportunity to potentially reduce the incidence of background hemolysis. The DNA binding efficacy and preferred mode of binding of a series of chalcogenoxanthylium dyes were investigated by isothermal titration

In an effort to decipher the preferred DNA binding mode for compounds in this study, a preference for an AT- vs GC-rich sequence will be determined. In order to differentiate preferences for intercalation and/or groove binding, the binding of the compounds of this study to [poly(dAdT)]2 and [poly(dGdC)]2 were examined by ITC. Figure 3 shows the structure of [poly(dAdT)]2 and [poly(dGdC)]2 used in this study. It has long been established that known groove binding compounds (e.g., distamycin, berenil, and DAPI) show a strong preference (an order of magnitude or greater) for binding to [poly(dAdT)]2 relative to [poly(dGdC)]2.[6] The lower affinity for GC-rich sequences shown by groove binders is largely due to their restricted access to the minor groove of GC sequences caused by the protruding 2- NH2 group of guanine. Intercalators are only expected to be affected by this if a substituent is placed into the minor groove during formation of the intercalation complex. It is however expected that compounds that exhibit mixed binding mode (i.e., intercalation and groove

binding) will exhibit less (<10) of a preference for the AT sequence.[28,35,36]

**Figure 3.** AT-rich and GC-rich DNA sequences used in this study.

avoids hemoglobin attenuation. [33-35]

calorimetry (ITC).[35]

**1.3. Preference for AT-rich vs GC-rich DNA** 

### **1.2. Chalcogenoxanthyliums**

Although stored blood used during surgery and in blood transfusion is generally safe due to improved screening procedures, there is still a chance (a slight risk) that pathogens within the stored blood may be transmitted from donor to recipient.[27,28] This can occur if the blood was collected from an infected individual before there were detectable levels of the causative pathogen. As a result, there remains a need to develop protocols in which to reduce the risk of pathogen transmission, if only in a precautionary or preventative role.

Photodynamic therapy (PDT) is one approach that has been considered as a viable means in which to purge stored blood samples of deleterious pathogens.[27-32] In PDT, light is used along with endogenous oxygen and an appropriate photosensitizer (a molecule that has the ability to absorb light energy, i.e., photoexcitation, and transfer this energy to another chemical entity inducing a change) to treat or reduce an affliction. Photosensitizers are effective mainly because they are able to absorb appropriate light energy and produce excited triplet states at which time they can transfer energy to ground state oxygen (which is also triplet state) via intersystem crossing producing very toxic singlet oxygen species. PDT has been used for years in the treatment of certain cancers and lesions, as well as age-related macular degeneration. Photofrin, a hematoporhyrin belonging to the porphyrin class of compounds, is probably the most well-known and has been used for many years to treat bladder cancers. Other photosensitizers include those in the clorin class (e.g., photochlor), as well as dyes such as phthalocyanine.

PDT can be applied in pathogen reduction, especially in the removal of microbial material from blood products. In this application, PDT is normally referred to as photodynamic antimicrobial chemotherapy (PACT). Compounds containing the xanthylium core (rhodamines and rosamines), are among some of the most highly touted class of compounds being considered for PACT and have been explored by Wagner, Detty and coworkers.[27,31,32] These compounds have been found to selectively accumulate in cancer cells and mitochondria, and have also been considered as p-glycoprotein inhibitors and mitochondrial stains.[33,34] However, the parent rhodamines and rosamines have been mostly ineffective due to short-lived and low yield of triplet excited state upon photoexcitation. Detty and coworkers have synthesized a group of related chalcogenoxanthyliums (**Figure 2**) that are based on the parent compounds.[33,34]

(X = chalchogen, R = 9-aryl substituent)

**Figure 2.** General structure for the chalcogenoxanthylium derivatives.

These chalcogenoxanthylium derivatives represent an improvement over the parent rhodamine and rosamine since the inclusion of the heavier chalcogen (e.g.,S and Se instead of O) provides the known "heavy atom effect" which increases the production of long-lived excited triplet states.[33] Furthermore, the substituents (for example, a 2-thienyl instead of a phenyl) in the 9-position can be "tuned" such that they absorb light at wavelength that avoids hemoglobin attenuation. [33-35]

To date, PACT has been mostly unsuccessful due largely to 1) low efficacy against pathogens, and 2) unwanted background hemolysis of red blood cells.[32] Both these shortcomings are mostly due to the non-specific actions of the photosensitizers when exposed to the requisite light. To circumvent these problems, photosensitizers that are able to target the pathogenic DNA relative to the red blood cells are currently being explored.[32,35] One approach to target these pathogens in the presence of red blood cells is to use photosensitizers that bind strongly to the pathogenic DNA, since mature red blood cells do not contain organelles or genomic nucleic acids.[32,35] The chalcogenoxanthylium derivatives are advantageous to use since their substituents can be tuned such that 1) they absorb light in a spectral region where light attenuation by hemoglobin absorption is avoided, 2) increased yield of singlet excited state that are responsible for destruction of pathogens, and 3) their planarity and hydrophobicity can be altered to monitor the effects on their interaction with DNA. Thus, offering greater opportunity to potentially reduce the incidence of background hemolysis. The DNA binding efficacy and preferred mode of binding of a series of chalcogenoxanthylium dyes were investigated by isothermal titration calorimetry (ITC).[35]

### **1.3. Preference for AT-rich vs GC-rich DNA**

Applications of Calorimetry in a Wide Context –

with both DNA grooves.

**1.2. Chalcogenoxanthyliums** 

well as dyes such as phthalocyanine.

(X = chalchogen, R = 9-aryl substituent)

(**Figure 2**) that are based on the parent compounds.[33,34]

**Figure 2.** General structure for the chalcogenoxanthylium derivatives.

132 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

under investigation for several years as potential therapeutic (especially anticancer) compounds that bind to DNA with improved sequence-selectivity due to their interactions

Although stored blood used during surgery and in blood transfusion is generally safe due to improved screening procedures, there is still a chance (a slight risk) that pathogens within the stored blood may be transmitted from donor to recipient.[27,28] This can occur if the blood was collected from an infected individual before there were detectable levels of the causative pathogen. As a result, there remains a need to develop protocols in which to reduce the risk of pathogen transmission, if only in a precautionary or preventative role.

Photodynamic therapy (PDT) is one approach that has been considered as a viable means in which to purge stored blood samples of deleterious pathogens.[27-32] In PDT, light is used along with endogenous oxygen and an appropriate photosensitizer (a molecule that has the ability to absorb light energy, i.e., photoexcitation, and transfer this energy to another chemical entity inducing a change) to treat or reduce an affliction. Photosensitizers are effective mainly because they are able to absorb appropriate light energy and produce excited triplet states at which time they can transfer energy to ground state oxygen (which is also triplet state) via intersystem crossing producing very toxic singlet oxygen species. PDT has been used for years in the treatment of certain cancers and lesions, as well as age-related macular degeneration. Photofrin, a hematoporhyrin belonging to the porphyrin class of compounds, is probably the most well-known and has been used for many years to treat bladder cancers. Other photosensitizers include those in the clorin class (e.g., photochlor), as

PDT can be applied in pathogen reduction, especially in the removal of microbial material from blood products. In this application, PDT is normally referred to as photodynamic antimicrobial chemotherapy (PACT). Compounds containing the xanthylium core (rhodamines and rosamines), are among some of the most highly touted class of compounds being considered for PACT and have been explored by Wagner, Detty and coworkers.[27,31,32] These compounds have been found to selectively accumulate in cancer cells and mitochondria, and have also been considered as p-glycoprotein inhibitors and mitochondrial stains.[33,34] However, the parent rhodamines and rosamines have been mostly ineffective due to short-lived and low yield of triplet excited state upon photoexcitation. Detty and coworkers have synthesized a group of related chalcogenoxanthyliums

Me2N X NMe2

R

In an effort to decipher the preferred DNA binding mode for compounds in this study, a preference for an AT- vs GC-rich sequence will be determined. In order to differentiate preferences for intercalation and/or groove binding, the binding of the compounds of this study to [poly(dAdT)]2 and [poly(dGdC)]2 were examined by ITC. Figure 3 shows the structure of [poly(dAdT)]2 and [poly(dGdC)]2 used in this study. It has long been established that known groove binding compounds (e.g., distamycin, berenil, and DAPI) show a strong preference (an order of magnitude or greater) for binding to [poly(dAdT)]2 relative to [poly(dGdC)]2.[6] The lower affinity for GC-rich sequences shown by groove binders is largely due to their restricted access to the minor groove of GC sequences caused by the protruding 2- NH2 group of guanine. Intercalators are only expected to be affected by this if a substituent is placed into the minor groove during formation of the intercalation complex. It is however expected that compounds that exhibit mixed binding mode (i.e., intercalation and groove binding) will exhibit less (<10) of a preference for the AT sequence.[28,35,36]

**Figure 3.** AT-rich and GC-rich DNA sequences used in this study.

#### 134 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In this chapter, calorimetric data of naphthalene diimide derivatives binding to both calf thymus DNA (ctDNA), as well as AT- and GC-rich DNA sequences will be described. The binding characteristics of selected chalcogenoxanthylium derivatives will also be compared. In an effort to gain insight into the involvement of a minor groove vs. intercalative binding mode, the binding of the compounds to [poly(dAdT)]2 and [poly(dCdG)]2 sequences (using ITC) will be discussed. The calorimetric approach will be validated using known/classical DNA intercalating and minor groove binding compounds. Although the main focus of the chapter will be analysis of calorimetric data, the data will also be compared to studies on the same systems using ITC-independents approaches such as a gel electrophoresis based topoisomerase I DNA unwinding assays and fluorescence-based ethidium bromide displacement studies.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 135

given off. Note, in all cases, titration peaks corresponded to negative power compensation resulting from exothermically driven processes. In each case, response signals were corrected for the small heat of dilution associated with the titration of the drug into the MES buffer. The heat of dilution for titrating MES buffer into DNA was found to be negligible. The heat released (i.e., area associated with negative peaks) on binding of the drug to DNA sites was directly proportional to the amount of binding. A binding isotherm of heat released (kcal/mol of injectant) versus the molar ratio ([drug]/[DNA] in bp) was constructed

and the data fitted by non-linear least square fitting analysis to an appropriate model.

for 3 h, stained with ethidium bromide for 45 min and photographed.

Typically, 0.24 µg of supercoiled pUC19 plasmid DNA was incubated with human topoisomerase I (Topo I) enzyme (Invitrogen) for 5 min at 37 ºC. An appropriate amount of the compound of interest was then added (all except for the first two tubes, which serves as controls) and the reaction mixture incubated for a further 1 h at 37 ºC. After incubation, the reaction was terminated using 0.5% SDS and 0.5 mg/mL proteinase K. Both the enzyme and compound of interest was then extracted using a mixture of phenol:chloroform:isoamyl alcohol (25:24:1). The remaining DNA sample was then run on an agarose gel (1%) at 75 V

A solution of ethidium bromide (EtBr, 5 10-6 M, 1.0 mL) was pre-incubated with ultrapure calf thymus DNA (1 10-5 M in base pairs, 1.4 mL) obtained from Invitrogen. at room temperature (22-23 C) for 15 min in MES00 buffer, pH 6.3. Aliquots of exactly 3 L of the compound (7 10-5 M) were then titrated into the EtBr-DNA solution and the change in fluorescence measured (Photon Technology International fluorometer), after 3 min incubation periods (excitation 545 nm and emission 595 nm). The addition of 3 L aliquots was continued until the DNA was saturated (i.e., no further change in fluorescence due to EtBr displacement). [28,36] Control experiments showed that the compounds (free or DNAbound) had no significant background fluorescence at the excitation (545 nm) and emission

**3.1. Using relative binding affinity for AT- vs GC-DNA to evaluate binding** 

In order to validate the approach of using relative preferences for AT vs GC to ascertain the preferred DNA binding mode, several known/classical DNA binding compounds were investigated using ITC. These include two compounds known to bind DNA via the minor groove, distamycin A and berenil, (Figure 4) and two compounds known to bind DNA via intercalation (ethidium bromide, normally regarded as the classical DNA intercalator, and

**2.2. Topoismerase I DNA unwinding assay** 

**2.3. Ethidium bromide displacement assay** 

(595 nm) wavelengths of EtBr.

**3. Results and discussion** 

daunomycin) (Figure 5).[2,3,6]

**mode** 

### **2. Methods and materials**

### **2.1. Isothermal titration calorimetry**

In general, calorimetric titrations were carried out on a MicroCal VP-ITC (MicroCal Inc., Northampton, MA), an instrument specifically suited for studying biomolecular interactions. The MicroCal VP-ITC is a highly sensitive microcalorimeter that operates on a power compensation method, whereby heat exchange processes occurring in a sample cell is compared to a reference cell as the instruments keeps the two cell temperatures identical. This results in exothermic processes yielding negative (less than zero) peaks as the instrument decreases the power (µcal/s) supplied to the sample cell relative to the reference cell, while endothermic processes yield positive (greater than zero) peaks as the instrument increases the power supplied to the sample cell compared to the reference cell. The intensity of each peak corresponds to the quantity of the heat exchange. The data was analyzed using the Origin 7.0 software provided by the manufacturer. Experiments were typically run at either 25-30 °C in MES00 buffer (1 10-2 M MES (2(*N*-morpholino) ethanesulfonic acid) containing 1 10-3 M EDTA, with the pH adjusted to 6.25 with NaOH) for runs involving calf thymus DNA (ctDNA, ultrapure, Invitrogen). Due to the relative instability of the shorter DNA sequence (particularly the AT-rich sequence), experiments using the [poly(dAdT)]2 and [poly(dCdG)]2 sequences (Midland Certified Reagents, Midland , TX) were done in MES40 (i.e., MES00 with 40 mM NaCl). Note, the MES00 buffer was selected for the ctDNA studies due to its low concentration of salt; this would presumably promote stronger binding interactions which would yield more intense peaks and thus better signal/noise ratios. Typically, either 5 or 12 µL of the drug solution (typically 5-7 10-5 M) was injected into a buffered solution of DNA (typically 10-15 10-6 M in bp, 1.4 mL) over 20- 24 s at 240 s intervals using a 250 µL syringe rotating at 300 rpm. The initial delay (hold period before injections) was set at 240 s. Before use, samples were degassed at 20 °C using the ThermoVac accessory (provided by MicroCal Inc.). During the isothermal titration experiments, all injections manifested in a peak that corresponded to the decrease in the power (µcal/s) supplied to keep the temperatures of the sample and reference cells (containing either water or MES buffer) the same for each injection and represented the heat given off. Note, in all cases, titration peaks corresponded to negative power compensation resulting from exothermically driven processes. In each case, response signals were corrected for the small heat of dilution associated with the titration of the drug into the MES buffer. The heat of dilution for titrating MES buffer into DNA was found to be negligible. The heat released (i.e., area associated with negative peaks) on binding of the drug to DNA sites was directly proportional to the amount of binding. A binding isotherm of heat released (kcal/mol of injectant) versus the molar ratio ([drug]/[DNA] in bp) was constructed and the data fitted by non-linear least square fitting analysis to an appropriate model.

### **2.2. Topoismerase I DNA unwinding assay**

Applications of Calorimetry in a Wide Context –

displacement studies.

**2. Methods and materials** 

**2.1. Isothermal titration calorimetry** 

134 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In this chapter, calorimetric data of naphthalene diimide derivatives binding to both calf thymus DNA (ctDNA), as well as AT- and GC-rich DNA sequences will be described. The binding characteristics of selected chalcogenoxanthylium derivatives will also be compared. In an effort to gain insight into the involvement of a minor groove vs. intercalative binding mode, the binding of the compounds to [poly(dAdT)]2 and [poly(dCdG)]2 sequences (using ITC) will be discussed. The calorimetric approach will be validated using known/classical DNA intercalating and minor groove binding compounds. Although the main focus of the chapter will be analysis of calorimetric data, the data will also be compared to studies on the same systems using ITC-independents approaches such as a gel electrophoresis based topoisomerase I DNA unwinding assays and fluorescence-based ethidium bromide

In general, calorimetric titrations were carried out on a MicroCal VP-ITC (MicroCal Inc., Northampton, MA), an instrument specifically suited for studying biomolecular interactions. The MicroCal VP-ITC is a highly sensitive microcalorimeter that operates on a power compensation method, whereby heat exchange processes occurring in a sample cell is compared to a reference cell as the instruments keeps the two cell temperatures identical. This results in exothermic processes yielding negative (less than zero) peaks as the instrument decreases the power (µcal/s) supplied to the sample cell relative to the reference cell, while endothermic processes yield positive (greater than zero) peaks as the instrument increases the power supplied to the sample cell compared to the reference cell. The intensity of each peak corresponds to the quantity of the heat exchange. The data was analyzed using the Origin 7.0 software provided by the manufacturer. Experiments were typically run at either 25-30 °C in MES00 buffer (1 10-2 M MES (2(*N*-morpholino) ethanesulfonic acid) containing 1 10-3 M EDTA, with the pH adjusted to 6.25 with NaOH) for runs involving calf thymus DNA (ctDNA, ultrapure, Invitrogen). Due to the relative instability of the shorter DNA sequence (particularly the AT-rich sequence), experiments using the [poly(dAdT)]2 and [poly(dCdG)]2 sequences (Midland Certified Reagents, Midland , TX) were done in MES40 (i.e., MES00 with 40 mM NaCl). Note, the MES00 buffer was selected for the ctDNA studies due to its low concentration of salt; this would presumably promote stronger binding interactions which would yield more intense peaks and thus better signal/noise ratios. Typically, either 5 or 12 µL of the drug solution (typically 5-7 10-5 M) was injected into a buffered solution of DNA (typically 10-15 10-6 M in bp, 1.4 mL) over 20- 24 s at 240 s intervals using a 250 µL syringe rotating at 300 rpm. The initial delay (hold period before injections) was set at 240 s. Before use, samples were degassed at 20 °C using the ThermoVac accessory (provided by MicroCal Inc.). During the isothermal titration experiments, all injections manifested in a peak that corresponded to the decrease in the power (µcal/s) supplied to keep the temperatures of the sample and reference cells (containing either water or MES buffer) the same for each injection and represented the heat Typically, 0.24 µg of supercoiled pUC19 plasmid DNA was incubated with human topoisomerase I (Topo I) enzyme (Invitrogen) for 5 min at 37 ºC. An appropriate amount of the compound of interest was then added (all except for the first two tubes, which serves as controls) and the reaction mixture incubated for a further 1 h at 37 ºC. After incubation, the reaction was terminated using 0.5% SDS and 0.5 mg/mL proteinase K. Both the enzyme and compound of interest was then extracted using a mixture of phenol:chloroform:isoamyl alcohol (25:24:1). The remaining DNA sample was then run on an agarose gel (1%) at 75 V for 3 h, stained with ethidium bromide for 45 min and photographed.

#### **2.3. Ethidium bromide displacement assay**

A solution of ethidium bromide (EtBr, 5 10-6 M, 1.0 mL) was pre-incubated with ultrapure calf thymus DNA (1 10-5 M in base pairs, 1.4 mL) obtained from Invitrogen. at room temperature (22-23 C) for 15 min in MES00 buffer, pH 6.3. Aliquots of exactly 3 L of the compound (7 10-5 M) were then titrated into the EtBr-DNA solution and the change in fluorescence measured (Photon Technology International fluorometer), after 3 min incubation periods (excitation 545 nm and emission 595 nm). The addition of 3 L aliquots was continued until the DNA was saturated (i.e., no further change in fluorescence due to EtBr displacement). [28,36] Control experiments showed that the compounds (free or DNAbound) had no significant background fluorescence at the excitation (545 nm) and emission (595 nm) wavelengths of EtBr.

### **3. Results and discussion**

### **3.1. Using relative binding affinity for AT- vs GC-DNA to evaluate binding mode**

In order to validate the approach of using relative preferences for AT vs GC to ascertain the preferred DNA binding mode, several known/classical DNA binding compounds were investigated using ITC. These include two compounds known to bind DNA via the minor groove, distamycin A and berenil, (Figure 4) and two compounds known to bind DNA via intercalation (ethidium bromide, normally regarded as the classical DNA intercalator, and daunomycin) (Figure 5).[2,3,6]

136 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Isothermal titration calorimetric data for distamycin, berenil, daunomycin and ethidium bromide binding to the AT- and GC-rich sequences are shown in Figure 6. As can be seen from the raw data, both minor groove binders distamycin A and berenil show a strong preference for the AT-rich sequence relative to the GC-rich sequence. In fact, ITC signals for each compound binding to the GC-rich sequence was found to be negligible, showing only background signal that was associated with the heats of dilution when the compound was titrated into the cell buffer. Binding constants found for distamycin A and berenil binding to the AT-rich sequence were 2.20±0.4 x 107 M-1 and 1.76±0.3 x 106 M-1, respectively.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 137

ethidium bromide and daunomycin bind DNA via intercalation, since neither exhibited a significant preference. This is suggested from the fact that the minor groove in the GC-rich sequence is partially blocked by the protruded 2-NH2 group of guanine, preventing a compound that uses the minor groove for DNA binding to be blocked.[6] This is not the case for the AT-rich sequence. On the other hand, a compound such as ethidium bromide and daunomycin which intercalates into DNA by sliding between adjacent base pairs, will essentially be unimpeded from binding to either the AT or GC-rich sequences. The reported binding modes for distamycin A, berenil, ethidium bromide and daunomycin herein are also consistent with the wealth of literature reports on the binding mode for all four

**Figure 6.** Calorimetric data for the titration of 60 µM of the compounds (from left to right): distamycin A, berenil, daunomycin and ethidium bromide into 15 µM of AT-rich DNA (top), GC-DNA (bottom) at 30 C. Binding isotherms (heat change vs drug/DNA molar ratio) were obtained from the integration of

As was mentioned earlier, the NDI class of compounds is an excellent model system to study DNA binding interactions especially since it offers a useful platform for the syntheses of many homologous series. These molecules are threading intercalators in which side chains on either side of the main intercalating moiety provides the potential for specific recognition sites on the DNA.[12-19] The specific roles of a variety of substituents will be studied with a focus on identifying differential contributions from each moiety. A

**4. Binding of the NDI derivatives to DNA using ITC** 

compounds, thus validating our approach.[2,3,6,8,10,37,38]

raw data and fitted to a "one-site" model

**Figure 4.** Structures of some common DNA minor groove binding compounds.

A different result was observed with the classical DNA intercalator, ethidium bromide and the known chemotherapeutic DNA intercalator, daunomycin. The isothermal calorimetric data for ethidium bromide and daunomycin showed binding to both the AT- and GC-rich sequences and indicated no significant preference for either sequence. Binding constants obtained for the AT-rich and GC-rich sequence were 1.78±0.5 x 105 M-1 and 3.38± 0.8 x 105 M-1, and 2.93±0.63 x 106 M-1 and 3.24±0.60 x 105 M-1, for ethidium bromide and daunomycin, respectively.

**Figure 5.** Structures of two common DNA intercalators.

The results observed for distamycin A, berenil, ethidium bromide and daunomycin are consistent with both distamycin A and berenil binding via the minor groove, since each compound showed a significant preference for the AT-rich sequence, while as expected, ethidium bromide and daunomycin bind DNA via intercalation, since neither exhibited a significant preference. This is suggested from the fact that the minor groove in the GC-rich sequence is partially blocked by the protruded 2-NH2 group of guanine, preventing a compound that uses the minor groove for DNA binding to be blocked.[6] This is not the case for the AT-rich sequence. On the other hand, a compound such as ethidium bromide and daunomycin which intercalates into DNA by sliding between adjacent base pairs, will essentially be unimpeded from binding to either the AT or GC-rich sequences. The reported binding modes for distamycin A, berenil, ethidium bromide and daunomycin herein are also consistent with the wealth of literature reports on the binding mode for all four compounds, thus validating our approach.[2,3,6,8,10,37,38]

Applications of Calorimetry in a Wide Context –

respectively.

136 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Isothermal titration calorimetric data for distamycin, berenil, daunomycin and ethidium bromide binding to the AT- and GC-rich sequences are shown in Figure 6. As can be seen from the raw data, both minor groove binders distamycin A and berenil show a strong preference for the AT-rich sequence relative to the GC-rich sequence. In fact, ITC signals for each compound binding to the GC-rich sequence was found to be negligible, showing only background signal that was associated with the heats of dilution when the compound was titrated into the cell buffer. Binding constants found for distamycin A and berenil binding to

the AT-rich sequence were 2.20±0.4 x 107 M-1 and 1.76±0.3 x 106 M-1, respectively.

**Figure 4.** Structures of some common DNA minor groove binding compounds.

**Figure 5.** Structures of two common DNA intercalators.

A different result was observed with the classical DNA intercalator, ethidium bromide and the known chemotherapeutic DNA intercalator, daunomycin. The isothermal calorimetric data for ethidium bromide and daunomycin showed binding to both the AT- and GC-rich sequences and indicated no significant preference for either sequence. Binding constants obtained for the AT-rich and GC-rich sequence were 1.78±0.5 x 105 M-1 and 3.38± 0.8 x 105 M-1, and 2.93±0.63 x 106 M-1 and 3.24±0.60 x 105 M-1, for ethidium bromide and daunomycin,

The results observed for distamycin A, berenil, ethidium bromide and daunomycin are consistent with both distamycin A and berenil binding via the minor groove, since each compound showed a significant preference for the AT-rich sequence, while as expected,

**Figure 6.** Calorimetric data for the titration of 60 µM of the compounds (from left to right): distamycin A, berenil, daunomycin and ethidium bromide into 15 µM of AT-rich DNA (top), GC-DNA (bottom) at 30 C. Binding isotherms (heat change vs drug/DNA molar ratio) were obtained from the integration of raw data and fitted to a "one-site" model

### **4. Binding of the NDI derivatives to DNA using ITC**

As was mentioned earlier, the NDI class of compounds is an excellent model system to study DNA binding interactions especially since it offers a useful platform for the syntheses of many homologous series. These molecules are threading intercalators in which side chains on either side of the main intercalating moiety provides the potential for specific recognition sites on the DNA.[12-19] The specific roles of a variety of substituents will be studied with a focus on identifying differential contributions from each moiety. A

#### Applications of Calorimetry in a Wide Context – 138 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

quaternary amino group will also be incorporated into each NDI side chain to provide electrostatic interaction with the negatively charged DNA backbone. The NDI derivatives in this chapter (Figure 7 and 8) were synthesized by Dixon and coworkers and have three main motifs.[26,36]

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 139

**Figure 7.** Representative structure for the acyclic NDI derivatives, showing the ethylamino (ethyl linker) side chain derivatives [**NDI-1e** (bottom, left) and **NDI-2e** (bottom, right)] and the propylamino

**Figure 8.** Structures for the cyclic ethylamino NDI derivatives [**NDI-3** (top, left) and **NDI-4** (bottom, left)] and the cyclic propylamino derivatives **NDI-5** (right). Both **NDI-3** and **NDI-5** contain a side chain *N*methyl pyrrolidine five-membered ring, while **NDI-4** contains a six-membered *N*-methyl piperidine ring.

In general, the inclusion of a cyclic component in the side chain resulted in a biphasic raw calorimetric data for each cyclic NDI compound binding to DNA (**Figure 9**). The raw calorimetric data for the cyclic compounds binding to ctDNA were best defined by a model that assumes two types of binding sites (K1, K2) and argues for the involvement of at least two different types of binding modes for the compounds with ring-containing substituents. This biphasic binding mode has been reported by us for larger members of an acyclic substituent NDI series and will be briefly discussed below.[36] In general, the higher binding constant (K1) for the cyclic NDI derivatives was in the order (~107-108 M-1), while a lower binding constant (K2) was in the order of (~106 M-1) for compounds possessing the *N*methyl pyrrolidine ring (**NDI-3** and **NDI-5**) binding to ctDNA. The DNA binding constant for the *N*-methyl piperidine derivative (**NDI-4**) showed strong but significantly lower binding constants compared to the *N*-methyl pyrrolidine derivatives. Calorimetric data for

(propyl linker) derivatives [**NDI-1p**,(top, left) and **NDI-2p** (top, right)].

**5. Effect of the side chain ring size and linker length** 

Ring Size: Compounds that contains a ring (*N*-methyl pyrrolidine or *N*-methyl piperidine) at the distal end of the side chain, as well as possessing different ring size. To date, the effect of ring size on intercalator-DNA interaction has been mostly unexplored. We have studied two homologous types of NDI that differ by a single carbon with five- vs six-membered heterocyclic rings. These are at identical distances from the main intercalating moiety. The rings are non-aromatic and are not expected to stack with the DNA bases. However, they differ in steric bulk which should have implications during binding. One could predict that **NDI-3** will show relatively lower binding affinity than **NDI-4**, however, the increase in bulkiness might have only kinetic consequences.26 We are interested in determining whether these substituent variations might have an effect on both the preferred DNA binding mode adopted by these compounds, and consequently their relative DNA binding affinity. We also compare the effect of having a cyclic structure in the side chain vs. acyclic alkyl substituents*.*

Linker length: Insights into the effect of changing the linker length for two sets of NDI derivatives (acyclic aliphatic and cyclic aliphatic substituents) will be discussed. In both sets of compounds, the side chain linker length differ by one carbon (ethyl vs propyl). This means the quaternary amino group (present in all the NDI compounds) is one carbon further from the main intercalating core for the propyl linker. For the acyclic aliphatic derivatives, we compare the trimethyl-propylamino (**NDI-1p**) and dibutylmethylpropylamino (**NDI-2p**) derivatives (that are one carbon further from the main intercalating core) to the trimethyl-ethylamino (**NDI-1e**) and dibutylmethyl-ethylamino (**NDI-2e**) derivatives. For the cyclic aliphatic compounds, the ethyl-linker-containing compound, **NDI-3**, is compared to the propyl-linker-containing **NDI-5**. Given the difference in steric bulk of the cyclic aliphatic compared to the acyclic derivatives, there may be steric consequences. We will also be able to gain insights into acyclic vs. cyclic substituent effects on DNA binding.

Substituent length/size: In order to gain additional insights into the role of the side chain size, an analysis of the DNA binding characteristics of NDI compounds that differ in the size and side chain linker-length of their alkyl-amine side chain will also be done*.* As the length and size of the substituent increases, so does the steric bulk. Of course, hydrophobicity also increases with substituent size. We seek to investigate the effects of steric bulk and hydrophobicity on DNA binding of these derivatives. Hydrophobicity has been reported to be a significant driving force in DNA binding interactions with binding increasing with hydrophobicity.[2,3] We have investigated the relative importance of this factor using a model NDI series in which size/steric contributions should also be a factor. Both hydrophobicity and molecular size increases along the series. If hydrophobicity is the predominant driving force, then one might expect binding to increase with size/hydrophobicity. However, if a size/steric effect dominates, binding should decrease.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 139

Applications of Calorimetry in a Wide Context –

motifs.[26,36]

substituents*.*

on DNA binding.

138 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

quaternary amino group will also be incorporated into each NDI side chain to provide electrostatic interaction with the negatively charged DNA backbone. The NDI derivatives in this chapter (Figure 7 and 8) were synthesized by Dixon and coworkers and have three main

Ring Size: Compounds that contains a ring (*N*-methyl pyrrolidine or *N*-methyl piperidine) at the distal end of the side chain, as well as possessing different ring size. To date, the effect of ring size on intercalator-DNA interaction has been mostly unexplored. We have studied two homologous types of NDI that differ by a single carbon with five- vs six-membered heterocyclic rings. These are at identical distances from the main intercalating moiety. The rings are non-aromatic and are not expected to stack with the DNA bases. However, they differ in steric bulk which should have implications during binding. One could predict that **NDI-3** will show relatively lower binding affinity than **NDI-4**, however, the increase in bulkiness might have only kinetic consequences.26 We are interested in determining whether these substituent variations might have an effect on both the preferred DNA binding mode adopted by these compounds, and consequently their relative DNA binding affinity. We also compare the effect of having a cyclic structure in the side chain vs. acyclic alkyl

Linker length: Insights into the effect of changing the linker length for two sets of NDI derivatives (acyclic aliphatic and cyclic aliphatic substituents) will be discussed. In both sets of compounds, the side chain linker length differ by one carbon (ethyl vs propyl). This means the quaternary amino group (present in all the NDI compounds) is one carbon further from the main intercalating core for the propyl linker. For the acyclic aliphatic derivatives, we compare the trimethyl-propylamino (**NDI-1p**) and dibutylmethylpropylamino (**NDI-2p**) derivatives (that are one carbon further from the main intercalating core) to the trimethyl-ethylamino (**NDI-1e**) and dibutylmethyl-ethylamino (**NDI-2e**) derivatives. For the cyclic aliphatic compounds, the ethyl-linker-containing compound, **NDI-3**, is compared to the propyl-linker-containing **NDI-5**. Given the difference in steric bulk of the cyclic aliphatic compared to the acyclic derivatives, there may be steric consequences. We will also be able to gain insights into acyclic vs. cyclic substituent effects

Substituent length/size: In order to gain additional insights into the role of the side chain size, an analysis of the DNA binding characteristics of NDI compounds that differ in the size and side chain linker-length of their alkyl-amine side chain will also be done*.* As the length and size of the substituent increases, so does the steric bulk. Of course, hydrophobicity also increases with substituent size. We seek to investigate the effects of steric bulk and hydrophobicity on DNA binding of these derivatives. Hydrophobicity has been reported to be a significant driving force in DNA binding interactions with binding increasing with hydrophobicity.[2,3] We have investigated the relative importance of this factor using a model NDI series in which size/steric contributions should also be a factor. Both hydrophobicity and molecular size increases along the series. If hydrophobicity is the predominant driving force, then one might expect binding to increase with size/hydrophobicity. However, if a size/steric effect dominates, binding should decrease.

**Figure 7.** Representative structure for the acyclic NDI derivatives, showing the ethylamino (ethyl linker) side chain derivatives [**NDI-1e** (bottom, left) and **NDI-2e** (bottom, right)] and the propylamino (propyl linker) derivatives [**NDI-1p**,(top, left) and **NDI-2p** (top, right)].

**Figure 8.** Structures for the cyclic ethylamino NDI derivatives [**NDI-3** (top, left) and **NDI-4** (bottom, left)] and the cyclic propylamino derivatives **NDI-5** (right). Both **NDI-3** and **NDI-5** contain a side chain *N*methyl pyrrolidine five-membered ring, while **NDI-4** contains a six-membered *N*-methyl piperidine ring.

### **5. Effect of the side chain ring size and linker length**

In general, the inclusion of a cyclic component in the side chain resulted in a biphasic raw calorimetric data for each cyclic NDI compound binding to DNA (**Figure 9**). The raw calorimetric data for the cyclic compounds binding to ctDNA were best defined by a model that assumes two types of binding sites (K1, K2) and argues for the involvement of at least two different types of binding modes for the compounds with ring-containing substituents. This biphasic binding mode has been reported by us for larger members of an acyclic substituent NDI series and will be briefly discussed below.[36] In general, the higher binding constant (K1) for the cyclic NDI derivatives was in the order (~107-108 M-1), while a lower binding constant (K2) was in the order of (~106 M-1) for compounds possessing the *N*methyl pyrrolidine ring (**NDI-3** and **NDI-5**) binding to ctDNA. The DNA binding constant for the *N*-methyl piperidine derivative (**NDI-4**) showed strong but significantly lower binding constants compared to the *N*-methyl pyrrolidine derivatives. Calorimetric data for

140 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

the two compounds that differed only in ring size (*N*-methyl pyrrolidine vs *N*-methyl piperidine) showed that **NDI-3** (*N*-methyl pyrrolidine substituent) exhibited larger binding constants (K1 = 1.17± 0.3 x 108 M-1, K2 = 5.6±0.65 x 106 M-1) as compared to larger **NDI-4** (K1=1.70 ±0.4 x 107 M-1 and K2=3.26 ±0.54 x 106 M-1) when binding to ctDNA. Thus both binding constants were lower for the larger *N*-methyl piperidine derivative. Given that **NDI-4** possesses a more bulky *N*-methyl piperidyl substituent suggest that steric hindrance may play a role here. Studies on a series of NDI containing acyclic substituents also found two binding constants; one binding constant was found to be as a result of intercalation, while the other was found to via a non-intercalative mode, presumably via the DNA minor groove.[36] Assuming that the two binding modes found for the cyclic substituents here are similar (given the similarities between the two sets of compounds), the two binding modes found here for the cyclic derivatives are presumed to also be via intercalation (lower binding constant , K2) and minor groove binding (higher binding constant, K1). In which case, **NDI-4** with its larger more bulky substituent may find difficulty in sliding itself through adjacent base pairs. This is of course a requirement for intercalation. Furthermore, given that these compounds possess two substituents on either side of the main intercalating moiety (i.e., threading), one substituent must "thread" through DNA base pairs if it is to adopt an intercalating geometry. Since both binding constant decrease for the *N*-methyl piperidine derivative, the second binding mode (i.e., presumed to be via the minor groove) is also affected sterically.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 141

**6. NDI binding mode determination via AT vs GC preference of the** 

implying a greater involvement of minor groove binding for **NDI-4**.

Calorimetric studies were carried out to evaluate preferences for AT vs GC-rich sequences, in an effort to detect a possible minor groove binding mode, implied by the above result (**Figure 10**). In general, the cyclic NDI derivatives possessing the ethylamino linker (**NDI-3** and **NDI-4**) exhibited a roughly two-fold preference (2.0x for **NDI-3**, 2.4x for **NDI-4**) for the AT-rich sequence relative to the GC-rich sequence (**Table 1**). The difference in affinity for the AT- vs GC-rich sequence is similar to at least one of the acyclic substituent NDI compounds (a dipropylmethyl ethylamino side chain) reported in an earlier study (see section on the acyclic derivatives below), and which was suggested to have a second minor groove binding mode.[36] We therefore suggest here that the cyclic NDI derivatives **NDI-3** and **NDI-4** does have a minor groove binding mode. It is interesting to note that **NDI-4** showed a slightly greater preference for the AT-rich DNA sequence compared to **NDI-3**,

The cyclic derivative with the propylamino linker (**NDI-5**) exhibited even less of a preference (~1.4x). However, the difference between the **NDI-5** binding constant for AT vs GCrich sequences could be considered as the same within experimental error. This result may imply that there is a greater contribution from non-intercalative binding from the cyclic ethylamino derivatives relative to the propylamino derivatives. This result is somewhat similar to what was observed in the series of acyclic substituent NDI derivatives. However, given the small differences in AT vs GC-sequences, this would warrant additional studies to confirm.

**Figure 10.** Calorimetric data for the titration of 60 µM **NDI-5** (left), **NDI-3** (middle) and **NDI-4** (right) into 15 µM of AT-rich DNA (top), GC-DNA (bottom) at 30 C. Binding isotherms (heat change vs drug/DNA molar ratio) were obtained from the integration of raw data and fitted to a "one-site" model.

**cyclic NDI derivatives** 

According to the calorimetrically determined binding constants, the linker length did not appear to have significant role for these cyclic side chain containing derivatives since **NDI-5** (ethylamino/ethyl linker) and **NDI-3** (propylamino/propyl linker) both had very similar binding constants for both the higher and lower binding sites (K1 = 1.08 x 108 M-1, K2 =5.1±0.72 x 106 M-1 and K1 = 1.17± 0.3 x 108 M-1, K2=5.6±0.65 x 106 M-1, respectively). It therefore appears that the size of the cyclic substituent plays a greater role than the substituent linker in determining the DNA binding affinity.

**Figure 9.** Calorimetric data for the titration of 60 µM **NDI-4** (left), **NDI-3** (middle) and **NDI-5** (right) into 12.5 µM of ctDNA at 30 C. Binding isotherms (heat change vs drug/DNA molar ratio) were obtained from the integration of raw data and fitted to a "two-site" model.

### **6. NDI binding mode determination via AT vs GC preference of the cyclic NDI derivatives**

Applications of Calorimetry in a Wide Context –

140 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

(i.e., presumed to be via the minor groove) is also affected sterically.

substituent linker in determining the DNA binding affinity.

the two compounds that differed only in ring size (*N*-methyl pyrrolidine vs *N*-methyl piperidine) showed that **NDI-3** (*N*-methyl pyrrolidine substituent) exhibited larger binding constants (K1 = 1.17± 0.3 x 108 M-1, K2 = 5.6±0.65 x 106 M-1) as compared to larger **NDI-4** (K1=1.70 ±0.4 x 107 M-1 and K2=3.26 ±0.54 x 106 M-1) when binding to ctDNA. Thus both binding constants were lower for the larger *N*-methyl piperidine derivative. Given that **NDI-4** possesses a more bulky *N*-methyl piperidyl substituent suggest that steric hindrance may play a role here. Studies on a series of NDI containing acyclic substituents also found two binding constants; one binding constant was found to be as a result of intercalation, while the other was found to via a non-intercalative mode, presumably via the DNA minor groove.[36] Assuming that the two binding modes found for the cyclic substituents here are similar (given the similarities between the two sets of compounds), the two binding modes found here for the cyclic derivatives are presumed to also be via intercalation (lower binding constant , K2) and minor groove binding (higher binding constant, K1). In which case, **NDI-4** with its larger more bulky substituent may find difficulty in sliding itself through adjacent base pairs. This is of course a requirement for intercalation. Furthermore, given that these compounds possess two substituents on either side of the main intercalating moiety (i.e., threading), one substituent must "thread" through DNA base pairs if it is to adopt an intercalating geometry. Since both binding constant decrease for the *N*-methyl piperidine derivative, the second binding mode

According to the calorimetrically determined binding constants, the linker length did not appear to have significant role for these cyclic side chain containing derivatives since **NDI-5** (ethylamino/ethyl linker) and **NDI-3** (propylamino/propyl linker) both had very similar binding constants for both the higher and lower binding sites (K1 = 1.08 x 108 M-1, K2 =5.1±0.72 x 106 M-1 and K1 = 1.17± 0.3 x 108 M-1, K2=5.6±0.65 x 106 M-1, respectively). It therefore appears that the size of the cyclic substituent plays a greater role than the

**Figure 9.** Calorimetric data for the titration of 60 µM **NDI-4** (left), **NDI-3** (middle) and **NDI-5** (right) into 12.5 µM of ctDNA at 30 C. Binding isotherms (heat change vs drug/DNA molar ratio) were

obtained from the integration of raw data and fitted to a "two-site" model.

Calorimetric studies were carried out to evaluate preferences for AT vs GC-rich sequences, in an effort to detect a possible minor groove binding mode, implied by the above result (**Figure 10**). In general, the cyclic NDI derivatives possessing the ethylamino linker (**NDI-3** and **NDI-4**) exhibited a roughly two-fold preference (2.0x for **NDI-3**, 2.4x for **NDI-4**) for the AT-rich sequence relative to the GC-rich sequence (**Table 1**). The difference in affinity for the AT- vs GC-rich sequence is similar to at least one of the acyclic substituent NDI compounds (a dipropylmethyl ethylamino side chain) reported in an earlier study (see section on the acyclic derivatives below), and which was suggested to have a second minor groove binding mode.[36] We therefore suggest here that the cyclic NDI derivatives **NDI-3** and **NDI-4** does have a minor groove binding mode. It is interesting to note that **NDI-4** showed a slightly greater preference for the AT-rich DNA sequence compared to **NDI-3**, implying a greater involvement of minor groove binding for **NDI-4**.

The cyclic derivative with the propylamino linker (**NDI-5**) exhibited even less of a preference (~1.4x). However, the difference between the **NDI-5** binding constant for AT vs GCrich sequences could be considered as the same within experimental error. This result may imply that there is a greater contribution from non-intercalative binding from the cyclic ethylamino derivatives relative to the propylamino derivatives. This result is somewhat similar to what was observed in the series of acyclic substituent NDI derivatives. However, given the small differences in AT vs GC-sequences, this would warrant additional studies to confirm.

**Figure 10.** Calorimetric data for the titration of 60 µM **NDI-5** (left), **NDI-3** (middle) and **NDI-4** (right) into 15 µM of AT-rich DNA (top), GC-DNA (bottom) at 30 C. Binding isotherms (heat change vs drug/DNA molar ratio) were obtained from the integration of raw data and fitted to a "one-site" model.

142 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

### **7. DNA binding mode determination using ITC-independent approaches**

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 143

binding modes have already been established (e.g., distamycin A and berenil). As expected, none of the compounds known to be minor groove binders were able to cause appreciable displacement of EtBr from its intercalative sites, consistent with these compounds binding to non-intercalative sites (**Table 1**). However, the intercalating molecules were able to displace ethidium bromide effectively, as was evident by the significant decrease in EtBr-DNA

**Figure 11.** Topo I assay of of the classical DNA intercalator **EtBr** (left) and the known minor groove binder **berenil** (right) using 5 units of the topoisomerase enzyme. From left of each gel, lanes 1 contain only DNA (no compound nor topoisomerase) and serve as controls. Lanes 2 contain DNA and topoisomerase, but no compound. Remaining lanes contain DNA, topoisomerase and increasing

**8. Binding mode determination of cyclic NDI derivatives via ITC-**

associated with the propylamino linker will be addressed later.

When topo assays were done on the NDI derivatives containing the cyclic amino side chains (**NDI-5**, **NDI-3**, and **NDI-4**), each compound was able to cause re-supercoiling, indicating that intercalation is indeed involved in the binding of each compound to DNA. This was not surprising since NDI compounds are known to bind to DNA via intercalation.[17-19] However, **NDI-3** was better able to elicit re-supercoiling than **NDI-5**, which was in turn better than **NDI-4**. That is, while **NDI-3** was able to cause complete re-supercoiling of our plasmid DNA at ~6 µM, **NDI-4** requires >10 µM for complete re-supercoiling (**Table 1**). This suggests that the binding of **NDI-3** involves more of an intercalative mode than either **NDI-5** or **NDI-4** and is consistent with what was observed in the ITC studies for these compounds described above. That is, the strength of the lower binding constants (K2) was in the order **NDI-3**>**NDI-5**>**NDI-4**. The lower binding constant (K2 in this report), has been found to be that of the intercalative binding mode for a similar series of NDI.[36] It appears that the bulkier *N*-methyl piperidine is either sterically hindering intercalation, or forcing **NDI-4** into a more non-intercalative binding mode, while **NDI-5**, with its propylamino linker, exhibits lower affinity for the DNA as compared to **NDI-4**. The lower binding affinity

The behavior of the cyclic substituent NDI compounds in the ITC studies and topo assays were also consistent with our EtBr displacement studies which showed that **NDI-3** was better able to displace EtBr from its intercalative sites; thus **NDI-3** caused a greater decrease in EtBr fluorescence compared to **NDI-4** (**Table 1**). Our EtBr displacement assays also showed that **NDI-5** was able to displace EtBr to the same extent as **NDI-3**, suggesting that both have a similar intercalative strengths. Again, this is consistent with what we observed

complex fluorescence.

concentrations of compound (taken from [42]).

**independent approaches** 

Two additional approaches were also utilized to determine the binding mode involved for the compounds in this study. These were a topoisomerase I DNA unwinding assays (topo assay) and ethidium bromide (EtBr) displacement studies. A brief description of the two techniques is in order. Briefly, the topo assay exploits the ability of topoisomerase I enzyme to relax supercoiled DNA, such as the plasmid pUC19 used in all our studies.[39,40] Under the conditions of our topo assay, supercoiled plasmid pUC19 DNA is first relaxed by using excess topoisomerase I enzyme and then is exposed to the compound under study. After extraction of the compound and enzyme, a compound that was bound via intercalation will cause re-supercoiling of the plasmid DNA. Re-supercoiling is due to the change in DNA linking number that accompanies relaxation by the topoisomerase enzyme and occurs to the extent to which the intercalator molecule was initially bound.[39,40] An intercalating molecule will perturb the DNA such that the DNA will unwind, causing the topoisomerase enzyme (which is present in excess) to relax the DNA, thus changing the linking number. The extent to which DNA unwinding occurs will be dependent upon the extent to which DNA binding occurs, thus the minimum concentration needed to cause complete resupercoiling will be indicative of how much compound was initially bound and thus the relative binding affinity. Conversely, minor groove binders should not induce appreciable re-supercoiling due to negligible DNA unwinding upon binding, and negligible change in DNA linking number.

With the EtBr displacement assays, EtBr, a known intercalator is first bound to DNA, occupying its intercalative sites. The compound of interest is then added to determine whether it is able to displace EtBr from its intercalative sites. Displacement is monitored by a decrease in EtBr–DNA fluorescence.[28,36,41] It is well established that the fluorescence yield of EtBr is enhanced significantly when it binds to DNA. This occurs as EtBr occupies its intercalative sites between bases in the DNA molecule. However, in the presence of another intercalator, there is competition for a limited/defined number of intercalation sites. As the other intercalator molecules are added, they begin to displace EtBr from these intercalative site, increasing the amount of free (unbound) EtBr. This is usually observed as a decrease in EtBr-DNA fluorescence.

Both the topo assay and ETBr displacement assays has been used by our group, as well as other groups, to determine DNA binding mode of DNA binding compounds.[28,35,36,41,42] To validate the topo assay approach, we have run assays on several known DNA binding compounds. These include the classical DNA intercalator, EtBr, and known minor-groove binding compounds such as distamycin A, berenil. **Figure 11** shows representative topo assay for EtBr and berenil.[42] As is expected, the classical DNA intercalator, EtBr, was able to elicit significant re-supercoiling back to the levels of the control (lane 1), whereas, the known minor groove binding compound was unable to do so, even at the high concentrations. In fact, essentially no re-supercoiling was observed for berenil, confirming its known minor groove binding mode. Similarly, we have done validation studies of our EtBr displacement assay, by running studies on DNA binding compounds in which their binding modes have already been established (e.g., distamycin A and berenil). As expected, none of the compounds known to be minor groove binders were able to cause appreciable displacement of EtBr from its intercalative sites, consistent with these compounds binding to non-intercalative sites (**Table 1**). However, the intercalating molecules were able to displace ethidium bromide effectively, as was evident by the significant decrease in EtBr-DNA complex fluorescence.

Applications of Calorimetry in a Wide Context –

DNA linking number.

a decrease in EtBr-DNA fluorescence.

142 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**7. DNA binding mode determination using ITC-independent approaches** 

Two additional approaches were also utilized to determine the binding mode involved for the compounds in this study. These were a topoisomerase I DNA unwinding assays (topo assay) and ethidium bromide (EtBr) displacement studies. A brief description of the two techniques is in order. Briefly, the topo assay exploits the ability of topoisomerase I enzyme to relax supercoiled DNA, such as the plasmid pUC19 used in all our studies.[39,40] Under the conditions of our topo assay, supercoiled plasmid pUC19 DNA is first relaxed by using excess topoisomerase I enzyme and then is exposed to the compound under study. After extraction of the compound and enzyme, a compound that was bound via intercalation will cause re-supercoiling of the plasmid DNA. Re-supercoiling is due to the change in DNA linking number that accompanies relaxation by the topoisomerase enzyme and occurs to the extent to which the intercalator molecule was initially bound.[39,40] An intercalating molecule will perturb the DNA such that the DNA will unwind, causing the topoisomerase enzyme (which is present in excess) to relax the DNA, thus changing the linking number. The extent to which DNA unwinding occurs will be dependent upon the extent to which DNA binding occurs, thus the minimum concentration needed to cause complete resupercoiling will be indicative of how much compound was initially bound and thus the relative binding affinity. Conversely, minor groove binders should not induce appreciable re-supercoiling due to negligible DNA unwinding upon binding, and negligible change in

With the EtBr displacement assays, EtBr, a known intercalator is first bound to DNA, occupying its intercalative sites. The compound of interest is then added to determine whether it is able to displace EtBr from its intercalative sites. Displacement is monitored by a decrease in EtBr–DNA fluorescence.[28,36,41] It is well established that the fluorescence yield of EtBr is enhanced significantly when it binds to DNA. This occurs as EtBr occupies its intercalative sites between bases in the DNA molecule. However, in the presence of another intercalator, there is competition for a limited/defined number of intercalation sites. As the other intercalator molecules are added, they begin to displace EtBr from these intercalative site, increasing the amount of free (unbound) EtBr. This is usually observed as

Both the topo assay and ETBr displacement assays has been used by our group, as well as other groups, to determine DNA binding mode of DNA binding compounds.[28,35,36,41,42] To validate the topo assay approach, we have run assays on several known DNA binding compounds. These include the classical DNA intercalator, EtBr, and known minor-groove binding compounds such as distamycin A, berenil. **Figure 11** shows representative topo assay for EtBr and berenil.[42] As is expected, the classical DNA intercalator, EtBr, was able to elicit significant re-supercoiling back to the levels of the control (lane 1), whereas, the known minor groove binding compound was unable to do so, even at the high concentrations. In fact, essentially no re-supercoiling was observed for berenil, confirming its known minor groove binding mode. Similarly, we have done validation studies of our EtBr displacement assay, by running studies on DNA binding compounds in which their

**Figure 11.** Topo I assay of of the classical DNA intercalator **EtBr** (left) and the known minor groove binder **berenil** (right) using 5 units of the topoisomerase enzyme. From left of each gel, lanes 1 contain only DNA (no compound nor topoisomerase) and serve as controls. Lanes 2 contain DNA and topoisomerase, but no compound. Remaining lanes contain DNA, topoisomerase and increasing concentrations of compound (taken from [42]).

## **8. Binding mode determination of cyclic NDI derivatives via ITCindependent approaches**

When topo assays were done on the NDI derivatives containing the cyclic amino side chains (**NDI-5**, **NDI-3**, and **NDI-4**), each compound was able to cause re-supercoiling, indicating that intercalation is indeed involved in the binding of each compound to DNA. This was not surprising since NDI compounds are known to bind to DNA via intercalation.[17-19] However, **NDI-3** was better able to elicit re-supercoiling than **NDI-5**, which was in turn better than **NDI-4**. That is, while **NDI-3** was able to cause complete re-supercoiling of our plasmid DNA at ~6 µM, **NDI-4** requires >10 µM for complete re-supercoiling (**Table 1**). This suggests that the binding of **NDI-3** involves more of an intercalative mode than either **NDI-5** or **NDI-4** and is consistent with what was observed in the ITC studies for these compounds described above. That is, the strength of the lower binding constants (K2) was in the order **NDI-3**>**NDI-5**>**NDI-4**. The lower binding constant (K2 in this report), has been found to be that of the intercalative binding mode for a similar series of NDI.[36] It appears that the bulkier *N*-methyl piperidine is either sterically hindering intercalation, or forcing **NDI-4** into a more non-intercalative binding mode, while **NDI-5**, with its propylamino linker, exhibits lower affinity for the DNA as compared to **NDI-4**. The lower binding affinity associated with the propylamino linker will be addressed later.

The behavior of the cyclic substituent NDI compounds in the ITC studies and topo assays were also consistent with our EtBr displacement studies which showed that **NDI-3** was better able to displace EtBr from its intercalative sites; thus **NDI-3** caused a greater decrease in EtBr fluorescence compared to **NDI-4** (**Table 1**). Our EtBr displacement assays also showed that **NDI-5** was able to displace EtBr to the same extent as **NDI-3**, suggesting that both have a similar intercalative strengths. Again, this is consistent with what we observed

144 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry


in the ITC and topo assay studies described above. That is, **NDI-5** and **NDI-3** having very similar K2 (ITC), and both eliciting re-supercoiling of the plasmid DNA at roughly similar concentrations.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 145

**Figure 12.** Calorimetric data (raw) for the acyclic ethylamino derivatives binding to ctDNA. In each case, 70 µM of the NDI was titrated into ctDNA (12.5 µM) at 30 C. Data is shown for the trimethyl ethylamino derivative **NDI-1e** (top, left), diethylmethyl ethylamino derivative (top, right), dipropylmethyl ethylamino derivative (bottom, left), and the dibutylmethyl ethylamino derivative **NDI-2e** (bottom,right). Binding isotherm (heat change vs drug/DNA molar ratio) was obtained from the integration of raw data and fitted to either a "one-site" model (**NDI-1e**) and a "two-site" model (all

was indicated by a single-phased binding isotherm that was well-defined by a one-site binding model. Larger members of the ethylamino series (diethylmethyl-, dipropylmethyland dibutylmethyl-ethylamino substituents) adopted two binding modes; a lower affinity binding mode between 3-4 x 106 M-1 and an additional higher affinity binding mode of between 31 - 78 x 106 M-1.[36] This was indicated by a biphasic binding isotherm that was fitted well to a two-site model; one site associated with intercalation and the other associated with minor groove binding. If we compare the results found for the smallest compound in that study, with that of the smallest compound in another study done by us with a similar NDI series with propylamino linker instead,[42] we find that only a single type of binding mode and binding constant (**NDI-1e**, *K* = 15±3 x 106 M-1 and **NDI-1p**, K = 1.2

others). The plot for **NDI-1e** and **NDI-2e** were taken from [36].

*a* MES00 buffer, pH 6.25

*b* MES40 buffer, pH 6.25.

*c* Minimum concentration required for complete re-supercoiling.

*<sup>d</sup>* Decrease in EtBr fluorescence per µL of compound added.

Data for acyclic **NDI-#**e series are from reference [36].

Data for the acyclic **NDI-#**p series are from reference [42].

**Table 1.** Representative DNA binding affinity data for the compounds in this study.

### **9. Effect of the length/size of the substituent and linker length (Ethyl vs propyl)**

As was reported by us, data obtained from calorimetric measurements show that the length/size of the substituent plays a significant role in both the preferred binding mode and relative binding affinity of the compounds of these studies.[36] The compounds of this study showed tight binding to DNA with values of *K*b between 105 to 108 M-1, presumably dependent on their preferred mode of binding to DNA. Figure 12 shows the calorimetric data for the four acyclic NDI derivatives (with ethylamino side chain linkers) binding to ctDNA. In that report, we found only a single type of binding constant (binding mode) for the smallest compound in the series (containing a trimethyl-ethylamino side chain).[36] This

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 145

Applications of Calorimetry in a Wide Context –

*K*b (ctDNA) (106 M-1) (ITC)a

concentrations.

Compound

**NDI-2e** 78±23

**NDI-3** 117±30

**NDI-4** 17.0±4

**NDI-5** 104± 35

 Minimum concentration required for complete re-supercoiling. *<sup>d</sup>* Decrease in EtBr fluorescence per µL of compound added. Data for acyclic **NDI-#**e series are from reference [36]. Data for the acyclic **NDI-#**p series are from reference [42].

**Table 1.** Representative DNA binding affinity data for the compounds in this study.

**9. Effect of the length/size of the substituent and linker length (Ethyl vs** 

As was reported by us, data obtained from calorimetric measurements show that the length/size of the substituent plays a significant role in both the preferred binding mode and relative binding affinity of the compounds of these studies.[36] The compounds of this study showed tight binding to DNA with values of *K*b between 105 to 108 M-1, presumably dependent on their preferred mode of binding to DNA. Figure 12 shows the calorimetric data for the four acyclic NDI derivatives (with ethylamino side chain linkers) binding to ctDNA. In that report, we found only a single type of binding constant (binding mode) for the smallest compound in the series (containing a trimethyl-ethylamino side chain).[36] This

MES00 buffer, pH 6.25

MES40 buffer, pH 6.25.

*a*

*b*

*c*

**propyl)** 

144 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*K*b (AT) (106 M-1) (ITC)b

**distamycin A** --- 2.20 ± 0.4 --- --- 6 **Berenil** --- 1.76 ±0.3 --- --- 31 **EtBr** --- 0.18±0.05 0.34±0.08 2 -- **daunomycin** --- 2.9 ±0.6 3.24±0.6 --- --- **NDI-1e** 15±3 1.11±0.27 1.17±0.10 3.5 400

**NDI-1p** 1.22±0.16 10.1 ±0.7 --- 3 --- **NDI-2p** 0.57 ± 0.2 8.7 ±0.4 --- 5 ---

in the ITC and topo assay studies described above. That is, **NDI-5** and **NDI-3** having very similar K2 (ITC), and both eliciting re-supercoiling of the plasmid DNA at roughly similar

> *K*b (GC) (106 M1) (ITC)b

3.9±1.1 1.38±0.15 0.38±0.09 >6.7 358

5.66±0.65 0.5±0.09 0.25±0.05 6 949

3.26±0.54 0.39±0.08 0.16±0.04 >10 777

5.10±0.72 1.16±0.24 0.85±0.09 >6 1030

Topo assay (10-6 M)c

EtBr displacement Assay (F/µL)d

**Figure 12.** Calorimetric data (raw) for the acyclic ethylamino derivatives binding to ctDNA. In each case, 70 µM of the NDI was titrated into ctDNA (12.5 µM) at 30 C. Data is shown for the trimethyl ethylamino derivative **NDI-1e** (top, left), diethylmethyl ethylamino derivative (top, right), dipropylmethyl ethylamino derivative (bottom, left), and the dibutylmethyl ethylamino derivative **NDI-2e** (bottom,right). Binding isotherm (heat change vs drug/DNA molar ratio) was obtained from the integration of raw data and fitted to either a "one-site" model (**NDI-1e**) and a "two-site" model (all others). The plot for **NDI-1e** and **NDI-2e** were taken from [36].

was indicated by a single-phased binding isotherm that was well-defined by a one-site binding model. Larger members of the ethylamino series (diethylmethyl-, dipropylmethyland dibutylmethyl-ethylamino substituents) adopted two binding modes; a lower affinity binding mode between 3-4 x 106 M-1 and an additional higher affinity binding mode of between 31 - 78 x 106 M-1.[36] This was indicated by a biphasic binding isotherm that was fitted well to a two-site model; one site associated with intercalation and the other associated with minor groove binding. If we compare the results found for the smallest compound in that study, with that of the smallest compound in another study done by us with a similar NDI series with propylamino linker instead,[42] we find that only a single type of binding mode and binding constant (**NDI-1e**, *K* = 15±3 x 106 M-1 and **NDI-1p**, K = 1.2

146 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

±0.16 x 106 M-1) is found for the smallest member of the series whether the side chain is ethylamino or the one-carbon longer, propylamino substituent.[36,42] However, whereas larger members in the acyclic ethylamino series exhibited a dual binding mode, neither compound in the acyclic propylamino series (referred to as **NDI-1p** or **NDI-2p** in this chapter) was found to exhibit more than one binding mode. Additionally, in the ethylamino series, we observe that the relative binding affinity trend for the ethylamino series increased with substituent size. However, this feature was not observed in the propylamino series (one carbon longer on both sides of the main intercalating moiety), since **NDI-2p** with its dibutylmethyl-propylamino substituent exhibited a lower binding constant (0.57±0.17 x 106 M-1) compared to smaller homolog (**NDI-1p**) which had a binding constant of (1.2±0.16 x 106 M-1), a binding mode attributed to intercalative binding*.*[42] It is also clear that DNA binding affinity was in general greater for the ethylamino derivative, although some of this difference may be attributed to slightly different experimental conditions used in the two studies. It therefore implies that this small structural difference may (1) enable an additional mode of binding, i.e., a linker length that is one carbon shorter resulted in an additional binding mode, as well as (2), enhance the DNA binding mode by greater than an order of magnitude. An explanation for this could be that steric effects may dominate for the propylamino series, resulting in lower DNA binding, especially for the larger members, while hydrophobic and binding mode preferences may be dominant in the ethyl-amino series. The propyl amino derivatives are of course longer especially since the additional carbon linker is on both sides of the molecule, given that these are threading compounds. The longer (more dangling) molecular structure may make it more difficult to thread through adjacent base pairs. However, in the case of the ethylamino series, the solution for the larger substituents appear to be adoption of an additional DNA binding mode. Hydrophobic contributions may also play a role.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 147

capabilities that are less than expected based on their significantly higher binding affinities. Since the ability to elicit re-supercoiling is primarily based on an intercalative ability, this argues for a greater involvement of non-intercalative binding for ethylamino derivatives

In an effort to further corroborate our DNA binding characterization approach used for the NDI derivatives discussed above using a different/independent homologous series, we will also briefly describe DNA binding studies of a homologous series of chalcogenoxanthylium derivatives to DNA, reported by our group.[35] The chalgenoxanthylium derivatives in this study were synthesized by Detty and coworkers and have been implicated as potential

Using this independent system as a comparison, we have also found that the results obtained from ITC were consistent with that found using topo assay and EtBr displacement studies. These studies have found that the nature of the substituent attached to the main xanthylium core plays a directing role in the preferred binding mode and accompanying DNA binding affinity.[35] While some of the compounds bind to DNA either through intercalation or via the minor groove, some exhibited mixed-binding modes.[35] Excerpts from the DNA binding studies for selected chalcogenoxanthylium derivatives (**Figure 13**)

In that report, ITC studies suggested that both the 9-substituent and the identity of the chalcogen play a role in the preferred binding mode and ultimately, the relative DNA binding constant.[35] With a 9-2 thienyl substituent attached to the main xanthylium core (e.g., 2-Se), there appeared to be a preference for intercalation. This was implied from the fact that compounds containing the 9-2 thienyl substituent showed no preference for the ATrich sequence, a feature that would be typical for a minor-groove binder. The 9-2 thienyl also bound to calf thymus DNA with lower affinity as compared to the 9-phenyl derivatives (e.g.,1-Se).[35] DNA intercalators are known to have lower DNA binding affinity as compared to minor-groove binders,[2] so this result may be due to a greater contribution from minor groove binding (i.e., less contribution from intercalation) with the 9-phenyl series. In addition to exhibiting a 2-3 higher binding constant compared to the corresponding 9-2 thienyl derivative, the 9-phenyl series exhibited a slight preference (2-3 times) for binding to [poly(dAdT)]2 as compared to the [poly(dGdC)]2. Here again, a possible minor groove binding was implied, since it is known that compounds that bind solely to the DNA minor groove generally show a preference for binding to AT-rich sequences relative to GC-rich sequences due to the occlusion from the GC-rich minor groove by the protruded 2-NH2 group of guanine.[6] As mentioned for the NDI series discussed earlier, it is expected that compounds that bind both via the DNA minor groove and by intercalation (i.e., mixed binding modes) will show a factor of <10 preference for AT-rich sequences, depending on the relative contribution from intercalation (i.e., the difference will

**11. Binding of the chalcogenoxanthylium derivatives to DNA** 

candidates for therapy against blood-borne pathogens.[27,31-33,35].

relative to their propylamino counterparts.

will now be discussed.

### **10. Comparison of binding mode for NDI derivative with ethyl vs propyl linker using topo assay**

Comparing the two series with different linker-length (i.e., ethylamino vs propylamino derivatives), it is also interesting to note that generally higher concentrations of the ethylamino derivatives were required for re-supercoiling, despite having higher binding constants as determined by ITC.[36,42] A striking example of this is seen from the fact that more than 6.5 uM of **NDI-2e** (K1= 78±23 x 106 M-1 and K2=3.9±1.1 x 106 M-1) was required for supercoiling, while the corresponding propylamino derivative **NDI-2p** with a significantly lower binding affinity (K = 0.57±0.17 x 106 M-1) required only 5 uM. Again, some of this may also be attributed to different experimental conditions. For example, a greater excess of the topoisomerase enzyme was used in the assays for the ethylamino series. However, this factor alone cannot account for the lack of associated re-supercoiling ability given the disproportionately higher DNA binding constants for the ethylamino derivatives. Overall, a side by side comparison of the topo assay results for the two series (ethylamino vs propylamino) suggests that the ethylamino derivatives displays relative re-supercoiling capabilities that are less than expected based on their significantly higher binding affinities. Since the ability to elicit re-supercoiling is primarily based on an intercalative ability, this argues for a greater involvement of non-intercalative binding for ethylamino derivatives relative to their propylamino counterparts.

### **11. Binding of the chalcogenoxanthylium derivatives to DNA**

Applications of Calorimetry in a Wide Context –

also play a role.

**linker using topo assay** 

146 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

±0.16 x 106 M-1) is found for the smallest member of the series whether the side chain is ethylamino or the one-carbon longer, propylamino substituent.[36,42] However, whereas larger members in the acyclic ethylamino series exhibited a dual binding mode, neither compound in the acyclic propylamino series (referred to as **NDI-1p** or **NDI-2p** in this chapter) was found to exhibit more than one binding mode. Additionally, in the ethylamino series, we observe that the relative binding affinity trend for the ethylamino series increased with substituent size. However, this feature was not observed in the propylamino series (one carbon longer on both sides of the main intercalating moiety), since **NDI-2p** with its dibutylmethyl-propylamino substituent exhibited a lower binding constant (0.57±0.17 x 106 M-1) compared to smaller homolog (**NDI-1p**) which had a binding constant of (1.2±0.16 x 106 M-1), a binding mode attributed to intercalative binding*.*[42] It is also clear that DNA binding affinity was in general greater for the ethylamino derivative, although some of this difference may be attributed to slightly different experimental conditions used in the two studies. It therefore implies that this small structural difference may (1) enable an additional mode of binding, i.e., a linker length that is one carbon shorter resulted in an additional binding mode, as well as (2), enhance the DNA binding mode by greater than an order of magnitude. An explanation for this could be that steric effects may dominate for the propylamino series, resulting in lower DNA binding, especially for the larger members, while hydrophobic and binding mode preferences may be dominant in the ethyl-amino series. The propyl amino derivatives are of course longer especially since the additional carbon linker is on both sides of the molecule, given that these are threading compounds. The longer (more dangling) molecular structure may make it more difficult to thread through adjacent base pairs. However, in the case of the ethylamino series, the solution for the larger substituents appear to be adoption of an additional DNA binding mode. Hydrophobic contributions may

**10. Comparison of binding mode for NDI derivative with ethyl vs propyl** 

Comparing the two series with different linker-length (i.e., ethylamino vs propylamino derivatives), it is also interesting to note that generally higher concentrations of the ethylamino derivatives were required for re-supercoiling, despite having higher binding constants as determined by ITC.[36,42] A striking example of this is seen from the fact that more than 6.5 uM of **NDI-2e** (K1= 78±23 x 106 M-1 and K2=3.9±1.1 x 106 M-1) was required for supercoiling, while the corresponding propylamino derivative **NDI-2p** with a significantly lower binding affinity (K = 0.57±0.17 x 106 M-1) required only 5 uM. Again, some of this may also be attributed to different experimental conditions. For example, a greater excess of the topoisomerase enzyme was used in the assays for the ethylamino series. However, this factor alone cannot account for the lack of associated re-supercoiling ability given the disproportionately higher DNA binding constants for the ethylamino derivatives. Overall, a side by side comparison of the topo assay results for the two series (ethylamino vs propylamino) suggests that the ethylamino derivatives displays relative re-supercoiling In an effort to further corroborate our DNA binding characterization approach used for the NDI derivatives discussed above using a different/independent homologous series, we will also briefly describe DNA binding studies of a homologous series of chalcogenoxanthylium derivatives to DNA, reported by our group.[35] The chalgenoxanthylium derivatives in this study were synthesized by Detty and coworkers and have been implicated as potential candidates for therapy against blood-borne pathogens.[27,31-33,35].

Using this independent system as a comparison, we have also found that the results obtained from ITC were consistent with that found using topo assay and EtBr displacement studies. These studies have found that the nature of the substituent attached to the main xanthylium core plays a directing role in the preferred binding mode and accompanying DNA binding affinity.[35] While some of the compounds bind to DNA either through intercalation or via the minor groove, some exhibited mixed-binding modes.[35] Excerpts from the DNA binding studies for selected chalcogenoxanthylium derivatives (**Figure 13**) will now be discussed.

In that report, ITC studies suggested that both the 9-substituent and the identity of the chalcogen play a role in the preferred binding mode and ultimately, the relative DNA binding constant.[35] With a 9-2 thienyl substituent attached to the main xanthylium core (e.g., 2-Se), there appeared to be a preference for intercalation. This was implied from the fact that compounds containing the 9-2 thienyl substituent showed no preference for the ATrich sequence, a feature that would be typical for a minor-groove binder. The 9-2 thienyl also bound to calf thymus DNA with lower affinity as compared to the 9-phenyl derivatives (e.g.,1-Se).[35] DNA intercalators are known to have lower DNA binding affinity as compared to minor-groove binders,[2] so this result may be due to a greater contribution from minor groove binding (i.e., less contribution from intercalation) with the 9-phenyl series. In addition to exhibiting a 2-3 higher binding constant compared to the corresponding 9-2 thienyl derivative, the 9-phenyl series exhibited a slight preference (2-3 times) for binding to [poly(dAdT)]2 as compared to the [poly(dGdC)]2. Here again, a possible minor groove binding was implied, since it is known that compounds that bind solely to the DNA minor groove generally show a preference for binding to AT-rich sequences relative to GC-rich sequences due to the occlusion from the GC-rich minor groove by the protruded 2-NH2 group of guanine.[6] As mentioned for the NDI series discussed earlier, it is expected that compounds that bind both via the DNA minor groove and by intercalation (i.e., mixed binding modes) will show a factor of <10 preference for AT-rich sequences, depending on the relative contribution from intercalation (i.e., the difference will be less as contributions from intercalation increases). The chalcogenoxanthylium derivative bearing a 9-(2-thienyl-5-diethylcarboxamide) substituent (compound 10) exhibited the strongest preference for the [poly(dAdT)]2 sequence. In fact, compound 10 showed essentially no binding to the [poly(dGdC)]2 sequence, while binding to [poly(dAdT)]2 with a K of 2.3 ±0.4 x 106 M-1.[35]

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 149

that compound **10** is not a strong intercalator, again consistent with the minor groove binding mode implied by both the ITC and topo assay. Given the higher binding constant found for **1-Se** relative to **2-Se** using ITC, if **1-Se** was primarily a DNA intercalator, it would exhibit a greater ability (compared to **2-Se**) to dislodge the classical DNA intercalator EtBr from its binding sites. The fact that it did not, strongly supports the idea that the binding of **1-Se** to DNA involves other binding modes. Also, the fact compound **10** showed little ability to dislodge ethidium bromide from DNA, while having the highest binding constant (as determined by ITC studies in an earlier study [35]), supports the idea of compound **10** involving significant non-intercalative DNA binding (presumably, via the minor-groove).

In this chapter, we have shown how ITC can be successfully used to characterize both the preferred DNA binding mode for series of compounds, as well as their relative DNA binding affinity. For this, we have selected two homologous series of compounds; series of symmetrical NDI threading intercalators in which the side chains are mandatorily involved in DNA binding, and a series of chalcogenoxanthilum derivatives. Both classes of

While the homologous NDI derivatives in this study all exhibit DNA intercalative abilities, the substituent on either side of the main intercalating core does play a significant role in determining whether or not additional modes are adopted. This occurs because these compounds require a threading geometry when intercalating between DNA base pairs, i.e., there is a necessity for the side chain to "thread" DNA. The side chains are therefore forced to direct DNA binding. We have found that the cyclic (non-aromatic) substituent at the distal end of a side chain play a significant role in both the DNA binding affinity and the preferred mode of binding. Larger ring sizes face steric barriers and have lower DNA binding affinity. The larger rings may however force additional (non-intercalative) binding modes to be involved. Additional studies may be needed to fully understand the full effects of ring size. Future studies may involve attachment of aromatic rings instead of nonaromatic rings in this study. Having flat aromatic rings on the substituent may enhance site recognition and DNA binding due to the ability to stack. We have also found that even a small modification in the linker length in NDI side chain play a significant role during binding of NDI derivatives of acyclic aliphatic side substituents to DNA. In fact, on comparing side chains with an ethyl linker vs those with a propyl linker, it was found that the ethyl linker could enhance DNA binding by more than an order of magnitude. Possession of the ethyl linker also enabled an additional DNA binding mode of higher affinity. The NDI scaffold therefore represent a versatile template for the design of many promising derivatives with enhanced DNA affinity and have implications in the rationale

design of DNA binding compounds with improved site recognition capabilities.

Using an independent system for comparison, the approach of using ITC to study binding to both ctDNA and AT vs GC-rich sequences, was shown to be an efficient and consistent approach in the determination of relative DNA binding affinity and preferred DNA binding

compounds have been shown to have biological activity.

**13. Conclusions** 

**Figure 13.** Structures of selected chalcogenoxanthylium derivatives reported in [35]. The 9-2 thienyl derivative (**2-Se,** left) shown bind mostly via intercalation, while **1-Se** derivative (middle) is a mixbinder, and compound **10** binds primarily via the DNA minor groove.

### **12. Binding mode determination of chalcogenoxanylium derivatives via ITC-independent approaches**

As was done for the NDI series discussed earlier, several independent (non-ITC) studies (ethidium bromide displacement and topo assay) were also carried out on the chalcogenoxanthylium derivatives in this study.[35] This was done in an effort to gain additional insights into the preferred DNA binding mode suggested by ITC.

Results from topo assays have been reported by us.[35] These results were in general consistent with the ITC studies on these compounds. We will now report new EtBr data on chalcogenoxanthylium derivatives discussed in this chapter that supports both ITC and topo assay studies.

Further evidence for the preferred DNA binding modes were also observed during ethidium bromide displacement assays on selected members of the chalcogenoxanthylium compounds binding to DNA. These were the seleno derivatives from the 9-2 thienyl series (**2-Se**), the 9-phenyl series (**1-Se**), and compound **10** (suggested to have primarily a nonintercalative binding from the ITC studies). While compound **2-Se** and **1-Se** were both able to cause dislodgement of ethidium bromide from DNA, **2-Se** was markedly better able to do so (decrease in fluorescence per µL of compound added was: **2-Se** = 711, **1-Se** = 581, compound **10** = 350. Considering that part of the change is fluorescence for the compounds was due to accompanying dilution during the titration, we see here that the order of intercalative ability is **2-Se**>**1-Se**>**10**. This order mirrors the results from both ITC and topo assay which showed that **2-Se** was a better intercalator than **1-Se**, which was in turn better than compound **10**. This implies that **2-Se** is a stronger intercalator than **1-Se**, consistent with both the ITC and topo assay studies. Compound **10** caused relatively small decreases in ethidium bromide fluorescent (less than any of the NDI derivatives in this study) indicating that it is not a potent displacer of ethidium bromide from its intercalative sites, suggesting that compound **10** is not a strong intercalator, again consistent with the minor groove binding mode implied by both the ITC and topo assay. Given the higher binding constant found for **1-Se** relative to **2-Se** using ITC, if **1-Se** was primarily a DNA intercalator, it would exhibit a greater ability (compared to **2-Se**) to dislodge the classical DNA intercalator EtBr from its binding sites. The fact that it did not, strongly supports the idea that the binding of **1-Se** to DNA involves other binding modes. Also, the fact compound **10** showed little ability to dislodge ethidium bromide from DNA, while having the highest binding constant (as determined by ITC studies in an earlier study [35]), supports the idea of compound **10** involving significant non-intercalative DNA binding (presumably, via the minor-groove).

### **13. Conclusions**

Applications of Calorimetry in a Wide Context –

**ITC-independent approaches** 

assay studies.

K of 2.3 ±0.4 x 106 M-1.[35]

148 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

binder, and compound **10** binds primarily via the DNA minor groove.

be less as contributions from intercalation increases). The chalcogenoxanthylium derivative bearing a 9-(2-thienyl-5-diethylcarboxamide) substituent (compound 10) exhibited the strongest preference for the [poly(dAdT)]2 sequence. In fact, compound 10 showed essentially no binding to the [poly(dGdC)]2 sequence, while binding to [poly(dAdT)]2 with a

**Figure 13.** Structures of selected chalcogenoxanthylium derivatives reported in [35]. The 9-2 thienyl derivative (**2-Se,** left) shown bind mostly via intercalation, while **1-Se** derivative (middle) is a mix-

**12. Binding mode determination of chalcogenoxanylium derivatives via** 

As was done for the NDI series discussed earlier, several independent (non-ITC) studies (ethidium bromide displacement and topo assay) were also carried out on the chalcogenoxanthylium derivatives in this study.[35] This was done in an effort to gain

Results from topo assays have been reported by us.[35] These results were in general consistent with the ITC studies on these compounds. We will now report new EtBr data on chalcogenoxanthylium derivatives discussed in this chapter that supports both ITC and topo

Further evidence for the preferred DNA binding modes were also observed during ethidium bromide displacement assays on selected members of the chalcogenoxanthylium compounds binding to DNA. These were the seleno derivatives from the 9-2 thienyl series (**2-Se**), the 9-phenyl series (**1-Se**), and compound **10** (suggested to have primarily a nonintercalative binding from the ITC studies). While compound **2-Se** and **1-Se** were both able to cause dislodgement of ethidium bromide from DNA, **2-Se** was markedly better able to do so (decrease in fluorescence per µL of compound added was: **2-Se** = 711, **1-Se** = 581, compound **10** = 350. Considering that part of the change is fluorescence for the compounds was due to accompanying dilution during the titration, we see here that the order of intercalative ability is **2-Se**>**1-Se**>**10**. This order mirrors the results from both ITC and topo assay which showed that **2-Se** was a better intercalator than **1-Se**, which was in turn better than compound **10**. This implies that **2-Se** is a stronger intercalator than **1-Se**, consistent with both the ITC and topo assay studies. Compound **10** caused relatively small decreases in ethidium bromide fluorescent (less than any of the NDI derivatives in this study) indicating that it is not a potent displacer of ethidium bromide from its intercalative sites, suggesting

additional insights into the preferred DNA binding mode suggested by ITC.

In this chapter, we have shown how ITC can be successfully used to characterize both the preferred DNA binding mode for series of compounds, as well as their relative DNA binding affinity. For this, we have selected two homologous series of compounds; series of symmetrical NDI threading intercalators in which the side chains are mandatorily involved in DNA binding, and a series of chalcogenoxanthilum derivatives. Both classes of compounds have been shown to have biological activity.

While the homologous NDI derivatives in this study all exhibit DNA intercalative abilities, the substituent on either side of the main intercalating core does play a significant role in determining whether or not additional modes are adopted. This occurs because these compounds require a threading geometry when intercalating between DNA base pairs, i.e., there is a necessity for the side chain to "thread" DNA. The side chains are therefore forced to direct DNA binding. We have found that the cyclic (non-aromatic) substituent at the distal end of a side chain play a significant role in both the DNA binding affinity and the preferred mode of binding. Larger ring sizes face steric barriers and have lower DNA binding affinity. The larger rings may however force additional (non-intercalative) binding modes to be involved. Additional studies may be needed to fully understand the full effects of ring size. Future studies may involve attachment of aromatic rings instead of nonaromatic rings in this study. Having flat aromatic rings on the substituent may enhance site recognition and DNA binding due to the ability to stack. We have also found that even a small modification in the linker length in NDI side chain play a significant role during binding of NDI derivatives of acyclic aliphatic side substituents to DNA. In fact, on comparing side chains with an ethyl linker vs those with a propyl linker, it was found that the ethyl linker could enhance DNA binding by more than an order of magnitude. Possession of the ethyl linker also enabled an additional DNA binding mode of higher affinity. The NDI scaffold therefore represent a versatile template for the design of many promising derivatives with enhanced DNA affinity and have implications in the rationale design of DNA binding compounds with improved site recognition capabilities.

Using an independent system for comparison, the approach of using ITC to study binding to both ctDNA and AT vs GC-rich sequences, was shown to be an efficient and consistent approach in the determination of relative DNA binding affinity and preferred DNA binding

Applications of Calorimetry in a Wide Context – 150 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

mode. The ITC studies were well corroborated by ITC-independent studies such as topo assays and EtBr displacement studies, thus exhibiting the efficacy of our approach.

Insights into the Relative DNA Binding Affinity and Preferred Binding Mode of Homologous Compounds Using Isothermal Titration Calorimetry (ITC) 151

[12] Hampel SM, Sidibe A, Gunaratnam M, Riou JF, Neidle S (2010) Tetrasubstituted Naphthalene Diimide Ligands with Selectivity for Telomeric G-Quadruplexes and

[13] Sato S, Hirano A, Takenaka S (2010) Selective Immobilization of Double Stranded DNA on a Gold Surface Through Threading Intercalation of a Naphthalene Diimide having

[14] Lee J, Guelev V, Sorey S, Hoffman DW, Iverson BL (2004) NMR Structural Analysis of a Modular Threading Tetraintercalator Bound to DNA. J Am Chem Soc. 126:14036-14042. [15] Gianolio DA, Segismundo JM, McLaughlin LW (2000) Tethered Napthalene-based

[16] Liu ZR, Hecker KH, Rill RL (1996) Selective DNA Binding of (N-alkylamine)- Substituted Naphthalene Imides and Diimides to G+C-rich DNA. J Biomol Struct

[17] Tanious FA, Yen SF, Wilson WD (1991) Kinetic and Equilibrium Analysis of a Threading Intercalation Mode: DNA Sequence and Ion Effects. Biochemistry 30:1813-

[18] Wilson, W. D. DNA Intercalators. In DNA and Aspects of Molecular Biology; Kool, E.

[19] Yen S, Gabbay E, Wilson WD (1982) Interaction of Aromatic Imides with Deoxyribonucleic Acid. Spectrophotometric and Viscometric Studies Biochemistry,

[20] Sato S, Kondo H, Takenaka, S, (2006) Linker Chain Effect of Ferrocenylnaphthalene Diimide Derivatives on a Tetraplex DNA Binding. Nucleic Acid Symposium Series

[21] Rusling D, Peng G, Srinivasan N, Fox K, Brown T, (2009) DNA Triplex Formation with

[22] Cuenca F, Greciano O, Gunaratnam M, Haider S, Munnur D, Nanjunda R, Wilson W, Neidle S (2008) Tri- and tetra-substituted Naphthalene Diimides as Potent G-

[23] Laronze-Cochard M, Kim Y-M, Brassart B, Riou J-F, Laronze J-Y, Sapi J (2009) Synthesis and Biological Evaluation of Novel 4,5-Bis(dialkylaminoalkyl)-Substituted Acridines as

[25] Luedtke, N, (2009) Targeting G-Quadruplexes with Small Molecules. Chimia 63: 134-

[26] Steullet V, Dixon, DW (1999) Self-Stacking of Naphthalene bis(dicarboximide) Probed

[27] Wagner, S, Skripchenko, A, Donnelly, D, Ramaswamy, K, Detty, M. (2005), Bioorg.

[28] McKnight, RE, Ye M, Ohulchanskyy, TY, Sahabi S, Wetzel, BR, Wagner, SJ, Skripchenko A, Detty MR (2007) Synthesis of Analogues of a Flexible Thiopyrylium Photosensitizer

Potent Telomeric G-Quadruplex Ligands, Eur. J. of Med. Chem. 44:3880–3888. [24] Gonzalez, V, Hurley, L (2010) The c-Myc NHE III: Function and Regulation, Annu. Rev.

5-Dimethylaminopropargyl Deoxyuridine. Nucleic Acid Res 87:1288-1296.

Quadruplex Ligands. Bioorg. Med. Chem. Lett.18:1668–1673.

Intercalators for Triplex Stabilization. Nucleic Acids Res. 28: 2128-2134.

Cancer Cells. Bioorg. Med. Chem. Lett. 20:6459-6463.

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139.

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by NMR. Perkin Trans. 2*:*1547-1558.

Med. Chem. 13:5927-5935.

1819.

### **Author details**

Ruel E. McKnight

*Department of Chemistry, State University of New York at Geneseo, 1 College Circle, Geneseo, NY, USA* 

### **Acknowledgement**

The author is very grateful to Professors Dabney Dixon and Michael Detty for providing the naphthalene diimide and chalcogenoxanthylium compounds, respectively, for this study. I would also like to acknowledge the very diligent students who have contributed to this work over the years (Douglas Jackson, Luke Marr, Kevin Siegenthaler, Eric Reisenauer, Sadia Sahabi, Shivani Polasani, Bilgehan Onogol, Manuel Pintado, Aaron Gleason, and James Keyes).

### **14. References**


[12] Hampel SM, Sidibe A, Gunaratnam M, Riou JF, Neidle S (2010) Tetrasubstituted Naphthalene Diimide Ligands with Selectivity for Telomeric G-Quadruplexes and Cancer Cells. Bioorg. Med. Chem. Lett. 20:6459-6463.

Applications of Calorimetry in a Wide Context –

**Author details** 

Ruel E. McKnight

James Keyes).

3709.

403:1-15.

Chem. 9: 1655-1665.

Ligands. Biochemistry 38:16067-16075.

Sequence Specific Agents. 2:141-167.

Annu. Rev. Pharmacol. Toxicol. 34, 191-218.

DNA Intercalation. Methods Enzymol. 323: 373-405.

**14. References** 

**Acknowledgement** 

*USA* 

150 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

mode. The ITC studies were well corroborated by ITC-independent studies such as topo

*Department of Chemistry, State University of New York at Geneseo, 1 College Circle, Geneseo, NY,* 

The author is very grateful to Professors Dabney Dixon and Michael Detty for providing the naphthalene diimide and chalcogenoxanthylium compounds, respectively, for this study. I would also like to acknowledge the very diligent students who have contributed to this work over the years (Douglas Jackson, Luke Marr, Kevin Siegenthaler, Eric Reisenauer, Sadia Sahabi, Shivani Polasani, Bilgehan Onogol, Manuel Pintado, Aaron Gleason, and

[1] Bailly C, Colson P, Hénichart J-P, Houssier C (1993) The different binding modes of Hoechst 33258 to DNA studied by electric linear dichroism. Nucleic Acids Res*.* 21:3705-

[4] Barcelo, F.; Capo, D.; Portugal, J. (2002) Thermodynamic characterization of the multivalent binding of chartreusin to DNA. Nucleic Acids Res. 30:4567-4573. [5] Tse WC, Boger DL (2004) A Fluorescent Intercalator Displacement Assay for Establishing DNA Binding Selectivity and Affinity. Acc. Chem. Res. 37:61-69. [6] Ren J, Chaires JB (1999) Sequence and Structural Selectivity of Nucleic Acid Binding

[7] Denny WA (2002) Acridine Derivatives as Chemotherapeutic Agents. Curr. Med.

[8] Chaires, JB (1996) Molecular Recognition of DNA by Daunomycin Advances in DNA

[9] Chen AY, Liu LF (1994) DNA Topoisomerases: Essential Enzymes and Lethal Targets.

[10] Pilch DS, Kirolos MA, Liu X, Plum GE, Breslauer KJ (1995) Berenil [1,3-bis(4' amidinophenyl)triazene] Binding to DNA Duplexes and to a RNA Duplex: Evidence for Both Intercalative and Minor Groove Binding Properties. Biochemistry 34:9962-9976. [11] Haq I, Jenkins T, Chowdhry B, Ren J, Chaires JB (2000) Parsing Free Energies of Drug-

[2] Chaires, JB (1997) Energetics of Drug-DNA Interactions. Biopolymers 44: 201-215. [3] Haq I (2002) Thermodynamics of Drug-DNA Interactions. Arch*.* Biochem. Biophys.

assays and EtBr displacement studies, thus exhibiting the efficacy of our approach.


152 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

for Purging Blood-Borne Pathogens and Binding Mode and Affinity Studies of their Complexes with DNA. Bioorg. Med. Chem. 15:4406-4418.

**Chapter 7** 

© 2013 Taneva et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Thermodynamic Signatures of** 

Stefka G. Taneva, Sonia Bañuelos and María A. Urbaneja

Additional information is available at the end of the chapter

known NPM3 and an invertebrate NPM-like.

**a Nuclear Chaperone** 

http://dx.doi.org/10.5772/54062

**1. Introduction** 

**Macromolecular Complexes ‒ Insights on the** 

**Stability and Interactions of Nucleoplasmin,** 

Nucleoplasmin (NP) is a nuclear chaperone that mediates chromatin remodeling processes, such as sperm decondensation at fertilization [1]. In *Xenopus laevis* eggs, where it was first isolated, this highly acidic protein is thought to be in charge of nucleosomal core histones H2A/H2B storage. Upon fertilization, NP decondenses the densely packed sperm chromatin by means of extracting its specific basic proteins and replacing them with H2A/H2B, therefore enabling the assembly of somatic-type nucleosomes. NP is additionally involved in chromatin remodeling during early development, in particular it is required in the replication licensing mechanism, probably to extract linker-type histones from somatic chromatin, and can facilitate pluripotent cell reprogramming. NP (also designated NPM2) belongs to the nucleophosmin/nucleoplasmin family of histone chaperones [2]. Whereas NP roles have been particularly related to fertilization and embryogenesis, nucleophosmin (or NPM1) is ubiquitously and abundantly expressed in adult cells. It is enriched in the nucleolus, and serves multiple functions that affect cell growth and apoptosis, therefore disregulation of NPM1 is linked to several human cancers. Particular mutations of NPM1, that destabilize its structure, and cause its mislocalization to the cytoplasm, trigger acute myeloid leukaemia (AML). Apart from nucleophosmin and NP, the family includes the less

NP is a homopentameric protein, composed of 200 residues, each subunit being built of two domains, namely core and tail. The core domain, corresponding to the N-terminal 120 residues, adopts an eight-stranded -barrel structure, and is responsible for oligomerization,

and reproduction in any medium, provided the original work is properly cited.


**Chapter 7** 

## **Thermodynamic Signatures of Macromolecular Complexes ‒ Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone**

Stefka G. Taneva, Sonia Bañuelos and María A. Urbaneja

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54062

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

Transfusion 2005, 45, 752-760.

Organometallics 26:6248-6257.

Acids Res. 15:6713-6731.

Biochem. Pharmacol. 63:1653-1662.

Assay. Bioorg. Med. Chem. Lett. 17:1013-1017.

Am. Chem. Soc. 123:5878-5891.

Resistance. Bioorg. Med. Chem. 12:4625-4631.

Unwinding Assay. Bioorg. Med. Chem. 16:10221-10227.

of DNA Host Duplexes. Biochemistry 32:5064-5073.

Chemother 42:13-28.

152 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Complexes with DNA. Bioorg. Med. Chem. 15:4406-4418.

(1998) Photodyanamic Therapy. J. Natl. Caner. Inst. 90:880-905.

for Purging Blood-Borne Pathogens and Binding Mode and Affinity Studies of their

[29] Wainwright M (1998) Photodynamic Antimicrobial Chemotherapy. J. Antimicrob.

[30] Dougherty T, Gomer C, Henderson B, Jori G, Kessel D, Korbelik M, Moan J, Pend Q

[31] Detty MR, Gibson SL, Wagner SJ (2004) Current Clinical and Preclinical Photosensitizers for use in Photodynamic Therapy. J. Med. Chem 47, 3897-3915. [32] Wagner, SJ, Skripchenko A, Cincotta L, Thompson-Montgomery D, Awatefe H (2005) Use of a Flexible Thiopyrylium Photosensitizer and Competitive Inhibitor for Pathogen Reduction of Viruses and Bacteria with Retention of Red Cell Storage Properties.

[33] Calitree B, Donnelly D, Holt J, Gannon M, Nygren C, Sukumaran D, Autschbach J, Detty M. (2007) Tellurium Analogues of Rosamine and Rhodamine Dyes: Synthesis, Structure, 125Te NMR, and Heteratom Contribution to Excitation Energies.

[34] Gibson S, Hilf R, Donnelly D, Detty M (2004) Analogues of Tetramethylrosamine as Transport Molecules for and inhibitors of P-Glycoprotein-Mediated Multi-Drug

[35] McKnight, RE, Onogul B, Polasani SR, Gannon MK, Detty MR (2008) Substituent Control of DNA Binding Modes in a Series of Chalcogenoxanthylium Photosensitizers as Determined by Isothermal Titration Calorimetry and Topoisomerase I DNA

[36] McKnight, RE, Reisenauer, E, Pintado, MV, Polasani, SR and Dixon, DW (2011) Substituent Effect on the Preferred DNA Binding Mode and Affinity of a Homologous

[37] Barcelo F, Portugal J, (1993) Berenil Recognizes and Changes the Characteristics of Adenine and Thymine Polynucleotide Structures. Biophys. Chem. 47:251-260. [38] Remata D, Mudd C, Berger R, Breslauer K (1993) Thermodynamic Characterization of Daunomycin-DNA Interactions: Comparison of Complete Binding Profiles for a Series

[39] Pommier, Y, Covey J-M, Kerrigan D, Markovits J, Pham R (2007) DNA Unwinding and Inhibition of Mouse Leukemia L1210 DNA Topoisomerase I DNA Intercalators. Nucleic

[40] Dziegielewski J, Slusarski B, Konitz A, Skladanowski A, Konopa (2002) Intercalation of Imidazoacridinones to DNA and its Relevance to Cytotoxic and Antitumor Activity. J.

[41] Boger DL, Fink BE, Brunette, SR, Tse WC, Hedrick, MP (2001) A Simple, High-Resolution Method for Establishing DNA Binding Affinity and Sequence Selectivity. J.

[42] McKnight, R. E.; Gleason, A. B.; Keyes, J. A.; Sahabi, S. (2007) Binding Mode and Affinity Studies of DNA Binding Agents Using Topoisomerase I DNA Unwinding

Series of Naphthalene Diimides, Bioorg. Med. Chem. Lett. 21:4288-4291.

Nucleoplasmin (NP) is a nuclear chaperone that mediates chromatin remodeling processes, such as sperm decondensation at fertilization [1]. In *Xenopus laevis* eggs, where it was first isolated, this highly acidic protein is thought to be in charge of nucleosomal core histones H2A/H2B storage. Upon fertilization, NP decondenses the densely packed sperm chromatin by means of extracting its specific basic proteins and replacing them with H2A/H2B, therefore enabling the assembly of somatic-type nucleosomes. NP is additionally involved in chromatin remodeling during early development, in particular it is required in the replication licensing mechanism, probably to extract linker-type histones from somatic chromatin, and can facilitate pluripotent cell reprogramming. NP (also designated NPM2) belongs to the nucleophosmin/nucleoplasmin family of histone chaperones [2]. Whereas NP roles have been particularly related to fertilization and embryogenesis, nucleophosmin (or NPM1) is ubiquitously and abundantly expressed in adult cells. It is enriched in the nucleolus, and serves multiple functions that affect cell growth and apoptosis, therefore disregulation of NPM1 is linked to several human cancers. Particular mutations of NPM1, that destabilize its structure, and cause its mislocalization to the cytoplasm, trigger acute myeloid leukaemia (AML). Apart from nucleophosmin and NP, the family includes the less known NPM3 and an invertebrate NPM-like.

NP is a homopentameric protein, composed of 200 residues, each subunit being built of two domains, namely core and tail. The core domain, corresponding to the N-terminal 120 residues, adopts an eight-stranded -barrel structure, and is responsible for oligomerization,

© 2013 Taneva et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Applications of Calorimetry in a Wide Context – 154 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

forming a ring with pentameric symmetry of 60 Å (diameter) and 40 Å (height) [3]. This compact core, shared by all NPM family members, confers an extreme stability to NP (see below). Probably, this is mainly due to a conserved network of hydrophobic interactions between the subunits, which, acting as a belt, firmly secures the pentamer. The C-terminal tail domain, instead, is conformationally flexible [4,5], therefore NP is considered "partially disordered" [6]. The tail harbors a segment rich in acidic residues (20 Asp and Glu within residues 120-150) termed "polyGlu", probably involved in histone binding , and a nuclear localization signal (NLS) that directs NP import into the nucleus.

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 155

G H T S (1)

H c dT (2)

thermodynamical characterization of the assembly of the complete complexes made of the full length proteins and have additionally built structural models of those import complexes [15]. NP loaded with histones can additionally incorporate importin , generating large

Calorimetry (DSC and ITC) is the most precise tool in the study of energetics of thermallyinduced conformational transitions of proteins and their assembly with other molecules, small ligands or macromolecules. Extensive reviews have been published on the basic thermodynamic formalism, calorimeters' design and application of DSC [17-20] and ITC [18,20-24]. Moreover, surveys on ITC application are published annually since 2002 [25-28]. Calorimetry on proteins in general will be briefly summarized here and examples for NP

The excess heat capacity of a protein in solution, as a function of temperature, and the heat released or absorbed upon binding interactions are the quantities registered in the DSC and ITC experiments. Both the folding and binding events are described by the Gibbs free energy (G), which determines the stability of the protein and the strength of association of molecules, respectively. The partitioning of G into enthalpic (H) and entropic (TS) terms

From the experimentally observed calorimetric curve, the DSC thermogram (typically an endothermic peak) and the ITC binding isotherm (exotherm or endotherm), a complete set of thermodynamic parameters of the studied folding/unfolding and binding phenomena is

In DSC the values of the thermodynamic parameters of the folded-unfolded state equilibrium: transition midpoint temperature Tm (the temperature at the maximum of the excess heat capacity curve), the enthalpy of unfolding H, calculated by the integral of the

o

where To and Tu are the temperatures of the onset and completion of the transition, respectively, and cP (the heat capacity change associated with unfolding) can be determined in a model-independent way [29]. In addition, the width at half-height of the transition Tm1/2

In ITC, the binding affinity Kb (Kb = e-G/RT, R is the gas constant and T is the absolute temperature), the enthalpy change H and the stoichiometry N of the binding interactions are determined by fitting the experimentally obtained binding isotherms assuming a model

is a measure of the cooperativity of the transition from folded to unfolded state.

T P T

assemblies that could represent putative NP/histones co-transport complexes [16].

**2. Calorimetry: Protein folding/unfolding and binding energetics** 

will be thoroughly reviewed.

excess heat capacity function:

provided.

is given by the basic thermodynamic equation:

<sup>u</sup>

The function of NP is activated through phosphorylation of up to 7 - 10 residues per monomer. NP phosphorylation degree correlates with *Xenopus* egg maturation, so that at the time of fertilization the protein is heavily phosphorylated and displays a maximal chromatin decondensing activity [5,7]. We have identified by mass spectrometry eight phosphorylation sites in natural NP: these phosphoresidues accumulate in flexible regions and loops, along both the core and tail domains, and cluster on a particular pole of the protein, known as distal face [8]. Phosphorylation causes a significant destabilization of the protein and we have made use of calorimetry (differential scanning calorimetry (DSC)) to dissect this effect, and its correlation with NP activation mechanism [9].

To fulfil its chromatin remodeling role, NP has to bind histones, basic proteins needed for packing of DNA. It acts as a reservoir for nucleosomal histones H2A/H2B, and is able to extract sperm specific basic proteins as well as linker-type histones, such as H1 from chromatin. The NP-mediated exchange of these more basic proteins with H2A/H2B results in a looser condensation state of chromatin [1,2]. We have thermodynamically described NP recognition of H2A/H2B and H5, a linker-type histone, by isothermal titration calorimetry (ITC) [10].

NP is the most abundant nuclear protein of *Xenopus* oocytes. Its nuclear import is mediated by the importin / heterodimer; in fact, NP is the prototypical substrate of this "classical" pathway, which is in charge of transport of most nuclear proteins [11]. Importin recognizes a nuclear localization signal (NLS) in its substrates, which consists of a sequence segment with conserved basic residues, and itself associates to importin [11,12]. The complex formed by importin / bound to the NLS cargo, traverses the nuclear envelope through the nuclear pore complexes. The transport relies on a gradient of the small GTPase Ran for directionality. The GTP-bound state of Ran is mostly nuclear and promotes the disassembly of the import complex once it reaches the nucleus, whereas in the cytoplasm, in the presence of Ran-GDP, the import complex formation is favoured [11,12].

Both importin and , belong to the karyopherin family of transport receptors, and their structures are constituted by a series of helical repeats, called ARM in the case of importin and HEAT in importin , that generate curved, flexible surfaces to bind their ligands. Importin displays additionally a short N-terminal region for importin binding (IBB domain) [12]. Most studies on the molecular basis of NLS recognition by nuclear transport receptors are so far limited to isolated domains of the proteins involved (e.g. using peptides corresponding to the NLS of NP and IBB of importin ) [13,14]. We have approached the thermodynamical characterization of the assembly of the complete complexes made of the full length proteins and have additionally built structural models of those import complexes [15]. NP loaded with histones can additionally incorporate importin , generating large assemblies that could represent putative NP/histones co-transport complexes [16].

### **2. Calorimetry: Protein folding/unfolding and binding energetics**

Applications of Calorimetry in a Wide Context –

154 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

localization signal (NLS) that directs NP import into the nucleus.

and its correlation with NP activation mechanism [9].

(ITC) [10].

forming a ring with pentameric symmetry of 60 Å (diameter) and 40 Å (height) [3]. This compact core, shared by all NPM family members, confers an extreme stability to NP (see below). Probably, this is mainly due to a conserved network of hydrophobic interactions between the subunits, which, acting as a belt, firmly secures the pentamer. The C-terminal tail domain, instead, is conformationally flexible [4,5], therefore NP is considered "partially disordered" [6]. The tail harbors a segment rich in acidic residues (20 Asp and Glu within residues 120-150) termed "polyGlu", probably involved in histone binding , and a nuclear

The function of NP is activated through phosphorylation of up to 7 - 10 residues per monomer. NP phosphorylation degree correlates with *Xenopus* egg maturation, so that at the time of fertilization the protein is heavily phosphorylated and displays a maximal chromatin decondensing activity [5,7]. We have identified by mass spectrometry eight phosphorylation sites in natural NP: these phosphoresidues accumulate in flexible regions and loops, along both the core and tail domains, and cluster on a particular pole of the protein, known as distal face [8]. Phosphorylation causes a significant destabilization of the protein and we have made use of calorimetry (differential scanning calorimetry (DSC)) to dissect this effect,

To fulfil its chromatin remodeling role, NP has to bind histones, basic proteins needed for packing of DNA. It acts as a reservoir for nucleosomal histones H2A/H2B, and is able to extract sperm specific basic proteins as well as linker-type histones, such as H1 from chromatin. The NP-mediated exchange of these more basic proteins with H2A/H2B results in a looser condensation state of chromatin [1,2]. We have thermodynamically described NP recognition of H2A/H2B and H5, a linker-type histone, by isothermal titration calorimetry

NP is the most abundant nuclear protein of *Xenopus* oocytes. Its nuclear import is mediated by the importin / heterodimer; in fact, NP is the prototypical substrate of this "classical" pathway, which is in charge of transport of most nuclear proteins [11]. Importin recognizes a nuclear localization signal (NLS) in its substrates, which consists of a sequence segment with conserved basic residues, and itself associates to importin [11,12]. The complex formed by importin / bound to the NLS cargo, traverses the nuclear envelope through the nuclear pore complexes. The transport relies on a gradient of the small GTPase Ran for directionality. The GTP-bound state of Ran is mostly nuclear and promotes the disassembly of the import complex once it reaches the nucleus, whereas in the cytoplasm, in

Both importin and , belong to the karyopherin family of transport receptors, and their structures are constituted by a series of helical repeats, called ARM in the case of importin and HEAT in importin , that generate curved, flexible surfaces to bind their ligands. Importin displays additionally a short N-terminal region for importin binding (IBB domain) [12]. Most studies on the molecular basis of NLS recognition by nuclear transport receptors are so far limited to isolated domains of the proteins involved (e.g. using peptides corresponding to the NLS of NP and IBB of importin ) [13,14]. We have approached the

the presence of Ran-GDP, the import complex formation is favoured [11,12].

Calorimetry (DSC and ITC) is the most precise tool in the study of energetics of thermallyinduced conformational transitions of proteins and their assembly with other molecules, small ligands or macromolecules. Extensive reviews have been published on the basic thermodynamic formalism, calorimeters' design and application of DSC [17-20] and ITC [18,20-24]. Moreover, surveys on ITC application are published annually since 2002 [25-28]. Calorimetry on proteins in general will be briefly summarized here and examples for NP will be thoroughly reviewed.

The excess heat capacity of a protein in solution, as a function of temperature, and the heat released or absorbed upon binding interactions are the quantities registered in the DSC and ITC experiments. Both the folding and binding events are described by the Gibbs free energy (G), which determines the stability of the protein and the strength of association of molecules, respectively. The partitioning of G into enthalpic (H) and entropic (TS) terms is given by the basic thermodynamic equation:

$$
\Delta \mathbf{G} = \Delta \mathbf{H} - \mathbf{T} \Delta \mathbf{S} \tag{1}
$$

From the experimentally observed calorimetric curve, the DSC thermogram (typically an endothermic peak) and the ITC binding isotherm (exotherm or endotherm), a complete set of thermodynamic parameters of the studied folding/unfolding and binding phenomena is provided.

In DSC the values of the thermodynamic parameters of the folded-unfolded state equilibrium: transition midpoint temperature Tm (the temperature at the maximum of the excess heat capacity curve), the enthalpy of unfolding H, calculated by the integral of the excess heat capacity function:

$$
\Delta \mathbf{H} = \int\_{\mathbf{T}\_o}^{\mathbf{T}\_y} \mathbf{c}\_P \mathbf{d} \mathbf{T} \tag{2}
$$

where To and Tu are the temperatures of the onset and completion of the transition, respectively, and cP (the heat capacity change associated with unfolding) can be determined in a model-independent way [29]. In addition, the width at half-height of the transition Tm1/2 is a measure of the cooperativity of the transition from folded to unfolded state.

In ITC, the binding affinity Kb (Kb = e-G/RT, R is the gas constant and T is the absolute temperature), the enthalpy change H and the stoichiometry N of the binding interactions are determined by fitting the experimentally obtained binding isotherms assuming a model

156 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

that well describes the binding process. While one binding constant describes a simple 1:1 molecular interaction, complex macromolecular recognition processes are described by model-independent macroscopic and model-dependent microscopic association constants, that account for the overall binding behaviour and for the association at each binding site, respectively [30,31]. Model independent analysis of more complex binding data, with two or more binding sites, based on general binding polynomial formalism, developed by Freire et al. [31], allows the type, independent or cooperative, of the binding interactions to be assessed. Methodology and analysis for heterotropic ligand binding cooperativy, i.e. for two or more different ligands binding to one protein has also been elaborated by Velázquez-Campoy et al. [32,33].

ITC is a suitable technique for characterizing allosteric interactions and conformational changes in proteins [32,34-37].

ITC also allows determination of the heat capacity change of binding interactions, cP, from the temperature dependence of the enthalpy change:

$$
\Delta \mathbf{c}\_{\rm P} = \hat{\boldsymbol{\varepsilon}} \Delta \mathbf{H} / \hat{\boldsymbol{\varepsilon}} \mathbf{T} \tag{3}
$$

Thermodynamic Signatures of Macromolecular

(8)

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 157

solv conf rot tr S S S S (6)

H H nH obs bind H ion (7)

<sup>a</sup> k A exp E / RT (9)

p t (10)

Additional information on protonation/deprotonation effects coupled to the binding interactions can be provided by titration experiments in various buffers of different ionization enthalpy, Hion. The number of protons, nH+, exchanged between the macromolecular complex and the bulk solution, and the binding enthalpy, Hbind, can be calculated from the dependence of the calorimetrically observed enthalpy change, Hobs, and

To decompose the free energy of binding into electrostatic and non-electrostatic contributions one has to study the ionic strength effect on the binding thermodynamics and

Valuable information on the hydration or solvent exposure of a polypeptide can be obtained by the absolute heat capacity [29]. A DSC method to accurately determine the absolute heat capacity of a protein from a series of calorimetric thermograms obtained at different protein concentrations has been described in [53]. The slope of a plot of the excess heat capacity

m C – *<sup>p</sup>* <sup>p</sup>

where m is the slope of the linear regression of the plot and υp is the partial specific volume of the protein. This information can be related to the integrity of the native state or the

The calorimetric transitions in many cases are irreversible and scanning rate dependent, suggesting that the denaturation process is kinetically controlled [54-56]. Appropriate kinetic models were applied to analyse the irreversible unfolding process, after obtaining a set of thermograms at various scanning rates. An irreversible protein denaturation event can be described in some cases by a simplified "two-state irreversible" kinetic model [54,57], assuming that only the native/folded and denatured/unfolded states are significantly populated during the denaturation. Mathematical expressions were derived to calculate the activation energy, *E*a, of the denaturation transition [54-58], using diverse experimental

analyse the data according to the Debye-Hückel approximation [52].

versus the protein mass in the calorimetric cell is related to the absolute *Cp*:

i. the values of the rate constant of the transition, k, at a given temperature:

k c / Q Q 

where *E*a is the activation energy and A is the frequency factor.

The rate constant of the reaction at a given temperature T is given by:

presence of residual structure in the denatured state.

information from the calorimetric transition:

Hion [42,50,51]:

with the assumption that the apparent heat capacities of the free molecules and the complex are constant over the temperature range under study. The changes in the heat capacity associated with protein-protein binding originate mostly from changes in the hydration heat capacity due to burial of polar and nonpolar groups upon complex formation and the loss of conformational degree of freedom upon binding [38-40]. Hence, cP can be calculated in terms of the change in the accessible surface areas (apolar (ASAap) and polar (ASApol)) upon the formation of protein-protein complex using the semi-empirical relationship [39,41-42]:

$$
\Delta \mathbf{c}\_{\mathrm{P}} = 0.45 \Lambda \text{ASA}\_{\mathrm{ap}} - 0.26 \Lambda \text{ASA}\_{\mathrm{pol}} \quad \text{cal} \, \text{K}^{-1} \text{mol}^{-1} \tag{4}
$$

A good correlation between the experimentally determined and the calculated from structural data cP values has been found in some cases [43-45], however significant difference was reported in other cases [42,46], suggested to be a consequence of changes in the conformational states and significant dynamic restriction of vibrational modes at the surface of the complex, as well as folding transitions coupled to the association event.

The values of cP can also be used to estimate the entropic component due to desolvation of the surfaces of both interacting proteins buried within the binding interface:

$$
\Delta \mathbf{S}\_{\text{solv}} = \Delta \mathbf{c}\_{\text{P}} \ln \left( \mathbf{T} / \mathbf{T} \, ^\ast \right) \tag{5}
$$

where T\* = 385.15 K is the temperature of entropy convergence [47,48] and to further decompose the entropic term, which besides the solvation term contains two more contributions (conformational, Sconf, associated with changes in conformational degree of freedom and rotational-translational Srot-tr, (Srot-tr = -7.96 cal mol-1K-1 [49] which accounts for changes in rotational/translational degrees of freedom):

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 157

$$
\Delta \mathbf{S} = \Delta \mathbf{S}\_{\text{solv}} + \Delta \mathbf{S}\_{\text{conf}} \, \, + \Delta \mathbf{S}\_{\text{rot-tr}} \, \tag{6}
$$

Additional information on protonation/deprotonation effects coupled to the binding interactions can be provided by titration experiments in various buffers of different ionization enthalpy, Hion. The number of protons, nH+, exchanged between the macromolecular complex and the bulk solution, and the binding enthalpy, Hbind, can be calculated from the dependence of the calorimetrically observed enthalpy change, Hobs, and Hion [42,50,51]:

Applications of Calorimetry in a Wide Context –

Campoy et al. [32,33].

changes in proteins [32,34-37].

the temperature dependence of the enthalpy change:

156 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

that well describes the binding process. While one binding constant describes a simple 1:1 molecular interaction, complex macromolecular recognition processes are described by model-independent macroscopic and model-dependent microscopic association constants, that account for the overall binding behaviour and for the association at each binding site, respectively [30,31]. Model independent analysis of more complex binding data, with two or more binding sites, based on general binding polynomial formalism, developed by Freire et al. [31], allows the type, independent or cooperative, of the binding interactions to be assessed. Methodology and analysis for heterotropic ligand binding cooperativy, i.e. for two or more different ligands binding to one protein has also been elaborated by Velázquez-

ITC is a suitable technique for characterizing allosteric interactions and conformational

ITC also allows determination of the heat capacity change of binding interactions, cP, from

with the assumption that the apparent heat capacities of the free molecules and the complex are constant over the temperature range under study. The changes in the heat capacity associated with protein-protein binding originate mostly from changes in the hydration heat capacity due to burial of polar and nonpolar groups upon complex formation and the loss of conformational degree of freedom upon binding [38-40]. Hence, cP can be calculated in terms of the change in the accessible surface areas (apolar (ASAap) and polar (ASApol)) upon the formation of protein-protein complex using the semi-empirical relationship [39,41-42]:

A good correlation between the experimentally determined and the calculated from structural data cP values has been found in some cases [43-45], however significant difference was reported in other cases [42,46], suggested to be a consequence of changes in the conformational states and significant dynamic restriction of vibrational modes at the

The values of cP can also be used to estimate the entropic component due to desolvation of

where T\* = 385.15 K is the temperature of entropy convergence [47,48] and to further decompose the entropic term, which besides the solvation term contains two more contributions (conformational, Sconf, associated with changes in conformational degree of freedom and rotational-translational Srot-tr, (Srot-tr = -7.96 cal mol-1K-1 [49] which accounts

surface of the complex, as well as folding transitions coupled to the association event.

the surfaces of both interacting proteins buried within the binding interface:

for changes in rotational/translational degrees of freedom):

<sup>P</sup> c H/ T (3)

1 1

solv P S c ln T / T \* (5)

<sup>P</sup> ap pol c 0.45 ASA – 0.26 ASA cal K mol (4)

$$
\Delta \mathbf{H}\_{\rm obs} = \Delta \mathbf{H}\_{\rm bind} + \mathbf{n}\_{\rm H+} \Delta \mathbf{H}\_{\rm ion} \tag{7}
$$

To decompose the free energy of binding into electrostatic and non-electrostatic contributions one has to study the ionic strength effect on the binding thermodynamics and analyse the data according to the Debye-Hückel approximation [52].

Valuable information on the hydration or solvent exposure of a polypeptide can be obtained by the absolute heat capacity [29]. A DSC method to accurately determine the absolute heat capacity of a protein from a series of calorimetric thermograms obtained at different protein concentrations has been described in [53]. The slope of a plot of the excess heat capacity versus the protein mass in the calorimetric cell is related to the absolute *Cp*:

$$\mathbf{m} \ = \mathbf{C}\_p - \ \upsilon\_p \tag{8}$$

where m is the slope of the linear regression of the plot and υp is the partial specific volume of the protein. This information can be related to the integrity of the native state or the presence of residual structure in the denatured state.

The calorimetric transitions in many cases are irreversible and scanning rate dependent, suggesting that the denaturation process is kinetically controlled [54-56]. Appropriate kinetic models were applied to analyse the irreversible unfolding process, after obtaining a set of thermograms at various scanning rates. An irreversible protein denaturation event can be described in some cases by a simplified "two-state irreversible" kinetic model [54,57], assuming that only the native/folded and denatured/unfolded states are significantly populated during the denaturation. Mathematical expressions were derived to calculate the activation energy, *E*a, of the denaturation transition [54-58], using diverse experimental information from the calorimetric transition:

i. the values of the rate constant of the transition, k, at a given temperature:

$$\mathbf{k} = \mathbf{A} \exp(-\mathbf{E\_a}/\mathbf{RT})\tag{9}$$

where *E*a is the activation energy and A is the frequency factor.

The rate constant of the reaction at a given temperature T is given by:

$$\mathbf{k} = \nu \ c\_p / \left( \mathbf{Q}\_t - \mathbf{Q} \right) \tag{10}$$

158 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

where is the scanning rate (K/min), cP the excess heat capacity at a given temperature, Q is the heat evolved at that temperature and Qt the total heat of the calorimetric transition.

ii. the dependence of the heat capacity evolved with temperature expressed as:

$$\frac{1}{2}\ln\left[\ln\mathbf{Q}\_{t}/\left(\mathbf{Q}\_{t}-\mathbf{Q}\right)\right] = E\_{\mathbf{a}}/\mathcal{R}\left(\mathbf{1}/\mathbf{T}\_{\mathbf{m}}-\mathbf{1}/\mathbf{T}\right) \tag{11}$$

iii. the heat capacity cpm at the transition temperature Tm, where the activation energy can also be calculated by the following eq.:

$$E\_a = eRT\_m^2 c\_P^m / Q\_t \tag{12}$$

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 159

**3. Nucleoplasmin thermal stability. Differential scanning calorimetry** 

other spectroscopic techniques.

unfolding.

[78].

stability equals that of the core domain [9].

NP is remarkably stable against chemical and physical challenges, including heat; e.g. the Tm of recombinant, non phosphorylated protein is 110.1°C [4,9]. This extreme stability, which is related, as previously mentioned, to the structural scaffolding role of the core domain, is *per se* an attractive issue to be thermodynamically described. We have characterized by DSC and other techniques the stability properties of NP and how they are related to the functionality of the protein. It should be mentioned that the overpressure used in the calorimeter allows to asses melting points above water boiling temperature, by contrast to

We have shown that the stability of NP is solely due to the core domain, the Tm of the isolated core (117.6°C) being still higher than that of the full length protein [9]. The slight destabilizing influence of the tail is explained by its strong acidic character, with negatively charged clusters, such as "polyGlu"; electrostatic repulsion is expected to occur between tails and the also negatively charged core domain. This is reflected by the fact that the full length protein is most stable at pH close to its theoretical isoelectric point (pI=5.1), when its

Analysis of the chemical denaturation of NP by fluorimetric and biochemical techniques has allowed to describe the unfolding mechanism of NP, in terms of a two-state process, where the pentamer dissociation is coupled with unfolding of the monomers, with no evidence of (partially) folded subunits (N5 5U) [78]. Both chemical and thermal unfolding of NP are reversible processes, while denaturation of the isolated core domain is reversible if chemically induced but irreversible upon heating [9,78]. This different behaviour suggests that the charged tail domains favour the solubility of the full length protein after thermal

**4. Effect of NP activation. Interplay between function and stability** 

NP activation, mediated by phosphorylation of multiple residues, implies an energetic cost for the protein. We have observed that NP extracted from *Xenopus* oocytes, corresponding to an intermediate phosphorylation state, is significantly destabilized with respect to recombinant, non phosphorylated NP (Tm 94.4°C, H 80 kcal/mol) [4]. Egg NP, which represents the most active protein in the final stage of egg maturation, exhibits a further destabilization (Tm 75°C, H 50 kcal/mol) [9]. This correlation between phosphorylation degree and loss of stability has been also characterized by chemical unfolding experiments

In order to explore the conformational consequences of NP activation, we assessed the impact of phosphorylation in particular sites on the protein stability. Apart from the experimental evidences pointing to CKII and mitosis promoting factor (MPF) as probable kinases that modify NP [7,79], the amount and identity of kinases phosphorylating NP has not been elucidated. On the other hand, NP can be phosphorylated *in vitro* only with very low yield. As an alternative approach to obtain homogeneous preparations of active NP

This "two-state" kinetic model has described the unfolding of bacteriorhodopsin [58], rhodopsin [59], plastocyanin [60], the major light harvesting complex of photosystem II [61], nucleoplasmin (see below, [9]) and some other proteins [62,63]. This model however cannot describe all cases of irreversible protein denaturation [64]. On the other hand, Davoodi et al. [65] have shown that scanning-rate dependence of DSC thermograms is not limited to irreversible processes only.

DSC can also be used to indirectly study ligand binding to proteins and for analysis of very tight binding that can not be analysed by ITC or other spectroscopic methods [66]. In addition, more comprehensive description of the binding energetics can be derived combining the two techniques, ITC and DSC [18].

Recently DSC was also recognized as a novel tool for disease diagnosis and monitoring [67- 70]. Calorimetric studies of blood plasma/serum have revealed a typical DSC thermogram for healthy individuals, whereas pronounced changes in thermograms for diseased subjects, including oncopatients, have been reported. Validation of the technique as an efficient tool for disease diagnostics needs further investigations of a large number of diseases.

Besides the classical application of ITC in studies of binding interactions, it has been proven as a powerful technique in diverse fields like drug discovery and lead optimization, nanotechnology, enzyme kinetics, etc. [71,73].

Kinetics of ligand binding to RNA and the subsequent RNA folding have recently been characterized by the so called kinITC [74]. ITC has also permitted documentation of the energy landscape of tertiary interactions along the RNA folding pathway [75]. Thermodynamic parameters, H and cP, of rigid amyloid fibril formation from monomeric -microglobulin, associated with degenerative disorders have also been determined by ITC [76]. Recently a protocol for novel application of the technique has been elaborated, in which ITC is used as a tracking tool, combined with chromatography, for identification of target protein in biomolecular mixture [77] and it has been suggested to be valuable when the target protein or ligand is unknown. References for the wide spectrum and examples of novel applications of ITC can be found in the surveys published each year in the Journal of Molecular Recognition [25-28].

### **3. Nucleoplasmin thermal stability. Differential scanning calorimetry**

Applications of Calorimetry in a Wide Context –

also be calculated by the following eq.:

combining the two techniques, ITC and DSC [18].

nanotechnology, enzyme kinetics, etc. [71,73].

Molecular Recognition [25-28].

irreversible processes only.

158 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

where is the scanning rate (K/min), cP the excess heat capacity at a given temperature, Q is the heat evolved at that temperature and Qt the total heat of the calorimetric transition.

iii. the heat capacity cpm at the transition temperature Tm, where the activation energy can

This "two-state" kinetic model has described the unfolding of bacteriorhodopsin [58], rhodopsin [59], plastocyanin [60], the major light harvesting complex of photosystem II [61], nucleoplasmin (see below, [9]) and some other proteins [62,63]. This model however cannot describe all cases of irreversible protein denaturation [64]. On the other hand, Davoodi et al. [65] have shown that scanning-rate dependence of DSC thermograms is not limited to

DSC can also be used to indirectly study ligand binding to proteins and for analysis of very tight binding that can not be analysed by ITC or other spectroscopic methods [66]. In addition, more comprehensive description of the binding energetics can be derived

Recently DSC was also recognized as a novel tool for disease diagnosis and monitoring [67- 70]. Calorimetric studies of blood plasma/serum have revealed a typical DSC thermogram for healthy individuals, whereas pronounced changes in thermograms for diseased subjects, including oncopatients, have been reported. Validation of the technique as an efficient tool

Besides the classical application of ITC in studies of binding interactions, it has been proven as a powerful technique in diverse fields like drug discovery and lead optimization,

Kinetics of ligand binding to RNA and the subsequent RNA folding have recently been characterized by the so called kinITC [74]. ITC has also permitted documentation of the energy landscape of tertiary interactions along the RNA folding pathway [75]. Thermodynamic parameters, H and cP, of rigid amyloid fibril formation from monomeric -microglobulin, associated with degenerative disorders have also been determined by ITC [76]. Recently a protocol for novel application of the technique has been elaborated, in which ITC is used as a tracking tool, combined with chromatography, for identification of target protein in biomolecular mixture [77] and it has been suggested to be valuable when the target protein or ligand is unknown. References for the wide spectrum and examples of novel applications of ITC can be found in the surveys published each year in the Journal of

for disease diagnostics needs further investigations of a large number of diseases.

tt a m ln lnQ / Q Q / R 1 / T – 1 / T *<sup>E</sup>* (11)

*<sup>t</sup> <sup>m</sup> Ea eRTmcP <sup>Q</sup>* <sup>2</sup> (12)

ii. the dependence of the heat capacity evolved with temperature expressed as:

NP is remarkably stable against chemical and physical challenges, including heat; e.g. the Tm of recombinant, non phosphorylated protein is 110.1°C [4,9]. This extreme stability, which is related, as previously mentioned, to the structural scaffolding role of the core domain, is *per se* an attractive issue to be thermodynamically described. We have characterized by DSC and other techniques the stability properties of NP and how they are related to the functionality of the protein. It should be mentioned that the overpressure used in the calorimeter allows to asses melting points above water boiling temperature, by contrast to other spectroscopic techniques.

We have shown that the stability of NP is solely due to the core domain, the Tm of the isolated core (117.6°C) being still higher than that of the full length protein [9]. The slight destabilizing influence of the tail is explained by its strong acidic character, with negatively charged clusters, such as "polyGlu"; electrostatic repulsion is expected to occur between tails and the also negatively charged core domain. This is reflected by the fact that the full length protein is most stable at pH close to its theoretical isoelectric point (pI=5.1), when its stability equals that of the core domain [9].

Analysis of the chemical denaturation of NP by fluorimetric and biochemical techniques has allowed to describe the unfolding mechanism of NP, in terms of a two-state process, where the pentamer dissociation is coupled with unfolding of the monomers, with no evidence of (partially) folded subunits (N5 5U) [78]. Both chemical and thermal unfolding of NP are reversible processes, while denaturation of the isolated core domain is reversible if chemically induced but irreversible upon heating [9,78]. This different behaviour suggests that the charged tail domains favour the solubility of the full length protein after thermal unfolding.

### **4. Effect of NP activation. Interplay between function and stability**

NP activation, mediated by phosphorylation of multiple residues, implies an energetic cost for the protein. We have observed that NP extracted from *Xenopus* oocytes, corresponding to an intermediate phosphorylation state, is significantly destabilized with respect to recombinant, non phosphorylated NP (Tm 94.4°C, H 80 kcal/mol) [4]. Egg NP, which represents the most active protein in the final stage of egg maturation, exhibits a further destabilization (Tm 75°C, H 50 kcal/mol) [9]. This correlation between phosphorylation degree and loss of stability has been also characterized by chemical unfolding experiments [78].

In order to explore the conformational consequences of NP activation, we assessed the impact of phosphorylation in particular sites on the protein stability. Apart from the experimental evidences pointing to CKII and mitosis promoting factor (MPF) as probable kinases that modify NP [7,79], the amount and identity of kinases phosphorylating NP has not been elucidated. On the other hand, NP can be phosphorylated *in vitro* only with very low yield. As an alternative approach to obtain homogeneous preparations of active NP with a defined modification level, we designed a series of phosphorylation mimicking mutants, in which different Ser and/or Thr residues representing phosphorylatable residues were substituted for Asp [8,9,80]. Most mutation sites correspond to phosphoresidues identified by mass spectrometry analysis of egg NP [9]. However, taking into account that some phosphoresidues might have remained undetected by the proteomic analysis, due to incomplete sequence coverage and/or heterogeneity of the NP natural samples, additional residues were mutated on the basis of prediction software, N-terminal amino acid analysis, sequence comparison within the NP family and structural considerations [8,80].

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 161

isolated from natural, hyperphosphorylated, egg NP is (partly) active in decondensing chromatin, and a recombinant core domain with 8 substitutions (CORE8D, with groups 1 and 2) resembles these functional properties [80]. Nevertheless, full activity can only be attained through accumulation of negative charges (or phosphoresidues) along both the core and tail domains of NP: the mutant NP13D reproduces the functionality of egg NP [8].

Comparison of the thermal unfolding profiles of wild type and mutant core domains reveals that the activating mutations strongly decrease the thermal stability of the protein (Figure 2). Destabilization is probably due to the electrostatic repulsion in the oligomer (already negatively charged at neutral pH), which becomes more intense in the mutants (see inset in

**Figure 2.** Phosphorylation mimicking mutations decrease the thermal stability of NP core domain. The effect of the mutations on the charge of the protein is also shown, by comparing the surface of the crystal structure of the mutant CORE8D [9] (left) and wild type CORE [3] (right), viewed from the distal

The mutant CORE3D (with group 2 mutations) is less stable, in spite of harbouring fewer substitutions than CORE5D (group 1 mutations), which could be due to the fact that the three residues 15, 66 and 96 locate in structured regions of the protein, whereas the five Nterminal mutations are in a flexible segment that could be re-arranged to alleviate the electrostatic repulsion in NP. The combination of both groups of mutations makes CORE8D the most unstable mutant core, as expected. The strong destabilizing effect (e.g. Tm of 34.5°C in the case of CORE8D) suggests a conformational change in the protein. Phosphorylation does not induce, however, significant changes in the secondary structure of NP [5,9]. Furthermore, we have solved the crystal structure of CORE8D and found that surprisingly enough it is almost identical to that of wild type core domain [9] (see Figure 2). On the other hand, the activating mutations seem to affect the dynamics of the core domain [9]. The irreversible thermal unfolding of the core can be described as a scanning ratedependent transition between two states, native and irreversibly denatured. From different mathematical expressions making use of diverse parameters from the calorimetric transition

face, and colored according to the electrostatic potential

Figure 2).

The mutation sites, which are indicated in Figure 1, can be classified in three groups: 1) mutations in the flexible, N-terminal segment of the protein, not visible in the 3D structure of the core domain (residues 2, 3, 5, 7, 8), 2) mutations of residues located in loop regions of the core domain distal face (15, 66 and 96) and 3) mutations in the tail domain (residues 159, 176, 177, 181 and 183). Apart from the group of three residues within the structured core domain, at least group 1 is expected to face also the distal pole of the protein, which is most probably implicated in histone binding [10,80]. A collection of NP mutants (full length and core domains) were generated, combining the three groups of mutations, as indicated in Figure 1.

**Figure 1.** Activation of recombinant NP achieved through phosphomimicking mutations. Their location is highlighted on our model of full length NP based on the crystal structure of the core domain [3] and SAXS data [10]. Orange circles denote substitutions of residues 2, 3, 5, 7, 9 for Asp in the N-terminal segment ("group 1"); red ones correspond to substitutions at 15, 66 and 96 ("group 2"), and green ones to mutations in residues 159, 176, 177, 181, 183 of the tail domain ("group 3"). NP5D carries only mutations in the tail; NP8D harbors groups 1 and 2; NP10D groups 1 and 3; and NP13D comprises all mutations. For the sake of clarity, the positions are shown in only one monomer

By contrast to recombinant, non-phosphorylated NP, which shows negligible ability to decondense chromatin, phosphorylation mimicking mutations render the protein active to varying extents depending on the number and position of mutations**.** The mutants are capable of decondensing *Xenopus* demembranated sperm nuclei and extracting spermspecific basic proteins, as well as linker-type histones from chromatin. The core domain isolated from natural, hyperphosphorylated, egg NP is (partly) active in decondensing chromatin, and a recombinant core domain with 8 substitutions (CORE8D, with groups 1 and 2) resembles these functional properties [80]. Nevertheless, full activity can only be attained through accumulation of negative charges (or phosphoresidues) along both the core and tail domains of NP: the mutant NP13D reproduces the functionality of egg NP [8].

Applications of Calorimetry in a Wide Context –

Figure 1.

160 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

with a defined modification level, we designed a series of phosphorylation mimicking mutants, in which different Ser and/or Thr residues representing phosphorylatable residues were substituted for Asp [8,9,80]. Most mutation sites correspond to phosphoresidues identified by mass spectrometry analysis of egg NP [9]. However, taking into account that some phosphoresidues might have remained undetected by the proteomic analysis, due to incomplete sequence coverage and/or heterogeneity of the NP natural samples, additional residues were mutated on the basis of prediction software, N-terminal amino acid analysis,

The mutation sites, which are indicated in Figure 1, can be classified in three groups: 1) mutations in the flexible, N-terminal segment of the protein, not visible in the 3D structure of the core domain (residues 2, 3, 5, 7, 8), 2) mutations of residues located in loop regions of the core domain distal face (15, 66 and 96) and 3) mutations in the tail domain (residues 159, 176, 177, 181 and 183). Apart from the group of three residues within the structured core domain, at least group 1 is expected to face also the distal pole of the protein, which is most probably implicated in histone binding [10,80]. A collection of NP mutants (full length and core domains) were generated, combining the three groups of mutations, as indicated in

**Figure 1.** Activation of recombinant NP achieved through phosphomimicking mutations. Their location is highlighted on our model of full length NP based on the crystal structure of the core domain [3] and SAXS data [10]. Orange circles denote substitutions of residues 2, 3, 5, 7, 9 for Asp in the N-terminal segment ("group 1"); red ones correspond to substitutions at 15, 66 and 96 ("group 2"), and green ones to mutations in residues 159, 176, 177, 181, 183 of the tail domain ("group 3"). NP5D carries only mutations in the tail; NP8D harbors groups 1 and 2; NP10D groups 1 and 3; and NP13D comprises all

By contrast to recombinant, non-phosphorylated NP, which shows negligible ability to decondense chromatin, phosphorylation mimicking mutations render the protein active to varying extents depending on the number and position of mutations**.** The mutants are capable of decondensing *Xenopus* demembranated sperm nuclei and extracting spermspecific basic proteins, as well as linker-type histones from chromatin. The core domain

mutations. For the sake of clarity, the positions are shown in only one monomer

sequence comparison within the NP family and structural considerations [8,80].

Comparison of the thermal unfolding profiles of wild type and mutant core domains reveals that the activating mutations strongly decrease the thermal stability of the protein (Figure 2). Destabilization is probably due to the electrostatic repulsion in the oligomer (already negatively charged at neutral pH), which becomes more intense in the mutants (see inset in Figure 2).

**Figure 2.** Phosphorylation mimicking mutations decrease the thermal stability of NP core domain. The effect of the mutations on the charge of the protein is also shown, by comparing the surface of the crystal structure of the mutant CORE8D [9] (left) and wild type CORE [3] (right), viewed from the distal face, and colored according to the electrostatic potential

The mutant CORE3D (with group 2 mutations) is less stable, in spite of harbouring fewer substitutions than CORE5D (group 1 mutations), which could be due to the fact that the three residues 15, 66 and 96 locate in structured regions of the protein, whereas the five Nterminal mutations are in a flexible segment that could be re-arranged to alleviate the electrostatic repulsion in NP. The combination of both groups of mutations makes CORE8D the most unstable mutant core, as expected. The strong destabilizing effect (e.g. Tm of 34.5°C in the case of CORE8D) suggests a conformational change in the protein. Phosphorylation does not induce, however, significant changes in the secondary structure of NP [5,9]. Furthermore, we have solved the crystal structure of CORE8D and found that surprisingly enough it is almost identical to that of wild type core domain [9] (see Figure 2).

On the other hand, the activating mutations seem to affect the dynamics of the core domain [9]. The irreversible thermal unfolding of the core can be described as a scanning ratedependent transition between two states, native and irreversibly denatured. From different mathematical expressions making use of diverse parameters from the calorimetric transition

162 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

(eqs. 9-12), the activation energy *Ea* of the denaturation was calculated and compared for wild type CORE and CORE8D. We obtained a higher *Ea* value for wtCORE (69.8 ± 2.6 kcal/mol) than for CORE8D (52.1 ± 2.4 kcal/mol), indicating that the mutations destabilize also kinetically the core domain, reducing the energy barrier of the transition to the unfolded state [9]. In addition, to further characterize the conformational change associated with protein activation, the excess heat capacity cP of wtCORE and CORE8D was measured at various protein concentrations (at 37°C), in order to calculate the absolute heat capacity, *Cp*, of their native states, which is related to solvent exposure of protein hydrophobic groups (eq. 8, see above). The obtained *Cp* values were 0.23 and 0.42 cal K-1 g-1 for wtCORE and CORE8D, respectively, suggesting faster dynamics or faster conformational fluctuations in the mutant [9]. Furthermore, the activation process affects the hydrodynamic properties of the protein (see below).

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 163

The mutations-induced destabilization of NP is also readily observed by chemical unfolding experiments [9]. Since NP denaturation proceeds through pentamer dissociation intimately coupled to unfolding of the monomers, the activation mechanism, in spite of not affecting conformationally the protein at the level of secondary structure and tertiary structure of the core domain, seems to weaken its quaternary interactions. In support of this notion, we have observed, by size exclusion chromatography and dynamic light scattering, that the activating mutations induce an expansion of the NP pentamer dimensions in solution, both in the core domains (from an average diameter of 64.5 Å to 68.8 Å for CORE8D, as measured by DLS) and the full length mutants (from 93.7 to 99.5 Å in the case of NP13D) [9]. Considering the similarity between the crystal structures of inactive, wild type, and active, mutant core domain, this "swelling" must affect mainly flexible regions of the protein, such

Therefore, in NP, an inverse correlation exists between activity and stability (Figure 3), the higher the histone chaperone activity performed by NP, the lower its thermal and chemical

In summary, we observed that NP activation mechanism, that depends on the accumulation of negative charge, probably on flexible regions of the distal pole of the protein, implies a destabilizing cost and an expansion of the oligomer in solution. The destabilizing mechanism seems to be the electrostatic repulsion in the pentamer, that weakens the quaternary interactions (tending to "open" apart the structure), which are essential for the stability of this protein. However, the loss of stability does not compromise, under physiological conditions, NP function or folding, which is granted by the extremely stable core domain. Moreover, the activation penalty may explain why this protein, from a mesophilic organism, displays such a remarkable thermal stability: it is necessary to afford

**5. Nucleoplasmin chaperoning function studied by isothermal titration** 

The high number of positive charges that histone proteins carry makes them prone to unproductive interactions with nucleic acids and other cellular components. Therefore free histones eventually do not exist within the cellular context and need to be escorted by histone chaperones, which shield their charge, and facilitate their controlled transfer during nucleosome assembly or reorganization. To perform its function, nucleoplasmin has to bind both linker-type and nucleosomal histones. Thermodynamics provided a detailed knowledge of NP-histone complex formation and elicited how NP carries its chaperoning

The experimental isotherms of the binding interactions of NP with histones, H5 and H2A/H2B, and the enthalpic and entropic contributions to the Gibbs free energy for the first

as the N-terminal segment, loops of the core domain, and the tail domain.

stability, and larger its dimensions in solution.

the strong destabilization upon activation.

binding site are summarized in Figure 4.

**calorimetry** 

activity [10].

To understand the contribution of both NP domains to its activation mechanism, we also characterized the function and stability of full length NP, with the three groups of mutations and combinations thereof (Figure 3). Substitutions located in the core domain (NP8D) affect the protein stability to a greater extent than those in the tail domain (NP5D), highlighting again that addition of charges in structurally well defined locations is more deleterious for the stability of the protein than in flexible regions. The most active mutant, NP13D, is also the most unstable (Tm 55.2°C, H 17.9 kcal/mol). Taking into account that at neutral pH aspartic acid has one negative charge, while a phosphoryl group would display an average negative charge of -1.5 [81], 13 Asp would be a reasonable approximation of 7-10 phosphates per monomer in egg NP; however, the fact that this mutant is less stable than egg NP reflects that the conformational properties of phosphorylated NP may not be exactly reproduced [9].

**Figure 3.** Inverse correlation between NP activity (expressed as percentage of histone H5 extracted from chicken erythrocyte chromatin, in a solubilization assay [8]) and thermal stability (Tm as measured by DSC). Linear regression of the phosphomimicking mutants data is shown

The mutations-induced destabilization of NP is also readily observed by chemical unfolding experiments [9]. Since NP denaturation proceeds through pentamer dissociation intimately coupled to unfolding of the monomers, the activation mechanism, in spite of not affecting conformationally the protein at the level of secondary structure and tertiary structure of the core domain, seems to weaken its quaternary interactions. In support of this notion, we have observed, by size exclusion chromatography and dynamic light scattering, that the activating mutations induce an expansion of the NP pentamer dimensions in solution, both in the core domains (from an average diameter of 64.5 Å to 68.8 Å for CORE8D, as measured by DLS) and the full length mutants (from 93.7 to 99.5 Å in the case of NP13D) [9]. Considering the similarity between the crystal structures of inactive, wild type, and active, mutant core domain, this "swelling" must affect mainly flexible regions of the protein, such as the N-terminal segment, loops of the core domain, and the tail domain.

Applications of Calorimetry in a Wide Context –

the protein (see below).

reproduced [9].

162 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

(eqs. 9-12), the activation energy *Ea* of the denaturation was calculated and compared for wild type CORE and CORE8D. We obtained a higher *Ea* value for wtCORE (69.8 ± 2.6 kcal/mol) than for CORE8D (52.1 ± 2.4 kcal/mol), indicating that the mutations destabilize also kinetically the core domain, reducing the energy barrier of the transition to the unfolded state [9]. In addition, to further characterize the conformational change associated with protein activation, the excess heat capacity cP of wtCORE and CORE8D was measured at various protein concentrations (at 37°C), in order to calculate the absolute heat capacity, *Cp*, of their native states, which is related to solvent exposure of protein hydrophobic groups (eq. 8, see above). The obtained *Cp* values were 0.23 and 0.42 cal K-1 g-1 for wtCORE and CORE8D, respectively, suggesting faster dynamics or faster conformational fluctuations in the mutant [9]. Furthermore, the activation process affects the hydrodynamic properties of

To understand the contribution of both NP domains to its activation mechanism, we also characterized the function and stability of full length NP, with the three groups of mutations and combinations thereof (Figure 3). Substitutions located in the core domain (NP8D) affect the protein stability to a greater extent than those in the tail domain (NP5D), highlighting again that addition of charges in structurally well defined locations is more deleterious for the stability of the protein than in flexible regions. The most active mutant, NP13D, is also the most unstable (Tm 55.2°C, H 17.9 kcal/mol). Taking into account that at neutral pH aspartic acid has one negative charge, while a phosphoryl group would display an average negative charge of -1.5 [81], 13 Asp would be a reasonable approximation of 7-10 phosphates per monomer in egg NP; however, the fact that this mutant is less stable than egg NP reflects that the conformational properties of phosphorylated NP may not be exactly

**Figure 3.** Inverse correlation between NP activity (expressed as percentage of histone H5 extracted from chicken erythrocyte chromatin, in a solubilization assay [8]) and thermal stability (Tm as measured

by DSC). Linear regression of the phosphomimicking mutants data is shown

Therefore, in NP, an inverse correlation exists between activity and stability (Figure 3), the higher the histone chaperone activity performed by NP, the lower its thermal and chemical stability, and larger its dimensions in solution.

In summary, we observed that NP activation mechanism, that depends on the accumulation of negative charge, probably on flexible regions of the distal pole of the protein, implies a destabilizing cost and an expansion of the oligomer in solution. The destabilizing mechanism seems to be the electrostatic repulsion in the pentamer, that weakens the quaternary interactions (tending to "open" apart the structure), which are essential for the stability of this protein. However, the loss of stability does not compromise, under physiological conditions, NP function or folding, which is granted by the extremely stable core domain. Moreover, the activation penalty may explain why this protein, from a mesophilic organism, displays such a remarkable thermal stability: it is necessary to afford the strong destabilization upon activation.

### **5. Nucleoplasmin chaperoning function studied by isothermal titration calorimetry**

The high number of positive charges that histone proteins carry makes them prone to unproductive interactions with nucleic acids and other cellular components. Therefore free histones eventually do not exist within the cellular context and need to be escorted by histone chaperones, which shield their charge, and facilitate their controlled transfer during nucleosome assembly or reorganization. To perform its function, nucleoplasmin has to bind both linker-type and nucleosomal histones. Thermodynamics provided a detailed knowledge of NP-histone complex formation and elicited how NP carries its chaperoning activity [10].

The experimental isotherms of the binding interactions of NP with histones, H5 and H2A/H2B, and the enthalpic and entropic contributions to the Gibbs free energy for the first binding site are summarized in Figure 4.

164 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 165

binding sites model and a general model based on the overall association constants. Eight thermodynamic parameters: four association constants (intrinsic association constant (K) and cooperativity binding parameters: k1 (associated with the binding of an additional ligand), k2 (binding of a ligand with contact to one nearest-neighbour) and k3 (binding of a ligand with contact to two nearest-neighbours)) and four enthalpies were defined in the cooperativity model (details on the model can be found in [10] and in Supplementary

The binding of histone molecules upon occupancy of the first binding site progresses with an energetic penalty, with exception of H2A/H2B molecules that bind to a non-adjacent site (k1 = 1). Therefore, negative cooperativity was observed for all four additional H5 molecules (k1 < 1), while only for H2A/H2B histone dimers bound to NP adjacently. Since the source of the cooperativity interaction may be an allosteric conformational change in NP induced by histone binding or a direct histone-histone interaction upon binding, or/as well as a combination of both, our results indicate different origin of the negative cooperativity for the binding of H5 and H2A/H2B to NP. Hence the main source of the cooperative binding interaction of H2A/H2B dimers is H2A/H2B-H2A/H2B interaction, whereas a conformational change in the NP pentamer upon binding of the first H5 molecule should provide a less favourable binding interface for the next histone molecules through energetic

Somewhat surprising, considering the strong opposite charge of NP and histones, the binding of both histone types to NP is dominated by a favourable entropic term indicating a strong contribution of the hydrophobic effect to the binding affinity (Figure 4, C and D). The enthalpic term also contributes favourably to the binding energy of H2A/H2B, while unfavourable enthalpy changes counterbalance the entropic contribution to the free energy

Furthemore, and contrary to the generally accepted major determinant of tail "polyGlu" tract in histone binding, the thermodynamic analysis as well as the low resolution structural models of NP/histone complexes, constructed by small angle X-ray scattering (SAXS) [10], demonstrate clearly that both NP domains are involved in the interaction with histones.

This was evidenced by comparing the binding energetics of the full-length protein with that of isolated core domain (CORE). Interestingly, NP core domain contributes equally to the intrinsic binding energy of H5 and H2A/H2B (G = -8.2 kcal/mol). The tail domain of NP provides an additional thermodynamic driving force (estimated as the difference between the binding free energies of histones to NP and CORE, GNP-CORE) (Figure 4 and Figure 5) for the much stronger binding of H5 (GNP-COREH5 = -5.5 kcal/mol) compared to H2A/H2B (GNP-COREH2AAH2B = -1.6 kcal/mol) suggesting that this domain is particularly essential in the

To approach an activity/energetics relationship, we analysed the energetics of histone association with NP variants with phosphorylation-mimicking mutations in both the core

Material of [10]).

communication.

of H5 binding (Figure 4, C and D).

binding to H5 molecules.

and tail domains (NP8D, NP13D, CORE, CORE8D).

**Figure 4.** Binding data of NP interactions with the linker, H5, and nucleosomal core, H2A/H2B, histones. (A, B) Baseline-corrected instrumental response of NP titration with successive additions of H5 and H2A/H2B (upper panels); integrated data and the fits of the binding isotherms (solid lines) according to a negative cooperativity model (see text) for H5 and H2A/H2B (lower panels). (C, D) Thermodynamic parameters (G, H, -TS) of the assembly of the first histone, H5 and H2A/H2B, molecule with NP

ITC data reveal that NP can accommodate five histone molecules utilizing a negative cooperative binding mechanism with dramatic difference in the binding strength. The binding affinity of histones for the first site is moderate for nucleosomal core (G = −9.8±0.1 kcal/mol, Kb=1.5×107 M−1) and extremely high for linker (G = −13.6±0.4 kcal/mol, Kb=1010 M−1) histones (Figure 4, C and D), which can provide the basis for its histone exchange capabilities. The binding isotherms of the complex formation of histones with NP were analyzed using a site specific cooperative binding model. The model, developed especially for NP-histone interactions, considers negative cooperative interactions for both adjacently and non-adjacently bound histones and fit the experimental data better than an independent binding sites model and a general model based on the overall association constants. Eight thermodynamic parameters: four association constants (intrinsic association constant (K) and cooperativity binding parameters: k1 (associated with the binding of an additional ligand), k2 (binding of a ligand with contact to one nearest-neighbour) and k3 (binding of a ligand with contact to two nearest-neighbours)) and four enthalpies were defined in the cooperativity model (details on the model can be found in [10] and in Supplementary Material of [10]).

Applications of Calorimetry in a Wide Context –

molecule with NP

164 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 4.** Binding data of NP interactions with the linker, H5, and nucleosomal core, H2A/H2B, histones. (A, B) Baseline-corrected instrumental response of NP titration with successive additions of H5 and H2A/H2B (upper panels); integrated data and the fits of the binding isotherms (solid lines) according to a negative cooperativity model (see text) for H5 and H2A/H2B (lower panels). (C, D) Thermodynamic parameters (G, H, -TS) of the assembly of the first histone, H5 and H2A/H2B,

ITC data reveal that NP can accommodate five histone molecules utilizing a negative cooperative binding mechanism with dramatic difference in the binding strength. The binding affinity of histones for the first site is moderate for nucleosomal core (G = −9.8±0.1 kcal/mol, Kb=1.5×107 M−1) and extremely high for linker (G = −13.6±0.4 kcal/mol, Kb=1010 M−1) histones (Figure 4, C and D), which can provide the basis for its histone exchange capabilities. The binding isotherms of the complex formation of histones with NP were analyzed using a site specific cooperative binding model. The model, developed especially for NP-histone interactions, considers negative cooperative interactions for both adjacently and non-adjacently bound histones and fit the experimental data better than an independent The binding of histone molecules upon occupancy of the first binding site progresses with an energetic penalty, with exception of H2A/H2B molecules that bind to a non-adjacent site (k1 = 1). Therefore, negative cooperativity was observed for all four additional H5 molecules (k1 < 1), while only for H2A/H2B histone dimers bound to NP adjacently. Since the source of the cooperativity interaction may be an allosteric conformational change in NP induced by histone binding or a direct histone-histone interaction upon binding, or/as well as a combination of both, our results indicate different origin of the negative cooperativity for the binding of H5 and H2A/H2B to NP. Hence the main source of the cooperative binding interaction of H2A/H2B dimers is H2A/H2B-H2A/H2B interaction, whereas a conformational change in the NP pentamer upon binding of the first H5 molecule should provide a less favourable binding interface for the next histone molecules through energetic communication.

Somewhat surprising, considering the strong opposite charge of NP and histones, the binding of both histone types to NP is dominated by a favourable entropic term indicating a strong contribution of the hydrophobic effect to the binding affinity (Figure 4, C and D). The enthalpic term also contributes favourably to the binding energy of H2A/H2B, while unfavourable enthalpy changes counterbalance the entropic contribution to the free energy of H5 binding (Figure 4, C and D).

Furthemore, and contrary to the generally accepted major determinant of tail "polyGlu" tract in histone binding, the thermodynamic analysis as well as the low resolution structural models of NP/histone complexes, constructed by small angle X-ray scattering (SAXS) [10], demonstrate clearly that both NP domains are involved in the interaction with histones.

This was evidenced by comparing the binding energetics of the full-length protein with that of isolated core domain (CORE). Interestingly, NP core domain contributes equally to the intrinsic binding energy of H5 and H2A/H2B (G = -8.2 kcal/mol). The tail domain of NP provides an additional thermodynamic driving force (estimated as the difference between the binding free energies of histones to NP and CORE, GNP-CORE) (Figure 4 and Figure 5) for the much stronger binding of H5 (GNP-COREH5 = -5.5 kcal/mol) compared to H2A/H2B (GNP-COREH2AAH2B = -1.6 kcal/mol) suggesting that this domain is particularly essential in the binding to H5 molecules.

To approach an activity/energetics relationship, we analysed the energetics of histone association with NP variants with phosphorylation-mimicking mutations in both the core and tail domains (NP8D, NP13D, CORE, CORE8D).

166 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 167

Although the hydrophobic interactions are the major source of NP/histone binding free energy (about 80% of the intrinsic free energy for H2A/H2B and about 60% of that for H5), electrostatic and polar interactions between the acidic NP and basic histones also play an important role, either in direct binding or helping in orienting properly the binding partners, given the structural features of NP and histones. In order to get more insight into the nature of binding interactions we studied the ionic strength effect on the binding energetics (Figure 7, left panel). We found that despite the highly charged nature of H5 and NP, the non-electrostatic interactions contribute stronger to the stabilization of NP/histone complexes than the electrostatic ones (Figure 7, right panel). The significantly lower observed free energy of binding G for H2A/H2B compared to H5 originates from lower Gel (electrostatic) term (the non-electrostatic term Gnel is comparable for H2A/H2B and H5), that should reflect the distinct number of positively charged residues in each histone type. For H2A/H2B and H5 binding to the NP13D mutant G is −9.8±0.1 and -11.9±0.14, and

the Gel term −2.6 kcal/mol and −5.1 kcal/mol, respectively (Figure 7, right panel).

**Figure 7.** Ionic strength dependence of the association constant of H5 binding to the first (■ ), nonadjacent (●) and adjacent (▲ ) binding sites of NP13D variant (left panel). Extrapolation of ∂ln(K) / ∂I1/2 to 1M NaCl yields the non-electrostatic contribution Gnel to the binding energy G. Contribution of Gnel and the electrostatic contribution, Gel, to G for H5 binding to CORE8D, NP and NP13D, and of

ITC data also show that the NP flexible tail domain undergoes a histone binding-induced transition to a more structured or ordered state. This follows from the conformational entropy difference between full length proteins and core domains. We estimated from the heat capacity change, that there is a conformational entropy loss of ca. -20 kcal/mol upon H5 binding to the full-length protein as compared to the core domain (and even higher ca. -33 kcal/mol for H5 binding to the mutant proteins, NP8D and CORE8D), that can be attributed to the ordering of the intrinsically disordered nucleoplasmin tails [5] when bound to

histones and indicates that NP tails do establish contacts with the histone molecules.

On the other hand, cP (obtained from the temperature dependence of H, presented for the NP13D variant in Figure 8) is smaller for the core domain NP variants compared to the full-

H2A/H2B to NP13D (right panel)

**Figure 5.** NP core (full bars) and tail (crossed bars) domain contributions to the intrinsic ΔG of their binding to linker and nucleosomal histones

As mentioned above the NP activity is regulated by its phosphorylation state. Insertion of mutations (8 and 13) gradually enhanced the binding affinity and affected to different extent the changes in the Gibbs energy contributors, the entropic and enthalpic terms. This reflects a strong impact of phosphorylation mimicking mutations in both core and tail domains of NP on its recognition by histones (Figure 6). The strongest affinity observed for the NP variant with the highest number of mutations, NP13D, is compatible with the fact that it mimicks the activity of the hyperphosphorylated native protein and can explain the protein activation through post-translational modifications.

**Figure 6.** Effect of phosphorylation mimicking mutations on the binding energetics. Bar graphs comparing the intrinsic Gibbs energy, enthalpy and entropy changes, for the intrinsic binding of the two histone types, H5 and H2A/H2B, to NP and the phosphomimicking mutants NP8D and NP13D

Although the hydrophobic interactions are the major source of NP/histone binding free energy (about 80% of the intrinsic free energy for H2A/H2B and about 60% of that for H5), electrostatic and polar interactions between the acidic NP and basic histones also play an important role, either in direct binding or helping in orienting properly the binding partners, given the structural features of NP and histones. In order to get more insight into the nature of binding interactions we studied the ionic strength effect on the binding energetics (Figure 7, left panel). We found that despite the highly charged nature of H5 and NP, the non-electrostatic interactions contribute stronger to the stabilization of NP/histone complexes than the electrostatic ones (Figure 7, right panel). The significantly lower observed free energy of binding G for H2A/H2B compared to H5 originates from lower Gel (electrostatic) term (the non-electrostatic term Gnel is comparable for H2A/H2B and H5), that should reflect the distinct number of positively charged residues in each histone type. For H2A/H2B and H5 binding to the NP13D mutant G is −9.8±0.1 and -11.9±0.14, and the Gel term −2.6 kcal/mol and −5.1 kcal/mol, respectively (Figure 7, right panel).

Applications of Calorimetry in a Wide Context –

binding to linker and nucleosomal histones

activation through post-translational modifications.

166 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 5.** NP core (full bars) and tail (crossed bars) domain contributions to the intrinsic ΔG of their

**Figure 6.** Effect of phosphorylation mimicking mutations on the binding energetics. Bar graphs comparing the intrinsic Gibbs energy, enthalpy and entropy changes, for the intrinsic binding of the two histone types, H5 and H2A/H2B, to NP and the phosphomimicking mutants NP8D and NP13D

As mentioned above the NP activity is regulated by its phosphorylation state. Insertion of mutations (8 and 13) gradually enhanced the binding affinity and affected to different extent the changes in the Gibbs energy contributors, the entropic and enthalpic terms. This reflects a strong impact of phosphorylation mimicking mutations in both core and tail domains of NP on its recognition by histones (Figure 6). The strongest affinity observed for the NP variant with the highest number of mutations, NP13D, is compatible with the fact that it mimicks the activity of the hyperphosphorylated native protein and can explain the protein

**Figure 7.** Ionic strength dependence of the association constant of H5 binding to the first (■ ), nonadjacent (●) and adjacent (▲ ) binding sites of NP13D variant (left panel). Extrapolation of ∂ln(K) / ∂I1/2 to 1M NaCl yields the non-electrostatic contribution Gnel to the binding energy G. Contribution of Gnel and the electrostatic contribution, Gel, to G for H5 binding to CORE8D, NP and NP13D, and of H2A/H2B to NP13D (right panel)

ITC data also show that the NP flexible tail domain undergoes a histone binding-induced transition to a more structured or ordered state. This follows from the conformational entropy difference between full length proteins and core domains. We estimated from the heat capacity change, that there is a conformational entropy loss of ca. -20 kcal/mol upon H5 binding to the full-length protein as compared to the core domain (and even higher ca. -33 kcal/mol for H5 binding to the mutant proteins, NP8D and CORE8D), that can be attributed to the ordering of the intrinsically disordered nucleoplasmin tails [5] when bound to histones and indicates that NP tails do establish contacts with the histone molecules.

On the other hand, cP (obtained from the temperature dependence of H, presented for the NP13D variant in Figure 8) is smaller for the core domain NP variants compared to the full168 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

length NP that would indicate a smaller molecular surface area involved in the binding of H5 to the core domain fragments than to full length NP.

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 169

assembly by removing the linker histones and depositing H2A/H2B dimers onto DNA

These data provided new insight into NP/histones assembly and interactions. It should be emphasized that the binding affinity of NP is enhanced upon insertion of phosphorylationmimicking mutations that explains the protein activation through post-translational modifications. Importantly the data reveal a negative cooperativity-based regulatory mechanism for the linker histone/nucleosomal histone exchange, that in general renders proteins operative in a wider concentration range [83], with significantly populated intermediate liganded states. The employed site-specific cooperativity model, an extension of a previous one that analyses the interaction of another pentameric protein (cholera toxin, with the oligosaccharide portion of its cell surface receptor) considering only nearestneighbour cooperative interactions [84], has potential application in studies of other macromolecular complexes between proteins sharing structural complexity with NP and

**6. Recognition of nucleoplasmin and histones by nuclear transport** 

of a large macromolecular nuclear import complex.

Nucleoplasmin, that possesses a classical bipartite NLS targeting sequence in each tail domain, is a prototypic substrate of the best characterized route for protein import into the nucleus, which is mediated by importin / heterodimer. However, as mentioned in Introduction, most structural and energetic approaches on cargo-import receptor recognition have been achieved merely using peptides carrying the corresponding NLS or IBB sequence [13, 85-91], and to date only two studies (besides ours [10]) deal with assembly of a macromolecular transport complex of full-length proteins [92,93]. On the other hand there has been paid little attention to nuclear import of oligomeric proteins. Therefore understanding the molecular basis of recognition of an oligomeric cargo as nucleoplasmin by its transport receptors, importin heterodimer, would shed light on the arrangement

We obtained saturated NP/importin /β complexes proving that all five available NLS binding sites of NP can be occupied by importins. Whereas *in vivo* binding of one /β heterodimer to any protein should be enough to deliver it to the nucleus, it has been reported that the presence of multiple NLSs in NP [94] enhances its nuclear accumulation, suggesting that the number of NLSs might govern the traffic rate, which would play an advantage for oligomeric nuclear proteins, provided with multiple recognition sites. The binding isotherms of the NP//β complex formation (Figure 9A) were well fitted with an independent binding sites model, reflecting that NP makes use of different energetic scheme for assembling with histones and importins, most likely due to the involvement of dissimilar binding surfaces. The binding reaction is enthalpy-driven and counterbalanced by an unfavorable entropy change (Figure 9B) resulting in a relatively high-affinity interaction, Kb = 18.5 × 106 M-1 (Kd = 57 ± 15 nM). The entropic penalty most probably reflects an ordering effect on the otherwise flexible and mobile NLS motifs [5] upon the interaction event. This

[1,2,82].

their ligands.

**receptors** 

Since no high resolution structural data are available for the NP/histone complexes the experimental cP heat capacity changes cannot be compared with the ones estimated from structural data. We therefore roughly estimated the area buried within the binding interface from the SAXS data, in terms of "dummy" atoms of the corresponding "phase" that are in contact with the atoms of another "phase" in MONSA models (for details on SAXS experiments and data analysis see ref.[10]).

**Figure 8.** Temperature dependence of the thermodynamic parameters of the binding of the first H5 molecule to NP13D mutant. Intrinsic enthalpy (H, ■ ), entropy (-TS, ●) and free energy (G, ▲ ) of binding. The heat capacity change cP (cP = (∂H/∂T)) is determined from linear regression analysis of ∆H data (solid line). The intrinsic free energy of binding is almost independent of temperature reflecting compensation of the enthalpic and entropic terms

The interaction interface area corresponding to NP tail/H5 is approximately double that of NP core/H5, whereas NP tail/H2A/H2B is half of that of NP core/H2A/H2B, which reflects strong difference in the binding of NP tails to both histone types. Although the ratio of the interaction interface areas NP core/NP tails is a rough estimate, it well compares with the ratio estimated from the experimentally determined heat capacity changes, cPNPcore/cPNPtails (cPNPtails = cPNP - cPcore).

The significant differences between the intrinsic association constants and the cooperative character of NP binding to the nucleosomal and the linker histones defines different "affinity windows" for NP binding from picomolar to nanomolar and from nanomolar to micromolar for H5 and H2A/H2B, respectively. This difference in recognition of nucleosomal and linker histones might provide an efficient mechanism for regulation of the dynamic histone exchange and might allow NP to fulfill its histone chaperone role, simultaneously acting as a reservoir for the core histones and a chromatin decondensing factor. Our data are compatible with the traditional model where NP facilitates nucleosome assembly by removing the linker histones and depositing H2A/H2B dimers onto DNA [1,2,82].

Applications of Calorimetry in a Wide Context –

experiments and data analysis see ref.[10]).

compensation of the enthalpic and entropic terms

(cPNPtails = cPNP - cPcore).

168 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

H5 to the core domain fragments than to full length NP.

length NP that would indicate a smaller molecular surface area involved in the binding of

Since no high resolution structural data are available for the NP/histone complexes the experimental cP heat capacity changes cannot be compared with the ones estimated from structural data. We therefore roughly estimated the area buried within the binding interface from the SAXS data, in terms of "dummy" atoms of the corresponding "phase" that are in contact with the atoms of another "phase" in MONSA models (for details on SAXS

**Figure 8.** Temperature dependence of the thermodynamic parameters of the binding of the first H5 molecule to NP13D mutant. Intrinsic enthalpy (H, ■ ), entropy (-TS, ●) and free energy (G, ▲ ) of binding. The heat capacity change cP (cP = (∂H/∂T)) is determined from linear regression analysis of ∆H data (solid line). The intrinsic free energy of binding is almost independent of temperature reflecting

The interaction interface area corresponding to NP tail/H5 is approximately double that of NP core/H5, whereas NP tail/H2A/H2B is half of that of NP core/H2A/H2B, which reflects strong difference in the binding of NP tails to both histone types. Although the ratio of the interaction interface areas NP core/NP tails is a rough estimate, it well compares with the ratio estimated from the experimentally determined heat capacity changes, cPNPcore/cPNPtails

The significant differences between the intrinsic association constants and the cooperative character of NP binding to the nucleosomal and the linker histones defines different "affinity windows" for NP binding from picomolar to nanomolar and from nanomolar to micromolar for H5 and H2A/H2B, respectively. This difference in recognition of nucleosomal and linker histones might provide an efficient mechanism for regulation of the dynamic histone exchange and might allow NP to fulfill its histone chaperone role, simultaneously acting as a reservoir for the core histones and a chromatin decondensing factor. Our data are compatible with the traditional model where NP facilitates nucleosome These data provided new insight into NP/histones assembly and interactions. It should be emphasized that the binding affinity of NP is enhanced upon insertion of phosphorylationmimicking mutations that explains the protein activation through post-translational modifications. Importantly the data reveal a negative cooperativity-based regulatory mechanism for the linker histone/nucleosomal histone exchange, that in general renders proteins operative in a wider concentration range [83], with significantly populated intermediate liganded states. The employed site-specific cooperativity model, an extension of a previous one that analyses the interaction of another pentameric protein (cholera toxin, with the oligosaccharide portion of its cell surface receptor) considering only nearestneighbour cooperative interactions [84], has potential application in studies of other macromolecular complexes between proteins sharing structural complexity with NP and their ligands.

### **6. Recognition of nucleoplasmin and histones by nuclear transport receptors**

Nucleoplasmin, that possesses a classical bipartite NLS targeting sequence in each tail domain, is a prototypic substrate of the best characterized route for protein import into the nucleus, which is mediated by importin / heterodimer. However, as mentioned in Introduction, most structural and energetic approaches on cargo-import receptor recognition have been achieved merely using peptides carrying the corresponding NLS or IBB sequence [13, 85-91], and to date only two studies (besides ours [10]) deal with assembly of a macromolecular transport complex of full-length proteins [92,93]. On the other hand there has been paid little attention to nuclear import of oligomeric proteins. Therefore understanding the molecular basis of recognition of an oligomeric cargo as nucleoplasmin by its transport receptors, importin heterodimer, would shed light on the arrangement of a large macromolecular nuclear import complex.

We obtained saturated NP/importin /β complexes proving that all five available NLS binding sites of NP can be occupied by importins. Whereas *in vivo* binding of one /β heterodimer to any protein should be enough to deliver it to the nucleus, it has been reported that the presence of multiple NLSs in NP [94] enhances its nuclear accumulation, suggesting that the number of NLSs might govern the traffic rate, which would play an advantage for oligomeric nuclear proteins, provided with multiple recognition sites. The binding isotherms of the NP//β complex formation (Figure 9A) were well fitted with an independent binding sites model, reflecting that NP makes use of different energetic scheme for assembling with histones and importins, most likely due to the involvement of dissimilar binding surfaces. The binding reaction is enthalpy-driven and counterbalanced by an unfavorable entropy change (Figure 9B) resulting in a relatively high-affinity interaction, Kb = 18.5 × 106 M-1 (Kd = 57 ± 15 nM). The entropic penalty most probably reflects an ordering effect on the otherwise flexible and mobile NLS motifs [5] upon the interaction event. This

loss of conformational flexibility of the NLS segment in the NP tails [5] is estimated to correspond to conformational entropy change ΔSconf = -282 cal mol-1 K-1 (using eq. 6) that dominates the entropic penalty. This conformational entropy change is unfavorable and greater than the favorable solvation entropy (ΔSsolv = 223 cal mol-1K-1, calculated from eq. 5), associated with hydrophobic interactions, thus resulting in an unfavorable entropy contribution to the Gibbs free energy of binding (Figure 9C).

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 171

Since protein phosphorylation is one of the mechanisms that up- or down-regulate nuclear transport [95,96] and it had been described that phosphorylated nucleoplasmin presents higher import rate than its unphosphorylated form [79], we studied how phosphorylation of NP affects its interaction with the import receptor. Nevertheless, phosphorylation mimicking mutations in residues close to NLS sequence, as in mutant NP13D, which shows high binding affinity to histones and is active in histone chaperoning, do not modulate the interaction with importin. NP13D mutant displays the same binding strength (ΔG), though different ΔH and –TΔS terms, compared to unphosphorylated protein (Figure 10). No effect has been observed when phosphorylated monopartite NLS from simian virus 40-large T antigen interacts with importin [97]. Altogether, phosphorylation-mediated regulation of nuclear import must involve interactions other than post-translationally modified NLS with

**Figure 10.** Comparison of the energetics (ΔG, ΔH and -TΔS) of importin binding to NP and NP13D

Importin binds similarly to a peptide corresponding to the NLS sequence when the latter is isolated or in the context of the full-length NP macromolecule, suggesting that no other regions of NP contribute significantly to the binding. The similar large negative ΔcP values, - 817 and -796 cal mol-1 K-1 for NLS and full-length NP respectively, also suggest that the surface area buried within the binding interface is comparable in both cases. It is not surprising that the NLS recognition is not significantly affected by the protein context considering the flexibility displayed by NP tail domains harboring the NLS segments. The same notion applies to the interaction of importin IBB domain with importin . The former domain binds likewise to importin independently of whether it is an isolated peptide or connected to the ARM domain of importin , as is evidenced by the good correspondence of the heat capacity ΔcP value of -727.4 cal mol-1 K-1, predicted from the Xray structure of importin β bound to the IBB domain of importin [98], with buried polar

importin.

mutant

**Figure 9.** Energetics of NP assembly with the nuclear transport receptor importin /. Binding isotherms: the upper panel represents baseline-corrected instrumental response of importin / titration with NP; the lower panel shows the integrated data and the fit of the binding isotherm (solid line) by an independent binding site model (A). Enthalpic (H) and entropic (-TS) contributions to the free energy (G) of binding (B). Dissection of the binding entropy, S, into solvation, Ssolv, and conformational, Sconf, terms (C)

Similar binding mode and thermodynamic parameters (ΔG = -8.67 0.1 kcal/mol, ΔH = -15 0.3 kcal/mol and stoichiometry 5 per NPM pentamer) characterize the recognition of nucleophosmin (NPM), an abundant nucleolar protein, structurally homologous to nucleoplasmin (as mentioned in the Introduction) and related to oncogenic transformation, by the nuclear transport machinery (unpublished data), which supports an equivalent import mechanism for both chaperones.

Full-length importin , not assembled with importin β, is also able to bind NP, albeit with a lower apparent affinity (Kd = 513 ± 87 nM) and with a lower enthalpic contribution to the free energy of binding. The loss of apparent affinity comes from the fact that the importin N-terminal domain, the IBB domain, which contains a similar sequence to the NP-NLS, exerts an autoinhibitory role in the binding process [90,91] because in the absence of importin β, it occupies the NLS binding site and therefore it must be displaced by NP-NLSs. In this regard a truncated importin mutant lacking the IBB domain, ΔIBB-importin or Δ, shows a similar affinity for NP (Kd = 54 ± 6 nM) as importin /β [15].

Since protein phosphorylation is one of the mechanisms that up- or down-regulate nuclear transport [95,96] and it had been described that phosphorylated nucleoplasmin presents higher import rate than its unphosphorylated form [79], we studied how phosphorylation of NP affects its interaction with the import receptor. Nevertheless, phosphorylation mimicking mutations in residues close to NLS sequence, as in mutant NP13D, which shows high binding affinity to histones and is active in histone chaperoning, do not modulate the interaction with importin. NP13D mutant displays the same binding strength (ΔG), though different ΔH and –TΔS terms, compared to unphosphorylated protein (Figure 10). No effect has been observed when phosphorylated monopartite NLS from simian virus 40-large T antigen interacts with importin [97]. Altogether, phosphorylation-mediated regulation of nuclear import must involve interactions other than post-translationally modified NLS with importin.

Applications of Calorimetry in a Wide Context –

conformational, Sconf, terms (C)

import mechanism for both chaperones.

170 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

contribution to the Gibbs free energy of binding (Figure 9C).

loss of conformational flexibility of the NLS segment in the NP tails [5] is estimated to correspond to conformational entropy change ΔSconf = -282 cal mol-1 K-1 (using eq. 6) that dominates the entropic penalty. This conformational entropy change is unfavorable and greater than the favorable solvation entropy (ΔSsolv = 223 cal mol-1K-1, calculated from eq. 5), associated with hydrophobic interactions, thus resulting in an unfavorable entropy

**Figure 9.** Energetics of NP assembly with the nuclear transport receptor importin /. Binding

isotherms: the upper panel represents baseline-corrected instrumental response of importin / titration with NP; the lower panel shows the integrated data and the fit of the binding isotherm (solid line) by an independent binding site model (A). Enthalpic (H) and entropic (-TS) contributions to the free energy (G) of binding (B). Dissection of the binding entropy, S, into solvation, Ssolv, and

Similar binding mode and thermodynamic parameters (ΔG = -8.67 0.1 kcal/mol, ΔH = -15 0.3 kcal/mol and stoichiometry 5 per NPM pentamer) characterize the recognition of nucleophosmin (NPM), an abundant nucleolar protein, structurally homologous to nucleoplasmin (as mentioned in the Introduction) and related to oncogenic transformation, by the nuclear transport machinery (unpublished data), which supports an equivalent

Full-length importin , not assembled with importin β, is also able to bind NP, albeit with a lower apparent affinity (Kd = 513 ± 87 nM) and with a lower enthalpic contribution to the free energy of binding. The loss of apparent affinity comes from the fact that the importin N-terminal domain, the IBB domain, which contains a similar sequence to the NP-NLS, exerts an autoinhibitory role in the binding process [90,91] because in the absence of importin β, it occupies the NLS binding site and therefore it must be displaced by NP-NLSs. In this regard a truncated importin mutant lacking the IBB domain, ΔIBB-importin or Δ,

shows a similar affinity for NP (Kd = 54 ± 6 nM) as importin /β [15].

**Figure 10.** Comparison of the energetics (ΔG, ΔH and -TΔS) of importin binding to NP and NP13D mutant

Importin binds similarly to a peptide corresponding to the NLS sequence when the latter is isolated or in the context of the full-length NP macromolecule, suggesting that no other regions of NP contribute significantly to the binding. The similar large negative ΔcP values, - 817 and -796 cal mol-1 K-1 for NLS and full-length NP respectively, also suggest that the surface area buried within the binding interface is comparable in both cases. It is not surprising that the NLS recognition is not significantly affected by the protein context considering the flexibility displayed by NP tail domains harboring the NLS segments. The same notion applies to the interaction of importin IBB domain with importin . The former domain binds likewise to importin independently of whether it is an isolated peptide or connected to the ARM domain of importin , as is evidenced by the good correspondence of the heat capacity ΔcP value of -727.4 cal mol-1 K-1, predicted from the Xray structure of importin β bound to the IBB domain of importin [98], with buried polar

172 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and apolar solvent accessible areas (ΔASA) of 1402.5 and 2426.7 Ǻ2, respectively (eq. 4), and the experimentally determined ΔcP = -840 cal mol-1 K-1 value for full length interaction. Moreover, both proteins behave as independent units when they form the heterodimer complex since they display the same thermal stability as the one they exhibit when free in solution, thanks to flexibility of the linker between the IBB and the rest of importin [15]. These data support the idea that residues which act as link between both importins exhibit such flexibility that allows each of the importin entities to interact with a wide range of ligands during the nuclear translocation process.

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 173

number of importin molecules can be loaded on NP/histone complexes, in which can bind both to NP-NLS as to histones-NLS-like binding sites, as was demonstrated using a NP mutant with impaired binding to . The binding is an enthalpy driven process and it is

0 2 4 6 8 10 12

**NP**

**[importin ]/[histones] [importin ]/[NP]**

**Figure 11.** ITC isotherms for the binding interactions of the nucleosomal, H2A/H2B (violet) and linker, H5 (blue) histones, and NP (pink) with importin ∆IBB (a truncated form lacking the autoinhibitory N-

We have also described the formation of quaternary NP/H5/importin / complexes by means of fluorescence and centrifugation, which makes conceivable that heterodimer might "pull" NP/histones complexes into the nucleus, importin α binding either to NP, histones or both. Since importin binds to both linker and core histones, NP/histones cotransport mediated by importin , could also be expected. However, this hypothetical route seems unlikely since importin competes with NP for histones, inducing the release of the latter from NP (unpublished data). Even though no detailed study has been performed, the comparable thermodynamic signature for H5/importin and H5/importin interaction supports the notion that H5 always binds through importin in the presence of heterodimer, which would explain the formation of quaternary complexes. Therefore the assembly of NP/histone/importin complexes might have physiological meaning since it supports the existence of a putative and redundant histone import pathway in which positively charged histones would be protected against unspecific interactions by the

In summary, we have highlighted the importance of calorimetry in the study of nuclear chaperones. Detailed analysis demonstrated that the nuclear chaperone NP can associate with the two histone types and the transport machinery, and that co-complexes of NP, histones, and importins can assemble proving that ITC is suitable to study biological

**H5**

characterized by nanomolar affinity [16].

terminal domain)

histone chaperone nucleoplasmin.

**7. Conclusion and future prospects** 




**kcal mol-1 of injectant**


**H2AH2B**


0

Given the fact that the NP//β complexes are formed by multiple proteins that present flexible domains, SAXS technique has provided valuable information about the structure of those assemblies. Multiple models of NP fit equally well the experimental SAXS data reflecting the inherent flexibility of the particle, due to the adaptable linkers between the NP core domain and the NLS (residues 121-154 of NP) [15], which allows the accommodation of five bulky heterodimers per NP pentamer. This 3D in solution structural model, the first one for a complete nuclear transport complex with an oligomeric cargo, is consistent with the notion that the canonical binding elements (NLS and IBB) are the ones determining the molecular basis of the recognition. The multidomain NP//β complex remains stable by virtue of two attachment points: recognition of the NLS by importin and recognition of the IBB domain by importin β, which otherwise allow for conformational flexibility. This modular and articulated architecture might facilitate the passage of such a large particle through the nuclear pore complex.

Due to their highly basic nature histones need nuclear import receptors to be transferred to the nucleus, and most of the pathways described are mainly mediated by karyopherins of family [99,100]. On the other hand, histones present multiple NLS-like motives and are also recognized by importin family members for nuclear targeting [101]. Accordingly, we observed that both nucleosomal and linker histones bind to importin β (unpublished data), as previously demonstrated, and to importin Δα [16]. The high affinity exothermic binding interactions (Figure 11) suggest specific recognition events of importin Δα by H5 and H2A/H2B. Regardless of the different stoichiometry, two importin Δα per H5 and one per H2A/H2B, the thermodynamic parameters are quite similar, the apparent binding affinity and the enthalpy are in the order of 9 and 28 nM, and −20 and −17 kcal/mol for H2A/H2B and H5, respectively. Similar binding energetics, though higher stoichiometry (five per NP pentamer), characterizes the assembly of importin Δα with NP (Kd = 54 nM and H = -18.5 kcal/mol, Figure 11). This suggests that similar molecular interactions are involved in the complex formation of importin Δα with the binding motifs of the two histone types and of NP.

Importantly, ITC together with fluorescence anisotropy and centrifugation in sucrose gradients show that NP, histones and importin can associate and form co-complexes, NP/H5/importin and NP/H2A/H2B/importin of discrete size, that would support a co-transport of histones and NP to the nucleus, mediated by the classical import pathway. Depending on the histone type, linker or core, and the amount of bound histones, different number of importin molecules can be loaded on NP/histone complexes, in which can bind both to NP-NLS as to histones-NLS-like binding sites, as was demonstrated using a NP mutant with impaired binding to . The binding is an enthalpy driven process and it is characterized by nanomolar affinity [16].

**Figure 11.** ITC isotherms for the binding interactions of the nucleosomal, H2A/H2B (violet) and linker, H5 (blue) histones, and NP (pink) with importin ∆IBB (a truncated form lacking the autoinhibitory Nterminal domain)

We have also described the formation of quaternary NP/H5/importin / complexes by means of fluorescence and centrifugation, which makes conceivable that heterodimer might "pull" NP/histones complexes into the nucleus, importin α binding either to NP, histones or both. Since importin binds to both linker and core histones, NP/histones cotransport mediated by importin , could also be expected. However, this hypothetical route seems unlikely since importin competes with NP for histones, inducing the release of the latter from NP (unpublished data). Even though no detailed study has been performed, the comparable thermodynamic signature for H5/importin and H5/importin interaction supports the notion that H5 always binds through importin in the presence of heterodimer, which would explain the formation of quaternary complexes. Therefore the assembly of NP/histone/importin complexes might have physiological meaning since it supports the existence of a putative and redundant histone import pathway in which positively charged histones would be protected against unspecific interactions by the histone chaperone nucleoplasmin.

#### **7. Conclusion and future prospects**

Applications of Calorimetry in a Wide Context –

ligands during the nuclear translocation process.

through the nuclear pore complex.

NP.

172 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and apolar solvent accessible areas (ΔASA) of 1402.5 and 2426.7 Ǻ2, respectively (eq. 4), and the experimentally determined ΔcP = -840 cal mol-1 K-1 value for full length interaction. Moreover, both proteins behave as independent units when they form the heterodimer complex since they display the same thermal stability as the one they exhibit when free in solution, thanks to flexibility of the linker between the IBB and the rest of importin [15]. These data support the idea that residues which act as link between both importins exhibit such flexibility that allows each of the importin entities to interact with a wide range of

Given the fact that the NP//β complexes are formed by multiple proteins that present flexible domains, SAXS technique has provided valuable information about the structure of those assemblies. Multiple models of NP fit equally well the experimental SAXS data reflecting the inherent flexibility of the particle, due to the adaptable linkers between the NP core domain and the NLS (residues 121-154 of NP) [15], which allows the accommodation of five bulky heterodimers per NP pentamer. This 3D in solution structural model, the first one for a complete nuclear transport complex with an oligomeric cargo, is consistent with the notion that the canonical binding elements (NLS and IBB) are the ones determining the molecular basis of the recognition. The multidomain NP//β complex remains stable by virtue of two attachment points: recognition of the NLS by importin and recognition of the IBB domain by importin β, which otherwise allow for conformational flexibility. This modular and articulated architecture might facilitate the passage of such a large particle

Due to their highly basic nature histones need nuclear import receptors to be transferred to the nucleus, and most of the pathways described are mainly mediated by karyopherins of family [99,100]. On the other hand, histones present multiple NLS-like motives and are also recognized by importin family members for nuclear targeting [101]. Accordingly, we observed that both nucleosomal and linker histones bind to importin β (unpublished data), as previously demonstrated, and to importin Δα [16]. The high affinity exothermic binding interactions (Figure 11) suggest specific recognition events of importin Δα by H5 and H2A/H2B. Regardless of the different stoichiometry, two importin Δα per H5 and one per H2A/H2B, the thermodynamic parameters are quite similar, the apparent binding affinity and the enthalpy are in the order of 9 and 28 nM, and −20 and −17 kcal/mol for H2A/H2B and H5, respectively. Similar binding energetics, though higher stoichiometry (five per NP pentamer), characterizes the assembly of importin Δα with NP (Kd = 54 nM and H = -18.5 kcal/mol, Figure 11). This suggests that similar molecular interactions are involved in the complex formation of importin Δα with the binding motifs of the two histone types and of

Importantly, ITC together with fluorescence anisotropy and centrifugation in sucrose gradients show that NP, histones and importin can associate and form co-complexes, NP/H5/importin and NP/H2A/H2B/importin of discrete size, that would support a co-transport of histones and NP to the nucleus, mediated by the classical import pathway. Depending on the histone type, linker or core, and the amount of bound histones, different

In summary, we have highlighted the importance of calorimetry in the study of nuclear chaperones. Detailed analysis demonstrated that the nuclear chaperone NP can associate with the two histone types and the transport machinery, and that co-complexes of NP, histones, and importins can assemble proving that ITC is suitable to study biological

Applications of Calorimetry in a Wide Context – 174 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

recognition in complex macromolecular assemblies. Notably, a link between NP phosphorylation state, its stability and the strength with which it assembles with histones is demonstrated.

Thermodynamic Signatures of Macromolecular

Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 175

*Unidad de Biofísica (CSIC/UPV-EHU), Departamento de Bioquímica y Biología Molecular,* 

[1] Prado A, Ramos I, Frehlick LJ, Muga A, Ausió J (2004) Nucleoplasmin: a nuclear

[2] Frehlick LJ, Eirín-López JM, Ausió J (2007) New insights into the nucleophosmin/nucleoplasmin family of nuclear chaperones. Bioessays 29, 49-59. [3] Dutta S, Akey IV, Dingwall C, Hartman KL, Laue T, Nolte RT, Head JF, Akey CW (2001) The crystal structure of nucleoplasmin-core: implications for histone binding and

[4] Hierro A, Arizmendi JM, Bañuelos S, Prado A, Muga A (2002) Electrostatic interactions at the C-terminal domain of nucleoplasmin modulate its chromatin decondensation

[5] Hierro A, Arizmendi JM, De las Rivas J, Urbaneja MA, Prado A, Muga A (2001) Structural and functional properties of Escherichia coli-derived nucleoplasmin. A comparative study of recombinant and natural proteins. Eur. J. Biochem. 268, 1739-

[6] Sickmeier M, Hamilton JA, Le Gall T, Vacic V, Cortese MS, Tantos A, Szabo B, Tompa P, Chen J, Uversky VN, Obradovic Z, Dunker AK (2007) DisProt: the Database of

[7] Cotten M, Sealy L, Chalkley R (1986) Massive phosphorylation distinguishes Xenopus laevis nucleoplasmin isolated from oocytes or unfertilized eggs. Biochemistry 25, 5063–

[8] Bañuelos S, Omaetxebarria MJ, Ramos I, Larsen MR, Arregi I, Jensen OM, Arizmendi JM, Prado A, Muga A (2007) Phosphorylation of both nucleoplasmin domains is required for activation of its chromatin decondensation activity. J. Biol. Chem. 282,

[9] Taneva SG, Muñoz I, Franco G, Falces J, Arregi I, Muga A, Montoya G, Urbaneja MA, Bañuelos S (2008) Activation of nucleoplasmin, an oligomeric histone chaperone,

[10] Taneva SG, Bañuelos S, Arregi I, Falces J, Konarev P, Svergun D, Velázquez-Campoy A, Urbaneja MA (2009). A mechanism for histone chaperoning activity of nucleoplasmin:

[11] Görlich D, Kutay U (1999) Transport between the cell nucleus and the cytoplasm. Annu.

[12] Stewart M (2007) Molecular mechanism of the nuclear protein import cycle. Nat. Rev.

Sonia Bañuelos and María A. Urbaneja

*Universidad del País Vasco, Bilbao, Spain* 

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**8. References** 

1748.

5069.

21213-21221.

One key feature of NP assembly with histones is the negative cooperative interactions, that render the protein operative in a wider concentration range and is an effective mechanism of regulation of the activity of macromolecular complexes. We have dissected the thermodynamic cooperativity of NP and its variants, core domain fragments and phosphorylation mimicking mutants, and presented strong evidence of the involvement of both NP domains in binding of histones, the NP tail domain being particularly essential in the assembly with H5 molecules. Only the nuclear localization signal NLS, however, is the recognition site in the multi-component NP/importin / complex. The significant differences in the enthalpic and entropic terms of the Gibbs free energy of NP association with histones and importins reflect different energetic strategy for NP chaperoning functions and its recognition for nuclear trafficking.

Both the experimental results and the methodological approach, ITC complemented with SAXS, allow a mechanistic understanding of nucleosome assembly/disassembly and its nuclear trafficking. The NP/histone complexes, which were modeled using five-fold symmetry, have a much more compact shape than the NP/importin /β complex, reconstructed with multiple models, reflecting inherent flexibility.

Future work should focus towards description of the energetics of NPM export mechanism and the molecular recognition between NPM and nuclear export machinery (exportin), as well as with other proteins and peptides/small molecules. NPM is overexpressed in solid cancers (gastric, colon, ovarian and prostate), while genetic modifications of *NPM1* gene by chromosomal translocation, mutation and deletion are involved in lymphomas and leukemias [102-105]. Mutations of *NPM1* gene result in aberrant cytoplasmic localization of NPM in about 35% of acute myeloid leukemia (AML) patients [102]. The involvement of NPM in human cancer has received an increasing research interest during the last years, but the molecular mechanism of NPM implication in leukaemia and tumorigenesis is not understood yet. Studying the energetics of NPM binding with different (de)stabilizing ligands/drugs would help to regulate its interaction with cellular partners and thereby control its localization and function. This will entail, on one hand knowledge about the NPM nucleo-cytoplasmic shuttling and on the other is expected to provide a strategy for molecular therapeutics.

### **Author details**

Stefka G. Taneva *Unidad de Biofísica (CSIC/UPV-EHU), Departamento de Bioquímica y Biología Molecular, Universidad del País Vasco, Bilbao, Spain, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria*  Sonia Bañuelos and María A. Urbaneja

*Unidad de Biofísica (CSIC/UPV-EHU), Departamento de Bioquímica y Biología Molecular, Universidad del País Vasco, Bilbao, Spain* 

### **8. References**

Applications of Calorimetry in a Wide Context –

functions and its recognition for nuclear trafficking.

reconstructed with multiple models, reflecting inherent flexibility.

demonstrated.

molecular therapeutics.

*Universidad del País Vasco, Bilbao, Spain,* 

**Author details** 

Stefka G. Taneva

174 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

recognition in complex macromolecular assemblies. Notably, a link between NP phosphorylation state, its stability and the strength with which it assembles with histones is

One key feature of NP assembly with histones is the negative cooperative interactions, that render the protein operative in a wider concentration range and is an effective mechanism of regulation of the activity of macromolecular complexes. We have dissected the thermodynamic cooperativity of NP and its variants, core domain fragments and phosphorylation mimicking mutants, and presented strong evidence of the involvement of both NP domains in binding of histones, the NP tail domain being particularly essential in the assembly with H5 molecules. Only the nuclear localization signal NLS, however, is the recognition site in the multi-component NP/importin / complex. The significant differences in the enthalpic and entropic terms of the Gibbs free energy of NP association with histones and importins reflect different energetic strategy for NP chaperoning

Both the experimental results and the methodological approach, ITC complemented with SAXS, allow a mechanistic understanding of nucleosome assembly/disassembly and its nuclear trafficking. The NP/histone complexes, which were modeled using five-fold symmetry, have a much more compact shape than the NP/importin /β complex,

Future work should focus towards description of the energetics of NPM export mechanism and the molecular recognition between NPM and nuclear export machinery (exportin), as well as with other proteins and peptides/small molecules. NPM is overexpressed in solid cancers (gastric, colon, ovarian and prostate), while genetic modifications of *NPM1* gene by chromosomal translocation, mutation and deletion are involved in lymphomas and leukemias [102-105]. Mutations of *NPM1* gene result in aberrant cytoplasmic localization of NPM in about 35% of acute myeloid leukemia (AML) patients [102]. The involvement of NPM in human cancer has received an increasing research interest during the last years, but the molecular mechanism of NPM implication in leukaemia and tumorigenesis is not understood yet. Studying the energetics of NPM binding with different (de)stabilizing ligands/drugs would help to regulate its interaction with cellular partners and thereby control its localization and function. This will entail, on one hand knowledge about the NPM nucleo-cytoplasmic shuttling and on the other is expected to provide a strategy for

*Unidad de Biofísica (CSIC/UPV-EHU), Departamento de Bioquímica y Biología Molecular,* 

*Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria* 


	- [13] Fontes M R, Teh T, Kobe B (2000) Structural basis of recognition of monopartite and bipartite nuclear localization sequences by mammalian importin-. J. Mol. Biol. 297, 1183–1194.

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Insights on the Stability and Interactions of Nucleoplasmin, a Nuclear Chaperone 177

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[34] Shiou-Ru T, Charalampos GK (2009) Dynamic activation of an allosteric regulatory

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**Section 3** 

**Application of MicroCalorimetry to Study** 

**Protein Stability and Folding Reversibility** 

**Application of MicroCalorimetry to Study Protein Stability and Folding Reversibility** 

Applications of Calorimetry in a Wide Context –

Reviews 6, 493-505.

182 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[105] Grisendi S, Mecucci C, Falini B, Pandolfi PP (2006) Nucleophosmin and cancer. Nature

**Chapter 8** 

© 2013 Elkordy et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Determination of Folding Reversibility of** 

Amal A. Elkordy, Robert T. Forbes and Brian W. Barry

groups and maximises exposure of polar groups to the solvent [2].

that deduce stability within a given biomolecule [10].

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/51131

**1. Introduction** 

**Lysozyme Crystals Using Microcalorimetry** 

An important aspect in the preparation of proteins as pharmaceutical products is stabilisation of the native protein conformation (folded, three-dimensional, tertiary state), which is required for biological activity. Moreover, it is not enough for this conformation to be stable, but the protein must be able to find the state or folding pathway in a short time from a denatured, unfolded conformation [1]. Folding minimises exposure of non-polar

Lysozyme, a globular protein, molecular weight 14,300 Da, was chosen as a model protein; it consists of a single 129 amino acid chain divided into two domains cross linked by four disulfide bridges. The hydrophilic groups tend to concentrate on the surface and the hydrophobic groups in the core [3]. The goal of this study was to investigate the influences of crystallisation on folding reversibility of lysozyme in solution as assessed calorimetrically. Many literature reports cited the value of High Sensitivity Differential Scanning Calorimetry (HSDSC) for determining thermodynamic parameters (transition temperature, *Tm*, and enthalpies, H) that describe the folded and unfolded states [4-6]. Furthermore, HSDSC was used to measure thermal transition reversibility that is no less important than *Tm* and H [7- 8]; a protein transition is considered reversible if the molecule renatures upon cooling after heat treatment. Thermodynamic or conformational stability is defined as the difference in free energy (G) between the folded and unfolded state. This stability is the sum of weak non-covalent interactions including hydrogen bonds, van der Waal interactions, salt bridges and hydrophobic forces [9]. Thermodynamic stability is divided into biophysical, which includes the study of thermodynamics, protein denaturation and renaturation (as is discussed in this Chapter) and biochemical, which involves comparative studies of protein conformation and stability of two or more proteins to establish various structural features

## **Determination of Folding Reversibility of Lysozyme Crystals Using Microcalorimetry**

Amal A. Elkordy, Robert T. Forbes and Brian W. Barry

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/51131

### **1. Introduction**

An important aspect in the preparation of proteins as pharmaceutical products is stabilisation of the native protein conformation (folded, three-dimensional, tertiary state), which is required for biological activity. Moreover, it is not enough for this conformation to be stable, but the protein must be able to find the state or folding pathway in a short time from a denatured, unfolded conformation [1]. Folding minimises exposure of non-polar groups and maximises exposure of polar groups to the solvent [2].

Lysozyme, a globular protein, molecular weight 14,300 Da, was chosen as a model protein; it consists of a single 129 amino acid chain divided into two domains cross linked by four disulfide bridges. The hydrophilic groups tend to concentrate on the surface and the hydrophobic groups in the core [3]. The goal of this study was to investigate the influences of crystallisation on folding reversibility of lysozyme in solution as assessed calorimetrically.

Many literature reports cited the value of High Sensitivity Differential Scanning Calorimetry (HSDSC) for determining thermodynamic parameters (transition temperature, *Tm*, and enthalpies, H) that describe the folded and unfolded states [4-6]. Furthermore, HSDSC was used to measure thermal transition reversibility that is no less important than *Tm* and H [7- 8]; a protein transition is considered reversible if the molecule renatures upon cooling after heat treatment. Thermodynamic or conformational stability is defined as the difference in free energy (G) between the folded and unfolded state. This stability is the sum of weak non-covalent interactions including hydrogen bonds, van der Waal interactions, salt bridges and hydrophobic forces [9]. Thermodynamic stability is divided into biophysical, which includes the study of thermodynamics, protein denaturation and renaturation (as is discussed in this Chapter) and biochemical, which involves comparative studies of protein conformation and stability of two or more proteins to establish various structural features that deduce stability within a given biomolecule [10].

© 2013 Elkordy et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Differential scanning calorimetry has the ability to provide detailed information about both the physical and energetic properties of a substance [11]. The HSDSC technique was described in detail by Cooper and Johnson (1994) [12]. In summary, all equilibrium processes involving molecules are governed by free energy changes (G), made up of enthalpy (H) and entropy (S). The relationship between (H) and (S) is given by the Gibbs free energy equation:

$$
\Delta \mathbf{G} = \Delta \mathbf{H} - \mathbf{T} . \tag{1}
$$

Determination of Folding Reversibility of Lysozyme Crystals Using Microcalorimetry 187

assuming that (H0) and (S0) do not vary significantly with temperature over the range of

The HSDSC provides an insight into the thermal stability and instability (e.g. formation of soluble and insoluble aggregates) of solutions of different formulations. HSDSC was used to assess the thermal stability of lysozyme solutions after storage at stressed conditions [13]. Consecutive heating scans indicated the folding reversibility of thermal transitions [8, 14] and the validity of calorimetrically measured protein folding reversibility [15-17]. Creighton (1994) [18] reported mechanisms and thermodynamic factors controlling protein folding-

In the present study, HSDSC investigated thermal changes; in particular protein refolding performance, of crystallised samples (in low and high protein concentrations) upon heat treatment. The thermal structural transition of lysozyme involves two thermodynamic states, native and denatured [19] as for other globular proteins [20]. However, Hirai et al. (1999) [21] indicated that folding-and-unfolding kinetics of proteins depend on the number of amino acid residues. Proteins with residues above ~100 do not follow simple two state kinetics in a folding-and-unfolding process as a single cooperative unit. Accordingly during HSDSC analysis of lysozyme, there might be formation of intermediates between native and denatured states. The thermodynamic stability of proteins not only requires that the transition temperature (*Tm*) and other thermodynamic parameters remain constant but also implies reversibility of protein from unfolded (denatured) to folded (native) state after removing the effect of an external condition such as heat. Anfinsen (1973) [22] reported that denaturation of Ribonuclease A, by heat or urea, was reversible when denatured molecules returned to a normal environment of temperature and solvent. Hence, both structure and

Consequently, formation of the native state is a global property of the protein as described [1]. This state is necessary for stability and activity; proteins are marginally stable and achieve stability only within narrow ranges of conditions of solvent and temperature. The free energy of stabilization of proteins under ordinary conditions is ~ 5-15 kcal mol-1 [1].

Proteins undergo various structural changes if physiological conditions alter. Accordingly, they may denature and the denatured protein tends to adsorb to surfaces and aggregate with other protein molecules. Katakam et al. (1995) [23] proposed that denaturation of recombinant human growth hormone involves unfolding of the molecule; the unfolded part adsorbs to surfaces and aggregates with neighbouring molecules. Shaking and exposure to an air/water interface, heating, lyophilisation or reconstitution of lyophilised protein may

The combination of HSDSC and enzymatic activity determined if refolding of denatured crystallised lysozyme after thermal denaturation in HSDSC arises from the nativeness, three-dimensional folded state, of the initial lysozyme structure. This means that enzymatic activity was employed to investigate if folding reversibility of the thermal transition reflects

aggregate protein with subsequent loss of stability and activity.

the renaturation of the unfolded protein to folded native structure.

interest.

and-unfolding.

enzymatic activity were regained.

where T is the temperature. Differential scanning calorimeters measure enthalpies, which provide the basis for determining the thermodynamic properties of a system. Both enthalpy and entropy are related to the heat capacity of the system. The enthalpy is the total energy (at constant pressure) required to heat the system from absolute zero to the required temperature:

$$\mathbf{H} = \int\_{0}^{\mathbf{T}} \mathbf{C}\_{P}(\mathbf{T}) \, \mathbf{d} \mathbf{T} \tag{2}$$

where Cp (T) is the temperature-dependent heat capacity at constant pressure. The total entropy of the system can be expressed as:

$$\mathbf{S} = \int\_{0}^{\mathbf{T}} \mathbf{[C\_{P}(T)/T].dT} \tag{3}$$

Accordingly, differences in H and S can be expressed as:

$$
\Delta \mathbf{H} = \int\_0^\mathbf{T} \, \Delta \mathbf{C}\_\mathbf{P}(\mathbf{T}) \, \mathbf{d} \, \mathbf{T} \tag{4}
$$

and

$$
\Delta \mathbf{S} = \int\_0^T \Delta [\mathbf{C}\_P(\mathbf{T})/\mathbf{T}] \, d\mathbf{T} \tag{5}
$$

Thermodynamic parameters depend on conditions, such as temperature, pressure, concentration and composition. Thus, it is necessary to correct experimental results to standard conditions (standard states) denoted by the superscript 0 (*e.g.* G0) for simplicity of comparison of data from different situations. The standard state of solutes in dilute solutions is a concentration of 1 M. The standard temperature and pressure are usually 25°C and 1 atm, respectively. The standard free energy change (G0), which is the free energy change during the reaction where all components are in their standard states, can be measured from:

$$\text{L}\text{G}^{0} = -\text{RT.lı}\text{InK} \tag{6}$$

where R is the gas constant and K is the equilibrium constant for the process and is related to (H0) and (S0) and to the absolute temperature by:

$$\mathbf{\dot{n}RK} = -\left(\Delta \mathbf{H}^0 / \mathbf{RT}\right) + \left(\Delta \mathbf{S}^0 / \mathbf{R}\right) \tag{7}$$

assuming that (H0) and (S0) do not vary significantly with temperature over the range of interest.

Applications of Calorimetry in a Wide Context –

entropy of the system can be expressed as:

<sup>T</sup>

<sup>T</sup>

to (H0) and (S0) and to the absolute temperature by:

Accordingly, differences in H and S can be expressed as:

Gibbs free energy equation:

temperature:

and

measured from:

186 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Differential scanning calorimetry has the ability to provide detailed information about both the physical and energetic properties of a substance [11]. The HSDSC technique was described in detail by Cooper and Johnson (1994) [12]. In summary, all equilibrium processes involving molecules are governed by free energy changes (G), made up of enthalpy (H) and entropy (S). The relationship between (H) and (S) is given by the

where T is the temperature. Differential scanning calorimeters measure enthalpies, which provide the basis for determining the thermodynamic properties of a system. Both enthalpy and entropy are related to the heat capacity of the system. The enthalpy is the total energy (at constant pressure) required to heat the system from absolute zero to the required

T

T

where Cp (T) is the temperature-dependent heat capacity at constant pressure. The total

<sup>p</sup> <sup>0</sup>

<sup>p</sup> <sup>0</sup>

Thermodynamic parameters depend on conditions, such as temperature, pressure, concentration and composition. Thus, it is necessary to correct experimental results to standard conditions (standard states) denoted by the superscript 0 (*e.g.* G0) for simplicity of comparison of data from different situations. The standard state of solutes in dilute solutions is a concentration of 1 M. The standard temperature and pressure are usually 25°C and 1 atm, respectively. The standard free energy change (G0), which is the free energy change during the reaction where all components are in their standard states, can be

where R is the gas constant and K is the equilibrium constant for the process and is related

G = H – T.S (1)

<sup>p</sup> <sup>0</sup> H C (T).dT (2)

<sup>p</sup> <sup>0</sup> S [C (T)/T].dT (3)

<sup>H</sup>ΔC (T).dT (4)

<sup>S</sup>Δ[C (T)/T].dT (5)

G0 = - RT.lnK (6)

lnK = - (H0/RT) + (S0/R) (7)

The HSDSC provides an insight into the thermal stability and instability (e.g. formation of soluble and insoluble aggregates) of solutions of different formulations. HSDSC was used to assess the thermal stability of lysozyme solutions after storage at stressed conditions [13]. Consecutive heating scans indicated the folding reversibility of thermal transitions [8, 14] and the validity of calorimetrically measured protein folding reversibility [15-17]. Creighton (1994) [18] reported mechanisms and thermodynamic factors controlling protein foldingand-unfolding.

In the present study, HSDSC investigated thermal changes; in particular protein refolding performance, of crystallised samples (in low and high protein concentrations) upon heat treatment. The thermal structural transition of lysozyme involves two thermodynamic states, native and denatured [19] as for other globular proteins [20]. However, Hirai et al. (1999) [21] indicated that folding-and-unfolding kinetics of proteins depend on the number of amino acid residues. Proteins with residues above ~100 do not follow simple two state kinetics in a folding-and-unfolding process as a single cooperative unit. Accordingly during HSDSC analysis of lysozyme, there might be formation of intermediates between native and denatured states. The thermodynamic stability of proteins not only requires that the transition temperature (*Tm*) and other thermodynamic parameters remain constant but also implies reversibility of protein from unfolded (denatured) to folded (native) state after removing the effect of an external condition such as heat. Anfinsen (1973) [22] reported that denaturation of Ribonuclease A, by heat or urea, was reversible when denatured molecules returned to a normal environment of temperature and solvent. Hence, both structure and enzymatic activity were regained.

Consequently, formation of the native state is a global property of the protein as described [1]. This state is necessary for stability and activity; proteins are marginally stable and achieve stability only within narrow ranges of conditions of solvent and temperature. The free energy of stabilization of proteins under ordinary conditions is ~ 5-15 kcal mol-1 [1].

Proteins undergo various structural changes if physiological conditions alter. Accordingly, they may denature and the denatured protein tends to adsorb to surfaces and aggregate with other protein molecules. Katakam et al. (1995) [23] proposed that denaturation of recombinant human growth hormone involves unfolding of the molecule; the unfolded part adsorbs to surfaces and aggregates with neighbouring molecules. Shaking and exposure to an air/water interface, heating, lyophilisation or reconstitution of lyophilised protein may aggregate protein with subsequent loss of stability and activity.

The combination of HSDSC and enzymatic activity determined if refolding of denatured crystallised lysozyme after thermal denaturation in HSDSC arises from the nativeness, three-dimensional folded state, of the initial lysozyme structure. This means that enzymatic activity was employed to investigate if folding reversibility of the thermal transition reflects the renaturation of the unfolded protein to folded native structure.

### **2. Materials and methods**

### **2.1. Materials**

Chicken egg white lysozyme (purity 95%, 5% sodium chloride and sodium acetate), sodium chloride (99.5%), sodium phosphate (99.3%) and *Micrococcus lysodeikticus* were purchased from Sigma Chemical Company (St. Louis, Mo). Sodium acetate anhydrous (98%), potassium dihydrogen orthophosphate ( 99%) were obtained from BDH Chemicals Ltd. Poole, UK. Water was deionised, double distilled.

Determination of Folding Reversibility of Lysozyme Crystals Using Microcalorimetry 189

protein structure i.e. to correlate the folding reversibility with biological activity. In this assay, a bacterial suspension was prepared by adding 20 mg of *Micrococcus lysodeikticus* to 90 mL of phosphate buffer 0.067 M, pH 6.6, and 10 mL of 1% NaCl. The biological reaction was initiated by addition of 0.5 mL of each enzyme solution to 5 mL of the bacterial suspension. The activity unit of lysozyme is defined as the amount of enzyme decreasing the absorption rate at 450 nm at 0.001 /min at 25°C and pH 6.6. Rates were monitored using a UV/Vis.

All data were presented as mean of three determinations standard deviation. The

Differential scanning microcalorimetry experiments can thermodynamically characterise the unfolding transition by determing heat capacities, enthalpies and melting temperatures of native and denatured protein [25]. HSDSC monitored thermal stability and folding reversibility of reconstituted lysozyme preparations. For samples, traces for thermal denaturation and folding reversibilities, using (UU) method, of reconstituted crystallised lysozyme are illustrated in Figure 1(a) and (b) for 5mg/mL and 20mg/mL protein concentrations, respectively. Thermodynamic parameters and enzymatic activities are in Table 1. Figure 2 shows an example for folding reversibility of unprocessed lysozyme using (UD) method. As is evident in Figures 1 and 2, HSDSC profiles of all samples showed a single endothermic peak (first upscan). Lysozyme crystals started to unfold at ~65°C with a mean *Tm* 

It is noticeable that rescan profiles, whether endothermic (second heating cycle, Figure 1a and b dotted lines) or exothermic (downscan upon cooling, Figure 2 lower trace) showed two peaks, a main one and a small peak or shoulder. Deconvolution of the data (using ORIGIN DSC data analysis software) revealed two transition regions characterised by *Tm* at ~76.1°C (*Tm2*) for the main peak and at ~66°C for the shoulder, indicating that the lysozyme transition is not a two state transition. This may be explained on the basis that lysozyme consists of a single polypeptide chain divided into two structural domains (-helix and sheet). During refolding each domain may be refolded separately with different pathways. Consequently, two peaks appear instead of one; this explanation agrees with Remmele et al. (1998) [14] who attributed the three *Tm* peaks to the three domains of immunoglobulin-type

The other reasonable explanation is that lysozyme, when its folding process is analysed using circular dichroism, does not obey a single co-operative transition, but the process involves several parallel folding pathways. Each of the two domains stabilises with different kinetics [26]. In particular, the amides in the -helix are involved in the formation of stable helical structure and assembly of the hydrophobic core. Then a stable hydrogen bonded structure in the - domain forms. Accordingly, partially structured intermediates develop

**3.1. High Sensitivity Differential Scanning Calorimetry (HSDSC)** 

spectrophotometer (Pu 8700, Philips, UK) at 25°C.

domains that make up the Interleukin-1 receptor.

Student's *t*-test assessed significance.

**3. Results and discussion** 

of 76.1°C (*Tm1*).

### **2.2. Preparation of crystallized lysozyme**

Lysozyme was crystallised using a published method [24]. Crystals formed were filtered, dried and kept in a freezer (-15°C) until tested.

### **2.3. High Sensitivity Differential Scanning Calorimetry (HSDSC)**

Solution samples of crystallised lysozyme were analysed with a Microcal MCS differential scanning calorimeter (Microcal Inc., MA, USA). Degassed samples (5 and 20 mg product / 1 mL 0.1M sodium acetate buffer, pH 4.6) and reference (0.1M sodium acetate buffer, pH 4.6) were loaded into cells using a gas tight Hamilton 2.5 mL glass syringe. The folding reversibility of lysozyme denaturation was assessed by temperature cycling using two scan calorimetric methods. The upscan-upscan method (UU) employed two consecutive upscans from 20-90°C at 1°C/min. After the first upscan, the sample was immediately cooled in the calorimeter (downscan) to 20°C at 0.75°C /min (the fastest cooling rate allowed by the instrument) and the heating cycle was immediately repeated. Transition reversibility was measured as ratio (%) of enthalpy change of second upscan (H2) over that of first upscan (H1). The upscan-downscan method (UD) involved heating of protein solution from 20- 90°C at 1°C/min immediately followed by downscan (cooling) from 90-20°C at a cooling rate of 0.75°C/min. Enthalpies were measured and downscan (H3) / upscan (H1) enthalpy ratios were calculated as a measure of folding reversibility. The calorimeter was temperature- and heat capacity-calibrated using sealed hydrocarbon standards of known melting points and electrical pulses of known power, respectively.

Experiments were performed under 2 bar nitrogen pressure. A base line was run before each measurement by loading the reference in both the sample and reference cells; this base line was subtracted from the protein thermal data and the excess heat capacity was normalized for lysozyme concentration. Data analysis and deconvolution employed ORIGIN DSC data analysis software. The *Tm* (mid point of the transition peak) values for all transitions were calculated.

### **2.4. Enzymatic assay**

Biological activities of thermally denatured crystallised lysozyme were determined after cooling (in HSDSC) to determine whether the renaturation is due to the nativeness of the protein structure i.e. to correlate the folding reversibility with biological activity. In this assay, a bacterial suspension was prepared by adding 20 mg of *Micrococcus lysodeikticus* to 90 mL of phosphate buffer 0.067 M, pH 6.6, and 10 mL of 1% NaCl. The biological reaction was initiated by addition of 0.5 mL of each enzyme solution to 5 mL of the bacterial suspension. The activity unit of lysozyme is defined as the amount of enzyme decreasing the absorption rate at 450 nm at 0.001 /min at 25°C and pH 6.6. Rates were monitored using a UV/Vis. spectrophotometer (Pu 8700, Philips, UK) at 25°C.

All data were presented as mean of three determinations standard deviation. The Student's *t*-test assessed significance.

### **3. Results and discussion**

Applications of Calorimetry in a Wide Context –

Poole, UK. Water was deionised, double distilled.

**2.2. Preparation of crystallized lysozyme** 

dried and kept in a freezer (-15°C) until tested.

**2. Materials and methods** 

**2.1. Materials** 

calculated.

**2.4. Enzymatic assay** 

188 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Chicken egg white lysozyme (purity 95%, 5% sodium chloride and sodium acetate), sodium chloride (99.5%), sodium phosphate (99.3%) and *Micrococcus lysodeikticus* were purchased from Sigma Chemical Company (St. Louis, Mo). Sodium acetate anhydrous (98%), potassium dihydrogen orthophosphate ( 99%) were obtained from BDH Chemicals Ltd.

Lysozyme was crystallised using a published method [24]. Crystals formed were filtered,

Solution samples of crystallised lysozyme were analysed with a Microcal MCS differential scanning calorimeter (Microcal Inc., MA, USA). Degassed samples (5 and 20 mg product / 1 mL 0.1M sodium acetate buffer, pH 4.6) and reference (0.1M sodium acetate buffer, pH 4.6) were loaded into cells using a gas tight Hamilton 2.5 mL glass syringe. The folding reversibility of lysozyme denaturation was assessed by temperature cycling using two scan calorimetric methods. The upscan-upscan method (UU) employed two consecutive upscans from 20-90°C at 1°C/min. After the first upscan, the sample was immediately cooled in the calorimeter (downscan) to 20°C at 0.75°C /min (the fastest cooling rate allowed by the instrument) and the heating cycle was immediately repeated. Transition reversibility was measured as ratio (%) of enthalpy change of second upscan (H2) over that of first upscan (H1). The upscan-downscan method (UD) involved heating of protein solution from 20- 90°C at 1°C/min immediately followed by downscan (cooling) from 90-20°C at a cooling rate of 0.75°C/min. Enthalpies were measured and downscan (H3) / upscan (H1) enthalpy ratios were calculated as a measure of folding reversibility. The calorimeter was temperature- and heat capacity-calibrated using sealed hydrocarbon standards of known

Experiments were performed under 2 bar nitrogen pressure. A base line was run before each measurement by loading the reference in both the sample and reference cells; this base line was subtracted from the protein thermal data and the excess heat capacity was normalized for lysozyme concentration. Data analysis and deconvolution employed ORIGIN DSC data analysis software. The *Tm* (mid point of the transition peak) values for all transitions were

Biological activities of thermally denatured crystallised lysozyme were determined after cooling (in HSDSC) to determine whether the renaturation is due to the nativeness of the

**2.3. High Sensitivity Differential Scanning Calorimetry (HSDSC)**

melting points and electrical pulses of known power, respectively.

### **3.1. High Sensitivity Differential Scanning Calorimetry (HSDSC)**

Differential scanning microcalorimetry experiments can thermodynamically characterise the unfolding transition by determing heat capacities, enthalpies and melting temperatures of native and denatured protein [25]. HSDSC monitored thermal stability and folding reversibility of reconstituted lysozyme preparations. For samples, traces for thermal denaturation and folding reversibilities, using (UU) method, of reconstituted crystallised lysozyme are illustrated in Figure 1(a) and (b) for 5mg/mL and 20mg/mL protein concentrations, respectively. Thermodynamic parameters and enzymatic activities are in Table 1. Figure 2 shows an example for folding reversibility of unprocessed lysozyme using (UD) method. As is evident in Figures 1 and 2, HSDSC profiles of all samples showed a single endothermic peak (first upscan). Lysozyme crystals started to unfold at ~65°C with a mean *Tm*  of 76.1°C (*Tm1*).

It is noticeable that rescan profiles, whether endothermic (second heating cycle, Figure 1a and b dotted lines) or exothermic (downscan upon cooling, Figure 2 lower trace) showed two peaks, a main one and a small peak or shoulder. Deconvolution of the data (using ORIGIN DSC data analysis software) revealed two transition regions characterised by *Tm* at ~76.1°C (*Tm2*) for the main peak and at ~66°C for the shoulder, indicating that the lysozyme transition is not a two state transition. This may be explained on the basis that lysozyme consists of a single polypeptide chain divided into two structural domains (-helix and sheet). During refolding each domain may be refolded separately with different pathways. Consequently, two peaks appear instead of one; this explanation agrees with Remmele et al. (1998) [14] who attributed the three *Tm* peaks to the three domains of immunoglobulin-type domains that make up the Interleukin-1 receptor.

The other reasonable explanation is that lysozyme, when its folding process is analysed using circular dichroism, does not obey a single co-operative transition, but the process involves several parallel folding pathways. Each of the two domains stabilises with different kinetics [26]. In particular, the amides in the -helix are involved in the formation of stable helical structure and assembly of the hydrophobic core. Then a stable hydrogen bonded structure in the - domain forms. Accordingly, partially structured intermediates develop

190 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

during the folding of lysozyme. This explanation is supported by Buck et al. (1993) [27] who reported that lysozyme consists of two structural domains that are stabilised by different pathways.

Determination of Folding Reversibility of Lysozyme Crystals Using Microcalorimetry 191

**Figure 2.** Normalised calorimetric upscan (upper trace) and downscan (lower trace) of lysozyme, as received. Conditions: 5mg/mL protein, 0.1 M sodium acetate buffer, pH 4.6, heating rate 1°C/min,

20 30 40 50 60 70 80 90 100

**Temperature (oC)**

*Tm2*  (°C)

75.90.15 75.20.02

<sup>a</sup>*Tm1*, *Tm2* are mid-point peak transition temperatures of first and second upscans; H1, H2 are calorimetric enthalpies of transitions of first and second upscans; % enzymatic activity is the activity of each sample relative to fresh material of

**Table 2.** Folding reversibilities using upscan-downscan (UD) method of crystallised lysozyme samples a.

**Table 1.** Thermodynamic parameters for the thermal denaturation, folding reversibilities using consecutive upscan method (UU) and enzymatic activities of crystallised lysozyme samplesa.

% folding reversibility (H2 /H1)

> 66.51.4 52.41.6

% folding reversibility (H3 /H1)

> 43.6 (1.6) 48.6 (3.8)

% enzymatic activity

> 65.71.4 52.72.2

*Tm1*  (°C)

76.10.21 75.60.07

cooling rate 0.75°C/min.




**Excess heat capacity**

 **kcal/mol/°C**

0

5

10

15

Lysozyme Sample

Crystallised 5 mg mL-1 20 mg mL-1

that sample, S.D., n= 3.

Lysozyme Sample

Crystallised 5 mg mL-1 20 mg mL-1

a Values between brackets are S.D., n= 3.

**Figure 1.** Normalised consecutive calorimetric upscans, first upscan (solid line) and second upscan (dotted line) of crystallised lysozyme. Conditions: (a) 5mg/mL protein, 0.1 M sodium acetate buffer, pH 4.6, heating rate 1°C/min and (b) 20mg/mL protein, 0.1 M sodium acetate buffer, pH 4.6, heating rate 1°C/min.

**Figure 2.** Normalised calorimetric upscan (upper trace) and downscan (lower trace) of lysozyme, as received. Conditions: 5mg/mL protein, 0.1 M sodium acetate buffer, pH 4.6, heating rate 1°C/min, cooling rate 0.75°C/min.


<sup>a</sup>*Tm1*, *Tm2* are mid-point peak transition temperatures of first and second upscans; H1, H2 are calorimetric enthalpies of transitions of first and second upscans; % enzymatic activity is the activity of each sample relative to fresh material of that sample, S.D., n= 3.

**Table 1.** Thermodynamic parameters for the thermal denaturation, folding reversibilities using consecutive upscan method (UU) and enzymatic activities of crystallised lysozyme samplesa.


a Values between brackets are S.D., n= 3.

Applications of Calorimetry in a Wide Context –

pathways.

1°C/min.

190 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

during the folding of lysozyme. This explanation is supported by Buck et al. (1993) [27] who reported that lysozyme consists of two structural domains that are stabilised by different

**Figure 1.** Normalised consecutive calorimetric upscans, first upscan (solid line) and second upscan (dotted line) of crystallised lysozyme. Conditions: (a) 5mg/mL protein, 0.1 M sodium acetate buffer, pH 4.6, heating rate 1°C/min and (b) 20mg/mL protein, 0.1 M sodium acetate buffer, pH 4.6, heating rate

**Table 2.** Folding reversibilities using upscan-downscan (UD) method of crystallised lysozyme samples a.

#### 192 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

A comparison of calorimetric enthalpy (Hcal) and the theoretical enthalpy (HVH, van't Hoff enthalpy) changes, to judge the validity of a two-state mechanism for the unfolding of lysozyme, reveals the presence of intermediates [25]. It was reported that, in the unfolded state, proteins aggregate and react chemically with amino acid residues exposed to the solvent; this can lead to misfolding or irreversible denaturation [28]. Also, the formation of any irreversible component alters the shape of a HSDSC thermodynamic peak over the temperature range at which it forms [29].

Determination of Folding Reversibility of Lysozyme Crystals Using Microcalorimetry 193

interaction between water and protein molecules in crystalline states. Takano et al. (1999) [6] used differential scanning calorimetry to examine the contribution of hydrogen bonds to the conformational stability of mutant human lysozyme. The authors commented that hydrogen bonding between human lysozyme atoms and water bound with the protein molecules in crystals contributes to the protein conformational stability. The net contribution of one intramolecular hydrogen bond to protein stability in terms of Gibbs energy was ~8.9 kJ/mol. On the basis of Takano et al. (1999) [6] study, hydrogen bonds are one of the important factors stabilising the folded conformations of proteins. From these results crystals were capable of refolding and hence lysozyme crystals not only maintained thermal stability and conformational integrity as suggested previously [24], but also improved refolding ability, which is necessary in protein formulation and processing. Refer to a study by Elkordy et al. [17] for folding reversibility of lyophilised and spray dried lysozyme. Also, a study by Forbes et al. [16] reported the folding reversibility of spray dried and crystallised trypsin.

For folding reversibility calculated by (UD) method, Table 2 above summarises the results of folding reversibilities of crystallised lysozyme at low and high protein concentrations. From Table 2, it is apparent that the percentage folding reversibility calculated by (UU) method (Table 1) was significantly higher ( *p*  0.05) than that derived from the (UD) method (Table 2). This implies that the latter method underestimates the apparent folding reversibility of

Lysozyme solutions upon cooling in the HSDSC after thermal denaturation were assayed for biological activity towards *Micrococcus lysodeikticus.* Based on the HSDSC results, all samples renatured to some extent after thermal stress. Thus, enzymatic assay should answer an important question. Is this renaturation or folding reversibility related to regain of the native structure of lysozyme (which is essential for biological activity), or does it result from misfolding, i.e. folding of the protein in a manner different from the original natured

Table 1 presents percentage enzymatic activities of preheated solutions, in HSDSC, of crystallised lysozyme (relative to an aqueous solution of a fresh sample). It is evident that the biological activity of lysozyme was maintained by crystals (5mg/mL and 20mg/mL). The results were consistent with data of folding reversibilities. This answers the question posed previously in that folding reversibility was related to the native structure of lysozyme that is required for its activity, as the greater the folding reversibility, the higher the enzymatic activity. The results illustrated that lysozyme crystals maintained structural integrity even after heating in the HSDSC. A review by Jen and Merkle (2001) [32] showed that hydrated

From the HSDSC and enzymatic activity results, the folding reversibility, calculated by consecutive upscans (UU, Tables 1), correlated with enzymatic activity of lysozyme, confirming that the upscan-downscan method (UD, Table 2) underestimates the magnitude of folding reversibility. However, proteins are diverse molecules and the presence of

samples.

**3.2. Enzymatic assay** 

structure which subsequently leads to loss of activity?

protein within crystals is present in a folded, native form.

For low protein concentration (5mg/mL, Figure 1a), Table 1 shows no significant difference between *Tm1* (transition temperature of first upscan) and *Tm2* (transition temperature of second upscan) for protein samples.

It was reported that determination of the mechanism and pathway of unfolding and refolding depends on the identification of the intermediates that may not be stable at the equilibrium [18]. Thus, detection and characterisation of kinetic folding intermediates is complex. This intricacy can arise from accumulation of intermediates or from subpopulations of the unfolded state refolding at different rates. Also, events in folding are obscure [1]. With respect to samples with high protein concentration (20mg/mL, Figure 1b), Table 1 demonstrates that *Tm2* decreased compared to its corresponding *Tm1* .

On comparing low and high protein concentrations, thermal stabilities (*Tm1* and *Tm2*) of lysozyme crystals at high concentration significantly decreased (*p*  0.05). Accordingly, high protein concentration influences thermal stability, this is in agreement with previously published data for dried proteins [17]. Moreover, folding reversibilities and enthalpies of first upscan of all samples (Figure 1 and Table 1) decreased with increasing concentration. Enthalpy values correlated with the content of ordered secondary structure of protein [30]. The decrease in enthalpy of protein may be attributed to denaturation at high protein concentration because a partially unfolded protein needs less heat energy to denature than a native form [17]. In general, crystals are chemically and physically pure substances (atoms or molecules within crystals are arranged in highly ordered patterns in three dimensional structures); the other possible reason for the observed reversibility of lysozyme at high protein concentration is that the water in lysozyme crystal lattices inhibits protein-protein interactions and aggregation, to some extent, which may take place at high lysozyme concentration after denaturation by heat in the HSDSC. Consequently, the crystallisation maintains the three-dimensional folded structure of lysozyme and enhances the renaturation of the protein. Water molecules play an important role in the function of proteins through maintaining their tertiary structure. The structure of biological macromolecules in an aqueous solution is similar to that in a crystalline state [31]. There are two kinds of hydration shell of biomolecules in aqueous solution; the primary and secondary hydration shells. Water molecules in the primary hydration shell are directly bound to molecules. The water molecules in the secondary hydration shell have a character intermediate between those of the primary hydration shell and bulk water. On the other hand, crystal water is classified into groups that correspond to the hydration shells in solutions. These water molecules correspond mainly to those in the primary hydration shell and partly to those in the secondary hydration shell [31]. Consequently, there is strong interaction between water and protein molecules in crystalline states. Takano et al. (1999) [6] used differential scanning calorimetry to examine the contribution of hydrogen bonds to the conformational stability of mutant human lysozyme. The authors commented that hydrogen bonding between human lysozyme atoms and water bound with the protein molecules in crystals contributes to the protein conformational stability. The net contribution of one intramolecular hydrogen bond to protein stability in terms of Gibbs energy was ~8.9 kJ/mol. On the basis of Takano et al. (1999) [6] study, hydrogen bonds are one of the important factors stabilising the folded conformations of proteins. From these results crystals were capable of refolding and hence lysozyme crystals not only maintained thermal stability and conformational integrity as suggested previously [24], but also improved refolding ability, which is necessary in protein formulation and processing. Refer to a study by Elkordy et al. [17] for folding reversibility of lyophilised and spray dried lysozyme. Also, a study by Forbes et al. [16] reported the folding reversibility of spray dried and crystallised trypsin.

For folding reversibility calculated by (UD) method, Table 2 above summarises the results of folding reversibilities of crystallised lysozyme at low and high protein concentrations. From Table 2, it is apparent that the percentage folding reversibility calculated by (UU) method (Table 1) was significantly higher ( *p*  0.05) than that derived from the (UD) method (Table 2). This implies that the latter method underestimates the apparent folding reversibility of samples.

### **3.2. Enzymatic assay**

Applications of Calorimetry in a Wide Context –

temperature range at which it forms [29].

second upscan) for protein samples.

192 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

A comparison of calorimetric enthalpy (Hcal) and the theoretical enthalpy (HVH, van't Hoff enthalpy) changes, to judge the validity of a two-state mechanism for the unfolding of lysozyme, reveals the presence of intermediates [25]. It was reported that, in the unfolded state, proteins aggregate and react chemically with amino acid residues exposed to the solvent; this can lead to misfolding or irreversible denaturation [28]. Also, the formation of any irreversible component alters the shape of a HSDSC thermodynamic peak over the

For low protein concentration (5mg/mL, Figure 1a), Table 1 shows no significant difference between *Tm1* (transition temperature of first upscan) and *Tm2* (transition temperature of

It was reported that determination of the mechanism and pathway of unfolding and refolding depends on the identification of the intermediates that may not be stable at the equilibrium [18]. Thus, detection and characterisation of kinetic folding intermediates is complex. This intricacy can arise from accumulation of intermediates or from subpopulations of the unfolded state refolding at different rates. Also, events in folding are obscure [1]. With respect to samples with high protein concentration (20mg/mL, Figure 1b),

On comparing low and high protein concentrations, thermal stabilities (*Tm1* and *Tm2*) of lysozyme crystals at high concentration significantly decreased (*p*  0.05). Accordingly, high protein concentration influences thermal stability, this is in agreement with previously published data for dried proteins [17]. Moreover, folding reversibilities and enthalpies of first upscan of all samples (Figure 1 and Table 1) decreased with increasing concentration. Enthalpy values correlated with the content of ordered secondary structure of protein [30]. The decrease in enthalpy of protein may be attributed to denaturation at high protein concentration because a partially unfolded protein needs less heat energy to denature than a native form [17]. In general, crystals are chemically and physically pure substances (atoms or molecules within crystals are arranged in highly ordered patterns in three dimensional structures); the other possible reason for the observed reversibility of lysozyme at high protein concentration is that the water in lysozyme crystal lattices inhibits protein-protein interactions and aggregation, to some extent, which may take place at high lysozyme concentration after denaturation by heat in the HSDSC. Consequently, the crystallisation maintains the three-dimensional folded structure of lysozyme and enhances the renaturation of the protein. Water molecules play an important role in the function of proteins through maintaining their tertiary structure. The structure of biological macromolecules in an aqueous solution is similar to that in a crystalline state [31]. There are two kinds of hydration shell of biomolecules in aqueous solution; the primary and secondary hydration shells. Water molecules in the primary hydration shell are directly bound to molecules. The water molecules in the secondary hydration shell have a character intermediate between those of the primary hydration shell and bulk water. On the other hand, crystal water is classified into groups that correspond to the hydration shells in solutions. These water molecules correspond mainly to those in the primary hydration shell and partly to those in the secondary hydration shell [31]. Consequently, there is strong

Table 1 demonstrates that *Tm2* decreased compared to its corresponding *Tm1* .

Lysozyme solutions upon cooling in the HSDSC after thermal denaturation were assayed for biological activity towards *Micrococcus lysodeikticus.* Based on the HSDSC results, all samples renatured to some extent after thermal stress. Thus, enzymatic assay should answer an important question. Is this renaturation or folding reversibility related to regain of the native structure of lysozyme (which is essential for biological activity), or does it result from misfolding, i.e. folding of the protein in a manner different from the original natured structure which subsequently leads to loss of activity?

Table 1 presents percentage enzymatic activities of preheated solutions, in HSDSC, of crystallised lysozyme (relative to an aqueous solution of a fresh sample). It is evident that the biological activity of lysozyme was maintained by crystals (5mg/mL and 20mg/mL). The results were consistent with data of folding reversibilities. This answers the question posed previously in that folding reversibility was related to the native structure of lysozyme that is required for its activity, as the greater the folding reversibility, the higher the enzymatic activity. The results illustrated that lysozyme crystals maintained structural integrity even after heating in the HSDSC. A review by Jen and Merkle (2001) [32] showed that hydrated protein within crystals is present in a folded, native form.

From the HSDSC and enzymatic activity results, the folding reversibility, calculated by consecutive upscans (UU, Tables 1), correlated with enzymatic activity of lysozyme, confirming that the upscan-downscan method (UD, Table 2) underestimates the magnitude of folding reversibility. However, proteins are diverse molecules and the presence of

194 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

correlation between folding reversibility and biological activity of lysozyme, as demonstrated in this study, may not be applicable to other proteins.

Determination of Folding Reversibility of Lysozyme Crystals Using Microcalorimetry 195

[9] Daniel RM 1996. The upper limits of enzyme thermal stability. Enzyme Microb.

[10] Quinn ÉÁ 2000. The stability of proteins in hydrofluoroalkane propellants. Ph. D.

[11] Clas S.-D, Dalton CR, Hancock BC 1999. Differential scanning calorimetry: applications

[12] Cooper A, Johnson CM (1994). Introduction to microcalorimetry and biomolecular energetics. In Methods in Molecular Biology: Microscopy, Optical Spectroscopy, and Macroscopic Techniques, Vol. 22 (Jones, C., Mulloy, B. and Thomas, A. H., Eds.)

[13] Elkordy A A, Forbes R T, Barry B W 2004. Stability of crystallised and spray-dried

[14] Remmele R L, Nightlinger N S, Srinivasan S, Gombotz W R 1998. Interleukin-1 receptor (IL-1R) liquid formulation development using differential scanning calorimetry. Pharm

[15] Branchu S, Forbes R T, Nyqvist H, York P 1998. The relationship between the folding

[16] Forbes R T, Barry B W, Elkordy AA 2007. Preparation and characterisation of spraydried and crystallised trypsin: FT-Raman study to detect protein denaturation after

[17] Elkordy A A, Forbes R T, Barry B W 2008. Study of protein conformational stability and integrity using calorimetry and FT-Raman spectroscopy correlated with enzymatic

[18] Creighton T E 1994. The protein folding problem. In: Pain, R.H. (Ed.),*.* Mechanisms of protein folding. Oxford University Press, Oxford, New York, Tokyo, pp. 1-25. [19] Schmid F X 1992. Kinetics of unfolding and refolding of single-domain proteins. In: Creighton, T.E. (Ed.), Protein folding. Freeman, W.H. and Company, New York, pp.

[20] Catanzano F, Giancola C, Graziano G, Barone G 1996. Temperature-induced denaturation of ribonuclease S: A thermodynamic study. Biochem. 35: 13378-13385. [21] Hirai M, Arai S, Iwase H 1999. Complementary analysis of thermal transition multiplicity of hen egg-white lysozyme at low pH using X-ray scattering and scanning

[22] Anfinsen C B 1973. Principles that govern the folding of protein chains. Sci. 181: 223-

[23] Katakam M, Bell L N, Banaga A K 1995. Effect of surfactants on the physical stability of

[24] Elkordy A A, Forbes R T, Barry B W 2002. Integrity of crystalline lysozyme exceeds that

[25] Matouschek A, Serrano L, Fersht A R 1994. Analysis of protein folding by protein engineering. In: Pain, R.H. (Ed.), Mechanisms of protein folding. Oxford University

recombinant human growth hormone. J Pharm Sci. 84: 713-716.

reversibility and enzymatic activity of trypsin. J Pharm Sci. 1 (suppl.): 541.

Technol. 19: 74-79.

Res. 15: 200-208.

197-241.

230.

Thesis, University of Bradford, UK.

in drug development. PSTT 2: 311-320.

lysozyme. Int J Pharm. 278: 209-219.

Humana Press Inc., Totowa, NJ, pp. 109-124.

thermal stress. European J Pharm Sci. 30: 315-323.

activity. European J Pharm Sci. 33: 177-190.

calorimetry. J Phys Chem B. 103: 549-556.

of a spray dried form. Int J Pharm. 247: 79-90.

Press, Oxford, New York, Tokyo, pp. 137-159.

### **4. Conclusions**

The overall results suggested that reconstituted lysozyme crystals were able to refold after heating. The folding reversibility arises from the nativeness of the initial lysozyme structure as demonstrated by biological activity data. The results indicated that the upscan-downscan method underestimated the extent of folding reversibility. Consequently, it is preferable to calculate this reversibility, employing high sensitivity differential scanning calorimetry, by the consecutive heating upscan method.

### **Author details**

Amal A. Elkordy\* *Department of Pharmacy, Health and Well-being, University of Sunderland, Sunderland, UK* 

Robert T. Forbes and Brian W. Barry *School of Pharmacy, University of Bradford, Bradford, UK* 

### **5. References**


<sup>\*</sup> Corresponding Author

[9] Daniel RM 1996. The upper limits of enzyme thermal stability. Enzyme Microb. Technol. 19: 74-79.

Applications of Calorimetry in a Wide Context –

the consecutive heating upscan method.

Robert T. Forbes and Brian W. Barry

*School of Pharmacy, University of Bradford, Bradford, UK* 

**4. Conclusions** 

**Author details** 

Amal A. Elkordy\*

**5. References** 

Sci. 8: 18-22.

67: 767-772.

Corresponding Author

 \*

(DSC). Pharm Res. 8: S-48.

Food Chem. 45: 1116-1125.

194 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

demonstrated in this study, may not be applicable to other proteins.

correlation between folding reversibility and biological activity of lysozyme, as

The overall results suggested that reconstituted lysozyme crystals were able to refold after heating. The folding reversibility arises from the nativeness of the initial lysozyme structure as demonstrated by biological activity data. The results indicated that the upscan-downscan method underestimated the extent of folding reversibility. Consequently, it is preferable to calculate this reversibility, employing high sensitivity differential scanning calorimetry, by

*Department of Pharmacy, Health and Well-being, University of Sunderland, Sunderland, UK* 

[1] Lesk A M 2001. In vivo, in vitro, in silicio. In: Lesk, A.M. (Ed.), Introduction to protein

[2] Rupley J A, Gratton E, Careri G 1983. Water and globular proteins. Trends in Biochem

[4] Pikal M J, Lukes A L, Lang J E, Gaines K 1978. Quantitative crystallinity determination for b-lactam antibiotics by solution calorimetry: correlations with stability. J Pharm Sci.

[5] Freire, E. (1995). Thermal denaturation methods in the study of protein folding. In *Methods in Enzymology*, Vol. 259 (Johnson, M. L. and Ackers, G. K., Eds.) Academic Press, San Diego, New York, Boston, London, Sydney, Tokyo, Toronto, pp. 144-168. [6] Takano K, Yamagata Y, Kubota M, Funahashi J, Fujii S, Yutani K 1999. Contribution of hydrogen bonds to the conformational stability of human lysozyme: Calorimetry and x-

[7] Maneri L R, Farid A R, Smialkowski P J, Seaman M B, Baldoni J M, Sokoloski T D 1991. Preformulation of proteins using high sensitivity differential scanning calorimetry

[8] Boye J I, Alli I, Ismail A A 1997. Use of differential scanning calorimetry and infrared spectroscopy in the study of thermal and structural stability of -lactalbumin. J Agric

architecture. Oxford University Press, Oxford, New York, pp.: 15-35, 143.

[3] Rosenberger F 1996. Protein crystallization. J Cryst Growth. 166: 40-54.

ray analysis of six ser → ala mutants. Biochem. 38: 6623-6629.


	- [26] Radford S E, Dobson C M, Evans P A 1992. The folding of hen lysozyme involves partially structured intermediates and multiple pathways. Nature. 358: 302-307.

**Chapter 9** 

© 2013 Campderrós et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

The protein preserved by freeze-drying simplifies aseptic handling and enhances stability of protein products, with limited shelf lives in solution, by obtaining a dry powder without excessive heating. However, during the freeze-drying process the protein may lose its

and reproduction in any medium, provided the original work is properly cited.

**Calorimetric Study of Inulin as Cryo- and** 

**Lyoprotector of Bovine Plasma Proteins** 

Laura T. Rodriguez Furlán, Javier Lecot, Antonio Pérez Padilla,

Inulin is a generic term applied to heterogeneous blends of fructo-oligosaccharides [1] which are reserve carbohydrate sources present in many plant foods such as bananas, onions, garlic, leeks, artichokes and chicory, which represents the main commercial source. This polysaccharide has a wide range of both, nutritional and technological applications. Nutritionally, inulin is regarded as a soluble fiber which promotes the growth of intestinal bacteria, acting as a prebiotic. Also, is a non-digestible carbohydrate with minimal impact on blood sugar and unlike fructose, it is not insulemic and does not raise triglycerides being generally considered suitable for diabetics and potentially helpful in managing blood sugarrelated illnesses [2-4]. Among the technological benefits, inulin is used as fat and sugar replacement, low caloric bulking agent, texturing and water-binding agent [5,6]. One general property of the saccharides is the stabilization of proteins by their incorporation into carbohydrate solutions before freeze-drying being this a known preservation procedure [7- 10]. The previous incorporation of saccharide promotes the formation of amorphous, glassy systems, inhibits crystallization and influences the kinetics of deteriorative reactions upon storage by which its structured integrity is maintained [8,9,11,12]. To act successfully as a protectant, the saccharides should have a high glass transition temperature (*Tg*), a poor hygroscopicity, a low crystallization rate, containing no reducing groups. When freezedrying is envisaged as a method of drying, a relatively high *T´g* of the freeze concentrated fraction is preferable. Previous studies demonstrated that inulin meets these requirements being excellent protector of therapeutical proteins and viruses over the drying and storage

Mercedes E. Campderrós and Noemi E. Zaritzky

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54462

**1. Introduction** 

processes [13,14].


**Chapter 9** 

## **Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins**

Laura T. Rodriguez Furlán, Javier Lecot, Antonio Pérez Padilla, Mercedes E. Campderrós and Noemi E. Zaritzky

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54462

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

folding. Biochem. 32: 669-678.

New York, pp. 287-323.

1533-1540.

196 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

globulin in soybean seeds. Food Chem. 6: 309-322.

perspective. Pharm Res. 18: 1483-1488.

[26] Radford S E, Dobson C M, Evans P A 1992. The folding of hen lysozyme involves partially structured intermediates and multiple pathways. Nature. 358: 302-307. [27] Buck M, Radford S E, Dobson C M 1993. A partially folded state of hen egg white lysozyme in trifluoroethanol: Structural characterization and implications for protein

[28] Creighton T E 1993. Proteins in solution and in membranes. In: Creighton, T. E. (Ed.),*.* Proteins: Structures and molecular properties, 2nd Ed., Freeman, W.H. and Company,

[29] Lepock J R, Ritchie K P, Kolios M C, Rodahl A M, Heinz K A, Kruuv J 1992. Influence of transition rates and scan rate on kinetic simulations of differential scanning calorimetry profiles of reversible and irreversible protein denaturation. Biochem. 31: 12706-12712. [30] Koshiyama I, Hamano M, Fukushima D 1981. A heat denaturation study of the 11 S

[31] Urabe H, Sugawara Y, Ataka M, Rupprecht A 1998. Low-frequency Raman spectra of lysozyme crystals and oriented DNA films: dynamics of crystal water. Biophys J. 74:

[32] Jen A, Merkle H P 2001. Diamonds in the rough: Protein crystals from a formulation

Inulin is a generic term applied to heterogeneous blends of fructo-oligosaccharides [1] which are reserve carbohydrate sources present in many plant foods such as bananas, onions, garlic, leeks, artichokes and chicory, which represents the main commercial source. This polysaccharide has a wide range of both, nutritional and technological applications. Nutritionally, inulin is regarded as a soluble fiber which promotes the growth of intestinal bacteria, acting as a prebiotic. Also, is a non-digestible carbohydrate with minimal impact on blood sugar and unlike fructose, it is not insulemic and does not raise triglycerides being generally considered suitable for diabetics and potentially helpful in managing blood sugarrelated illnesses [2-4]. Among the technological benefits, inulin is used as fat and sugar replacement, low caloric bulking agent, texturing and water-binding agent [5,6]. One general property of the saccharides is the stabilization of proteins by their incorporation into carbohydrate solutions before freeze-drying being this a known preservation procedure [7- 10]. The previous incorporation of saccharide promotes the formation of amorphous, glassy systems, inhibits crystallization and influences the kinetics of deteriorative reactions upon storage by which its structured integrity is maintained [8,9,11,12]. To act successfully as a protectant, the saccharides should have a high glass transition temperature (*Tg*), a poor hygroscopicity, a low crystallization rate, containing no reducing groups. When freezedrying is envisaged as a method of drying, a relatively high *T´g* of the freeze concentrated fraction is preferable. Previous studies demonstrated that inulin meets these requirements being excellent protector of therapeutical proteins and viruses over the drying and storage processes [13,14].

The protein preserved by freeze-drying simplifies aseptic handling and enhances stability of protein products, with limited shelf lives in solution, by obtaining a dry powder without excessive heating. However, during the freeze-drying process the protein may lose its

© 2013 Campderrós et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

activity and must be protected from conformational changes or denaturation [11,15]. The stabilization of proteins conferred by saccharides during freeze- drying has been explained by several mechanisms. First, replacing the hydrogen bonding between water and protein stabilizes the protein during drying processes, and second, the formation of a glass matrix where the protein is encapsulated avoiding its unfolding and thus preserving its conformation during freeze-drying [8,12,16-18]. Therefore, through the correct selection of the saccharide it is possible to improve the stability of proteins through their encapsulation in a glassy matrix, where molecular mobility is quite limited so that the rates of diffusioncontrolled reactions, like protein unfolding or protein aggregation, are reduced [16,19,20].

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 199

**Figure 1.** Phases diagram of the water–saccharide system. The curve A-B-C-D-E indicated the freezedried process. (*Tf* = freezing temperature; *Tg*= glass transition temperature; *T´g*= glass transition

Although many authors reported the use of saccharides as cryoprotectants of proteins and inulin as a good protector agent of some compounds, the present study is an attempt to evaluate inulin as cryoprotector of food proteins such as bovine plasma proteins, taking profit of the nutritional and technological benefit of the polysaccharide. Also there is a limited amount of data on glass transition temperatures for multicomponent mixtures and on the comparison of experimental and predicted values for such mixtures [28]. Then, the purposes of this study were *i)* to investigate the transition temperatures and the thermal denaturation of bovine plasma proteins stabilized with inulin in a glassy matrix in comparison to the effect of a monosaccharide (glucose) and a disaccharide (sucrose) at different concentrations using DSC, *ii)* to compare the quality, performance and storage

The glass transition temperatures of the maximally concentrated frozen solutions (*T´g*) were analyzed and compared to the experimental results by applying the predictive equations of Miller/Fox and Gordon/Taylor extended for multi-component systems. The glass transition (*Tg*) of the freeze dried multi-component mixtures, the onset crystallization temperature (*Tc*) of the solute at temperatures above *Tg*, in the freeze dried samples were determined. Furthermore, the kinetics of the denaturation and the thermal denaturation (*Td*) of the freeze-dried samples, at different DSC scan rates, protein concentrations and pH, were analyzed and the thermodynamic compatibility of the different matrix components were determined. The enthalpy of change involved in the denaturation reactions of proteins (

was also determined. A kinetic model that describes bovine plasma proteins denaturation

The inulin used as cryoprotectant is mainly constituted by linear chains of fructose, with a glucose terminal unit, and has a molecular weight of 2400 g/mol. The commercial product

*H*)

temperature of the overcooling solution; *C´g* = saccharide concentration)

conditions of these products.

**2. Materials and methods** 

was proposed.

**2.1. Raw materials** 

Information about the energy of a protein can be obtained by means of thermal denaturation studies, allowing the characterization of their behavior during freeze-drying cycle. Differential scanning calorimetry (DSC) is one of the most useful methods for assessing protein thermal behavior and to obtain thermodynamic parameters of folding-unfolding transitions [21].

During the freeze-drying of a protein solution with or without saccharides to protect the structure, the primary drying is the most time consuming stage of the process. It should be carry out at the maximum allowable temperature usually associated to the glass transition temperature of the maximally freeze concentrate solution (*T´g*). Below this temperature a glassy state that behaves as an amorphous solid is obtained. If the temperature of the frozen system rises above the *T´g*, the material becomes less viscous and freeze-drying may cause the loss of the porous structure and the product collapse [20,22,23]. In the freeze-dried sample, water is removed and the solute concentration in the matrix increases, obtaining a material with an amorphous structure that exhibits a glass-rubber transition at a specific temperature which is named as the glass transition temperature (*Tg*) [24-28]. It is noteworthy that amorphous materials are stable in the glassy state below *Tg*, when the temperature is higher the viscosity decreases and thus the rate of chemical reactions increases and crystallization events occur, increasing the rate of deterioration during storage [22,25,27-29]. Both transitions *T´g* and *Tg* are important parameters in the development of the freezedrying cycle because not only ensures the stability and quality of the product, but also allow to improve the efficiency of the manufacturing process [20,22,28,30].

A diagram of phases for the water-saccharide system is shown in Figure 1. The curve of the freezing temperature separates the zones corresponding to the liquid and the solid (ice) solution phases. In fact, this procedure is aimed at obtaining a glassy system at room temperature as indicated in D. To get to this state, the freeze-dried process indicated by the curve A-B-C-D-E is carried out. The curve for the glass transition temperature (*Tg*) is reached when the solution is overcooled (B-C) until the *T´g* in point C, where the concentration of the vitrification agent (saccharide) is given by *C´g*. Then the water is eliminated and the solute concentration increases (C-D-E), obtaining a solid with an amorphous structure that exhibits a glass transition temperature (*Tg*) [22,28].

Therefore, the determination of the freeze-drying cycle is important because of physical changes that occur in the solution during the process, its study can be applied to improve processability, quality, and stability of the product during storage [29].

**Figure 1.** Phases diagram of the water–saccharide system. The curve A-B-C-D-E indicated the freezedried process. (*Tf* = freezing temperature; *Tg*= glass transition temperature; *T´g*= glass transition temperature of the overcooling solution; *C´g* = saccharide concentration)

Although many authors reported the use of saccharides as cryoprotectants of proteins and inulin as a good protector agent of some compounds, the present study is an attempt to evaluate inulin as cryoprotector of food proteins such as bovine plasma proteins, taking profit of the nutritional and technological benefit of the polysaccharide. Also there is a limited amount of data on glass transition temperatures for multicomponent mixtures and on the comparison of experimental and predicted values for such mixtures [28]. Then, the purposes of this study were *i)* to investigate the transition temperatures and the thermal denaturation of bovine plasma proteins stabilized with inulin in a glassy matrix in comparison to the effect of a monosaccharide (glucose) and a disaccharide (sucrose) at different concentrations using DSC, *ii)* to compare the quality, performance and storage conditions of these products.

The glass transition temperatures of the maximally concentrated frozen solutions (*T´g*) were analyzed and compared to the experimental results by applying the predictive equations of Miller/Fox and Gordon/Taylor extended for multi-component systems. The glass transition (*Tg*) of the freeze dried multi-component mixtures, the onset crystallization temperature (*Tc*) of the solute at temperatures above *Tg*, in the freeze dried samples were determined. Furthermore, the kinetics of the denaturation and the thermal denaturation (*Td*) of the freeze-dried samples, at different DSC scan rates, protein concentrations and pH, were analyzed and the thermodynamic compatibility of the different matrix components were determined. The enthalpy of change involved in the denaturation reactions of proteins (*H*) was also determined. A kinetic model that describes bovine plasma proteins denaturation was proposed.

### **2. Materials and methods**

#### **2.1. Raw materials**

Applications of Calorimetry in a Wide Context –

transitions [21].

198 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

to improve the efficiency of the manufacturing process [20,22,28,30].

processability, quality, and stability of the product during storage [29].

a glass transition temperature (*Tg*) [22,28].

activity and must be protected from conformational changes or denaturation [11,15]. The stabilization of proteins conferred by saccharides during freeze- drying has been explained by several mechanisms. First, replacing the hydrogen bonding between water and protein stabilizes the protein during drying processes, and second, the formation of a glass matrix where the protein is encapsulated avoiding its unfolding and thus preserving its conformation during freeze-drying [8,12,16-18]. Therefore, through the correct selection of the saccharide it is possible to improve the stability of proteins through their encapsulation in a glassy matrix, where molecular mobility is quite limited so that the rates of diffusioncontrolled reactions, like protein unfolding or protein aggregation, are reduced [16,19,20].

Information about the energy of a protein can be obtained by means of thermal denaturation studies, allowing the characterization of their behavior during freeze-drying cycle. Differential scanning calorimetry (DSC) is one of the most useful methods for assessing protein thermal behavior and to obtain thermodynamic parameters of folding-unfolding

During the freeze-drying of a protein solution with or without saccharides to protect the structure, the primary drying is the most time consuming stage of the process. It should be carry out at the maximum allowable temperature usually associated to the glass transition temperature of the maximally freeze concentrate solution (*T´g*). Below this temperature a glassy state that behaves as an amorphous solid is obtained. If the temperature of the frozen system rises above the *T´g*, the material becomes less viscous and freeze-drying may cause the loss of the porous structure and the product collapse [20,22,23]. In the freeze-dried sample, water is removed and the solute concentration in the matrix increases, obtaining a material with an amorphous structure that exhibits a glass-rubber transition at a specific temperature which is named as the glass transition temperature (*Tg*) [24-28]. It is noteworthy that amorphous materials are stable in the glassy state below *Tg*, when the temperature is higher the viscosity decreases and thus the rate of chemical reactions increases and crystallization events occur, increasing the rate of deterioration during storage [22,25,27-29]. Both transitions *T´g* and *Tg* are important parameters in the development of the freezedrying cycle because not only ensures the stability and quality of the product, but also allow

A diagram of phases for the water-saccharide system is shown in Figure 1. The curve of the freezing temperature separates the zones corresponding to the liquid and the solid (ice) solution phases. In fact, this procedure is aimed at obtaining a glassy system at room temperature as indicated in D. To get to this state, the freeze-dried process indicated by the curve A-B-C-D-E is carried out. The curve for the glass transition temperature (*Tg*) is reached when the solution is overcooled (B-C) until the *T´g* in point C, where the concentration of the vitrification agent (saccharide) is given by *C´g*. Then the water is eliminated and the solute concentration increases (C-D-E), obtaining a solid with an amorphous structure that exhibits

Therefore, the determination of the freeze-drying cycle is important because of physical changes that occur in the solution during the process, its study can be applied to improve

The inulin used as cryoprotectant is mainly constituted by linear chains of fructose, with a glucose terminal unit, and has a molecular weight of 2400 g/mol. The commercial product

#### Applications of Calorimetry in a Wide Context – 200 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

was provided by Orafti Chile S.A. and was obtained from chicory. The other saccharides employed to compare their performance were: *i)* a monosaccharide, glucose (Parafarn, Argentine), with a purity of 99.99% and *ii)* a disaccharide, commercial sucrose (Ledesma S.A., Argentine).

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 201

sucrose, inulin) was added to the rest, in concentrations of 5%, 10% and 15% (w/v). A part of these solutions was reserved for DSC analysis to determine *T'g* and the others were placed on stainless steel trays, frozen in a freezer at -40 C and freeze-dried using a lyophilizer (Rificor S.A., Argentine) at 1 bar for 48 h. The samples temperature was controlled by a temperature sensor. The denatured protein content was determined before and after the

The solutions containing plasma proteins–saccharides mixture were analyzed to determine *T´g* at different pH values and saccharide concentrations by DSC with a Q100DTA Instrument (USA)*.* The pH was adjusted using 0.1 N of NaOH and HCl. Protein concentrate solutions (average composition: saccharide 5% p/v - protein 4% p/v; saccharide 10% p/v protein 4% p/v; saccharide 15% p/v - protein 4% p/v), (10 ± 2 mg) were weighed into aluminum DSC pans, hermetically sealed, and then loaded onto the DSC instrument at room temperature, using an empty pan as a reference. Samples Solutions were: (a) equilibrated at 20 °C and held for 1 min; (b) cooled at 2 °C/min until -80 °C for glucose, -60 °C for sucrose and -40 °C for inulin and held for 30 min; (c) warmed up to the annealing temperature (-50, -40 and -20 °C, for glucose, sucrose and inulin, respectively) by employing an annealing time of 30 min at heating rate of 2 °C/min [31]; (e) recooled at the same temperature of step (b) and held for 30 min; (f) warmed up to 0 °C at heating rate of 2 °C/min. The effectiveness of the procedure was verified corroborating the absence of ice devitrification in thermograms, that is to say the nonexistence of an exothermic peak

Heat induced conformational changes on freeze-dried bovine plasma protein concentrate (BPP concentrate) in the amorphous carbohydrate matrix. The freeze-dried solids were analyzed to determine *Tg, Tc* and *Td* at different pH values and saccharide concentrations by DSC with a Q100DTA Instrument (USA)*.* The pH was adjusted using 0.1 N of NaOH and HCl. Protein concentrates (average composition: freeze-dried with saccharide 5% (p/v) = saccharide 35% p/p - protein 55% p/p; freeze-dried with saccharide 10% (p/v) = saccharide 64% p/p - protein 28% p/p; freeze-dried with saccharide 15% (p/v) = saccharide 79 % p/p protein 14% p/p), (12.5 ± 2.5 mg) were weighed into aluminum DSC pans, hermetically sealed, and then loaded onto the DSC instrument at room temperature, using an empty pan

Freeze–dried solids were equilibrated at 0 °C, held for 1 min and then warmed up to 200 °C at heating rate of 2 °C/min. To check the irreversibility of the reaction of heat-induced conformational changes, the samples after the end of the first heating stage described before, were re-scanned. For this, the protein-saccharide samples were cooled to 20 °C and stabilized during 5 min, and then warmed up to 200°C. Samples of freeze dried bovine plasma protein concentrate (BPP concentrates) in the amorphous carbohydrate matrix at pH

**2.3. Differential Scanning Calorimetry (DSC) measurements** 

**Determination of** *Tg, Tc* **and** *Td* **of proteins in the freeze–dried solids** 

**Determination of** *T´g* **in the protein solutions** 

freeze-drying.

previous to the ice melting.

as a reference.

The protein used in the study was spray dried bovine plasma (Yerubá S.A. Argentine). The molecular weights of the proteins were in the range of 15.000 to 80.000 Da. The composition was 76±5% proteins, <0.1% fat, 10% ash, 4% water, 1% low molecular weight compounds.

### **2.2. Preparation of Protein/carbohydrate samples: Concentration of bovine plasma proteins through ultrafiltration and freeze-drying treatments**

The protein concentrate was obtained by means of a membrane process**,** which allowed protein concentration, eliminating insoluble macroscopic components, reducing the saline content [18]. The steps of the process were: i) the bovine plasma was dissolved in de-ionized water to a concentration of 3% w/v using a mixer at a low speed to avoid the formation of vortex and to minimize the appearance of foam; ii) the solution was passed through a porous support (Viledon FO 2431D, Germany) to remove macroscopic aggregates and reduce the saline content; iii) the feed solution (3 L) was thermostatized in a water bath and impelled with a centrifugal pump, first through a frontal flow stainless steel filter, with a pore size of 60 m (Gora, Argentine) (this procedure of microfiltration (MF) reduces the amount of bacteria and spores and acts as cold pasteurization, moreover this stage protects the ultrafiltration (UF) membrane from fouling); and finally, iv) the UF was performed using Pellicon cassette module (Millipore, Bedford, MA, USA), containing modified polyethersulfone membranes with a molecular weight cut-off (MWCO) of 10 kDa, with a membrane area of 0.5 m2. The concentration of proteins by UF was carried out by continuously removing the permeate stream until the desired concentration of 4% (w/v), was achieved. The experimental runs were performed at a transmembrane pressure (*P*) of 1.5 bar, flow rate of (2.9 0.05) L/min and a temperature of 10 °C. Additionally a discontinuous diafiltration (DD) process was applied to removal salts and other contaminant of low molecular weight. For this operation the starting solution was the UF concentrate, which was diluted to the initial volume (3 L) with de-ionized water in a single state and ultrafiltered to the desired concentration range.

The UF membrane undergoes a fouling process during protein permeation so a cleaning protocol may be applied. It was performed by applying a "Cleaning in Place" (CIP) procedure according to the manufacturer's instructions. At the end of each run, a cycle of water/ alkali (NaOH, pH=12.5 ± 0.5)/ water wash was applied to the membrane at (40 2) °C and at a transmembrane pressure of 1 bar. Furthermore, a cleaning step using NaClO (commercial grade) 300 ppm was carried out at the same temperature and pressure to ensure sanitation and cleaning. Measurements of normalized water permeability were performed in order to verify recovery of flow through the membrane which ensures the recuperation of membrane permeability.

The bovine plasma protein (BPP) concentrate obtained by UF (concentration: 4 % w/v) was fractioned: A fraction as witness sample was reserved and the protective agent (glucose, sucrose, inulin) was added to the rest, in concentrations of 5%, 10% and 15% (w/v). A part of these solutions was reserved for DSC analysis to determine *T'g* and the others were placed on stainless steel trays, frozen in a freezer at -40 C and freeze-dried using a lyophilizer (Rificor S.A., Argentine) at 1 bar for 48 h. The samples temperature was controlled by a temperature sensor. The denatured protein content was determined before and after the freeze-drying.

### **2.3. Differential Scanning Calorimetry (DSC) measurements**

### **Determination of** *T´g* **in the protein solutions**

Applications of Calorimetry in a Wide Context –

S.A., Argentine).

200 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

was provided by Orafti Chile S.A. and was obtained from chicory. The other saccharides employed to compare their performance were: *i)* a monosaccharide, glucose (Parafarn, Argentine), with a purity of 99.99% and *ii)* a disaccharide, commercial sucrose (Ledesma

The protein used in the study was spray dried bovine plasma (Yerubá S.A. Argentine). The molecular weights of the proteins were in the range of 15.000 to 80.000 Da. The composition was 76±5% proteins, <0.1% fat, 10% ash, 4% water, 1% low molecular weight compounds.

The protein concentrate was obtained by means of a membrane process**,** which allowed protein concentration, eliminating insoluble macroscopic components, reducing the saline content [18]. The steps of the process were: i) the bovine plasma was dissolved in de-ionized water to a concentration of 3% w/v using a mixer at a low speed to avoid the formation of vortex and to minimize the appearance of foam; ii) the solution was passed through a porous support (Viledon FO 2431D, Germany) to remove macroscopic aggregates and reduce the saline content; iii) the feed solution (3 L) was thermostatized in a water bath and impelled with a centrifugal pump, first through a frontal flow stainless steel filter, with a pore size of 60 m (Gora, Argentine) (this procedure of microfiltration (MF) reduces the amount of bacteria and spores and acts as cold pasteurization, moreover this stage protects the ultrafiltration (UF) membrane from fouling); and finally, iv) the UF was performed using Pellicon cassette module (Millipore, Bedford, MA, USA), containing modified polyethersulfone membranes with a molecular weight cut-off (MWCO) of 10 kDa, with a membrane area of 0.5 m2. The concentration of proteins by UF was carried out by continuously removing the permeate stream until the desired concentration of 4% (w/v), was achieved. The experimental runs were performed at a transmembrane pressure (

1.5 bar, flow rate of (2.9 0.05) L/min and a temperature of 10 °C. Additionally a discontinuous diafiltration (DD) process was applied to removal salts and other contaminant of low molecular weight. For this operation the starting solution was the UF concentrate, which was diluted to the initial volume (3 L) with de-ionized water in a single

The UF membrane undergoes a fouling process during protein permeation so a cleaning protocol may be applied. It was performed by applying a "Cleaning in Place" (CIP) procedure according to the manufacturer's instructions. At the end of each run, a cycle of water/ alkali (NaOH, pH=12.5 ± 0.5)/ water wash was applied to the membrane at (40 2) °C and at a transmembrane pressure of 1 bar. Furthermore, a cleaning step using NaClO (commercial grade) 300 ppm was carried out at the same temperature and pressure to ensure sanitation and cleaning. Measurements of normalized water permeability were performed in order to verify recovery of flow through the membrane which ensures the

The bovine plasma protein (BPP) concentrate obtained by UF (concentration: 4 % w/v) was fractioned: A fraction as witness sample was reserved and the protective agent (glucose,

state and ultrafiltered to the desired concentration range.

recuperation of membrane permeability.

*P*) of

**2.2. Preparation of Protein/carbohydrate samples: Concentration of bovine plasma proteins through ultrafiltration and freeze-drying treatments** 

The solutions containing plasma proteins–saccharides mixture were analyzed to determine *T´g* at different pH values and saccharide concentrations by DSC with a Q100DTA Instrument (USA)*.* The pH was adjusted using 0.1 N of NaOH and HCl. Protein concentrate solutions (average composition: saccharide 5% p/v - protein 4% p/v; saccharide 10% p/v protein 4% p/v; saccharide 15% p/v - protein 4% p/v), (10 ± 2 mg) were weighed into aluminum DSC pans, hermetically sealed, and then loaded onto the DSC instrument at room temperature, using an empty pan as a reference. Samples Solutions were: (a) equilibrated at 20 °C and held for 1 min; (b) cooled at 2 °C/min until -80 °C for glucose, -60 °C for sucrose and -40 °C for inulin and held for 30 min; (c) warmed up to the annealing temperature (-50, -40 and -20 °C, for glucose, sucrose and inulin, respectively) by employing an annealing time of 30 min at heating rate of 2 °C/min [31]; (e) recooled at the same temperature of step (b) and held for 30 min; (f) warmed up to 0 °C at heating rate of 2 °C/min. The effectiveness of the procedure was verified corroborating the absence of ice devitrification in thermograms, that is to say the nonexistence of an exothermic peak previous to the ice melting.

#### **Determination of** *Tg, Tc* **and** *Td* **of proteins in the freeze–dried solids**

Heat induced conformational changes on freeze-dried bovine plasma protein concentrate (BPP concentrate) in the amorphous carbohydrate matrix. The freeze-dried solids were analyzed to determine *Tg, Tc* and *Td* at different pH values and saccharide concentrations by DSC with a Q100DTA Instrument (USA)*.* The pH was adjusted using 0.1 N of NaOH and HCl. Protein concentrates (average composition: freeze-dried with saccharide 5% (p/v) = saccharide 35% p/p - protein 55% p/p; freeze-dried with saccharide 10% (p/v) = saccharide 64% p/p - protein 28% p/p; freeze-dried with saccharide 15% (p/v) = saccharide 79 % p/p protein 14% p/p), (12.5 ± 2.5 mg) were weighed into aluminum DSC pans, hermetically sealed, and then loaded onto the DSC instrument at room temperature, using an empty pan as a reference.

Freeze–dried solids were equilibrated at 0 °C, held for 1 min and then warmed up to 200 °C at heating rate of 2 °C/min. To check the irreversibility of the reaction of heat-induced conformational changes, the samples after the end of the first heating stage described before, were re-scanned. For this, the protein-saccharide samples were cooled to 20 °C and stabilized during 5 min, and then warmed up to 200°C. Samples of freeze dried bovine plasma protein concentrate (BPP concentrates) in the amorphous carbohydrate matrix at pH 8, 6 and 4, at different heating rates of 2 and 5 °C/min in the temperature range 20–200 °C were analyzed. The pH was adjusted using 0.1 N of NaOH and HCl. Measurements were carried out on three separate samples (replicates). The following parameters were calculated at least in triplicate: *Td*, at maximum heat flow, and *H*, the enthalpy change involved in the overall heat-induced reactions within the protein molecules, that was determined by integrating the area beneath the enthalpy peak and above a straight baseline drawn in between the beginning and the end of the transition temperature range [32-34]; the *T´g* and *Tg* were determined from the midpoint of the transition of the baseline shift on the amorphous sample.

In the freeze dried samples, at temperatures above *Tg*, the onset crystallization temperature (*Tc*) of the added solute was determined from the intersection of the baseline and the tangent of the exothermic peak. The enthalpy change involved in the overall heat-induced reactions within the protein molecules, *Hc*, was determined by integrating the area beneath the exothermic peak and above a straight baseline drawn between the beginning and end of the transition temperature range [22,32,33].

### **2.4. Determination of native protein content**

The native protein content is a measure of protein functionality preservation. It was determined after isoelectric precipitation of denatured/aggregated protein [18,35]. Dispersions of protein concentrate at 1% (w/v) were adjusted to pH value inferior of the pI of plasma proteins ( 4.8) using 0.1 N of NaOH and HCl. An aliquot of the solution was centrifuged in a refrigerated ultracentrifuge (Beckman J2-HS) at 20,000 rpm 30 min at 5 ºC. Protein concentration in the supernatants was diluted in a dissociating buffer (EDTA 50 mM, urea 8 M, pH= 10) and determined by molecular absorptiometry at 280 nm. The results were reported as percentage of the total protein concentration [36]. The percentage of native protein content of suspensions at pH 4.8 was obtained as the ratio between soluble protein (*SP*) and total protein (*TP*) contents after aggregation of denatured protein (Eq. 1).

$$NP\% = \left(\frac{SP}{TP}\right) \times 100\tag{1}$$

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 203

 

, density; the subscripts t, 1, 2, 3 mean:

a *P*<0.05 was statistically significant [37]. Statistical GraphPad InStat software (1998) was

The Miller/Fox equation can be used for the determination of *T´*<sup>g</sup> dependence with the composition in a multi-component system, assuming constant density of the solutions, independent of temperature [28,38,39]. For a ternary mixture (protein-saccharide-water), it

> / // *<sup>g</sup> tg t tg t tg t m m m*

The Gordon and Taylor equation [40] predicts the plasticizing effect of water on the *T*<sup>g</sup> for a multicomponent system. The equation has been used among others, for systems treated as binary mixtures, determining experimentally the glass transition of the respective solid [41,42]. Instead we proposed a system considering each individual component: bovine

> *w kw k w w T kw T k w T*

*1 2*

where *w1*, *w2*, *w3,* are the weight fraction of each component defined as (*mi* /*mt)*, and *k* is an empirical constant proportional to the plasticizing effect of water. This parameter was calculated to fit experimental data from a nonlinear optimization procedure (Gauss Newton

Unfolding of protein is suggested to involve at least two steps according to Lumry and Eyring model (1954). The first step is a reversible unfolding of the native protein (*N*). This is followed by an irreversible change of the denatured protein (D) into a final irreversible state

> 1 2 1

*k k*

A special case was when *k2k-1*, where most of the *D* molecules will be converted to *I* as an alternative to refolding back to the native state. In this case, the denaturation process can be

*k N DI* 

regarded as one-step process following first-order kinetics [44-46], (Eq.5).

*1 g1 2 g 2 <sup>g</sup>*

protein concentrate, saccharide and water, with each corresponding property [43]:

Eqs. (2) and (3) were used for the determination of *T´g*of the frozen solutions.

 1 2 3 1 1 2 2 3 3

 *m T m T* (2)

> *3 2*

*3 g 3 2*

(3)

(4)

 

used.

can be written as:

**3. Theoretical considerations** 

**3.1. Equations for** *T´***g prediction** 

1

*T m T*

where *T*g, glass transition temperature; *m,* mass;

total and each pure component, respectively.

 

*T*

procedure) using the software Excel 2003 (Microsoft).

**3.2. Theory of protein unfolding** 

(*I*) [44,45].

#### **2.5. Scanning electron microscopy**

The microstructure of freeze-dried plasma concentrates with and without saccharides was analyzed by scanning electron microscopy (SEM) using an LEO1450VP equipment (Zeiss, Germany). Powder samples were mounted on double-sided carbon adhesive tape on aluminum stubs and gold-coated and processed in a standard sputter. The micrographs were obtained in high vacuum at 10 KeV.

### **2.6. Statistical analysis**

The experimental data were statistically analyzed by the Tukey-Kramer multiple comparison test, in the cases where 2 or more comparisons were considered, assuming that a *P*<0.05 was statistically significant [37]. Statistical GraphPad InStat software (1998) was used.

### **3. Theoretical considerations**

Applications of Calorimetry in a Wide Context –

amorphous sample.

within the protein molecules,

transition temperature range [22,32,33].

**2.5. Scanning electron microscopy** 

were obtained in high vacuum at 10 KeV.

**2.6. Statistical analysis** 

**2.4. Determination of native protein content** 

at least in triplicate: *Td*, at maximum heat flow, and

202 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

8, 6 and 4, at different heating rates of 2 and 5 °C/min in the temperature range 20–200 °C were analyzed. The pH was adjusted using 0.1 N of NaOH and HCl. Measurements were carried out on three separate samples (replicates). The following parameters were calculated

overall heat-induced reactions within the protein molecules, that was determined by integrating the area beneath the enthalpy peak and above a straight baseline drawn in between the beginning and the end of the transition temperature range [32-34]; the *T´g* and *Tg* were determined from the midpoint of the transition of the baseline shift on the

In the freeze dried samples, at temperatures above *Tg*, the onset crystallization temperature (*Tc*) of the added solute was determined from the intersection of the baseline and the tangent of the exothermic peak. The enthalpy change involved in the overall heat-induced reactions

exothermic peak and above a straight baseline drawn between the beginning and end of the

The native protein content is a measure of protein functionality preservation. It was determined after isoelectric precipitation of denatured/aggregated protein [18,35]. Dispersions of protein concentrate at 1% (w/v) were adjusted to pH value inferior of the pI of plasma proteins ( 4.8) using 0.1 N of NaOH and HCl. An aliquot of the solution was centrifuged in a refrigerated ultracentrifuge (Beckman J2-HS) at 20,000 rpm 30 min at 5 ºC. Protein concentration in the supernatants was diluted in a dissociating buffer (EDTA 50 mM, urea 8 M, pH= 10) and determined by molecular absorptiometry at 280 nm. The results were reported as percentage of the total protein concentration [36]. The percentage of native protein content of suspensions at pH 4.8 was obtained as the ratio between soluble protein

(*SP*) and total protein (*TP*) contents after aggregation of denatured protein (Eq. 1).

% x 100 *SP NP TP* 

The microstructure of freeze-dried plasma concentrates with and without saccharides was analyzed by scanning electron microscopy (SEM) using an LEO1450VP equipment (Zeiss, Germany). Powder samples were mounted on double-sided carbon adhesive tape on aluminum stubs and gold-coated and processed in a standard sputter. The micrographs

The experimental data were statistically analyzed by the Tukey-Kramer multiple comparison test, in the cases where 2 or more comparisons were considered, assuming that

*H*, the enthalpy change involved in the

(1)

*Hc*, was determined by integrating the area beneath the

#### **3.1. Equations for** *T´***g prediction**

The Miller/Fox equation can be used for the determination of *T´*<sup>g</sup> dependence with the composition in a multi-component system, assuming constant density of the solutions, independent of temperature [28,38,39]. For a ternary mixture (protein-saccharide-water), it can be written as:

$$\frac{1}{T\_{\rm g}} = \frac{m\_1}{m\_t T\_{\rm g1} \left(\rho\_1 / \rho\_t\right)} + \frac{m\_2}{m\_t T\_{\rm g2} \left(\rho\_2 / \rho\_t\right)} + \frac{m\_3}{m\_t T\_{\rm g3} \left(\rho\_3 / \rho\_t\right)}\tag{2}$$

where *T*g, glass transition temperature; *m,* mass; , density; the subscripts t, 1, 2, 3 mean: total and each pure component, respectively.

The Gordon and Taylor equation [40] predicts the plasticizing effect of water on the *T*<sup>g</sup> for a multicomponent system. The equation has been used among others, for systems treated as binary mixtures, determining experimentally the glass transition of the respective solid [41,42]. Instead we proposed a system considering each individual component: bovine protein concentrate, saccharide and water, with each corresponding property [43]:

$$T\_g = \frac{\left(\boldsymbol{\nu}\_l T\_{\rm g1} + k \boldsymbol{\nu}\_2 T\_{\rm g2} + k^2 \boldsymbol{\nu}\_3 T\_{\rm g3}\right)}{\left(\boldsymbol{\nu}\_l + k \boldsymbol{\nu}\_2 + k^2 \boldsymbol{\nu}\_3\right)}\tag{3}$$

where *w1*, *w2*, *w3,* are the weight fraction of each component defined as (*mi* /*mt)*, and *k* is an empirical constant proportional to the plasticizing effect of water. This parameter was calculated to fit experimental data from a nonlinear optimization procedure (Gauss Newton procedure) using the software Excel 2003 (Microsoft).

Eqs. (2) and (3) were used for the determination of *T´g*of the frozen solutions.

#### **3.2. Theory of protein unfolding**

Unfolding of protein is suggested to involve at least two steps according to Lumry and Eyring model (1954). The first step is a reversible unfolding of the native protein (*N*). This is followed by an irreversible change of the denatured protein (D) into a final irreversible state (*I*) [44,45].

$$N \underset{k\_{-1}}{\leftrightarrow} D \underset{k\_{-1}}{\rightarrow} I \tag{4}$$

A special case was when *k2k-1*, where most of the *D* molecules will be converted to *I* as an alternative to refolding back to the native state. In this case, the denaturation process can be regarded as one-step process following first-order kinetics [44-46], (Eq.5).

204 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

$$N \xrightarrow{k} I \tag{5}$$

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 205

Therefore, it is important to note that the higher value of *T´g* observed in frozen solutions with inulin, allowed higher freezing temperatures during processing reducing production

**Figure 2.** DSC thermograms for freeze bovine plasma protein-saccharide solutions. Down-arrows

Saccharide Concentration (%, w/v) *T´g1* (°C) *T´g2* (°C) *Tg* (°C)

**Table 1.** Effect of type and concentration of cryoprotectant on glass transition temperature (*T´g*) and lyoprotectant on glass transition temperature (*Tg*) of freeze bovine plasma proteins solutions (heating rate: 2 °C/min). Values represents the means ± standard deviation; n = 3. Values followed by different

letters in the same column are significantly different from each other (*P* < 0.05).

10 -50.12 ± 1.03c,d -31.86 ± 0.60c

5 -51.48 ± 1.05c

5 -62.50 ± 0.58a -39.24 ± 0.75a 16.31 ± 0.38a 10 -61.06 ± 0.45a,b -39.91 ± 0.83a 41.52 ± 0.29b 15 -59.82 ± 0.68b -44.96 ± 0.49b 60.31 ± 0.48c

15 -48.42 ± 0.98d -33.72 ± 0.45d 64.28 ± 0.46f

5 -26.96 ± 0.68e - 48.85 ± 0.35d 10 -23.67 ± 0.55f - 66.18 ± 0.69g 15 -22.40 ± 0.45f - 69.25 ± 0.45h


48.01 ± 0.56d

52.48 ± 0.52e

indicate *T´g*. Scan rate = 2°C/min ; pH = 8.

Glucose

Sucrose

Inulin

costs.

where the first-order rate constant *k* can be identified with *k*1 of Eq. (4). The total absorbed heat now equals the enthalpy change from *N* to *I*; it was generally assumed that the enthalpy change from *D* to *I* was negligible compared to that from *N* to *D* [44].

Experimentally, the irreversibility of unfolding was verified in a rescan. For an irreversible process, in the DSC rescanned thermograms no transition could be observed.

### **4. Results and discussion**

#### **4.1. Effect of saccharides on glass transition of the freeze concentrated matrix**

As was previously mentioned, to avoid collapse of the products during the freeze-dried process, a temperature below the glass transition temperature of the frozen concentrated solutions, must be attained. Inulin as protein protective agent was comparatively studied, employing mono and disaccharides. The thermograms of Figure 2 show the transition temperatures of the frozen solutions of bovine plasma with inulin compared to the other saccharides, obtained in a single scan.

The result indicated that at each saccharide concentration, *T´g* was higher for inulin (Table 1), suggesting that it has a greater cryostabilizing effect on bovine plasma proteins than the other saccharides, improving product stability. It was also observed that *T´g* increased with the molecular weight of the cryoprotectant that is: inulin > sucrose > glucose. The same tendency was reported previously by means of the evaluation of protein shelf life time [18]. By the other hand, it was reported that inulin exhibit better stabilizing properties than sucrose and trehalose in the prevention of the nonPEGlated lipoplexes aggregation [14]. Many studies concluded that transition temperatures increased with the saccharides molecular weight [22,23,27].For example *T´g* of freeze–dried surimi depended strongly on the type and content of sugar and at each sugar level the *T´g* was trehalose > sucrose > glucose > sorbitol [47].

Thermograms of bovine plasma solutions revealed the existence of two glass transitions (*T´g1* and *T´g2*) for glucose and sucrose as protective agents, evidenced as deviations in the base line (indicated by arrows in Figure 1). Similar results were found by Telis and Sobral [48] who worked with freeze–dried tomato. This may be because the presence of phases formed by different proportions of saccharide, water, and proteins present in the frozen solution [47-49]. Also it was observed that when the saccharide concentration increased, *T´g1* and *T´g2* increased and decreased respectively (Table 1). However a constant average value was maintained between both *T´g* values for each sugar, being -51.2 ± 0.8 and -41.1 ± 0.1 for glucose and sucrose, respectively. Similar results were found in [47] on freeze–dried surimi product with trehalose. For inulin only one *T´g* was found, which increased with the increase of saccharide concentration. From these results and considering that the water acts as plasticizer, i.e. decreases drastically *T´g* of food polymers [26], it can be concluded that the conditions of the freeze-drying process, are linked directly to *T´g* of the frozen solution. Therefore, it is important to note that the higher value of *T´g* observed in frozen solutions with inulin, allowed higher freezing temperatures during processing reducing production costs.

Applications of Calorimetry in a Wide Context –

**4. Results and discussion** 

saccharides, obtained in a single scan.

glucose > sorbitol [47].

204 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*k*

where the first-order rate constant *k* can be identified with *k*1 of Eq. (4). The total absorbed heat now equals the enthalpy change from *N* to *I*; it was generally assumed that the

Experimentally, the irreversibility of unfolding was verified in a rescan. For an irreversible

**4.1. Effect of saccharides on glass transition of the freeze concentrated matrix** 

As was previously mentioned, to avoid collapse of the products during the freeze-dried process, a temperature below the glass transition temperature of the frozen concentrated solutions, must be attained. Inulin as protein protective agent was comparatively studied, employing mono and disaccharides. The thermograms of Figure 2 show the transition temperatures of the frozen solutions of bovine plasma with inulin compared to the other

The result indicated that at each saccharide concentration, *T´g* was higher for inulin (Table 1), suggesting that it has a greater cryostabilizing effect on bovine plasma proteins than the other saccharides, improving product stability. It was also observed that *T´g* increased with the molecular weight of the cryoprotectant that is: inulin > sucrose > glucose. The same tendency was reported previously by means of the evaluation of protein shelf life time [18]. By the other hand, it was reported that inulin exhibit better stabilizing properties than sucrose and trehalose in the prevention of the nonPEGlated lipoplexes aggregation [14]. Many studies concluded that transition temperatures increased with the saccharides molecular weight [22,23,27].For example *T´g* of freeze–dried surimi depended strongly on the type and content of sugar and at each sugar level the *T´g* was trehalose > sucrose >

Thermograms of bovine plasma solutions revealed the existence of two glass transitions (*T´g1* and *T´g2*) for glucose and sucrose as protective agents, evidenced as deviations in the base line (indicated by arrows in Figure 1). Similar results were found by Telis and Sobral [48] who worked with freeze–dried tomato. This may be because the presence of phases formed by different proportions of saccharide, water, and proteins present in the frozen solution [47-49]. Also it was observed that when the saccharide concentration increased, *T´g1* and *T´g2* increased and decreased respectively (Table 1). However a constant average value was maintained between both *T´g* values for each sugar, being -51.2 ± 0.8 and -41.1 ± 0.1 for glucose and sucrose, respectively. Similar results were found in [47] on freeze–dried surimi product with trehalose. For inulin only one *T´g* was found, which increased with the increase of saccharide concentration. From these results and considering that the water acts as plasticizer, i.e. decreases drastically *T´g* of food polymers [26], it can be concluded that the conditions of the freeze-drying process, are linked directly to *T´g* of the frozen solution.

enthalpy change from *D* to *I* was negligible compared to that from *N* to *D* [44].

process, in the DSC rescanned thermograms no transition could be observed.

*N I* (5)

**Figure 2.** DSC thermograms for freeze bovine plasma protein-saccharide solutions. Down-arrows indicate *T´g*. Scan rate = 2°C/min ; pH = 8.


**Table 1.** Effect of type and concentration of cryoprotectant on glass transition temperature (*T´g*) and lyoprotectant on glass transition temperature (*Tg*) of freeze bovine plasma proteins solutions (heating rate: 2 °C/min). Values represents the means ± standard deviation; n = 3. Values followed by different letters in the same column are significantly different from each other (*P* < 0.05).

The effect of water as a plasticizer of the mixture protein-saccharide was predicted by the Miller/Fox and Gordon–Taylor equations, the results, were compared with experimental values (Table 1). The data of *T´g* of all pure components required for the Eq. (1) are listed in Table 2.

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 207

**4.2. Effect of saccharides on glass transition of the freeze-dried samples** 

**Figure 3.** DSC thermograms for freeze–dried bovine plasma protein–saccharide mixtures. Down-

temperatures, reducing the storage costs.

arrows indicate *Tg*. Heating rate: 2°C min-1; pH=8

The storage temperature of frozen or freeze-dried foods should be below the glass transition temperature as previously established [22,27,42,50]. Figure 3 shows the thermograms of the freeze-dried samples containing inulin compared with glucose and sucrose at different concentrations. The existence of these transitions evidenced the glassy state of the freeze– dried plasma protein/saccharides mixtures. Besides, Table 1 shows that *Tg* of the sample increases with increasing saccharide concentration. Similar results were found in the references [28,30]. This effect can be explained considering that sugar forms hydrogen– bridge bonds with proteins reducing the available volume for the interaction with water molecules, so water become less effective as plasticizer with an increase in saccharide content [51]. Also was observed that *Tg* of the freeze-dried samples increased with increasing of the molecular weight of the cryoprotectant. Processes of devitrification and hence product spoilage can occur if the temperature of storage is higher than the *Tg* of the sample. Therefore, the higher *Tg* value of inulin provides greater stability at higher

The densities of bovine plasma proteins, glucose, sucrose and inulin (at room temperature) were determined with a digital densimeter, and the results were: 0.4 ± 0.08 g/cm3, 0.6 ± 0.05 g/cm3, 0.8 ± 0.04 g/cm3 and 0.3 ± 0.05 g/cm3, respectively.

From literature the *Tg* of the water is -135 °C [41] and the *T´g* of plasma protein is -11 ± 2 °C [22]. The *Tg* value of bovine plasma protein for Eq. (3), was 65 ± 3 °C. Entering this data into Eqs. (2) and (4), the predicted values of *T´g* were obtained, which are listed in Table 3. The results showed that the glass transition property evaluated from the proposed models was in agreement with the experimental data with an average error of 4.86% for the Miller/ Fox equation and 0.09% for Gordon/Taylor equation. The value of *k* from the Gordon/Taylor equation is defined as the resistance to a *T´g* decrease induced by the plasticizing effect of water [26,41,47]. The order found for *k* value of the saccharides was: inulin > sucrose > glucose. Although the highest value of k is for inulin, this saccharide has the highest *Tg* value, allowing a greater value *T´g* and therefore generating a lower cost during processing, preventing also the collapse of the product at temperatures relatively higher during the freeze-drying.


**Table 2.** Data from references used in the calculation of *T´g* by Miller/Fox and Gordon/Taylor modified equation [18].


**Table 3.** Glass transition parameters for the multicomponent system: plasma bovine proteinssaccharides-water. *\**: *s*olution density (T=19.8°C)

#### **4.2. Effect of saccharides on glass transition of the freeze-dried samples**

Applications of Calorimetry in a Wide Context –

Table 2.

freeze-drying.

equation [18].

*\**

*Tg´* (°C)

*Tg´* (°C) (Gordon/

saccharides-water. *\**

206 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

g/cm3, 0.8 ± 0.04 g/cm3 and 0.3 ± 0.05 g/cm3, respectively.

The effect of water as a plasticizer of the mixture protein-saccharide was predicted by the Miller/Fox and Gordon–Taylor equations, the results, were compared with experimental values (Table 1). The data of *T´g* of all pure components required for the Eq. (1) are listed in

The densities of bovine plasma proteins, glucose, sucrose and inulin (at room temperature) were determined with a digital densimeter, and the results were: 0.4 ± 0.08 g/cm3, 0.6 ± 0.05

From literature the *Tg* of the water is -135 °C [41] and the *T´g* of plasma protein is -11 ± 2 °C [22]. The *Tg* value of bovine plasma protein for Eq. (3), was 65 ± 3 °C. Entering this data into Eqs. (2) and (4), the predicted values of *T´g* were obtained, which are listed in Table 3. The results showed that the glass transition property evaluated from the proposed models was in agreement with the experimental data with an average error of 4.86% for the Miller/ Fox equation and 0.09% for Gordon/Taylor equation. The value of *k* from the Gordon/Taylor equation is defined as the resistance to a *T´g* decrease induced by the plasticizing effect of water [26,41,47]. The order found for *k* value of the saccharides was: inulin > sucrose > glucose. Although the highest value of k is for inulin, this saccharide has the highest *Tg* value, allowing a greater value *T´g* and therefore generating a lower cost during processing, preventing also the collapse of the product at temperatures relatively higher during the

Glucose -85 -79 -72 Sucrose -59 -53 -46 Inulin -17 -15 -13 **Table 2.** Data from references used in the calculation of *T´g* by Miller/Fox and Gordon/Taylor modified

5 % (w/v) 10% (w/v) 15 % (w/v)

Glucose %(w/v) Sucrose %(w/v) Inulin %(w/v) *5 10* 15 *5* 10 *15 5 10 15* 

(g cm-3) 1.039 1.042 1.059 1.033 1.041 1.056 1.032 1.039 1.049

(Miller/Fox) -63.99 -60.46 -56.1 -54.07 -51.24 -47.04 -30.43 -23.64 -19.51 Difference (%) 2.32 0.99 6.63 4.79 2.18 2.95 11.40 0.12 14.8

Taylor modified) -62.69 -61.26 -60.03 -51.38 -50.58 -48.47 -26.70 -24.23 -22.11 Difference (%) 0.30 0.33 0.35 0.19 0.91 0.10 0.97 2.31 1.31 *k* 3.5 4.1 4.5

**Table 3.** Glass transition parameters for the multicomponent system: plasma bovine proteins-

: *s*olution density (T=19.8°C)

Saccharide *T´g* (°C)

The storage temperature of frozen or freeze-dried foods should be below the glass transition temperature as previously established [22,27,42,50]. Figure 3 shows the thermograms of the freeze-dried samples containing inulin compared with glucose and sucrose at different concentrations. The existence of these transitions evidenced the glassy state of the freeze– dried plasma protein/saccharides mixtures. Besides, Table 1 shows that *Tg* of the sample increases with increasing saccharide concentration. Similar results were found in the references [28,30]. This effect can be explained considering that sugar forms hydrogen– bridge bonds with proteins reducing the available volume for the interaction with water molecules, so water become less effective as plasticizer with an increase in saccharide content [51]. Also was observed that *Tg* of the freeze-dried samples increased with increasing of the molecular weight of the cryoprotectant. Processes of devitrification and hence product spoilage can occur if the temperature of storage is higher than the *Tg* of the sample. Therefore, the higher *Tg* value of inulin provides greater stability at higher temperatures, reducing the storage costs.

**Figure 3.** DSC thermograms for freeze–dried bovine plasma protein–saccharide mixtures. Downarrows indicate *Tg*. Heating rate: 2°C min-1; pH=8

### **4.3. Effect of saccharides on crystallization temperature of the freeze-dried samples**

It is important to determine the crystallization temperature (*Tc*) of the freeze-dried samples since crystallization causes the most drastic changes on physical properties of food polymers and affects considerably food stability. The glass transition is often followed by crystallization of the solutes where the molecular mobility increases and the sample crystallizes increasing the rate of food spoilage [27,28,30].

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 209

*H* (J g-1)

2.97 0.55a,d,c

110.07 1.22a 0.84 0.32a

107.27 0.85a,d 12.26 0.92e

104.91 0.89d 3.77 0.98d,f

**4.4. Thermal denaturation of BPP in a matrix of saccharide** 

Saccharide Concentration (%, w/v) *Td* (°C)

5

10

15

**Table 4.** Effect of saccharide concentration on the denaturation temperature of freeze dried BPP concentrate. Heating rate: 2°C min-1. pH=8. Values followed by different letters in the same column are

Inulin 143.81 0.89c

Sucrose 132.78 2.12b 5.08 0.98b,c

Sucrose 144.95 2.34c 22.40 1.23 Inulin 156.21 1.12e 12.22 1.43e

Sucrose 126.66 1.54f 7.01 1.22b Inulin 132.57 1.34b 5.78 0.76b,f,c

The functional structure of a protein in solution is determined by electrostatic forces, hydrogen bonds, Van der Waals interactions and hydrophobic interactions. All these interactions are influenced by water, becoming essential for the functional unfolding of most of the proteins. As water is eliminated during freeze-drying, peptide-peptide interactions prevail causing an alteration in the secondary, tertiary or quaternary structure of the protein, i.e. a conformational change of it. However, the presence of sugar displaces and supplants water forming hydrogen bonds with the dry protein which maintains its structured integrity into the glass matrix. In the case that the formation of the glass structure did not occur, the sugar would be excluded and it would not be available for the formation of hydrogen bonds to protect the dry protein from its

The thermal stability of BPP in a matrix of inulin compared with other saccharides was investigated using DSC. Table 4 shows the values of *Td* obtained for BPP concentrate without protective agents and in different matrixes of glucose, sucrose and inulin at different concentrations. The value of *Td* for BPP concentrate (88.19 ± 1.87 °C), was obtained from thermograms without protective agent and was similar to that reported in reference [53], for blood plasma. Comparing this value with the protein sample immersed in a matrix of saccharide, it was observed an increase in the value of *Td* in all the cases, indicating a higher thermal resistance due to the stabilizing effect of saccharides. A similar behavior was observed in the DSC study of whey protein concentrates with the addition of honey [54]. Evaluating among the saccharides at the same concentration, it can be concluded that the higher the molecular weight of the carbohydrate, the higher was the *Td*, thus inulin > sucrose > glucose. This behavior was in agreement with that reported in [55], in multi-block copolymers. With respect to the range of saccharide concentrations studied, optimum concentration was 10% (w/v), as it is shown in Table 4, in terms of the

*4.4.1. Effect of saccharide type and concentration* 

values of *Td* and *H*.

Glucose

Glucose

Glucose

significantly different from each other (*P* < 0.05).

unfolding or loss of conformation [13,14].

Fig 4 shows the crystallization temperature (*Tc*) obtained from the intersection of the baseline and the tangent of the exothermic peak, and the crystallization enthalpy (*Hc*) estimated as the area under the peak for the different protective agents at different concentrations. The crystallization temperature of freeze-dried samples was found to depend on the molecular weight and the saccharide concentration [27,30]. Therefore, the results showed that the presence of inulin at the same concentration than the other saccharides further increases the *Tc* value of freeze–dried solutions. Mixtures containing a saccharide concentration of 10 % (w/v) show an increase of *Hc*, indicating a higher amorphous content. This behavior can be explained considering that a suitable proportion of saccharide and protein in the mixture allows a better interaction among these components [51,52,43].

**Figure 4.** DSC thermogram for freeze-dried bovine plasma protein with the protective agents at different concentrations. The exothermic event indicates *Tc*. Heating rate: 2°C min-1; pH=8.

### **4.4. Thermal denaturation of BPP in a matrix of saccharide**

### *4.4.1. Effect of saccharide type and concentration*

Applications of Calorimetry in a Wide Context –

**samples** 

show an increase of

208 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and the tangent of the exothermic peak, and the crystallization enthalpy (

crystallizes increasing the rate of food spoilage [27,28,30].

allows a better interaction among these components [51,52,43].

**4.3. Effect of saccharides on crystallization temperature of the freeze-dried** 

It is important to determine the crystallization temperature (*Tc*) of the freeze-dried samples since crystallization causes the most drastic changes on physical properties of food polymers and affects considerably food stability. The glass transition is often followed by crystallization of the solutes where the molecular mobility increases and the sample

Fig 4 shows the crystallization temperature (*Tc*) obtained from the intersection of the baseline

area under the peak for the different protective agents at different concentrations. The crystallization temperature of freeze-dried samples was found to depend on the molecular weight and the saccharide concentration [27,30]. Therefore, the results showed that the presence of inulin at the same concentration than the other saccharides further increases the *Tc* value of freeze–dried solutions. Mixtures containing a saccharide concentration of 10 % (w/v)

explained considering that a suitable proportion of saccharide and protein in the mixture

**Figure 4.** DSC thermogram for freeze-dried bovine plasma protein with the protective agents at different concentrations. The exothermic event indicates *Tc*. Heating rate: 2°C min-1; pH=8.

*Hc*, indicating a higher amorphous content. This behavior can be

*Hc*) estimated as the

The thermal stability of BPP in a matrix of inulin compared with other saccharides was investigated using DSC. Table 4 shows the values of *Td* obtained for BPP concentrate without protective agents and in different matrixes of glucose, sucrose and inulin at different concentrations. The value of *Td* for BPP concentrate (88.19 ± 1.87 °C), was obtained from thermograms without protective agent and was similar to that reported in reference [53], for blood plasma. Comparing this value with the protein sample immersed in a matrix of saccharide, it was observed an increase in the value of *Td* in all the cases, indicating a higher thermal resistance due to the stabilizing effect of saccharides. A similar behavior was observed in the DSC study of whey protein concentrates with the addition of honey [54]. Evaluating among the saccharides at the same concentration, it can be concluded that the higher the molecular weight of the carbohydrate, the higher was the *Td*, thus inulin > sucrose > glucose. This behavior was in agreement with that reported in [55], in multi-block copolymers. With respect to the range of saccharide concentrations studied, optimum concentration was 10% (w/v), as it is shown in Table 4, in terms of the values of *Td* and *H*.


**Table 4.** Effect of saccharide concentration on the denaturation temperature of freeze dried BPP concentrate. Heating rate: 2°C min-1. pH=8. Values followed by different letters in the same column are significantly different from each other (*P* < 0.05).

The functional structure of a protein in solution is determined by electrostatic forces, hydrogen bonds, Van der Waals interactions and hydrophobic interactions. All these interactions are influenced by water, becoming essential for the functional unfolding of most of the proteins. As water is eliminated during freeze-drying, peptide-peptide interactions prevail causing an alteration in the secondary, tertiary or quaternary structure of the protein, i.e. a conformational change of it. However, the presence of sugar displaces and supplants water forming hydrogen bonds with the dry protein which maintains its structured integrity into the glass matrix. In the case that the formation of the glass structure did not occur, the sugar would be excluded and it would not be available for the formation of hydrogen bonds to protect the dry protein from its unfolding or loss of conformation [13,14].

210 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The protective effect of saccharides depends on its concentration, since as the concentration increases there are more possibilities of forming hydrogen bonds with the protein [11,18]. However, when concentrations were higher than 10 % (w/v), a lower protection was obtained. This result can be explained taking into account that at high concentrations, the saccharide starts to crystallize during freeze-drying, being prevented the formation of hydrogen bonds with the dry protein [12]. This behavior was confirmed by determination of the native proteins in the protein-saccharide matrixes employing eq. (1). The results are presented in Figure 5, which shows that there is a maximum at a concentration of 10% (w/v) for the different saccharides analyzed, indicating higher protein protection and stability.

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 211

*H* were

*H* values

*H* values at

With increasing alkalinity of the medium there is an increase in the values of *Td* for each saccharide (pH 8), indicating that BPP concentrate was more stable at higher pH. Similar results were found in previous works in porcine blood plasma proteins and whey protein concentrate [34,54]. Comparing between different saccharides at the same concentration, it

found at pH 4, this may be to the proximity with the isoelectric point of proteins (pI: 4.8-5.8),

The protein-saccharide mixtures were studied at different scanning rates (2 °C/min and 5 °C/min). As an example Figure 6 shows the transition temperature and enthalpy for sucrose

can be seen that inulin presents a higher *Td* in all the pH range. The maximum

pH = 6 were reported by Dàvila in reference [34]. The lowest values of *Td* and

**Figure 6.** Effect of DSC heating rate on *Td* values of freeze-dried BBP with sucrose 10%(w/v).

increased 5 2 °C in all the samples with increasing scanning rate, similar behavior was

scanning rate that was in agreement with the results reported in references [21,59]. Thus, the system was scanning rate dependent and so the thermal denaturation process was under

The irreversibility of BPP denaturation was investigated by a multiple reheating experiment, according to the method proposed by by Idakieva and Michnik [45,60]. From the initial DSC scan, we have determined the values of the transition temperatures at 107°C, 145 °C and 156 °C for glucose, sucrose and inulin at 10% w/v, respectively (Table 5). DSC tests were carried out as successive scans, where the heating was carried out up to different final

*H* are scanning rate dependent. *Td* values

*H* decreased ( 10%) with increasing

It was found for all the saccharides that *Td* and

reported in references [56-58]. Furthermore, the

*4.4.4. Study of Irreversibility of the Thermal Denaturation of BPP* 

temperatures, with a cooling up to 20°C between scans (Figure 7).

kinetic control [33,44].

were observed at pH 6 indicating a higher amount of native protein. Similar

thus decreasing the electrical net charge and facilitating aggregation reactions.

*4.4.3. Effect of scanning rate* 

at 10 % (w/v).

**Figure 5.** Native protein percentage of freeze dried BPP concentrate with different protective agents at different concentrations.

### *4.4.2. Effect of pH*

To determine the application of these formulations is important to know the variation of *Td* as a function of pH due to the wide range of environmental conditions existing in food. Table 5 shows the *Td* values of BPP concentrate in a glassy matrix of saccharides at different pH values.


**Table 5.** Effect of pH and addition of saccharides on the denaturation temperature of BPP concentrate. Heating rate: 2°C/min. Values represents the means ± standard deviation; n = 3. Values followed by different letters in the same column are significantly different from each other (*P*< 0.05).

With increasing alkalinity of the medium there is an increase in the values of *Td* for each saccharide (pH 8), indicating that BPP concentrate was more stable at higher pH. Similar results were found in previous works in porcine blood plasma proteins and whey protein concentrate [34,54]. Comparing between different saccharides at the same concentration, it can be seen that inulin presents a higher *Td* in all the pH range. The maximum *H* values were observed at pH 6 indicating a higher amount of native protein. Similar *H* values at pH = 6 were reported by Dàvila in reference [34]. The lowest values of *Td* and *H* were found at pH 4, this may be to the proximity with the isoelectric point of proteins (pI: 4.8-5.8), thus decreasing the electrical net charge and facilitating aggregation reactions.

### *4.4.3. Effect of scanning rate*

Applications of Calorimetry in a Wide Context –

different concentrations.

Glucose

Glucose

Glucose

*4.4.2. Effect of pH* 

pH values.

210 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The protective effect of saccharides depends on its concentration, since as the concentration increases there are more possibilities of forming hydrogen bonds with the protein [11,18]. However, when concentrations were higher than 10 % (w/v), a lower protection was obtained. This result can be explained taking into account that at high concentrations, the saccharide starts to crystallize during freeze-drying, being prevented the formation of hydrogen bonds with the dry protein [12]. This behavior was confirmed by determination of the native proteins in the protein-saccharide matrixes employing eq. (1). The results are presented in Figure 5, which shows that there is a maximum at a concentration of 10% (w/v) for the different saccharides analyzed, indicating higher protein protection and stability.

**Figure 5.** Native protein percentage of freeze dried BPP concentrate with different protective agents at

To determine the application of these formulations is important to know the variation of *Td* as a function of pH due to the wide range of environmental conditions existing in food. Table 5 shows the *Td* values of BPP concentrate in a glassy matrix of saccharides at different

Sucrose 144.95 1.34b 22.40 0.97b

Sucrose 134.56 2.16e 43.15 1.23d Inulin 152.98 1.52c,f 42.95 1.45d

Sucrose 107.67 1.56a 9.32 0.72e Inulin 151.84 1.89f 9.35 0.96e **Table 5.** Effect of pH and addition of saccharides on the denaturation temperature of BPP concentrate. Heating rate: 2°C/min. Values represents the means ± standard deviation; n = 3. Values followed by

*H* (J g-1)

12.22 0.55a

107.27 0.85a 12.26 0.82a

102.94 1.33d 34.74 0.92c

101.74 1.27d 9.58 0.98a,e

Saccharide pH *Td* (°C)

8

6

4

different letters in the same column are significantly different from each other (*P*< 0.05).

Inulin 156.21 1.12c

The protein-saccharide mixtures were studied at different scanning rates (2 °C/min and 5 °C/min). As an example Figure 6 shows the transition temperature and enthalpy for sucrose at 10 % (w/v).

**Figure 6.** Effect of DSC heating rate on *Td* values of freeze-dried BBP with sucrose 10%(w/v).

It was found for all the saccharides that *Td* and *H* are scanning rate dependent. *Td* values increased 5 2 °C in all the samples with increasing scanning rate, similar behavior was reported in references [56-58]. Furthermore, the *H* decreased ( 10%) with increasing scanning rate that was in agreement with the results reported in references [21,59]. Thus, the system was scanning rate dependent and so the thermal denaturation process was under kinetic control [33,44].

#### *4.4.4. Study of Irreversibility of the Thermal Denaturation of BPP*

The irreversibility of BPP denaturation was investigated by a multiple reheating experiment, according to the method proposed by by Idakieva and Michnik [45,60]. From the initial DSC scan, we have determined the values of the transition temperatures at 107°C, 145 °C and 156 °C for glucose, sucrose and inulin at 10% w/v, respectively (Table 5). DSC tests were carried out as successive scans, where the heating was carried out up to different final temperatures, with a cooling up to 20°C between scans (Figure 7).

212 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

For glucose, sucrose and inulin, the first heating was carried out up to 75°C, and 85°C (temperatures below the *Td* for all the saccharides), respectively; no thermal effect was observed in the thermal denaturation peak during the reheating experiment. However, if the rescanning was stopped over their transition temperatures, the endothermic peak of *Td* disappeared completely. Therefore, the endothermic peak of *Td* disappeared completely upon rescanning the sample at temperatures above *Td*; furthermore, as was previously described, the thermograms were scanning-rate dependent, suggesting both results that it was an irreversible event [61]. Similar behavior was also found for whey protein in an amorphous carbohydrate matrix [49], porcine blood plasma proteins [34] and BSA [33]. Irreversible denaturation of bovine plasma proteins might be due to processes such as aggregation, where hydrophobic interactions occur, and exposed thiol groups can form disulfide bonds, which result in an irreversible behavior [33]. Considering the Arrhenius law and the treatment developed in reference [43], the determination of the activation energy can be achieved from the experimental data. The obtained values were: 10443 J mol-1, for BPP without protective agent; 27216 J mol-1, 32058 J mol-1 and 42099 J mol-1 for BPP with glucose, sucrose and inulin, respectively, all of them at 10% (w/v). The results showed that Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 213

with the addition of protective agents the activation energy increased; besides with increasing molecular weight, the activation energy also increased. Therefore, the addition of saccharides, especially of inulin caused a decrease in the rate of degradation reactions,

**Figure 8.** Scanning electron micrographs of the freeze-dried product with different saccharides, with a

It was observed phases homogeneously distributed, indicating miscibility of the component in the matrix. The shapes were uniform, which was an attribute, linked with thermodynamic compatibility [62]. Based on the data previously obtained, comparing the transitions of the blends with respect to the value of the individual components, showed an

magnification of 200X for glucose and sucrose, 300X for inulin.

obtaining a higher stabilization upon storage [8,14,18].

*4.4.5. Study of the blends morphology through SEM* 

Figure 8 sowed the SEM micrographs of blends of protein-saccharides.

**Figure 7.** DSC thermograms of freeze dried BPP concentrate with saccharide at 10 % (w/v). DSC scans (2), (3), (4) represent thermograms from repeated heating and subsequent cooling. Scan (1) is a full scan to 120 °C (glucose), 155°C (sucrose) and 158 °C (inulin).

with the addition of protective agents the activation energy increased; besides with increasing molecular weight, the activation energy also increased. Therefore, the addition of saccharides, especially of inulin caused a decrease in the rate of degradation reactions, obtaining a higher stabilization upon storage [8,14,18].

### *4.4.5. Study of the blends morphology through SEM*

Applications of Calorimetry in a Wide Context –

212 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

For glucose, sucrose and inulin, the first heating was carried out up to 75°C, and 85°C (temperatures below the *Td* for all the saccharides), respectively; no thermal effect was observed in the thermal denaturation peak during the reheating experiment. However, if the rescanning was stopped over their transition temperatures, the endothermic peak of *Td* disappeared completely. Therefore, the endothermic peak of *Td* disappeared completely upon rescanning the sample at temperatures above *Td*; furthermore, as was previously described, the thermograms were scanning-rate dependent, suggesting both results that it was an irreversible event [61]. Similar behavior was also found for whey protein in an amorphous carbohydrate matrix [49], porcine blood plasma proteins [34] and BSA [33]. Irreversible denaturation of bovine plasma proteins might be due to processes such as aggregation, where hydrophobic interactions occur, and exposed thiol groups can form disulfide bonds, which result in an irreversible behavior [33]. Considering the Arrhenius law and the treatment developed in reference [43], the determination of the activation energy can be achieved from the experimental data. The obtained values were: 10443 J mol-1, for BPP without protective agent; 27216 J mol-1, 32058 J mol-1 and 42099 J mol-1 for BPP with glucose, sucrose and inulin, respectively, all of them at 10% (w/v). The results showed that

**Figure 7.** DSC thermograms of freeze dried BPP concentrate with saccharide at 10 % (w/v). DSC scans (2), (3), (4) represent thermograms from repeated heating and subsequent cooling. Scan (1) is a full scan

to 120 °C (glucose), 155°C (sucrose) and 158 °C (inulin).

Figure 8 sowed the SEM micrographs of blends of protein-saccharides.

It was observed phases homogeneously distributed, indicating miscibility of the component in the matrix. The shapes were uniform, which was an attribute, linked with thermodynamic compatibility [62]. Based on the data previously obtained, comparing the transitions of the blends with respect to the value of the individual components, showed an increase in the value *Td*. This increase in the *Td* values can be attributed to greater miscibility of the components of the mixtures, confirming what was observed in the micrographs [61]. Therefore, these results are in agreement with the concept of miscibility, which is based on the variation of the thermal behavior with respect to the individual materials [63].

Calorimetric Study of Inulin as Cryo- and Lyoprotector of Bovine Plasma Proteins 215

Laura T. Rodriguez Furlán, Antonio Pérez Padilla and Mercedes E. Campderrós\* *Research Institute of Chemical Technology (INTEQUI –CONICET-CCT San Luis), Faculty of* 

*Research and Development in Food Cryotechnology Centre (CIDCA- CONICET- CCT La Plata),* 

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[3] Hempel S, Jacob A, Rohm H (2007) Influence of Inulin Modification and Flour Type on the Sensory Quality of Prebiotic Wafer Crackers. Eur. food res. technol. 224: 335-341. [4] Nazzaro F, Fratianni F, Coppola R, Sada A, Pierangelo O (2009) Fermentative Ability of Alginate-prebiotic Encapsulated Lactobacillus Acidophilus and Survival under

[5] Kip P, Meyer D, Jellema R H (2006) Inulins Improve Sensory and Textural Properties of

[6] Ronkart S N, Paquot M, Fougnies C, Deroanne C, Blecker C S (2009) Effect of Water

[7] Baeza R I, Pilosof A M R (2002) Calorimetric Studies of Thermal Denaturation of b-Lactoglobulin in the Presence of Polysaccharides. Lebensm.-wiss. technol. 35: 393–399. [8] Buera P, Schebor C, Elizalde B (2005) Effects of Carbohydrate Crystallization on Stability of Dehydrated Foods and Ingredient Formulations. J. food eng. 67: 157-165. [9] Claude J, Ubbink J (2006) Thermal Degradation of Carbohydrate Polymers in Amorphous States: A Physical Study Including Colorimetry. Food chem. 96: 402-410. [10] Santivarangkna C, Higl B, Foerst P (2008) Protection Mechanisms of Sugars During Different Stages of Preparation Process of Dried Lactic Acid Starter Cultures. Food

[11] Allison S D, Chang B, Randolph T W, Carpenter J F (1999) Hydrogen Bonding Between Sugar and Protein is Responsible for Inhibition of Dehydration-Induced Protein

[12] Carpenter J F, Crowe L M, Crowe J H (1987) Stabilization of Phosphofructokinase with Sugars during Freeze-drying: Characterization of Enhanced Protection in the Presence

Simulated Gastrointestinal Conditions. J. funct. food 1(3): 319-323.

Uptake on Amorphous Inulin Properties. Food hydrocolloid 23: 922–927.

*Chemistry, Biochemistry and Pharmacy, UNSL, San Luis, Argentine* 

*Faculty of Engineering, UNLP, La Plata, Bs As, Argentine* 

Low-Fat Yoghurts. Int. dairy j. 16: 1098–1103.

Unfolding. Biochem. biophys. 365: 289-298.

of Divalent Cations. Biochim. biophys. acta 923(1): 109-115.

**Author details** 

Noemi E. Zaritzky

**6. References** 

82: 471-476.

microbiol. 25: 429-441.

 \*

Corresponding Author

*Argentine* 

Javier Lecot and Noemi E. Zaritzky

### **5. Conclusions**

The thermodynamic properties of the solution and the freeze–dried bovine plasma proteins– saccharides mixtures were investigated in this study. The DSC thermograms demonstrated that the bovine plasma proteins– inulin mixtures have the highest glass transition temperature for the protein solution and also the highest glass transition and denaturation temperature for the freeze–dried powder, optimizing the freeze–drying process and also stabilizing and protecting the proteins during storage in conditions below the collapse temperature of the material. Thermograms revealed the existence of two glass transitions in solutions (*T´g1* and *T´g2*) for glucose and sucrose. With increasing saccharide content, the *T´g1* and *T´g2* of the samples increased and decreased, respectively. For inulin only one *T´g* was found, which increased with saccharide concentration. Also was found that *T´g*, *Tg* and *Tc* depended on the molecular weight of saccharides, increasing with the increasing of molecular weight, being inulin > sucrose > glucose. The proposed model allowed the prediction of transition temperature in a multicomponent mixture which is useful to design a freeze–drying cycle and storage stability of plasma protein concentrates. The addition of saccharides allowed the increase of the protein denaturation temperature and enthalpy, with an optimal saccharide concentration of 10% (w/v) and a pH range between 6 and 8. This change in the thermal properties shows a greater compatibility of the blends with 10% (w/v) saccharide, because this concentration causes the greatest changes in the values of *Td* when compared with individual values of BPP. The results were corroborated by the SEM micrographs, showing homogeneously distributed phases, and denoting the highest miscibility between them. The temperature of thermal denaturation was scan rate dependent, and no thermal transition was detected in the re-scan experiments so it was concluded that the protein unfolding was irreversible and was adequately interpreted by the theoretical model employed.

Therefore, the results showed highest values of *Tg* and *Td* in the freeze–dried samples of inulin proven that this compound is a better protein protective agent during storage than mono and disaccharides such as glucose and sucrose. In this way prevent the unfolding of bovine plasma proteins submitted to higher temperatures. Furthermore, the higher *T´g* of frozen solutions of bovine proteins with inulin allows higher freezer temperatures during freeze–drying, reducing costs in a food elaboration. The finding about the inulin cryoprotant role of food proteins is relevant considering that it is a soluble fiber, categorized as a prebiotic, and being a valuable alternative as a functional ingredient for food formulation [64,65].

The findings regarding the protective effect of inulin on bovine plasma proteins, suggest that may be interesting the study of the behavior of formulated foods elaborated with the analyzed matrices (protein-saccharide-water) exposed to treatments such as cooling and freeze-drying.

### **Author details**

Applications of Calorimetry in a Wide Context –

**5. Conclusions** 

the theoretical model employed.

freeze-drying.

214 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

increase in the value *Td*. This increase in the *Td* values can be attributed to greater miscibility of the components of the mixtures, confirming what was observed in the micrographs [61]. Therefore, these results are in agreement with the concept of miscibility, which is based on

The thermodynamic properties of the solution and the freeze–dried bovine plasma proteins– saccharides mixtures were investigated in this study. The DSC thermograms demonstrated that the bovine plasma proteins– inulin mixtures have the highest glass transition temperature for the protein solution and also the highest glass transition and denaturation temperature for the freeze–dried powder, optimizing the freeze–drying process and also stabilizing and protecting the proteins during storage in conditions below the collapse temperature of the material. Thermograms revealed the existence of two glass transitions in solutions (*T´g1* and *T´g2*) for glucose and sucrose. With increasing saccharide content, the *T´g1* and *T´g2* of the samples increased and decreased, respectively. For inulin only one *T´g* was found, which increased with saccharide concentration. Also was found that *T´g*, *Tg* and *Tc* depended on the molecular weight of saccharides, increasing with the increasing of molecular weight, being inulin > sucrose > glucose. The proposed model allowed the prediction of transition temperature in a multicomponent mixture which is useful to design a freeze–drying cycle and storage stability of plasma protein concentrates. The addition of saccharides allowed the increase of the protein denaturation temperature and enthalpy, with an optimal saccharide concentration of 10% (w/v) and a pH range between 6 and 8. This change in the thermal properties shows a greater compatibility of the blends with 10% (w/v) saccharide, because this concentration causes the greatest changes in the values of *Td* when compared with individual values of BPP. The results were corroborated by the SEM micrographs, showing homogeneously distributed phases, and denoting the highest miscibility between them. The temperature of thermal denaturation was scan rate dependent, and no thermal transition was detected in the re-scan experiments so it was concluded that the protein unfolding was irreversible and was adequately interpreted by

Therefore, the results showed highest values of *Tg* and *Td* in the freeze–dried samples of inulin proven that this compound is a better protein protective agent during storage than mono and disaccharides such as glucose and sucrose. In this way prevent the unfolding of bovine plasma proteins submitted to higher temperatures. Furthermore, the higher *T´g* of frozen solutions of bovine proteins with inulin allows higher freezer temperatures during freeze–drying, reducing costs in a food elaboration. The finding about the inulin cryoprotant role of food proteins is relevant considering that it is a soluble fiber, categorized as a prebiotic, and being a valuable

The findings regarding the protective effect of inulin on bovine plasma proteins, suggest that may be interesting the study of the behavior of formulated foods elaborated with the analyzed matrices (protein-saccharide-water) exposed to treatments such as cooling and

alternative as a functional ingredient for food formulation [64,65].

the variation of the thermal behavior with respect to the individual materials [63].

Laura T. Rodriguez Furlán, Antonio Pérez Padilla and Mercedes E. Campderrós\* *Research Institute of Chemical Technology (INTEQUI –CONICET-CCT San Luis), Faculty of Chemistry, Biochemistry and Pharmacy, UNSL, San Luis, Argentine* 

Javier Lecot and Noemi E. Zaritzky

*Research and Development in Food Cryotechnology Centre (CIDCA- CONICET- CCT La Plata), Argentine* 

Noemi E. Zaritzky *Faculty of Engineering, UNLP, La Plata, Bs As, Argentine* 

### **6. References**


<sup>\*</sup> Corresponding Author

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**Section 4** 

**Thermal Analysis of Phase Transitions** 

**of Polymers and Paraffinic Wax** 


**Thermal Analysis of Phase Transitions of Polymers and Paraffinic Wax** 

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[58] Zamorano L S, Pina D G, Gavilanes F, Roig M G, Yu Sakharov I, Jadan A P, van Huystee, R B, Villar E, Shnyrov V L (2004) Two-state Irreversible Thermal Denaturation of Anionic Peanut (Arachis Hypogaea L.) Peroxidase. Thermochim. acta 417: 67-73. [59] Vermeer A W P, Norde W (2000) The Thermal Stability of Immunoglobulin: Unfolding

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[63] Mousavioun P, Doherty W O S, George G (2010) Thermal Stability and Miscibility of Poly(hydroxybutyrate) and Soda Lignin Blends. Ind. crop. prod. 32(3): 656-661. [64] Rodriguez Furlán L T, Pérez Padilla A, Campderrós M E (2010) Functional and Physical Properties of Bovine Plasma Proteins as a Function of Processing and pH, Application

[65] Rodriguez Furlán L T, Rinaldoni A N, Padilla A P, Campderrós M E (2011) Assessment of Functional Properties of Bovine Plasma Proteins Compared with other Proteins Concentrates, Application in a Hamburger Formulation. Am. j. food tech. 6 (9): 717-729.

**Chapter 10** 

© 2013 Parashar, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

**Silver Particulate Films** 

Additional information is available at the end of the chapter

resulted in an attempt to adopt eco friendly methods.

Pratima Parashar

**1. Introduction** 

information storage.

http://dx.doi.org/10.5772/54502

biochemical sensors and devices.

**on Compatible Softened Polymer Composites** 

Polymer/inorganic nanocomposites have been of great interest in recent years, not only for the novel properties of the nanocomposite materials but also for the continuously growing demand for the miniaturisation of electronics components, optical detectors, chemicals and

Polymer matrices have been frequently used as particle stabilizers in chemical synthesis of metal colloids since these prevent agglomeration of the particles. Within the past decade, incorporating silver nanoparticle into a polymer matrix is more interesting because the resulting nanocomposites exhibit applications in catalysis, drug wound dressing and optical

It is difficult to disperse silver nanoparticle homogeneously into a polymer matrix by ex situ methods because of easy agglomeration of nanoparticles. At present, it is possible to obtain nanoparticles of different shape and size in nanostructured polymeric environment using various polymeric systems and different approaches. Numerous methods used toxic and potentially hazardous reactants. Increasing environmental concerns over synthesis route

One of the simplest techniques to form such particulate structures, which are generally known as island or discontinuous metal films, is through vacuum evaporation of metal on to a dielectric substrate by stopping the deposition at a very early stage. The temporal instability exhibited by island films even in vacuum is attributed to mobility of islands followed by coalescence [1]. Further, these films get oxidised when they are exposed to atmosphere. The oxidation of islands causes an irreversible increase in electrical resistance [2]. An interesting sub-surface particulate structure formation was reported when certain inorganic materials are deposited on to softened polymer substrates [3-6] and the

## **Silver Particulate Films on Compatible Softened Polymer Composites**

Pratima Parashar

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54502

### **1. Introduction**

Polymer/inorganic nanocomposites have been of great interest in recent years, not only for the novel properties of the nanocomposite materials but also for the continuously growing demand for the miniaturisation of electronics components, optical detectors, chemicals and biochemical sensors and devices.

Polymer matrices have been frequently used as particle stabilizers in chemical synthesis of metal colloids since these prevent agglomeration of the particles. Within the past decade, incorporating silver nanoparticle into a polymer matrix is more interesting because the resulting nanocomposites exhibit applications in catalysis, drug wound dressing and optical information storage.

It is difficult to disperse silver nanoparticle homogeneously into a polymer matrix by ex situ methods because of easy agglomeration of nanoparticles. At present, it is possible to obtain nanoparticles of different shape and size in nanostructured polymeric environment using various polymeric systems and different approaches. Numerous methods used toxic and potentially hazardous reactants. Increasing environmental concerns over synthesis route resulted in an attempt to adopt eco friendly methods.

One of the simplest techniques to form such particulate structures, which are generally known as island or discontinuous metal films, is through vacuum evaporation of metal on to a dielectric substrate by stopping the deposition at a very early stage. The temporal instability exhibited by island films even in vacuum is attributed to mobility of islands followed by coalescence [1]. Further, these films get oxidised when they are exposed to atmosphere. The oxidation of islands causes an irreversible increase in electrical resistance [2]. An interesting sub-surface particulate structure formation was reported when certain inorganic materials are deposited on to softened polymer substrates [3-6] and the

© 2013 Parashar, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

222 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

morphology and formation of such structures depend on thermodynamic as well as deposition parameters [6, 5]. The use of softened polymer substrats provides the unique possibility of easily controlling the viscosity of the substrate to form a subsurface discontinuous silver particulate films. The morphology of sub-surface particulate structures also depends upon polymer metal interaction [7, 8]. The reported method is evaporation of silver on polymer substrate at high temperature and in vacuum of the order of 10-6 Torr. The ability to precisely tailor and optimize the nanocomposite structure creates opportunities for a wide range of applications.

Silver Particulate Films on Compatible Softened Polymer Composites 223

Various measurements like heat of mixing, viscometry, glass transition temperature, morphological studies by optical and electron microscopy, infrared spectroscopy and dynamic mechanical analysis, are used to study polymer compatibility. The compatibility of polymer composite is discussed using DSV, DSC, FTIR and SEM. Dilute solution viscometry is a simple and reliable method to investigate interactions of macromolecules in solution. It has been used as a complementary technique to prospect the effect of the position of nitrogen atom in the pyridine ring of P4VP on the interaction developed within PS/P4VP blends. This technique could not be applied to PS/P2VP blends because these blends show phase separation after twenty-four hour of preparation of solution. The criterion of single composition dependent glass transition is used to investigate the miscibility of polymer blends by DSC. Specific interactions most often liberate a heat of mixing and contribute towards the free energy of mixing. Fourier transform infrared spectroscopy is used to investigate specific interactions between the homopolymers in the blend compositions and compared to calorimetric results. SEM results confirm compatibility of blends at higher

Nanocomposites of metal nanoparticles in a polymer matrix have generated a great deal of interest which depends on the metal-polymer composition and their structure. Polymers are particularly attractive as the dielectric matrix in composites due to their versatile nature and can easily be processed into thin films. These nanocomposites exhibit a unique combination of desirable optical and electrical properties that are otherwise unattainable [16-20].All these properties depend on the size, size distribution and shape of the nanoparticles. The growth and arrangement of metal nanoparticles on various substrates are therefore key issues in all the fields of modern science and technology relating to nanoelectronics, photonics, catalysis

Since past, polymer membranes have been studied as supporting materials for colloidal metals which are well known catalysis. Strictly speaking, such a membrane contained colloidal metal-rich and metal-poor phases and the localization of colloidal metals is governed by non–linear diffusion equations. Poly (styrene-b-2-vinyl pyridine) diblock copolymer forms micro phase separated film [22] and Ag ion added to such a film is localized in P2VP micro domains not in PS phase. Theoretical study in the self assembly of inorganic/block copolymers hybrids by Ginzburg and co-workers have predicted that affinity, size and amount of inorganic nanoparticles can be exploited to control the phase

Metal–polymer nanocomposite containing widely separated nanoparticles exhibit insulating behaviour. As the percentage of metal in composite increases, the nanoparticle separation decreases. At a certain thickness of silver on softened polymer substrate, nanoparticles are quite densely packed but separated by polymer gap such a film offer a host of unique property relevant to practical applications. These applications include high dielectric constant passives, electromagnetic interference shielding, sensors, and detector designed for a variety of specific purposes with high performances, sensitivity and flexibility [24]. Further, the morphology of the cluster films deposited on softened polymer substrates is dependent on the polymer-metal interaction. Gold deposited on polystyrene (PS) and

temperature.

and sensors [21].

behaviour of inorganic/BCP hybrids [23].

### **2. Body**

Pyridine-containing polymers have attracted interests in recent years because they can be used in various applications as water-soluble polymers and coordination reagents for transition metals, especially 4-vinylpyridine because of its more interesting properties resulting from higher accessibility of the nitrogen atom [9].

Deposition of silver on interacting polymers like Poly (2-vinylpyridine) and Poly (4 vinylpyridine) resulted in the formation of smaller particles (~ a few tens of nm) with smaller inter-particle separations whereas silver deposited on softened inert polymer like polystyrene (PS), irrespective of the deposited thickness is of highly agglomerated structures. Therefore, silver films on inert polymer lack in application due to room temperature resistances equalling that of the substrate. But, silver films on interacting polymers have room temperature resistance in the range of a few tens to a few hundred M/sheet, which is desirable for device applications [8]. Both the interacting polymers are hygroscopic and costly. Therefore, blending an inert and stable polymer like PS with interacting polymers like P2VP and P4VP may provide a polymer matrix suitable for formation of subsurface silver films. Miscibility between the components polymers play a vital role in blending of polymers at the molecular levels. A compatible blend provides a firm basis for further application in devices. Earlier researchers [10-14] have suggested the improvement of miscibility of PS with P4VP by incorporating proton donors like poly (acrylic) acid and poly (p-vinyl phenol) or methacrylic acid into the chains of PS with P4VP in order to utilise its proton acceptor nature. Further, reversible addition-fragmentation chain transfer polymerization was developed by J.J. Yuan and et al [9] for the controlled preparation of PS/P4VP triblock copolymers as PS-b-P4VP-b-PS and P4VP-b-PS-b-P4VP.In order to retain the properties of both the polymers PS and P4VP, blending is carried out through solution casting and it is expected that combination of PS and P4VP should give rise to organised subsurface silver particulate structures with the advantages of both the polymers.

Polymer blending is a common way to develop new polymer materials with desirable combinations of properties. The main advantage of this method is to control the properties by varying the blend compositions [15]. A compatible blend is needed to have desirable combinations of properties of both the polymers. Compatibility of the two homopolymers is needed to an optimum extent for a blend to show superior properties. The compatibility signifies specific interaction such as dipole-dipole, ion-dipole and hydrogen bonding. Various measurements like heat of mixing, viscometry, glass transition temperature, morphological studies by optical and electron microscopy, infrared spectroscopy and dynamic mechanical analysis, are used to study polymer compatibility. The compatibility of polymer composite is discussed using DSV, DSC, FTIR and SEM. Dilute solution viscometry is a simple and reliable method to investigate interactions of macromolecules in solution. It has been used as a complementary technique to prospect the effect of the position of nitrogen atom in the pyridine ring of P4VP on the interaction developed within PS/P4VP blends. This technique could not be applied to PS/P2VP blends because these blends show phase separation after twenty-four hour of preparation of solution. The criterion of single composition dependent glass transition is used to investigate the miscibility of polymer blends by DSC. Specific interactions most often liberate a heat of mixing and contribute towards the free energy of mixing. Fourier transform infrared spectroscopy is used to investigate specific interactions between the homopolymers in the blend compositions and compared to calorimetric results. SEM results confirm compatibility of blends at higher temperature.

Applications of Calorimetry in a Wide Context –

a wide range of applications.

**2. Body** 

222 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

resulting from higher accessibility of the nitrogen atom [9].

morphology and formation of such structures depend on thermodynamic as well as deposition parameters [6, 5]. The use of softened polymer substrats provides the unique possibility of easily controlling the viscosity of the substrate to form a subsurface discontinuous silver particulate films. The morphology of sub-surface particulate structures also depends upon polymer metal interaction [7, 8]. The reported method is evaporation of silver on polymer substrate at high temperature and in vacuum of the order of 10-6 Torr. The ability to precisely tailor and optimize the nanocomposite structure creates opportunities for

Pyridine-containing polymers have attracted interests in recent years because they can be used in various applications as water-soluble polymers and coordination reagents for transition metals, especially 4-vinylpyridine because of its more interesting properties

Deposition of silver on interacting polymers like Poly (2-vinylpyridine) and Poly (4 vinylpyridine) resulted in the formation of smaller particles (~ a few tens of nm) with smaller inter-particle separations whereas silver deposited on softened inert polymer like polystyrene (PS), irrespective of the deposited thickness is of highly agglomerated structures. Therefore, silver films on inert polymer lack in application due to room temperature resistances equalling that of the substrate. But, silver films on interacting polymers have room temperature resistance in the range of a few tens to a few hundred M/sheet, which is desirable for device applications [8]. Both the interacting polymers are hygroscopic and costly. Therefore, blending an inert and stable polymer like PS with interacting polymers like P2VP and P4VP may provide a polymer matrix suitable for formation of subsurface silver films. Miscibility between the components polymers play a vital role in blending of polymers at the molecular levels. A compatible blend provides a firm basis for further application in devices. Earlier researchers [10-14] have suggested the improvement of miscibility of PS with P4VP by incorporating proton donors like poly (acrylic) acid and poly (p-vinyl phenol) or methacrylic acid into the chains of PS with P4VP in order to utilise its proton acceptor nature. Further, reversible addition-fragmentation chain transfer polymerization was developed by J.J. Yuan and et al [9] for the controlled preparation of PS/P4VP triblock copolymers as PS-b-P4VP-b-PS and P4VP-b-PS-b-P4VP.In order to retain the properties of both the polymers PS and P4VP, blending is carried out through solution casting and it is expected that combination of PS and P4VP should give rise to organised

subsurface silver particulate structures with the advantages of both the polymers.

Polymer blending is a common way to develop new polymer materials with desirable combinations of properties. The main advantage of this method is to control the properties by varying the blend compositions [15]. A compatible blend is needed to have desirable combinations of properties of both the polymers. Compatibility of the two homopolymers is needed to an optimum extent for a blend to show superior properties. The compatibility signifies specific interaction such as dipole-dipole, ion-dipole and hydrogen bonding. Nanocomposites of metal nanoparticles in a polymer matrix have generated a great deal of interest which depends on the metal-polymer composition and their structure. Polymers are particularly attractive as the dielectric matrix in composites due to their versatile nature and can easily be processed into thin films. These nanocomposites exhibit a unique combination of desirable optical and electrical properties that are otherwise unattainable [16-20].All these properties depend on the size, size distribution and shape of the nanoparticles. The growth and arrangement of metal nanoparticles on various substrates are therefore key issues in all the fields of modern science and technology relating to nanoelectronics, photonics, catalysis and sensors [21].

Since past, polymer membranes have been studied as supporting materials for colloidal metals which are well known catalysis. Strictly speaking, such a membrane contained colloidal metal-rich and metal-poor phases and the localization of colloidal metals is governed by non–linear diffusion equations. Poly (styrene-b-2-vinyl pyridine) diblock copolymer forms micro phase separated film [22] and Ag ion added to such a film is localized in P2VP micro domains not in PS phase. Theoretical study in the self assembly of inorganic/block copolymers hybrids by Ginzburg and co-workers have predicted that affinity, size and amount of inorganic nanoparticles can be exploited to control the phase behaviour of inorganic/BCP hybrids [23].

Metal–polymer nanocomposite containing widely separated nanoparticles exhibit insulating behaviour. As the percentage of metal in composite increases, the nanoparticle separation decreases. At a certain thickness of silver on softened polymer substrate, nanoparticles are quite densely packed but separated by polymer gap such a film offer a host of unique property relevant to practical applications. These applications include high dielectric constant passives, electromagnetic interference shielding, sensors, and detector designed for a variety of specific purposes with high performances, sensitivity and flexibility [24]. Further, the morphology of the cluster films deposited on softened polymer substrates is dependent on the polymer-metal interaction. Gold deposited on polystyrene (PS) and

224 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

subsequently annealed above its glass transition temperature results in a highly agglomerated film with large separation between the clusters, possibly due to inert nature of PS [1]. Silver deposited on PS also forms highly agglomerated subsurface particulate structure with large separations between the metal particles [25].Also, coalescence rate for gold particles in a poly(2-vinyl pyridine) matrix is much less than the coalescence rate for gold particles in a polystyrene matrix, indicating that homopolymer/metal interactions play an important role in the determination of the coalescence rate [7].Hence, this high coalescence rate in case of PS resulted in a highly agglomerated film even for a thickness of 300 nm. But, silver deposited on an interacting polymer like Poly (2-vinylpyridine) and poly (4-vinylpyridine) resulted in the formation of smaller particles (~ a few tens of nm) with smaller inter-particle separations [8].The differences in dispersion, size distribution and impregnation depth result from the differing natures of the polymer hosts and the processing conditions [26]. Therefore, it is desirable to restrict the nanoparticles to a small size regime along with a narrow size distribution by blending inert PS with interacting P2VP and P4VP.Therefore; it is interesting to blend PS with P2VP and P4VP in order to have desired morphology of silver particulate films on compatible polymer composite.

Silver Particulate Films on Compatible Softened Polymer Composites 225

For DSC study, the solvent is allowed to evaporate in a thermostat for 24 hours. The residuals of component polymers and their blend in powder form were then dried at 800 C for several days to ensure complete removal of any traces of residual solvent. The residuals of component polymers and their blends were found to be translucent. DSC measurements were carried out using a Shimadzu DSC-50. Small quantities of the samples, 8-10 mg were scanned at a heating rate of 5- 10 K/min-1 in the temperature range 28 to 2200C under

FTIR spectra of the blends were recorded using a Perkin-Elmer spectrometer (model 1000).

Thin films of homopolymers and their composite of approximately 5µm thickness were solution cast on a glass slide pre-coated with silver contacts with a gap of 1 cm X 1 c m for electrical studies. Silver films of various thicknesses were deposited on these substrates held at 457 K in a vacuum better than 8 × 10-6 Torr. The glass transition temperature of P4VP, P2VP and PS are 410, 357 and 373 K, respectively. Therefore, polymer substrates are softened at 457 K and sufficient fluidity is ensured. A chromel-alumel thermocouple was used to measure the substrate temperature by clamping it to the substrate surface holding the film. Source to substrate distance was maintained at 20 cm. A Telemark quartz crystal monitor (Model 850) was used to measure the deposition rate, as well as the overall film thickness. The deposition rate used was 0.4nm/s for all the films. Resistance measurements were carried out in-situ, using a Keithley electrometer model 617. The films were annealed at the deposition temperature for 1 hour before cooling them to room temperature. Stability of the films against exposure was studied by monitoring the film resistance during exposure to atmosphere by continuously leaking air into the vacuum chamber using a needle valve. The leak rate was such that the pressure increased by an order of magnitude in about a

Optical absorption spectra of the silver particulate films were obtained on a Shimadzu UV-

Scanning electron microscopy (SEM) measurements were carried out on Scanning electron

The effectiveness of dilute-solution viscometry is based on the assumption that mutual interactions of macromolecules in solution have a great influence on the viscosity in TPS (two polymers in a solvent) [11]. Therefore, compatibility among the polymers depends on the fact that the repulsive interactions among polymer molecules cause their shrinkage, leading to a lowering of solution viscosity, while attractive interaction increases the

The relative and reduced viscosities of homopolymer and their blends are found out from viscometric measurements. The intrinsic viscosity values of homopolymers and their blends

Vis-NIR spectrophotometer model SHIMADZU UV 3101 PC.

microscope model JEOL JSM 5800 CV with image processing software.

Nitrogen, N2.

minute.

viscosity.

**4. Results and discussion** 

**4.1. Viscosity measurements** 

### **3. Experimental**

Poly (4-vinyl pyridine) and Poly (2-vinylpyridine) used in this study, were procured from Sigma-Aldrich Chemicals Pvt. Ltd and Polystyrene from Alfa-Aesar (A Johnson Mathley company) respectively. The molecular weights of P4VP, P2VP and PS are 60,000, ~37,500 and 100,000, respectively. The structure of P4VP, P2VP and PS are (a), (b) and (c), respectively, as follows:

Polymer blends were prepared through solution blending by mixing in a common solvent, dimethylformamide (DMF). Blends of PS/P4VP with different compositions {PS (w)/P4VP (w) =0:100; 25:75, 50:50; 75:25; 100:0} were prepared. 1g of the total polymers at different ratios was dissolved in 20 ml of DMF at room temperature. Composite of PS/P2VP with different compositions {PS (w)/P2VP (w) = 0:100; 50:50; 100:0} were prepared. An amount of 0.5 g of the total polymers at different ratios, were dissolved in 5 ml of DMF at room temperature.

The stock solutions of PS, P4VP, and their different blend compositions were prepared in the common solvent DMF. Viscosity measurements were made using Ubbelohde Viscometer at 280C with an accuracy of ±0.2%.

For DSC study, the solvent is allowed to evaporate in a thermostat for 24 hours. The residuals of component polymers and their blend in powder form were then dried at 800 C for several days to ensure complete removal of any traces of residual solvent. The residuals of component polymers and their blends were found to be translucent. DSC measurements were carried out using a Shimadzu DSC-50. Small quantities of the samples, 8-10 mg were scanned at a heating rate of 5- 10 K/min-1 in the temperature range 28 to 2200C under Nitrogen, N2.

FTIR spectra of the blends were recorded using a Perkin-Elmer spectrometer (model 1000).

Thin films of homopolymers and their composite of approximately 5µm thickness were solution cast on a glass slide pre-coated with silver contacts with a gap of 1 cm X 1 c m for electrical studies. Silver films of various thicknesses were deposited on these substrates held at 457 K in a vacuum better than 8 × 10-6 Torr. The glass transition temperature of P4VP, P2VP and PS are 410, 357 and 373 K, respectively. Therefore, polymer substrates are softened at 457 K and sufficient fluidity is ensured. A chromel-alumel thermocouple was used to measure the substrate temperature by clamping it to the substrate surface holding the film. Source to substrate distance was maintained at 20 cm. A Telemark quartz crystal monitor (Model 850) was used to measure the deposition rate, as well as the overall film thickness. The deposition rate used was 0.4nm/s for all the films. Resistance measurements were carried out in-situ, using a Keithley electrometer model 617. The films were annealed at the deposition temperature for 1 hour before cooling them to room temperature. Stability of the films against exposure was studied by monitoring the film resistance during exposure to atmosphere by continuously leaking air into the vacuum chamber using a needle valve. The leak rate was such that the pressure increased by an order of magnitude in about a minute.

Optical absorption spectra of the silver particulate films were obtained on a Shimadzu UV-Vis-NIR spectrophotometer model SHIMADZU UV 3101 PC.

Scanning electron microscopy (SEM) measurements were carried out on Scanning electron microscope model JEOL JSM 5800 CV with image processing software.

### **4. Results and discussion**

Applications of Calorimetry in a Wide Context –

**3. Experimental** 

respectively, as follows:

temperature.

Viscometer at 280C with an accuracy of ±0.2%.

224 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

subsequently annealed above its glass transition temperature results in a highly agglomerated film with large separation between the clusters, possibly due to inert nature of PS [1]. Silver deposited on PS also forms highly agglomerated subsurface particulate structure with large separations between the metal particles [25].Also, coalescence rate for gold particles in a poly(2-vinyl pyridine) matrix is much less than the coalescence rate for gold particles in a polystyrene matrix, indicating that homopolymer/metal interactions play an important role in the determination of the coalescence rate [7].Hence, this high coalescence rate in case of PS resulted in a highly agglomerated film even for a thickness of 300 nm. But, silver deposited on an interacting polymer like Poly (2-vinylpyridine) and poly (4-vinylpyridine) resulted in the formation of smaller particles (~ a few tens of nm) with smaller inter-particle separations [8].The differences in dispersion, size distribution and impregnation depth result from the differing natures of the polymer hosts and the processing conditions [26]. Therefore, it is desirable to restrict the nanoparticles to a small size regime along with a narrow size distribution by blending inert PS with interacting P2VP and P4VP.Therefore; it is interesting to blend PS with P2VP and P4VP in order to have

desired morphology of silver particulate films on compatible polymer composite.

Poly (4-vinyl pyridine) and Poly (2-vinylpyridine) used in this study, were procured from Sigma-Aldrich Chemicals Pvt. Ltd and Polystyrene from Alfa-Aesar (A Johnson Mathley company) respectively. The molecular weights of P4VP, P2VP and PS are 60,000, ~37,500 and 100,000, respectively. The structure of P4VP, P2VP and PS are (a), (b) and (c),

Polymer blends were prepared through solution blending by mixing in a common solvent, dimethylformamide (DMF). Blends of PS/P4VP with different compositions {PS (w)/P4VP (w) =0:100; 25:75, 50:50; 75:25; 100:0} were prepared. 1g of the total polymers at different ratios was dissolved in 20 ml of DMF at room temperature. Composite of PS/P2VP with different compositions {PS (w)/P2VP (w) = 0:100; 50:50; 100:0} were prepared. An amount of 0.5 g of the total polymers at different ratios, were dissolved in 5 ml of DMF at room

The stock solutions of PS, P4VP, and their different blend compositions were prepared in the common solvent DMF. Viscosity measurements were made using Ubbelohde

### **4.1. Viscosity measurements**

The effectiveness of dilute-solution viscometry is based on the assumption that mutual interactions of macromolecules in solution have a great influence on the viscosity in TPS (two polymers in a solvent) [11]. Therefore, compatibility among the polymers depends on the fact that the repulsive interactions among polymer molecules cause their shrinkage, leading to a lowering of solution viscosity, while attractive interaction increases the viscosity.

The relative and reduced viscosities of homopolymer and their blends are found out from viscometric measurements. The intrinsic viscosity values of homopolymers and their blends

#### Applications of Calorimetry in a Wide Context – 226 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

were determined at 270 C in DMF by extrapolation to zero concentration of the plots of reduced viscosity (ηsp /C) versus concentration as shown in figure 1. The plots are not perfect linear, but no crossover is seen. A sharp crossover in the plots of reduced viscosity versus concentration indicates incompatibility of blends [27]. Therefore, some order of compatibility is expected in the blends.

Silver Particulate Films on Compatible Softened Polymer Composites 227

b11 = k1 [η] 2 (3)

= (b11 b22)1/2 (4)

(5)

, can be expressed as:

 (ηsp)m = [η1] C1+ [η2] C2+ b11C12+b22C22+2b12C1C2 (1) Where [η1] and [η2] are the intrinsic viscosities of component polymers 1 and 2, C1 and C2 are the concentrations of polymers 1 and 2 in solution of polymer blend, b11 and b22 are specific interaction coefficients of polymers 1 and 2 in single polymer solutions and b12 is the interaction coefficient for the polymer blend of component polymers 1 and 2.The coefficient b11 is related to the constant k in the Huggins equation, when component polymer 1 is alone

ηsp /C = [η] + k [η] 2 C (2)

Where k1 is the Huggins constant for component polymer 1 in solution. The theoretical

According to Krigbaum and Wall [30], information on the intermolecular interaction between polymer 1 and polymer 2 can be obtained by comparison of experimental b12 and

Negative values of ∆b are found for solutions of incompatible polymer system, while positive values of ∆b refer to attractive interaction in compatible systems. We can reduce the equation

Polymer 1-polymer 2 interaction, ∆b and theoretically ( ηsp)m can be calculated [15] as

Where Cm is the total concentration of polymers, C1+C2, and [η]m is the intrinsic viscosity of

Where X1 and X2 are weight fractions of polymer 1 and polymer 2, respectively. Interaction

Where bm defines the global interaction between all polymeric species. b12 may be obtained

(ηsp) m / Cm = [η]m + bm Cm (7)

(1) to the following form when total concentration of the mixture (C) approaches zero.

values. Hence, the miscibility of binary polymer blends can be characterized

( ηspm/C )c→0 =[η1](C1/C)c→0+ [η2](C2/C)c→0 (6)

[η]m = [η]1 X1 + [η]2 X2 (8)

bm = X12 b11 +X1X2b12 + 2 X22 b22 (9)

b12\*

in the solution. This also applies to b22.

theoretical b12\*

follows:

by the interaction parameter, ∆b:

blend. It can be theoretically defined as;

experimentally by Eq. (7).

parameter, b12, can be defined by the equation

The relationship between b11 and k can be written as

interaction coefficient between the two polymers, b12\*

∆b = b12 – b12\*

**Figure 1.** Reduced viscosity versus concentration composition of homopolymers in the blend for the PS/P4VP blends.

**Figure 2.** Relative viscosity versus original total concentration of 0.05g/ml.

Figure 2 shows a plot of relative viscosity versus blend composition at the original total concentration of 0.05g/ml. It is not found to be perfect linear for entire range. This indicates that the PS/P4VP blends are not hundred percent incompatible blend system [10, 28, 29].The concentration value is much lower than the critical concentration C" estimated by C" =1/ [η] [10].In the absence of specific interactions within the blend, polymer coils are independent if the solution concentration is below the critical concentration [10].The mixed solutions in DMF of PS and P4VP were clear indicating that no strong interactions are taking place between the blend components chains.

As proposed by Krigbaum and Wall [30], the specific viscosity ŋsp of a solution polymer blends can be expressed as:

Silver Particulate Films on Compatible Softened Polymer Composites 227

$$(\mathfrak{h}\_{\mathsf{f}^{\mathsf{g}}})\_{\mathsf{m}} = [\mathfrak{h}\_{\mathsf{f}}]\_{\mathsf{C}} \mathbf{C} + [\mathfrak{h}\_{\mathsf{f}}]\_{\mathsf{C}} \mathbf{C} + [\mathfrak{h}\_{\mathsf{f}}]\_{\mathsf{C}} \mathbf{C}^{\mathsf{2}} + \mathfrak{h}\_{\mathsf{f}} \mathbf{C} \mathbf{C}^{\mathsf{2}} + 2 \mathbf{b} \mathbf{c} \mathbf{C} \mathbf{C} \mathbf{C} \tag{1}$$

Where [η1] and [η2] are the intrinsic viscosities of component polymers 1 and 2, C1 and C2 are the concentrations of polymers 1 and 2 in solution of polymer blend, b11 and b22 are specific interaction coefficients of polymers 1 and 2 in single polymer solutions and b12 is the interaction coefficient for the polymer blend of component polymers 1 and 2.The coefficient b11 is related to the constant k in the Huggins equation, when component polymer 1 is alone in the solution. This also applies to b22.

$$\text{tr}\_{\mathbb{H}^{\otimes}}\langle \mathcal{C} = [\mathbb{I}\mathfrak{h}] + \mathbb{K}\left[\mathfrak{n}\right]^{2}\mathcal{C} \tag{2}$$

The relationship between b11 and k can be written as

Applications of Calorimetry in a Wide Context –

compatibility is expected in the blends.

PS/P4VP blends.

226 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

were determined at 270 C in DMF by extrapolation to zero concentration of the plots of reduced viscosity (ηsp /C) versus concentration as shown in figure 1. The plots are not perfect linear, but no crossover is seen. A sharp crossover in the plots of reduced viscosity versus concentration indicates incompatibility of blends [27]. Therefore, some order of

**Figure 1.** Reduced viscosity versus concentration composition of homopolymers in the blend for the

Figure 2 shows a plot of relative viscosity versus blend composition at the original total concentration of 0.05g/ml. It is not found to be perfect linear for entire range. This indicates that the PS/P4VP blends are not hundred percent incompatible blend system [10, 28, 29].The concentration value is much lower than the critical concentration C" estimated by C" =1/ [η] [10].In the absence of specific interactions within the blend, polymer coils are independent if the solution concentration is below the critical concentration [10].The mixed solutions in DMF of PS and P4VP were clear indicating that no strong interactions are taking place

As proposed by Krigbaum and Wall [30], the specific viscosity ŋsp of a solution polymer

**Figure 2.** Relative viscosity versus original total concentration of 0.05g/ml.

between the blend components chains.

blends can be expressed as:

$$\mathbf{b}\_{11} = \mathbf{k}\_1 \begin{bmatrix} \eta \end{bmatrix} 2 \tag{3}$$

Where k1 is the Huggins constant for component polymer 1 in solution. The theoretical interaction coefficient between the two polymers, b12\* , can be expressed as:

$$\mathbf{b}\_{12}\mathbf{\hat{}} = (\mathbf{b}\_{11}\mathbf{\hat{}}\mathbf{b}\_{22})^{1/2} \tag{4}$$

According to Krigbaum and Wall [30], information on the intermolecular interaction between polymer 1 and polymer 2 can be obtained by comparison of experimental b12 and theoretical b12\* values. Hence, the miscibility of binary polymer blends can be characterized by the interaction parameter, ∆b:

$$
\Delta \mathbf{b} = \mathbf{b} \mathbf{u} - \mathbf{b} \mathbf{u}^\* \tag{5}
$$

Negative values of ∆b are found for solutions of incompatible polymer system, while positive values of ∆b refer to attractive interaction in compatible systems. We can reduce the equation (1) to the following form when total concentration of the mixture (C) approaches zero.

$$(\text{\tiny \text{\tiny \text{\tiny \text{\tiny \text{\tiny \text{\tiny \text{\tiny \text{\tiny \text{\text}}}}}}})}) \rightarrow \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\}} \text{\$$

Polymer 1-polymer 2 interaction, ∆b and theoretically ( ηsp)m can be calculated [15] as follows:

$$(\mathfrak{h}\_{\mathsf{l}^{\mathsf{sp}}})\_{\mathsf{m}} / \mathsf{C}\_{\mathsf{m}} = [\mathfrak{h}]\_{\mathsf{m}} + \mathsf{h}\_{\mathsf{m}} \mathsf{C}\_{\mathsf{m}} \tag{7}$$

Where Cm is the total concentration of polymers, C1+C2, and [η]m is the intrinsic viscosity of blend. It can be theoretically defined as;

$$[\mathfrak{n}]\_{\mathfrak{m}} = [\mathfrak{n}]\_{\mathfrak{i}} \chi\_{\mathfrak{i}} + [\mathfrak{n}]\_{\mathfrak{i}} \chi\_{\mathfrak{i}} \tag{8}$$

Where X1 and X2 are weight fractions of polymer 1 and polymer 2, respectively. Interaction parameter, b12, can be defined by the equation

$$\mathbf{b}\_{\rm m} = \mathbf{X}i^2 \mathbf{b}\_{\rm l1} + \mathbf{X}\_{\rm l} \mathbf{X}\_{\rm l2} \mathbf{b}\_{\rm l2} + \mathbf{2} \,\, \mathbf{X}\_{\rm l} \mathbf{2} \cdot \mathbf{b}\_{\rm l2} \tag{9}$$

Where bm defines the global interaction between all polymeric species. b12 may be obtained experimentally by Eq. (7).

228 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

All the calculated and experimental values are summed up in Table 1. The experimental intrinsic viscosity values are compared with their weighed average values and are found to be lower than the theoretical values. Shih and Beatty [29] have studied immiscible systems by this method and found that the intrinsic viscosity always shows a negative deviation due to the repulsive interaction between the polymers. Hence, these blends were not thermodynamically compatible under equilibrium conditions.

The repulsive deviation causes a reduction in the hydrodynamic volume of the polymer molecules, and hence, the viscosity of the solution is reduced. It is found that ∆b values are very much less than unity and negative for all the blends except for the blend 25:75, for which slightly positive value of ∆b predicting some order of compatibility. Also, positive deviation in 25:75 can be attributed to increase in the proportion of the polar group, P4VP in the blend [11]. The difference between η1 and η2 are found to be large and therefore, a more effective parameter µ can be defined to predict about the compatibility [28].

$$
\mu = \Delta \mathbf{b} \,/\, \{\,\text{tr}\mathbf{p} - \mathbf{r}\mathbf{p}\}^2 \tag{10}
$$

Silver Particulate Films on Compatible Softened Polymer Composites 229

**Figure 3.** DSC thermograms of PS/P4VP blends

**Figure 4.** Glass transition temperature versus composition of PS/P4VP.

**Figure 5.** Verification of Gordon- Taylor equation for PS/P4VP blends.

Low values of µ observed in Table 1 may be due to weaker interaction between the polymers. The lower values of interaction parameters indicate that the PS and P4VP are not fully compatible, but physically miscible up to a certain extent.


**Table 1.** Intrinsic viscosity and interaction parametar of PS/P4VP blends.

#### **4.2. Differential scanning calorimetery**

DSC endothermograms for the homopolymers and their blends are shown in figure 3

All the blends exhibit a single Tg, intermediate between those of the parent polymers, PS and P4VP indicating the miscibility of these blends. The theoretical values of these can be predicted using Fox equation [31] and Gordon-Taylor equation [32].

$$\mathbf{1/T\_8 = X\_1/T\_{6^1} + X\_2/T\_{6^2}}\tag{11}$$

$$\mathbf{T\_{\beta} = (\lambda \mathbf{i} \, \mathbf{T} \mathbf{g} + \mathbf{k} \, \lambda \mathbf{i} \, \mathbf{T\_{\beta} 2}) / (\lambda \mathbf{i} + \mathbf{k} \, \mathbf{K} \mathbf{z})}\tag{12}$$

**Figure 3.** DSC thermograms of PS/P4VP blends

Applications of Calorimetry in a Wide Context –

228 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

thermodynamically compatible under equilibrium conditions.

fully compatible, but physically miscible up to a certain extent.

Intrinsic viscosity Slope of red

**Table 1.** Intrinsic viscosity and interaction parametar of PS/P4VP blends.

predicted using Fox equation [31] and Gordon-Taylor equation [32].

Experimental(dl/g) Theoretical(dl/g)

**4.2. Differential scanning calorimetery** 

Blend comp of PS/ P4VP

effective parameter µ can be defined to predict about the compatibility [28].

All the calculated and experimental values are summed up in Table 1. The experimental intrinsic viscosity values are compared with their weighed average values and are found to be lower than the theoretical values. Shih and Beatty [29] have studied immiscible systems by this method and found that the intrinsic viscosity always shows a negative deviation due to the repulsive interaction between the polymers. Hence, these blends were not

The repulsive deviation causes a reduction in the hydrodynamic volume of the polymer molecules, and hence, the viscosity of the solution is reduced. It is found that ∆b values are very much less than unity and negative for all the blends except for the blend 25:75, for which slightly positive value of ∆b predicting some order of compatibility. Also, positive deviation in 25:75 can be attributed to increase in the proportion of the polar group, P4VP in the blend [11]. The difference between η1 and η2 are found to be large and therefore, a more

Low values of µ observed in Table 1 may be due to weaker interaction between the polymers. The lower values of interaction parameters indicate that the PS and P4VP are not

> viscosity vs. concentration curve

0:100 0.167 0.167 0.018 - - - -

100:0 1.11 1.11 0.067 - - - -

25:75 0.284 0.402 0.024 0.053 0.034

50:50 0.325 0.638 0.03 0.017 0.034 -

75:25 0.64 0.874 0.045 0.018 0.034 -

DSC endothermograms for the homopolymers and their blends are shown in figure 3

All the blends exhibit a single Tg, intermediate between those of the parent polymers, PS and P4VP indicating the miscibility of these blends. The theoretical values of these can be

1/Tg = X1/Tg1 + X2/Tg2 (11)

Tg = (X1Tg1+kX2Tg2)/ (X1+ kX2) (12)

µ = ∆b / ( η2 –η1)2 (10)

Experimental Value, b12

 Theoretical value, b12\*

∆b µ

0.019 0.021

0.017 - 0.019

0.016 - 0.017

**Figure 4.** Glass transition temperature versus composition of PS/P4VP.

**Figure 5.** Verification of Gordon- Taylor equation for PS/P4VP blends.

230 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Silver Particulate Films on Compatible Softened Polymer Composites 231

frequency, ʋ = 1607 cm-1 corresponding to the –COOH…N≤ hydrogen bond [11]. Therefore, the incorporation of MAA into PS results in an augmentation in miscibility with P4VP, in comparison with the PS/P4VP system, which is highly incompatible [11]. The present solution cast PS/P4VP blends, needs to be applied in thin film form at higher temperature around 2000 C. Therefore, we need to ascertain about their compatibility at higher temperature. Figure 7 is the FTIR of the sample of the polymer blend PS/P4VP, 50:50 before and after DSC being carried out. This shows the absorption bands at 1598 and 1414 cm-1 corresponding to the pyridine ring of P4VP and at 822 cm-1 to the single substituted pyridine appeared in the spectra of PS/P4VP blend. Similarly, for PS, the absorption peaks at 1493cm-1 and 1448 cm-1, which were characteristic of the phenyl ring and the peak at 697cm-1, corresponding to the signals of the single substituted phenyl ring, appeared for the blend as well. Similar trends were observed by the triblockpolymers PS-P4VP-PS and P4VP-PS-P4VP, which were synthesized by chain transfer agent [33]. In case of PS-block-P4VP, the stretching bands overlap [14].The silver particulate film deposited on PS/P4VP (50:50) resulted in desired structure underlying the property of PS and P4VP [34].Figure 7 shows no shift in the frequency leads to the absence of hydrogen bond. Thus, the possibility of protonation of nitrogen of P4VP [14] is ruled out but some intermolecular interaction at

Figure 8 shows FTIR of PS/P2VP, 50:50 after DSC which clearly indicates the absorption bands at 1594 and 1414 cm-1 corresponding to the pyridine ring of PS and at 822 cm-1 to the single substituted pyridine ring appeared in the spectra of PS/P2VP blend. Similarly, the absorption peaks at 1495cm-1 and 1448 cm-1, which were characteristic of the phenyl ring and the peak at 697cm-1, corresponding to the signals of the single substituted phenyl ring for P2VP spectra, also appeared in the spectra of PS/P2VP, 50:50 blend. No shift in the frequency ruled out the possibility of any hydrogen bond in PS/P2VP. But single Tg of the

higher temperature leads to single Tg composition.

**Figure 7.** FTIR for PS/P4VP (50:50) before and after DSC.

blend suggests some order of the compatibility at higher temperature.

**Figure 6.** DSC thermogram of PS/P2VP, 50:50

Where X1, X2, Tg1 and Tg2 are the weight fractions and glass transition temperatures corresponding to polymer 1 and polymer 2, respectively. k is a constant which gives a semiquantitative measure of degree of the interaction between the two polymers. All the experimental and calculated values of Tg, are shown in Table 2. Positive deviation observed from Fox equation is attributed to intermolecular interaction between the polymers. Figure 4 shows the plot of Tg, with blend composition. It is well established that when interactions between blend components are strong, such as those affected by Hydrogen bonding, the experimentally determined Tg of the blends are higher than those calculated from the additivity rule as a result of the reduction of polymer chains mobility in the blend [10]. In order to estimate the strength of the intermolecular interactions within the PS/P4VP blends, we used the Gorden-Taylor equation to verify through the linear fit in figure 5. Slope (k) of the straight line obtained is found to be 0.85, indicating interaction between the polymers [32]. The intercept is about 100.470 C which corresponds to Tg of pure PS.


**Table 2.** Experimental and theoretical glass transition temperatures of PS/P4VP blend.

Figure 6 shows DSC thermogram of the blend PS/P2VP, 50:50.This indicates a single Tg, about 370K intermediate between those of the parent polymers, PS and P2VP indicating the compatibility of the blend on melt mixing at higher temperature.

#### **4.3. Fourier transform infrared spectroscopy**

The proton donor PS copolymer, PSMAA (PS-methacrylic acid) with P4VP in solvent chloroform observed the specific interactions with the formation of hydrogen bonds, at a frequency, ʋ = 1607 cm-1 corresponding to the –COOH…N≤ hydrogen bond [11]. Therefore, the incorporation of MAA into PS results in an augmentation in miscibility with P4VP, in comparison with the PS/P4VP system, which is highly incompatible [11]. The present solution cast PS/P4VP blends, needs to be applied in thin film form at higher temperature around 2000 C. Therefore, we need to ascertain about their compatibility at higher temperature. Figure 7 is the FTIR of the sample of the polymer blend PS/P4VP, 50:50 before and after DSC being carried out. This shows the absorption bands at 1598 and 1414 cm-1 corresponding to the pyridine ring of P4VP and at 822 cm-1 to the single substituted pyridine appeared in the spectra of PS/P4VP blend. Similarly, for PS, the absorption peaks at 1493cm-1 and 1448 cm-1, which were characteristic of the phenyl ring and the peak at 697cm-1, corresponding to the signals of the single substituted phenyl ring, appeared for the blend as well. Similar trends were observed by the triblockpolymers PS-P4VP-PS and P4VP-PS-P4VP, which were synthesized by chain transfer agent [33]. In case of PS-block-P4VP, the stretching bands overlap [14].The silver particulate film deposited on PS/P4VP (50:50) resulted in desired structure underlying the property of PS and P4VP [34].Figure 7 shows no shift in the frequency leads to the absence of hydrogen bond. Thus, the possibility of protonation of nitrogen of P4VP [14] is ruled out but some intermolecular interaction at higher temperature leads to single Tg composition.

Figure 8 shows FTIR of PS/P2VP, 50:50 after DSC which clearly indicates the absorption bands at 1594 and 1414 cm-1 corresponding to the pyridine ring of PS and at 822 cm-1 to the single substituted pyridine ring appeared in the spectra of PS/P2VP blend. Similarly, the absorption peaks at 1495cm-1 and 1448 cm-1, which were characteristic of the phenyl ring and the peak at 697cm-1, corresponding to the signals of the single substituted phenyl ring for P2VP spectra, also appeared in the spectra of PS/P2VP, 50:50 blend. No shift in the frequency ruled out the possibility of any hydrogen bond in PS/P2VP. But single Tg of the blend suggests some order of the compatibility at higher temperature.

**Figure 7.** FTIR for PS/P4VP (50:50) before and after DSC.

Applications of Calorimetry in a Wide Context –

**Figure 6.** DSC thermogram of PS/P2VP, 50:50

230 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Where X1, X2, Tg1 and Tg2 are the weight fractions and glass transition temperatures corresponding to polymer 1 and polymer 2, respectively. k is a constant which gives a semiquantitative measure of degree of the interaction between the two polymers. All the experimental and calculated values of Tg, are shown in Table 2. Positive deviation observed from Fox equation is attributed to intermolecular interaction between the polymers. Figure 4 shows the plot of Tg, with blend composition. It is well established that when interactions between blend components are strong, such as those affected by Hydrogen bonding, the experimentally determined Tg of the blends are higher than those calculated from the additivity rule as a result of the reduction of polymer chains mobility in the blend [10]. In order to estimate the strength of the intermolecular interactions within the PS/P4VP blends, we used the Gorden-Taylor equation to verify through the linear fit in figure 5. Slope (k) of the straight line obtained is found to be 0.85, indicating interaction between the polymers

[32]. The intercept is about 100.470 C which corresponds to Tg of pure PS.

**Table 2.** Experimental and theoretical glass transition temperatures of PS/P4VP blend.

Figure 6 shows DSC thermogram of the blend PS/P2VP, 50:50.This indicates a single Tg, about 370K intermediate between those of the parent polymers, PS and P2VP indicating the

The proton donor PS copolymer, PSMAA (PS-methacrylic acid) with P4VP in solvent chloroform observed the specific interactions with the formation of hydrogen bonds, at a

 0:100 148.3 - 25:75 129 125 50:50 119 116 75:25 107.7 107 100:0 93 -

compatibility of the blend on melt mixing at higher temperature.

**4.3. Fourier transform infrared spectroscopy** 

Blend comp of PS/P4VP Experimental Tg value (0C) Theoretical Tg value(0C)

DSC Fox equation

232 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Silver Particulate Films on Compatible Softened Polymer Composites 233

**Figure 9.** SEM photographs of PS/P4VP (50:50) a. after DSC and b. before DSC.

**Figure 10.** SEM photographs of PS/P2VP, (50:50) (a) after and (b) before DSC.

**Figure 8.** FTIR of PS/P2VP, 50:50 after DSC

### **4.4. Scanning electron microscopy**

Fig. 9a and 9b show the SEM of PS: P4VP (50:50) samples after and before the DSC have been carried out. It is clear that after DSC the blend mixed better than the blend as obtained at room temperature by solution cast which eventually show phase separation after few days of preparation. Fig.9b clearly shows the dispersed phase of polymers whereas Fig. 9a indicates better compatibly of polymers. This can be attributed to mixing of homoplymers around 2000C during the process of DSC. This is an indication of suitable compatibility of these blends at higher temperature.

Figs. 10a and 10b are the Scanning Electron Micrographs of PS/P2VP, 50:50 samples before and after the DSC have been carried out. It is clear that melt mixing at higher temperature gives more compatible blend than room temperature solution mixed blend. Thus, an order of compatibility is achieved in PS/P2VP, 50:50 blend as reported for PS/P4VP blends [35]. Therefore, we can expect formation of discontinuous silver subsurface film on the blend.

### **4.5. Electrical behaviour of discontinuous silver films on PS/P2VP and PS/P4VP**

Figure 11&12 shows the variation of the logarithm of resistance against inverse of temperature for silver films of different thicknesses deposited on polymers and their composite at a temperature of 457 K, during cooling to room temperature. It is interesting to note that while some of the films show only negative temperature coefficient of resistance (TCR) some show almost zero TCR. Some of the films show negative TCR at higher temperatures and almost zero TCR at lower temperatures. The 50 nm thick silver films on pure PS and 75:25 blend of PS/P4VP show negative TCR. Silver on PS showed similar behaviour in our earlier studies resulting in room temperature resistance same as that of the substrate with the formation of large silver particles separated by large distances [25]. Blending the inert polymer PS with an interacting polymer like P4VP to the extent of 25% does not seem to alter the morphology of the particulate film as indicated by the electrical Silver Particulate Films on Compatible Softened Polymer Composites 233

**Figure 9.** SEM photographs of PS/P4VP (50:50) a. after DSC and b. before DSC.

Applications of Calorimetry in a Wide Context –

**Figure 8.** FTIR of PS/P2VP, 50:50 after DSC

**4.4. Scanning electron microscopy** 

these blends at higher temperature.

232 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Fig. 9a and 9b show the SEM of PS: P4VP (50:50) samples after and before the DSC have been carried out. It is clear that after DSC the blend mixed better than the blend as obtained at room temperature by solution cast which eventually show phase separation after few days of preparation. Fig.9b clearly shows the dispersed phase of polymers whereas Fig. 9a indicates better compatibly of polymers. This can be attributed to mixing of homoplymers around 2000C during the process of DSC. This is an indication of suitable compatibility of

Figs. 10a and 10b are the Scanning Electron Micrographs of PS/P2VP, 50:50 samples before and after the DSC have been carried out. It is clear that melt mixing at higher temperature gives more compatible blend than room temperature solution mixed blend. Thus, an order of compatibility is achieved in PS/P2VP, 50:50 blend as reported for PS/P4VP blends [35]. Therefore, we can expect formation of discontinuous silver subsurface film on the blend.

**4.5. Electrical behaviour of discontinuous silver films on PS/P2VP and PS/P4VP** 

Figure 11&12 shows the variation of the logarithm of resistance against inverse of temperature for silver films of different thicknesses deposited on polymers and their composite at a temperature of 457 K, during cooling to room temperature. It is interesting to note that while some of the films show only negative temperature coefficient of resistance (TCR) some show almost zero TCR. Some of the films show negative TCR at higher temperatures and almost zero TCR at lower temperatures. The 50 nm thick silver films on pure PS and 75:25 blend of PS/P4VP show negative TCR. Silver on PS showed similar behaviour in our earlier studies resulting in room temperature resistance same as that of the substrate with the formation of large silver particles separated by large distances [25]. Blending the inert polymer PS with an interacting polymer like P4VP to the extent of 25% does not seem to alter the morphology of the particulate film as indicated by the electrical

**Figure 10.** SEM photographs of PS/P2VP, (50:50) (a) after and (b) before DSC.

234 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Silver Particulate Films on Compatible Softened Polymer Composites 235

of the films on pure P4VP [37]. Further, when 150 nm thick silver is deposited on a polymer blend with only 25% of P4VP, the films show desirable electrical characteristics in contrast with the very high room temperature resistance observed for films on pure PS even at 300

Figure 13&14 show the variation of logarithm of resistance (ln R) with logarithm of pressure in torr [ln (pressure)]. It is seen that the resistances show large increase beyond a pressure of about 0.5 torr, for all the films. The variation in resistance is very small till that pressure. Similar characteristics were shown by silver films on softened P4VP [39] and P2VP [36]. It was shown through X-ray photoelectron spectroscopy (XPS) studies at various electrons take off angles that silver clusters are formed at a depth of a couple of nm from the polymer surface [36,37]. It is known that the formation of subsurface particulate structure formation is subject to certain thermodynamic [6] and deposition conditions [5]. While the thermodynamic conditions are met for the deposition of metals on most of the polymer substrates, deposition conditions used in the present study are similar to those used in our earlier studies. Therefore, it is reasonable to assume that the particles are formed just a couple of nm below the polymer surface. The behaviour of the particulate films upon exposure to atmosphere is attributed to

**Figure 13.** Variation of ln R with log (Pressure) for silver films deposited on composite PS/P2VP held at

Figure 15 shows variation of room temperature resistance of silver particulate film of 150 nm thickness on PS/P2VP blends .It clearly indicates the decrease in resistance with increase in the amount of P2VP in the blend. Figure 16 shows variation of room temperature resistance of silver particulate film of various thicknesses on the blend PS/P2VP, 50:50.With the increase in the thickness of the silver particulate film the room temperature resistance of the film decreases [34]. Blending of P2VP with PS is expected to provide a polymer matrix where the size of silver clusters and inter-cluster separation can be modified because dispersion, size distribution and impregnation depth results from the natures of polymeric

oxidation of islands due to the inadequate polymer cover.

nm of silver [25].

457 K at a rate of 0.4 nm/s.

hosts [40].

**Figure 11.** Variation of ln R with 1/T for silver films deposited on the composite PS/P2VP held at 457 K at a rate of 0.4 nm/s.

**Figure 12.** Variation of ln R with 1/T for silver films deposited on the composite PS/P4VP held at 457 K at a rate of 0.4 nm/s.

behaviour. When the P4VP content is increased to 50%, a negative TCR at high temperature followed by almost zero TCR at lower temperatures exhibited by the 50 nm thick film is similar to the behaviour observed earlier for the case of pure P2VP and P4VP [36, 37] indicating that the film consists of small particles separated by small distances. With further increase in P4VP content, the negative TCR part diminishes, giving rise to a near zero TCR .Similarly, the films on composites PS/P2VP (50:50) initially show negative TCR but zero TCR at lower temperature. Blending of PS with P2VP and P4VP seems to result in a positive effect on the composites. Therefore, negative TCR is totally vanishing and give rise to near zero TCR at room temperature for films deposited on the composites. The over all resistance of film deposited on composite decreases with increase in thickness of silver films deposited on the composite. Similar trend were reported that the electrical conductivity of composites is increased with high silver loading (30-80%) [38]. It is also interesting to note that even at 50% P4VP, with an increase of silver deposited, films show electrical characteristics as that of the films on pure P4VP [37]. Further, when 150 nm thick silver is deposited on a polymer blend with only 25% of P4VP, the films show desirable electrical characteristics in contrast with the very high room temperature resistance observed for films on pure PS even at 300 nm of silver [25].

Applications of Calorimetry in a Wide Context –

at a rate of 0.4 nm/s.

at a rate of 0.4 nm/s.

234 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 11.** Variation of ln R with 1/T for silver films deposited on the composite PS/P2VP held at 457 K

**Figure 12.** Variation of ln R with 1/T for silver films deposited on the composite PS/P4VP held at 457 K

behaviour. When the P4VP content is increased to 50%, a negative TCR at high temperature followed by almost zero TCR at lower temperatures exhibited by the 50 nm thick film is similar to the behaviour observed earlier for the case of pure P2VP and P4VP [36, 37] indicating that the film consists of small particles separated by small distances. With further increase in P4VP content, the negative TCR part diminishes, giving rise to a near zero TCR .Similarly, the films on composites PS/P2VP (50:50) initially show negative TCR but zero TCR at lower temperature. Blending of PS with P2VP and P4VP seems to result in a positive effect on the composites. Therefore, negative TCR is totally vanishing and give rise to near zero TCR at room temperature for films deposited on the composites. The over all resistance of film deposited on composite decreases with increase in thickness of silver films deposited on the composite. Similar trend were reported that the electrical conductivity of composites is increased with high silver loading (30-80%) [38]. It is also interesting to note that even at 50% P4VP, with an increase of silver deposited, films show electrical characteristics as that Figure 13&14 show the variation of logarithm of resistance (ln R) with logarithm of pressure in torr [ln (pressure)]. It is seen that the resistances show large increase beyond a pressure of about 0.5 torr, for all the films. The variation in resistance is very small till that pressure. Similar characteristics were shown by silver films on softened P4VP [39] and P2VP [36]. It was shown through X-ray photoelectron spectroscopy (XPS) studies at various electrons take off angles that silver clusters are formed at a depth of a couple of nm from the polymer surface [36,37]. It is known that the formation of subsurface particulate structure formation is subject to certain thermodynamic [6] and deposition conditions [5]. While the thermodynamic conditions are met for the deposition of metals on most of the polymer substrates, deposition conditions used in the present study are similar to those used in our earlier studies. Therefore, it is reasonable to assume that the particles are formed just a couple of nm below the polymer surface. The behaviour of the particulate films upon exposure to atmosphere is attributed to oxidation of islands due to the inadequate polymer cover.

**Figure 13.** Variation of ln R with log (Pressure) for silver films deposited on composite PS/P2VP held at 457 K at a rate of 0.4 nm/s.

Figure 15 shows variation of room temperature resistance of silver particulate film of 150 nm thickness on PS/P2VP blends .It clearly indicates the decrease in resistance with increase in the amount of P2VP in the blend. Figure 16 shows variation of room temperature resistance of silver particulate film of various thicknesses on the blend PS/P2VP, 50:50.With the increase in the thickness of the silver particulate film the room temperature resistance of the film decreases [34]. Blending of P2VP with PS is expected to provide a polymer matrix where the size of silver clusters and inter-cluster separation can be modified because dispersion, size distribution and impregnation depth results from the natures of polymeric hosts [40].

236 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Silver Particulate Films on Compatible Softened Polymer Composites 237

Figure 17 a,b,c shows the SEM of silver particulate films of thickness 200 nm on PS, P2VP and PS/P2VP, 50:50.It is evident from the figure that decrease in the particle size in the films of P2VP and PS/P2VP, 50/50 resulted in the close proximity of particles with reduction in the inter-particle separation. Also, the decrease in the size of silver cluster in the blend PS/P2VP, 50:50 improves the tunnelling effect as expected [34].Thus, the room temperature resistance

of silver particulate film on the blend is now in the desirable range for applications.

**Figure 17. a,b,c**: SEM of silver particulate films of thickness 200 nm on PS, P2VP and PS/P2VP, 50:50.

and for the given conditions and thickness.

Figure 18 gives the variation of as deposited and room temperature resistances as a function of PS/P4VP composition for silver films of 50 nm thickness. It is seen that as the P4VP concentration increases there is a regular decrease of resistance at a fixed silver thickness. The plot of logarithm of these resistances with blend concentration gives linear fit as shown in figure19.Through this fit, one can estimate the resistance of the film at a particular blend

**Figure 14.** Variation of ln R with log (Pressure) for silver films deposited on composite PS/P4VP held at 457 K at a rate of 0.4 nm/s.

**Figure 15.** Variation of room temperature resistance of silver particulate film of 150 nm thickness verus composition of PS/P2VP.

**Figure 16.** Variation of room temperature resistance of silver particulate film verus their thicknesses for PS/P2VP,50:50.

Figure 17 a,b,c shows the SEM of silver particulate films of thickness 200 nm on PS, P2VP and PS/P2VP, 50:50.It is evident from the figure that decrease in the particle size in the films of P2VP and PS/P2VP, 50/50 resulted in the close proximity of particles with reduction in the inter-particle separation. Also, the decrease in the size of silver cluster in the blend PS/P2VP, 50:50 improves the tunnelling effect as expected [34].Thus, the room temperature resistance of silver particulate film on the blend is now in the desirable range for applications.

Applications of Calorimetry in a Wide Context –

457 K at a rate of 0.4 nm/s.

composition of PS/P2VP.

PS/P2VP,50:50.

236 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 14.** Variation of ln R with log (Pressure) for silver films deposited on composite PS/P4VP held at

**Figure 15.** Variation of room temperature resistance of silver particulate film of 150 nm thickness verus

**Figure 16.** Variation of room temperature resistance of silver particulate film verus their thicknesses for

**Figure 17. a,b,c**: SEM of silver particulate films of thickness 200 nm on PS, P2VP and PS/P2VP, 50:50.

Figure 18 gives the variation of as deposited and room temperature resistances as a function of PS/P4VP composition for silver films of 50 nm thickness. It is seen that as the P4VP concentration increases there is a regular decrease of resistance at a fixed silver thickness. The plot of logarithm of these resistances with blend concentration gives linear fit as shown in figure19.Through this fit, one can estimate the resistance of the film at a particular blend and for the given conditions and thickness.

238 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 18.** Variation of as-deposited and room temperature resistance with PS/P4VP blend composition for 50 nm silver films deposited at 457 K.

Polymer PS:P4VP

*4.6.1. Optical studies* 

Silver Particulate Films on Compatible Softened Polymer Composites 239

Rst R1 hra Rrt R0.5t Ratm

Silver film thickness Resistances (M/)

0:100 50 nm 1.9 26.8 27.1 32.8 72.3 25:75 50 nm 6.2 42.2 47.1 73.7 1042 25:75 85 nm 3.2 14.7 14.2 21.9 215 50:50 50 nm 15.9 119.5 159.4 241.3 2465 50:50 95 nm 2.9 29.9 30.1 52.2 418 75:25 50 nm 214 325 - - - 75:25 150 nm 14.8 98.2 248.9 501.3 5172 100:0 50 nm 302 491 - - - **Table 4.** Resistances for silver films deposited on PS/P4VP blends held at 457 K with a rate of 0.4 nm/s.

**4.6. Morphology of silver particulate films on PS/P2VP and PS/P4VP blends** 

Fig. 20a shows the optical absorption spectra recorded for 100 nm silver films deposited on polymeric blends of PS/P2VP held at 457 K at the deposition rate of 0.4 nm/s. It is well known that small silver particles embedded in polymer matrix exhibit plasmon resonance absorption and as a result absorption maxima occur in the visible-near infrared region and their spectral position depends on the particle size, shape, filling factor etc. in the polymer matrix. The surface plasmon resonance absorption for silver clusters in the polymer matrix generally occurs at a wavelength of ~ 430 nm [8]. It is well known that shift in the plasmon resonance peak towards higher wavelength occurs due to close proximity of the silver clusters [41-44].These nanoparticles exhibit unique optical properties originating from the characteristic surface plasmon by the collective motion of conduction electrons [43,44].Thus, the formation of silver nanoparticles can also be confirmed by UV/VIS absorption spectrum of composite films [44].Spectral position, half width and intensity of the plasmon resonance strongly depend on the particle size, shape and the dielectric properties of the particle material and the surrounding medium [45].Thus, the type of metal and the surrounding dielectric medium play a significant role in the excitation of particle plasmon resonance (PPR). The sensitivity of PPR frequency to small variations of these parameters can be exploited in various applications [46]. The differing natures of the polymeric hosts yield change in dispersion, size distribution and impregnation depth of silver clusters [26]. Therefore, silver particles embedded in PS/P2VP blends, a shift of the resonance position to higher wavelength (red shift) were found, which were correlated with changes of particle sizes and inter-separation in silver clusters. It is clearly seen (Fig.20a) that the plasmon resonance peak shifts towards the longer wavelength side for the PS/P2VP, 50:50 (435) as compared to pure polystyrene (429 nm). Also, there is increase in intensity of absorbing peaks which signify the decrease of particles size with the incorporation of P2VP into PS [44].P2VP exhibits two peaks (441,606 nm). It is interesting to note that PS/P2VP, 50:50 also shows an additional absorption band at higher wavelength (616 nm). The possible explanation is that silver nanoparticles are in a highly aggregated state leading to coupling

**Figure 19.** Variation of logarithm of resistances at 457 K and at room temperature with PS/P4VP blend composition for 50 nm silver films.

Table 3&4 gives the resistance data for the silver films of different thicknesses deposited on the PS/P2VP and P4VP, respectively.


**Table 3.** Resistances for silver films deposited on PS/P2VP blends held at 457 K with a rate of 0.4 nm/s.


**Table 4.** Resistances for silver films deposited on PS/P4VP blends held at 457 K with a rate of 0.4 nm/s.

### **4.6. Morphology of silver particulate films on PS/P2VP and PS/P4VP blends**

#### *4.6.1. Optical studies*

Applications of Calorimetry in a Wide Context –

for 50 nm silver films deposited at 457 K.

composition for 50 nm silver films.

Polymer PS:P2VP

the PS/P2VP and P4VP, respectively.

Silver Film Thickness

238 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 18.** Variation of as-deposited and room temperature resistance with PS/P4VP blend composition

**Figure 19.** Variation of logarithm of resistances at 457 K and at room temperature with PS/P4VP blend

Table 3&4 gives the resistance data for the silver films of different thicknesses deposited on

0:100 100 nm 12.28 32.2 32.68 34.22 63.4 0:100 150 nm 9.73 28.08 26.13 30.53 45.64 50:50 100 nm 47.07 111.57 114.76 489 >1000 50:50 150 nm 11.5 34.98 42.04 57.4 76.56 50:50 200 nm 10.35 29.9 30.1 38.41 68.25 100:0 150 nm 54.46 159.3 - - -

**Table 3.** Resistances for silver films deposited on PS/P2VP blends held at 457 K with a rate of 0.4 nm/s.

Resistances (MΩ/sheet)

Rts R1 hra Rrt R0.5T Ratm

Fig. 20a shows the optical absorption spectra recorded for 100 nm silver films deposited on polymeric blends of PS/P2VP held at 457 K at the deposition rate of 0.4 nm/s. It is well known that small silver particles embedded in polymer matrix exhibit plasmon resonance absorption and as a result absorption maxima occur in the visible-near infrared region and their spectral position depends on the particle size, shape, filling factor etc. in the polymer matrix. The surface plasmon resonance absorption for silver clusters in the polymer matrix generally occurs at a wavelength of ~ 430 nm [8]. It is well known that shift in the plasmon resonance peak towards higher wavelength occurs due to close proximity of the silver clusters [41-44].These nanoparticles exhibit unique optical properties originating from the characteristic surface plasmon by the collective motion of conduction electrons [43,44].Thus, the formation of silver nanoparticles can also be confirmed by UV/VIS absorption spectrum of composite films [44].Spectral position, half width and intensity of the plasmon resonance strongly depend on the particle size, shape and the dielectric properties of the particle material and the surrounding medium [45].Thus, the type of metal and the surrounding dielectric medium play a significant role in the excitation of particle plasmon resonance (PPR). The sensitivity of PPR frequency to small variations of these parameters can be exploited in various applications [46]. The differing natures of the polymeric hosts yield change in dispersion, size distribution and impregnation depth of silver clusters [26]. Therefore, silver particles embedded in PS/P2VP blends, a shift of the resonance position to higher wavelength (red shift) were found, which were correlated with changes of particle sizes and inter-separation in silver clusters. It is clearly seen (Fig.20a) that the plasmon resonance peak shifts towards the longer wavelength side for the PS/P2VP, 50:50 (435) as compared to pure polystyrene (429 nm). Also, there is increase in intensity of absorbing peaks which signify the decrease of particles size with the incorporation of P2VP into PS [44].P2VP exhibits two peaks (441,606 nm). It is interesting to note that PS/P2VP, 50:50 also shows an additional absorption band at higher wavelength (616 nm). The possible explanation is that silver nanoparticles are in a highly aggregated state leading to coupling of the plasmon vibrations between neighbouring particles [47].Similar results were found for silver particulate films of 150 and 200 nm films on PS/P2VP 50:50 blends. The shift in plasma resonance towards higher wavelength indicates close proximity and increase in particle size of silver nanoparticles with increasing thickness of silver particulate films [41].

Silver Particulate Films on Compatible Softened Polymer Composites 241

perhaps this is the reason for the better electrical behaviour of the film of thickness 150 nm

**Figure 21. a** Optical absorption spectra for 50 nm silver particulate films deposited on PS/P4VP blends, **b** Optical absorption spectra for the films of various thicknesses deposited on the PS /P4VP blends, **c** Optical absorption spectra for the films deposited on the blend PS/P4VP 50:50, **d** Optical absorption

Fig. 21 (c) shows the optical spectra for films of varying thickness on PS/P4VP, 50:50.The shift in plasma resonance towards higher wavelength indicates close proximity of silver

Fig. 21(d) shows the optical absorption spectra recorded for silver films on PS/P4VP, 75:25. It is clear that shift in surface plasma resonance is due to increase in particle size with the amount of silver deposited [8].The results are in agreement with the electrical properties of this blend which show increase in electrical conductivity on increasing silver loading [34].

As the fraction of the metal in a nanocomposite increases the nanoparticle separation decreases resulted in better electrical properties of nanocmposites [49]. Therefore, electrical behaviour of silver particulate films on PS/P4VP (50:50, 50 nm and 95 nm; 75:25, 50 nm and 150 nm) observed decrease in electrical resistance on increasing the thickness of film

spectra for the film deposited on the blend PS/P4VP 75:25.

nanoparticles with increasing thickness of silver particulate films [15].

on PS/P4VP, 75:25 [34].

**Figure 20. a:** Optical absorption spectra for 100 nm silver particulate films deposited on PS/P2VP blends, **b**: XRD curve for silver particulate films of thickness 200 nm on PS/ P2VP, 50:50.

Fig.20 b shows the XRD pattern with the diffraction peak around 380 for the silver particulate films of thickness of 200 nm on PS/P2VP, 50:50. The broadening of the Bragg peaks indicates the formation nanoparticles. The particle sizes calculated from the Fig.20b is 40.6 nm for the silver particulate film of 200 nm on PS: P2VP, 50:50. The particle sizes estimated from XRD suggest that there is a small reduction in particle size due to blending of PS and P2VP. XRD of PS/P2VP, 50:50 for 200 nm has been carried out to have preliminary idea about average size of the silver clusters.

Fig. 21(a) shows the optical absorption spectra recorded for 50 nm silver films deposited on polymeric blends of PS/P4VP held at 457 K at the deposition rate of 0.4 nm/s. For silver particles embedded in PS/P4VP blends, a shift of the resonance position to higher wavelength (red shift) were found, which were correlated with changes of particle sizes and inter-separation in silver clusters. It is clearly seen (Fig.21a) that the plasmon resonance peak shifts towards the longer wavelength side in comparison to pure PS (485.5 nm).It is 598, 651.6 and 754.5 nm for PS: P4VP, 75:25, 50:50 and 25:75, respectively for 50 nm silver particulate films on them. Also, there is increase in intensity of absorbing peaks which can be attributed to the decrease of particles size with the incorporation of P4VP into PS [48].

Fig. 21 (b) shows the optical spectra recorded for the films of various thicknesses on PS/P4VP blends. The blend 50:50 shows the most promising result among all the silver particulate films on the blends. The intensity and shift of absorption peak is optimum (793 nm) for 95 nm film on PS/P4VP, 50:50.The silver particulate film of thickness 150 nm on PS/P4VP, 75:25 also shows a red shift (705 nm).This shift in the plasmon resonance peak towards higher wavelength can be attributed to close proximity of the silver clusters [42-45], perhaps this is the reason for the better electrical behaviour of the film of thickness 150 nm on PS/P4VP, 75:25 [34].

Applications of Calorimetry in a Wide Context –

idea about average size of the silver clusters.

240 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

of the plasmon vibrations between neighbouring particles [47].Similar results were found for silver particulate films of 150 and 200 nm films on PS/P2VP 50:50 blends. The shift in plasma resonance towards higher wavelength indicates close proximity and increase in particle size of silver nanoparticles with increasing thickness of silver particulate films [41].

**Figure 20. a:** Optical absorption spectra for 100 nm silver particulate films deposited on PS/P2VP

Fig.20 b shows the XRD pattern with the diffraction peak around 380 for the silver particulate films of thickness of 200 nm on PS/P2VP, 50:50. The broadening of the Bragg peaks indicates the formation nanoparticles. The particle sizes calculated from the Fig.20b is 40.6 nm for the silver particulate film of 200 nm on PS: P2VP, 50:50. The particle sizes estimated from XRD suggest that there is a small reduction in particle size due to blending of PS and P2VP. XRD of PS/P2VP, 50:50 for 200 nm has been carried out to have preliminary

Fig. 21(a) shows the optical absorption spectra recorded for 50 nm silver films deposited on polymeric blends of PS/P4VP held at 457 K at the deposition rate of 0.4 nm/s. For silver particles embedded in PS/P4VP blends, a shift of the resonance position to higher wavelength (red shift) were found, which were correlated with changes of particle sizes and inter-separation in silver clusters. It is clearly seen (Fig.21a) that the plasmon resonance peak shifts towards the longer wavelength side in comparison to pure PS (485.5 nm).It is 598, 651.6 and 754.5 nm for PS: P4VP, 75:25, 50:50 and 25:75, respectively for 50 nm silver particulate films on them. Also, there is increase in intensity of absorbing peaks which can be attributed to the decrease of particles size with the incorporation of P4VP into PS [48].

Fig. 21 (b) shows the optical spectra recorded for the films of various thicknesses on PS/P4VP blends. The blend 50:50 shows the most promising result among all the silver particulate films on the blends. The intensity and shift of absorption peak is optimum (793 nm) for 95 nm film on PS/P4VP, 50:50.The silver particulate film of thickness 150 nm on PS/P4VP, 75:25 also shows a red shift (705 nm).This shift in the plasmon resonance peak towards higher wavelength can be attributed to close proximity of the silver clusters [42-45],

blends, **b**: XRD curve for silver particulate films of thickness 200 nm on PS/ P2VP, 50:50.

**Figure 21. a** Optical absorption spectra for 50 nm silver particulate films deposited on PS/P4VP blends, **b** Optical absorption spectra for the films of various thicknesses deposited on the PS /P4VP blends, **c** Optical absorption spectra for the films deposited on the blend PS/P4VP 50:50, **d** Optical absorption spectra for the film deposited on the blend PS/P4VP 75:25.

Fig. 21 (c) shows the optical spectra for films of varying thickness on PS/P4VP, 50:50.The shift in plasma resonance towards higher wavelength indicates close proximity of silver nanoparticles with increasing thickness of silver particulate films [15].

Fig. 21(d) shows the optical absorption spectra recorded for silver films on PS/P4VP, 75:25. It is clear that shift in surface plasma resonance is due to increase in particle size with the amount of silver deposited [8].The results are in agreement with the electrical properties of this blend which show increase in electrical conductivity on increasing silver loading [34].

As the fraction of the metal in a nanocomposite increases the nanoparticle separation decreases resulted in better electrical properties of nanocmposites [49]. Therefore, electrical behaviour of silver particulate films on PS/P4VP (50:50, 50 nm and 95 nm; 75:25, 50 nm and 150 nm) observed decrease in electrical resistance on increasing the thickness of film

242 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[40].Thus, electrical studies of these blends suggest possibility of modification in morphology of silver particulate films on PS/P4VP as compared to films on PS.

Silver Particulate Films on Compatible Softened Polymer Composites 243

Fig.22c shows the XRD pattern with the diffraction peak around 380 for the silver particulate films of thickness of 50 nm on P4VP, PS and PS/P4VP, 25:75, 50:50, and 75:25. The broadening of the Bragg peaks indicates the formation nanoparticles. The particle sizes calculated from the Fig.22c are 53, 51, 49, 46 and 30 nm for the blends (PS: P4VP) 100:0, 75:25, 50:50, 25:75 and 0:100, in that order. The particle sizes estimated from XRD suggest that there is a very small reduction in particle size due to blending of PS and P4VP.Figure 22d shows the XRD patterns for the silver particulate films on PS/P4VP, 75:25, 50:50 and 25:75 for 150, 95 and 85 nm thicknesses, respectively. The reflections at 380 and 440 correspond to metallic silver. The particle sizes calculated from the Fig.22d are 52.3, 51.6 and 53 nm for the blends (PS: P4VP) 75:25, 50:50, and 25:75, respectively for the diffraction angle

Electrical properties of polymer/metal composite films are strongly linked to particles' nanostructure [40]. As the fraction of the metal in a nanocomposite increases the nanoparticle separation decreases resulted in better electrical properties of nanocmposites [49-50,52,53]. SEM of the silver particulate films (Fig.22a & 22b) on homopolymers (PS, P4VP) clearly shows the characteristic nature of these polymers. The size and interseparation of silver clusters is less (average particle size-58 nm) in P4VP whereas size as well as inter-separation is wide in PS (average particle size-92 nm). As a result, PS do not show the desired electrical conductivity [51].Blending of P2VP and P4VP into PS modifies size, size distribution and inter-separation of silver particles deposited on their blends PS/P2VP, 50:50 and PS/P4VP, 50:50 and 75:25. Therefore, electrical behaviour of silver particulate films on PS/P2VP, 50:50 for 100, 150 and 200 nm observed decrease in electrical resistance on increasing the thickness of films [52]. Thus, electrical studies of these blends suggest possibility of modification in morphology of silver particulate films on PS/P2VP and

SEM of the silver particulate films of 200 nm on the homopolymers (PS, P2VP) and their blend PS/P2VP, 50:50 were shown in the Fig.23a. The acceleration voltage is 30 kV and magnification is 60 to 100 KX for all the SEM pictures. The particle sizes measured from respective SEM pictures are plotted as histogram. The corresponding histograms (Fig.23a) of silver particles of the films are shown side by side of the SEM pictures. The data fit into a log normal distribution for all the cases. Hence, the average size, ā and geometric standard deviation, σ a are determined from the log normal distribution of the curves. The average size, ā and geometric standard deviation, σ a are 205 nm and 4; 109 nm and 9, 129 nm and 3, respectively, for silver films on PS, P2VP and their blend (50:50). The size distribution and width of histograms as shown in the figure indicate that the particle size varies from 100 to 400 nm, 60 to 180 nm and 60 to 200nm for silver films on PS, P2VP and their blend (50:50).It is clear from the figure that the size and inter-separation of silver clusters is wide in PS whereas size as well as inter-separation is less in P2VP [8]. As a result, PS do not show the desired electrical conductivity [36].Blending of P2VP with PS modifies size, size distribution and inter-separation of silver particles on their blend PS/P2VP, 50:50 which results in

380.

*4.6.2. Micro structural studies* 

PS/P4VP as compared to films on PS.

Previous studies [8] of silver particulate films on PS for the 100 nm thickness exhibited minimum shift due to the presence of comparatively larger clusters with larger inter-cluster separations than on P2VP [8] for the same thickness. Also, silver particulate film on PS for the 50 nm thickness exhibited minimum shift due to the presence of comparatively larger clusters with larger inter-cluster separations than on P4VP [37] for the same thickness. Blending of P2VP with PS and P4VP with PS is expected to provide a polymer matrix where the size of silver clusters and inter-cluster separation can be modified because dispersion, size distribution and impregnation depth results from the natures of polymeric hosts [40].

Therefore, shift in the wavelength observed in optical spectra in the PS/P2VP, 50:50, and PS/P4VP, 75:25; 50:50; 25:75 can be attributed to modification in size distribution and better inter-cluster separations.

**Figure 22. a,b**: SEM images of PS/P4VP, (a) 0:100 and (b) 100:0 for silver particulate films of thickness 50 nm. Acceleration voltage- 20 kV, Magnification 50 KX, **c**: XRD curves for silver particulate films of thickness 50 nm on P4VP, PS, PS/ P4VP, 25:75, 50:50, 75:25, respectively. **d**: XRD curves for silver particulate films on PS/P4VP, 75:25, 50:50 and 25:75 for 150, 95 and 85 nm thicknesses, respectively

Fig.22c shows the XRD pattern with the diffraction peak around 380 for the silver particulate films of thickness of 50 nm on P4VP, PS and PS/P4VP, 25:75, 50:50, and 75:25. The broadening of the Bragg peaks indicates the formation nanoparticles. The particle sizes calculated from the Fig.22c are 53, 51, 49, 46 and 30 nm for the blends (PS: P4VP) 100:0, 75:25, 50:50, 25:75 and 0:100, in that order. The particle sizes estimated from XRD suggest that there is a very small reduction in particle size due to blending of PS and P4VP.Figure 22d shows the XRD patterns for the silver particulate films on PS/P4VP, 75:25, 50:50 and 25:75 for 150, 95 and 85 nm thicknesses, respectively. The reflections at 380 and 440 correspond to metallic silver. The particle sizes calculated from the Fig.22d are 52.3, 51.6 and 53 nm for the blends (PS: P4VP) 75:25, 50:50, and 25:75, respectively for the diffraction angle 380.

#### *4.6.2. Micro structural studies*

Applications of Calorimetry in a Wide Context –

inter-cluster separations.

242 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

morphology of silver particulate films on PS/P4VP as compared to films on PS.

[40].Thus, electrical studies of these blends suggest possibility of modification in

Previous studies [8] of silver particulate films on PS for the 100 nm thickness exhibited minimum shift due to the presence of comparatively larger clusters with larger inter-cluster separations than on P2VP [8] for the same thickness. Also, silver particulate film on PS for the 50 nm thickness exhibited minimum shift due to the presence of comparatively larger clusters with larger inter-cluster separations than on P4VP [37] for the same thickness. Blending of P2VP with PS and P4VP with PS is expected to provide a polymer matrix where the size of silver clusters and inter-cluster separation can be modified because dispersion, size distribution and impregnation depth results from the natures of polymeric hosts [40].

Therefore, shift in the wavelength observed in optical spectra in the PS/P2VP, 50:50, and PS/P4VP, 75:25; 50:50; 25:75 can be attributed to modification in size distribution and better

**Figure 22. a,b**: SEM images of PS/P4VP, (a) 0:100 and (b) 100:0 for silver particulate films of thickness 50 nm. Acceleration voltage- 20 kV, Magnification 50 KX, **c**: XRD curves for silver particulate films of thickness 50 nm on P4VP, PS, PS/ P4VP, 25:75, 50:50, 75:25, respectively. **d**: XRD curves for silver particulate films on PS/P4VP, 75:25, 50:50 and 25:75 for 150, 95 and 85 nm thicknesses, respectively

Electrical properties of polymer/metal composite films are strongly linked to particles' nanostructure [40]. As the fraction of the metal in a nanocomposite increases the nanoparticle separation decreases resulted in better electrical properties of nanocmposites [49-50,52,53]. SEM of the silver particulate films (Fig.22a & 22b) on homopolymers (PS, P4VP) clearly shows the characteristic nature of these polymers. The size and interseparation of silver clusters is less (average particle size-58 nm) in P4VP whereas size as well as inter-separation is wide in PS (average particle size-92 nm). As a result, PS do not show the desired electrical conductivity [51].Blending of P2VP and P4VP into PS modifies size, size distribution and inter-separation of silver particles deposited on their blends PS/P2VP, 50:50 and PS/P4VP, 50:50 and 75:25. Therefore, electrical behaviour of silver particulate films on PS/P2VP, 50:50 for 100, 150 and 200 nm observed decrease in electrical resistance on increasing the thickness of films [52]. Thus, electrical studies of these blends suggest possibility of modification in morphology of silver particulate films on PS/P2VP and PS/P4VP as compared to films on PS.

SEM of the silver particulate films of 200 nm on the homopolymers (PS, P2VP) and their blend PS/P2VP, 50:50 were shown in the Fig.23a. The acceleration voltage is 30 kV and magnification is 60 to 100 KX for all the SEM pictures. The particle sizes measured from respective SEM pictures are plotted as histogram. The corresponding histograms (Fig.23a) of silver particles of the films are shown side by side of the SEM pictures. The data fit into a log normal distribution for all the cases. Hence, the average size, ā and geometric standard deviation, σ a are determined from the log normal distribution of the curves. The average size, ā and geometric standard deviation, σ a are 205 nm and 4; 109 nm and 9, 129 nm and 3, respectively, for silver films on PS, P2VP and their blend (50:50). The size distribution and width of histograms as shown in the figure indicate that the particle size varies from 100 to 400 nm, 60 to 180 nm and 60 to 200nm for silver films on PS, P2VP and their blend (50:50).It is clear from the figure that the size and inter-separation of silver clusters is wide in PS whereas size as well as inter-separation is less in P2VP [8]. As a result, PS do not show the desired electrical conductivity [36].Blending of P2VP with PS modifies size, size distribution and inter-separation of silver particles on their blend PS/P2VP, 50:50 which results in

Applications of Calorimetry in a Wide Context – 244 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

improvement of tunnelling effect in the blend and the blend shows desired electrical behaviour [52]. This fact may be regarded as a consequence of the size as well as interseparation evolution of nanoparticles during the ongoing deposition process.

Silver Particulate Films on Compatible Softened Polymer Composites 245

normal distribution for all the cases. Hence, the average size, ā and geometric standard deviation, σ a are determined from the log normal distribution of the curves. The positive effect of blending P4VP with PS is clearly visible in these pictures. Figs. 24a, 25a show the particle size distribution for 50 and 95 nm thick silver films deposited on PS/P4VP, 50:50. The average size, ā and geometric standard deviation, σ a are 79.4 nm and ±1.2, respectively for the 50 nm film whereas the corresponding values for the 95 nm film are 95.4 nm and ±1.4. A closer look at the morphology of silver nanoparticles deposited on PS/P4VP, 50:50 in Figs.24a & 25a, clearly shows that particle size increases with the amount of silver deposited. The shape of the nanoparticles changes from near spherical particles to irregular ellipsoidal particles. The size distribution and width of histograms as shown in the figure indicate that the average size of the particle increases from 79.4 to 95.4 nm and the size distribution expands from 50-110 nm to 60-160 nm which results in improvement of tunnelling effect in PS/P4VP, 50:50 [40].And silver particulate film of thickness 95 nm show better electrical behaviour than silver particulate film of 50 nm on PS/P4VP, 50:50 [34]. It is evident that increase in size distribution decreases the inter-separation of silver clusters in this blend. This fact may be regarded as a consequence of the size as well as inter-separation evolution

**Figure 24. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 50 KX and **b** Corresponding

**Figure 25. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 100 KX and **b** Corresponding

of nanoparticles during the ongoing deposition process.

histogram of 50 nm thick silver film on PS/P4VP, 50:50.

histogram of 95 nm thick silver film on PS/P4VP, 50:50.

**Figure 23. a**: SEM of silver particulate films of 200 nm on PS, P2VP and PS/P2VP, 50:50 and their corresponding histograms. **b**: SEM of silver particulate films of 100, 150 and 200 nm on PS/P2VP, 50:50 and their corresponding histograms.

Fig.23b shows the particle size distribution for 100, 150 and 200 nm thickness films deposited on PS/P2VP, 50:50 and their corresponding histograms. The average size, ā and geometric standard deviation σ a are 94.8 nm, 1.5 and 100 nm, 5 and 129 nm, 3 for the 100, 150 and 200 nm film, respectively. It is evident from the figure that size distribution varied from 55-125, 65-135 to 70-200 nm for the 100, 150 and 200 nm films, respectively. Such dispersion of silver nanoparticle within the PS/P2VP, 50:50 leads to better electrical behaviour [52].This electric behaviour is not observed even for 300 nm silver particulate films on PS [20].Hence, silver particulate films on PS/P2VP, 50:50 at low volume fraction of silver consist of isolated and widely dispersed nanoparticles. But systematic and controlled increase of silver volume in the blend matrixes has shown increase in the size of silver clusters [52-53].

Figs.24a to 27a show the SEM pictures of various thicknesses of silver films deposited on PS/P4VP blends. The acceleration voltage is 20 kV and magnification is 50 to 100 KX for all the SEM pictures. The particle sizes measured from respective SEM pictures are plotted as histogram in figs. 24b to 27 b. The corresponding histograms (Figs.24b to 27 b) of silver particles of the films are shown side by side of the SEM pictures. The data fit into a log normal distribution for all the cases. Hence, the average size, ā and geometric standard deviation, σ a are determined from the log normal distribution of the curves. The positive effect of blending P4VP with PS is clearly visible in these pictures. Figs. 24a, 25a show the particle size distribution for 50 and 95 nm thick silver films deposited on PS/P4VP, 50:50. The average size, ā and geometric standard deviation, σ a are 79.4 nm and ±1.2, respectively for the 50 nm film whereas the corresponding values for the 95 nm film are 95.4 nm and ±1.4. A closer look at the morphology of silver nanoparticles deposited on PS/P4VP, 50:50 in Figs.24a & 25a, clearly shows that particle size increases with the amount of silver deposited. The shape of the nanoparticles changes from near spherical particles to irregular ellipsoidal particles. The size distribution and width of histograms as shown in the figure indicate that the average size of the particle increases from 79.4 to 95.4 nm and the size distribution expands from 50-110 nm to 60-160 nm which results in improvement of tunnelling effect in PS/P4VP, 50:50 [40].And silver particulate film of thickness 95 nm show better electrical behaviour than silver particulate film of 50 nm on PS/P4VP, 50:50 [34]. It is evident that increase in size distribution decreases the inter-separation of silver clusters in this blend. This fact may be regarded as a consequence of the size as well as inter-separation evolution of nanoparticles during the ongoing deposition process.

Applications of Calorimetry in a Wide Context –

and their corresponding histograms.

244 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

separation evolution of nanoparticles during the ongoing deposition process.

**Figure 23. a**: SEM of silver particulate films of 200 nm on PS, P2VP and PS/P2VP, 50:50 and their corresponding histograms. **b**: SEM of silver particulate films of 100, 150 and 200 nm on PS/P2VP, 50:50

volume in the blend matrixes has shown increase in the size of silver clusters [52-53].

Figs.24a to 27a show the SEM pictures of various thicknesses of silver films deposited on PS/P4VP blends. The acceleration voltage is 20 kV and magnification is 50 to 100 KX for all the SEM pictures. The particle sizes measured from respective SEM pictures are plotted as histogram in figs. 24b to 27 b. The corresponding histograms (Figs.24b to 27 b) of silver particles of the films are shown side by side of the SEM pictures. The data fit into a log

Fig.23b shows the particle size distribution for 100, 150 and 200 nm thickness films deposited on PS/P2VP, 50:50 and their corresponding histograms. The average size, ā and geometric standard deviation σ a are 94.8 nm, 1.5 and 100 nm, 5 and 129 nm, 3 for the 100, 150 and 200 nm film, respectively. It is evident from the figure that size distribution varied from 55-125, 65-135 to 70-200 nm for the 100, 150 and 200 nm films, respectively. Such dispersion of silver nanoparticle within the PS/P2VP, 50:50 leads to better electrical behaviour [52].This electric behaviour is not observed even for 300 nm silver particulate films on PS [20].Hence, silver particulate films on PS/P2VP, 50:50 at low volume fraction of silver consist of isolated and widely dispersed nanoparticles. But systematic and controlled increase of silver

improvement of tunnelling effect in the blend and the blend shows desired electrical behaviour [52]. This fact may be regarded as a consequence of the size as well as inter-

**Figure 24. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 50 KX and **b** Corresponding histogram of 50 nm thick silver film on PS/P4VP, 50:50.

**Figure 25. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 100 KX and **b** Corresponding histogram of 95 nm thick silver film on PS/P4VP, 50:50.

246 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Figs.26a & 27a show the particle size distribution for 50 nm and 150 nm thickness films deposited on PS/P4VP, 75:25. The average size, ā and geometric standard deviation, σ a are 88.6 nm and ±8.5 for the 50 nm film and 96.7 nm and ±4 for 150 nm film, respectively. It is evident from the figure that distribution of size increased from 50-120 nm to 60-140 nm .Such dispersion of silver nanoparticle within the PS/P4VP, 75:25 leads to better electrical behaviour [40].Such electric behaviour is not observed even for 300 nm silver particulate film on PS [36].Hence, silver particulate film of 50 nm thickness on PS/P4VP, 75/25 consist of isolated and widely dispersed nanoparticles. But systematic and controlled increase of silver in the PS/P4VP, 75:25 matrixes produced interesting result [40]. The silver particulate film of thickness 150 nm on PS/P4VP, 75:25 shows the room temperature resistance in few mega ohms a desirable range for applications.

Silver Particulate Films on Compatible Softened Polymer Composites 247

(nm) Standard deviation

(nm) Standard deviation

σ <sup>a</sup>

94.8 1.5 100 5 129 3

205 4

σ <sup>a</sup>

 - - 79.4 1.2 95.4 1.4 88.6 8.5 96.7 4.0 92 -

SEM, a

SEM, a

Table 5&6 has been compiled to show all the particles size of silver clusters embedded in PS/P2VP and PS/P4VP blends from XRD and SEM. The SEM has provided the morphology of silver clusters and their distribution. The XRD diffraction pattern represents the average throughout the film due to increased penetration and large beam size. The observed values of particle size from SEM are in the same range as the calculated values of the particle size from XRD. The difference in the values may be due to averaging over longer depths because of penetration of X-rays. Though, the trend of particle size measured from XRD and SEM are

**Table 5.** The average particle size for silver deposited on PS/P2VP blends. The deposition rate is

Particle size

 XRD

 0:100 50 30 58 - 25:75 50 46.6 - -

> 53 49.1 51.6 51.8 52.3 53.3

Particle size

 XRD

0:100 200 109 9

 - - 40.6

**Table 6.** The average particle size for silver deposited on PS/P4VP blends. The deposition rate is

The silver films deposited on polymer composites show an increase in resistance, when they are exposed to atmosphere. It may be possible to stabilise the resistance against exposure to atmosphere through the deposition of good quality inorganic passivators like alumina, zirconia etc, to make the films suitable for device applications. Also, silver films are more

similar.

0.4nm/s and temperature is 457K.

PS/P2VP Thickness (nm)

 50:50 100 150 200

100:0 200

PS/P4VP Thickness (nm)

 85 50:50 50 95 75:25 50 150 100:0 50

0.4nm/s and temperature is 457K.

**5. Further research** 

**Figure 26. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 100 KX and **b** Corresponding histogram of 50 nm thick silver film on PS/P4VP, 75:25.

**Figure 27. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 100 KX and **b** Corresponding histogram of 150 nm thick silver film on PS/P4VP, 75:25.

Table 5&6 has been compiled to show all the particles size of silver clusters embedded in PS/P2VP and PS/P4VP blends from XRD and SEM. The SEM has provided the morphology of silver clusters and their distribution. The XRD diffraction pattern represents the average throughout the film due to increased penetration and large beam size. The observed values of particle size from SEM are in the same range as the calculated values of the particle size from XRD. The difference in the values may be due to averaging over longer depths because of penetration of X-rays. Though, the trend of particle size measured from XRD and SEM are similar.


**Table 5.** The average particle size for silver deposited on PS/P2VP blends. The deposition rate is 0.4nm/s and temperature is 457K.


**Table 6.** The average particle size for silver deposited on PS/P4VP blends. The deposition rate is 0.4nm/s and temperature is 457K.

### **5. Further research**

Applications of Calorimetry in a Wide Context –

ohms a desirable range for applications.

histogram of 50 nm thick silver film on PS/P4VP, 75:25.

histogram of 150 nm thick silver film on PS/P4VP, 75:25.

246 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Figs.26a & 27a show the particle size distribution for 50 nm and 150 nm thickness films deposited on PS/P4VP, 75:25. The average size, ā and geometric standard deviation, σ a are 88.6 nm and ±8.5 for the 50 nm film and 96.7 nm and ±4 for 150 nm film, respectively. It is evident from the figure that distribution of size increased from 50-120 nm to 60-140 nm .Such dispersion of silver nanoparticle within the PS/P4VP, 75:25 leads to better electrical behaviour [40].Such electric behaviour is not observed even for 300 nm silver particulate film on PS [36].Hence, silver particulate film of 50 nm thickness on PS/P4VP, 75/25 consist of isolated and widely dispersed nanoparticles. But systematic and controlled increase of silver in the PS/P4VP, 75:25 matrixes produced interesting result [40]. The silver particulate film of thickness 150 nm on PS/P4VP, 75:25 shows the room temperature resistance in few mega

**Figure 26. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 100 KX and **b** Corresponding

**Figure 27. a** SEM micrograph, Acceleration voltage-20 kV, Magnification 100 KX and **b** Corresponding

The silver films deposited on polymer composites show an increase in resistance, when they are exposed to atmosphere. It may be possible to stabilise the resistance against exposure to atmosphere through the deposition of good quality inorganic passivators like alumina, zirconia etc, to make the films suitable for device applications. Also, silver films are more susceptible to oxygen in atmosphere than gold. Hence, deposition of gold nanopaticles on PS/P2VP and PS/P4VP composites may give more stabilised films which may be suitable films for sensitive applications.

Silver Particulate Films on Compatible Softened Polymer Composites 249

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[13] Jiao H, Goh S H, Valiyaveettil S (2001) Mesomorphic Interpolymer complexes and blends based on poly ( 4-vinylpyridine)- dodecylbenzenesulfonic acid complex and

[14] Kosonen H, Valkama S, Hartikainen J, Eerikainen H, Torkkel M, Jokela K, Serimaa R, Sundholm F, Brinke G, Ikkala O (2002) Mesomorphic Structure of Poly(styrene)-blockpoly(4-vinylpyridine) with Oligo(ethylene oxide)sulfonic Acid Side Chains as a Model for Molecularly Reinforced Polymer Electrolyte. Macromolecules 35: 10149-10154. [15] Wang X, Zuo J, Keil P, Grundmeier G (2007) Comparing the growth of PVD silver nanoparticles on ultra thin fluorocarbon plasma polymer films and self-assenbled

[16] Heilmann A (2002) Polymer Films with Embedded Metal Nanoparticles,

[17] Mayer A B R (2001) Colloidal metal nanoparticles dispersed in amphiphilic polymers.

poly(acrylic acid) or poly(p-vinvylphenol. Macromolecules, 34:7162-7165.

Spheres Just below a Polymer Surface. J. Colloid. Interface*. Sci*. 90: 335-342.

Amorphous Polymer Substrates. J. Appl. Phys. 72: 4458-4460.

Assembled Aggregates in Water. J Appl Polymer Sci, 89:1017-1025.

Poly(methyl methacrylate).Express polymer letters 1:44-50.

blends. Macromolecular Chemistry and Physics 200(4):678-682.

fluoroalkyl silane monolayers. Nanotecnology 18:265303-265313.

Electrochem. Systems 4: 11-15.

polymer Journal 42(10): 2807-2823.

Berlin:Springler.

Polym. Adv. Technol. 12: 96-106.

40.

### **6. Conclusion**

The following conclusions may be drawn from the study on **Silver Particulate Films on Compatible Softened Polymer Composites**

Viscometry studies indicate a very small interaction parameter resulting in physically miscible blends of PS/ P4VP.DSC studies indicate a single Tg in all the cases indicating the formation of compatible blends. This may be due to some intermolecular interaction at higher temperature. Hence, the blends found some order of compatibility at higher temperatures. FTIR and SEM support the results of miscibility as well as DSC. The fairly compatible blend of PS/P2VP and PS/P4VP can be obtained on melt mixing at higher temperature. Deposition of silver on polymer blends coated substrate held at 457 K provides an approach to produce stable island films with reasonable control over their electrical resistance. Higher thickness films show almost zero TCR near room temperature, a desirable property for most of the devices. Low thickness films show a negative TCR, characteristic of island film. Silver particulate films deposited on composite blends show better electrical properties compared to pure PS.The deposition of silver particulate films by evaporation on PS/P2VP and PS/P4VP blends yields positive effect of blending PS with P2VP and P4VP.The size distribution and dispersion of silver nanoparticles is found to be dependent on the nature of the polymer host and thickness of particulate films. With the addition of P2VP, P4VP and amount of silver, morphology of the silver particulate films on PS/P2VP (50:50) and PS/P4VP (50:50, 75:25) could be modified to give the desired electrical results.

### **Author details**

Pratima Parashar *Department of Materials Science, Mangalore University, Mangalagangotri, India CET, IILM Academy of Higher Learning, Greater Noida, India* 

### **Acknowledgement**

The author thanks DST for the XRD and NCL (Pune) for SEM facility. The author thanks DST for the funding through Women Scientist Scheme (WOS).

### **7. References**


[3] Kovacs G J, Vincent P S (1982) Formation and Thermodynamic Stability of a Novel Class of Useful Materials: Close-Packed Monolayers of Submicron Monodisperse Spheres Just below a Polymer Surface. J. Colloid. Interface*. Sci*. 90: 335-342.

Applications of Calorimetry in a Wide Context –

**Compatible Softened Polymer Composites**

films for sensitive applications.

**6. Conclusion** 

**Author details** 

Pratima Parashar

**7. References** 

**Acknowledgement** 

Appl. Phys. 38: 2223- 31.

248 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

susceptible to oxygen in atmosphere than gold. Hence, deposition of gold nanopaticles on PS/P2VP and PS/P4VP composites may give more stabilised films which may be suitable

The following conclusions may be drawn from the study on **Silver Particulate Films on** 

Viscometry studies indicate a very small interaction parameter resulting in physically miscible blends of PS/ P4VP.DSC studies indicate a single Tg in all the cases indicating the formation of compatible blends. This may be due to some intermolecular interaction at higher temperature. Hence, the blends found some order of compatibility at higher temperatures. FTIR and SEM support the results of miscibility as well as DSC. The fairly compatible blend of PS/P2VP and PS/P4VP can be obtained on melt mixing at higher temperature. Deposition of silver on polymer blends coated substrate held at 457 K provides an approach to produce stable island films with reasonable control over their electrical resistance. Higher thickness films show almost zero TCR near room temperature, a desirable property for most of the devices. Low thickness films show a negative TCR, characteristic of island film. Silver particulate films deposited on composite blends show better electrical properties compared to pure PS.The deposition of silver particulate films by evaporation on PS/P2VP and PS/P4VP blends yields positive effect of blending PS with P2VP and P4VP.The size distribution and dispersion of silver nanoparticles is found to be dependent on the nature of the polymer host and thickness of particulate films. With the addition of P2VP, P4VP and amount of silver, morphology of the silver particulate films on PS/P2VP (50:50)

and PS/P4VP (50:50, 75:25) could be modified to give the desired electrical results.

The author thanks DST for the XRD and NCL (Pune) for SEM facility. The author thanks

[1] Skofronick J G, Phillips W B (1967) Morphological Changes in Discontinuous Gold

[2] Fehlner F P (1967) Behavior of Ultrathin Zirconium Films upon Exposure to Oxygen. J.

*Department of Materials Science, Mangalore University, Mangalagangotri, India* 

*CET, IILM Academy of Higher Learning, Greater Noida, India* 

DST for the funding through Women Scientist Scheme (WOS).

Films following Deposition. J. Appl. Phys. 38(12): 4791-4796.


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[37] Rao K M, Pattabi M., Sainkar S. R, Lobo A., Kulkarni S K, Uchil J, Sastry M. S (1999) Preparation and characterisation of silver particulate structure deposited on softened

[38] Haoyan W, Eilers H (2008) Electrical Conductivity of Thin-Film Composites Containing Silver nanoparticles Embedded in a Dielectric Teflon AF Matrix. Thin Solid Films, 517:

[39] Pattabi M , Rao K M (1998) Electrical behaviour of discontinuous silver films deposited

[40] Kiesow A, Morris J E, Radehaus C, Heilmann A (2003) Switching behavior of plasma polymer films containing silver nanoparticles. J.Appl. Phy. 94 (10): 6988-6990. [41] Heilmann A, Kiesov A,Gruner M, Kreibig U (1999) Optical and electrical properties of embedded silver nanoparticles at low temperatures.Thin Solid Films 343-344:175-178. [42] Fritzsche W, Porwol H, Wiegand A, Boronmann, Khler J M (1998) In-situ formation of Ag-containing nanoparticles in thin polymer film. Nanostrutured Materials, 10 (1) 89-

[43] Akamatsu K, Takei S, Mizuhata M, Kajinami A, Deki S, Fujii M, Hayashi S, Yamamoto K (2000) Preparation and characterization of polymer thin films containing silver and

[44] Carotenuto G (2001) Synthesis and characterization of poly (*N*-vinylpyrrolidone) filled by monodispersed silver clusters with controlled size. Appl. Organometal. Chem.

[45] Kim J Y, Shin D H, Ihn K J, Suh K D (2003 ) Amphiphilic Polyurethane-co-polystyrene Network Films Containing Silver Nanoparticles. J Ind. Eng. Chem. 9(1):37-44. [46] Heilmann A, Quinten M, Werner J (1998) Optical response of thin plasma-polymer

[47] Mandal S, Arumgam S K, Pasricha R, Sastry M (2005) Silver nanoparticles of variable morphology synthesized in aqueous foams as novel templates. Bull. Mater. Sci.

[48] Kim JY, Shin DH, Ihn KJ (2005) Synthesis of CdS nanoparticles dispersed within amphiphilic poly(urethane acrylate-*co*-styrene) films. J.Appl.Polym Sci. 97(6):2357-2363. [49] Biswas A, Bayer I S, Marken B, Pounds D, Norton M G (2007) Networks of ultra-fine Ag nanocrystals in a Teflon AF® matrix by vapour phase e-beam-assisted deposition

[50] Parashar P (2011) Morphology of Silver Particulate Films Deposited on Softened Polymer Blends of Polystyrene and Poly (4-vinylpyridine)J.Appl.Polymer Sci. 121 (2):

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Polymer 33(5):1099-1101.

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tailored optical properties. J.Mater. Res 21:2168-2171.

[18] Beecroft L L (1997) Nanocomposite materials for optical applications. Chem.Mater.

[19] Caseri W (2000) Nanocomposites of polymers and metals or semiconductors: Historical

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[21] Yonzon C R, Stuart D A, Zhang X, Mcfarland A D, Haynes CL, Duyne R P V (2005) Towards advanced chemical and biological nanosensors—An overview. Talanta

[22] Saito R, Okamura S, Ishizu K (1992) Introduction of colloidal silver into a poly (2-vinyl pyridine) microdomain of microphase separated poly(styrene-*b*-2-vinyl pyridine) film.

[23] Tao L, Ho R M, Ho J C (2009) Phase Behavior in Self-assembly of Inorganic/Poly(4-

[24] Pennelli G (2006) Lateral reduction of random percolative networks formed by nanocrystals: Possibilities for a new concept electronic device. Appl. Phys. Lett.

[25] Rao K M, Pattabi M, Mayya K S, Sainkar S R, Murali Sastry M S (1997) Preparation and characterization of silver particulate films on softened polystyrene substrates. Thin

[26] Hassell T, Yoda S, Howdle S M., Brown P D (2006) Microstructural charecterisation of silver/polymer nanocomposites prepared using supercritical cabondioxide. J. of Phys:

[27] Dondos A S, Kondras P, Pierri P, Benoit H (1983) Hydrodynamic crossover in twopolymer mixtures from viscosity measurement. Macromolek Chem, 184(10):2153-2158 [28] Rao V, Ashokan P, Shridhar M H (1999) Studies on the compatibility and specific interaction in cellulose acetate hydrogen phthalate (CAP) and poly methyl

[29] Shih K S, Beatty C L (1990) Blends of polycarbonate and poly(hexamethylene sebacate): IV. Polymer blend intrinsic viscosity behavior and its relationship to solid-state blend

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[31] Fox, T G (1956) Influence of Diluent and of Copolymer Composition on the Glass

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	- [52] Parashar P (2011) Electrical behaviour of discontinuous silver films deposited on compatible Polystyrene/Poly (2- vinylpyridine) composite. J.Mater.Sci:Mater Electron, DOI 10.1007/s10854-011-0418-6.

**Chapter 11** 

© 2013 Alcazar-Vara and Buenrostro-Gonzalez, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

properly cited.

mechanisms involved on the *n*-paraffins crystallization process.

**Liquid-Solid Phase Equilibria of** 

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54575

**1. Introduction** 

**Paraffinic Systems by DSC Measurements** 

Several industrial sectors around the world deal with paraffinic wax in their processes or make use of it in their products. Hence, understanding physical properties of paraffins is of industrial importance. Some of these industrial sectors are: petroleum production, petroleum refining and products, chemical, energy and consumer products [1]. However, as it has been widely reported in literature [2-6], one of the most affected industrial sectors by the paraffin crystallization phenomena is the petroleum industry. Crude oils contain heavy paraffins that may form solid wax phases at low temperature in the pipelines and hydrocarbon production facilities. The problems caused by wax precipitation decreasing production rates and failure of facilities, are a major concern in the production and transportation of hydrocarbon fluids [7]. Paraffin waxes are mixtures of a wide range of high molecular weight alkanes that can crystallize from crude oils or solutions primarily due to temperature decreasing. They are rather non-polar molecules and their interactions are expected to be van der Waals or London dispersion type [4]. Paraffin waxes consist of branched (iso), cyclic and straight chain (normal) alkanes having chain lengths in excess of 17 carbon atoms (C17) and potentially up to and over C100 [8]. However, despite the fact that crude oils are extremely complex systems containing a multitude of components, it is generally accepted that the crystallizing materials that form the deposits are primarily *n*alkanes [9-10]. Therefore, in order to obtain a greater insight on the formation of wax deposits to prevent and solve these problems, it is necessary to get a deep knowledge of the

Other industrial problems associated to the paraffin phase behavior have been reported in literature and summarized below. In diesel fuels production operations, fuel-filter plugging and other associated fuel handling problems can occur in cold weather due to paraffin crystallization. Moreover, fuels produced from Fischer–Tropsch syntheses that are currently

and reproduction in any medium, provided the original work is properly cited.

Luis Alberto Alcazar-Vara and Eduardo Buenrostro-Gonzalez

[53] Parashar P (2011) Structural properties of silver particulate films deposited on softened polymer blends of polystyrene/poly (2-vinyl pyridine) J.Mater.Sci:Mater Electron, DOI 10.1007/s10854-011-0567-7

**Chapter 11** 

## **Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements**

Luis Alberto Alcazar-Vara and Eduardo Buenrostro-Gonzalez

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54575

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

DOI 10.1007/s10854-011-0418-6.

10.1007/s10854-011-0567-7

252 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[52] Parashar P (2011) Electrical behaviour of discontinuous silver films deposited on compatible Polystyrene/Poly (2- vinylpyridine) composite. J.Mater.Sci:Mater Electron,

[53] Parashar P (2011) Structural properties of silver particulate films deposited on softened polymer blends of polystyrene/poly (2-vinyl pyridine) J.Mater.Sci:Mater Electron, DOI

> Several industrial sectors around the world deal with paraffinic wax in their processes or make use of it in their products. Hence, understanding physical properties of paraffins is of industrial importance. Some of these industrial sectors are: petroleum production, petroleum refining and products, chemical, energy and consumer products [1]. However, as it has been widely reported in literature [2-6], one of the most affected industrial sectors by the paraffin crystallization phenomena is the petroleum industry. Crude oils contain heavy paraffins that may form solid wax phases at low temperature in the pipelines and hydrocarbon production facilities. The problems caused by wax precipitation decreasing production rates and failure of facilities, are a major concern in the production and transportation of hydrocarbon fluids [7]. Paraffin waxes are mixtures of a wide range of high molecular weight alkanes that can crystallize from crude oils or solutions primarily due to temperature decreasing. They are rather non-polar molecules and their interactions are expected to be van der Waals or London dispersion type [4]. Paraffin waxes consist of branched (iso), cyclic and straight chain (normal) alkanes having chain lengths in excess of 17 carbon atoms (C17) and potentially up to and over C100 [8]. However, despite the fact that crude oils are extremely complex systems containing a multitude of components, it is generally accepted that the crystallizing materials that form the deposits are primarily *n*alkanes [9-10]. Therefore, in order to obtain a greater insight on the formation of wax deposits to prevent and solve these problems, it is necessary to get a deep knowledge of the mechanisms involved on the *n*-paraffins crystallization process.

> Other industrial problems associated to the paraffin phase behavior have been reported in literature and summarized below. In diesel fuels production operations, fuel-filter plugging and other associated fuel handling problems can occur in cold weather due to paraffin crystallization. Moreover, fuels produced from Fischer–Tropsch syntheses that are currently

© 2013 Alcazar-Vara and Buenrostro-Gonzalez, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### 254 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

being investigated for converting natural gas to liquids (fuels) can be particularly problematic due to amounts of higher molecular weight paraffin wax produced [1]. Phase equilibrium data of n-alkane systems with different solvents are of importance for the safe and efficient operation of chemical plants. They are necessary for high-pressure polymerization processes and for the design of oil-recovery processes. Besides its importance for technological processes such as crystallization and purification at high pressure, phase equilibrium properties provides a good tool for examining the thermodynamic nature of many systems [11].Recently, the use of phase change material (PCM) thermal energy storage has gained considerable attention because of its high storage density (amount of energy stored per unit mass), and a narrow temperature range for charging and discharging the storage. Paraffin waxes have been used as PCM for many applications because of their advantageous thermal performances and phase behavior [12]. Finally, the control of crystallization processes is a problem of quite general relevance, which appears in many practical fields such as pharmaceutical and specialty chemical industries [13-15]. "Crystal design or engineering" enables, in principle, a direct handling of the structure, size, and shape of crystals entering into the elaboration of materials. Classical means of controlling size, morphology, and polymorphic expression of crystals make use of parameters such as temperature, pH, supersaturation, and solvent quality [15].

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 255

specific applications on the use of the Calorimetry to carry out relevant studies of phase equilibria properties. Finally, this chapter presents the characterization of the wax precipitation phenomena by using DSC measurements in crude oils that present solids deposition problems during their production and transporting, where the results obtained by using DSC technique are compared with those obtained with other techniques such as rheometry, spectroscopy and densitometry; in order to show advantages and disadvantages of the use of DSC method to measure liquid-solid phase equilibria of wax in crude oils.

**2. DSC methodology applied to measure liquid-solid phase equilibria of** 

As it was mentioned above, there are many experimental works in literature [3, 14, 16, 20-23, 28-30] reporting the use of DSC to study the paraffins crystallization process. In this section, it is described the DSC methodology to characterize the liquid-solid phase equilibria of paraffins in model systems and crude oil samples. The objective of this section is to provide the details of the DSC technique and the experimental conditions used to get the key

The measurement principle of differential scanning calorimetry (DSC) is based on the measurement of the difference in the heat flows to the sample crucible and reference crucible. These heat flows are directly proportional to the temperature difference between the furnace and crucible, but inversely proportional to the thermal resistance of the system. In Figure 1 is shown the measuring cell, furnace and liquid nitrogen cooling chamber of the Shimadzu DSC-60A differential scanning calorimeter used in the experiments to be

properties that characterize the liquid-solid phase equilibria of paraffins.

**Figure 1.** DSC measuring cell and temperature control system (Source: Shimadzu).

**paraffins** 

presented in this work.

Some experimental techniques reported in literature such as Microscopy and X-ray diffraction are powerful methods to determine the crystal structures but give limited insight into the crystallization process [16], while others methods used to get the liquid-solid equilibrium of paraffins have been used [17-18], but they are very complex due to they require the establishment of the equilibrium at each temperature of interest and the measurement of the composition of the phases present. Finally, visual methods have been also reported to measure solubility and phase behavior of paraffin waxes [1, 19]; however, these methods cannot be applied to test dark samples (e.g. black crude oils) [20]. Hence, for the study and measurement of paraffin crystallization process, Differential scanning calorimetry (DSC) is an experimental method widely used due to its simplicity, accuracy and fast response to monitor the phase transitions during cooling and heating that gives related thermodynamic quantities such as heat capacity and enthalpies of transition [3, 14, 16, 20-23]. DSC has been usually used for the determination of wax appearance and/or dissolution temperatures (WAT or WDT) in petroleum products [3, 20]. The WAT or cloud point is the singularly most important parameter relating to wax formation [4] and it is the temperature at which waxes first crystallize from solution during a cooling process. So that accurate WAT measurements by using reliable methods such as DSC are desirable since it represents a key factor to characterize the wax precipitation phenomena.

The objective of this chapter is to present the use of DSC technique on the measurement and characterization of the liquid-solid phase equilibria of paraffins. First, the details of the DSC method and the experimental conditions used to get the key properties to characterize the liquid-solid phase equilibria of paraffins are described. Then, experimental studies about the effect of the chemical nature of solvent and asphaltenes on liquid-solid phase behavior of paraffinic model systems; are presented and discussed in these sections in order to show specific applications on the use of the Calorimetry to carry out relevant studies of phase equilibria properties. Finally, this chapter presents the characterization of the wax precipitation phenomena by using DSC measurements in crude oils that present solids deposition problems during their production and transporting, where the results obtained by using DSC technique are compared with those obtained with other techniques such as rheometry, spectroscopy and densitometry; in order to show advantages and disadvantages of the use of DSC method to measure liquid-solid phase equilibria of wax in crude oils.

Applications of Calorimetry in a Wide Context –

254 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

parameters such as temperature, pH, supersaturation, and solvent quality [15].

represents a key factor to characterize the wax precipitation phenomena.

The objective of this chapter is to present the use of DSC technique on the measurement and characterization of the liquid-solid phase equilibria of paraffins. First, the details of the DSC method and the experimental conditions used to get the key properties to characterize the liquid-solid phase equilibria of paraffins are described. Then, experimental studies about the effect of the chemical nature of solvent and asphaltenes on liquid-solid phase behavior of paraffinic model systems; are presented and discussed in these sections in order to show

Some experimental techniques reported in literature such as Microscopy and X-ray diffraction are powerful methods to determine the crystal structures but give limited insight into the crystallization process [16], while others methods used to get the liquid-solid equilibrium of paraffins have been used [17-18], but they are very complex due to they require the establishment of the equilibrium at each temperature of interest and the measurement of the composition of the phases present. Finally, visual methods have been also reported to measure solubility and phase behavior of paraffin waxes [1, 19]; however, these methods cannot be applied to test dark samples (e.g. black crude oils) [20]. Hence, for the study and measurement of paraffin crystallization process, Differential scanning calorimetry (DSC) is an experimental method widely used due to its simplicity, accuracy and fast response to monitor the phase transitions during cooling and heating that gives related thermodynamic quantities such as heat capacity and enthalpies of transition [3, 14, 16, 20-23]. DSC has been usually used for the determination of wax appearance and/or dissolution temperatures (WAT or WDT) in petroleum products [3, 20]. The WAT or cloud point is the singularly most important parameter relating to wax formation [4] and it is the temperature at which waxes first crystallize from solution during a cooling process. So that accurate WAT measurements by using reliable methods such as DSC are desirable since it

being investigated for converting natural gas to liquids (fuels) can be particularly problematic due to amounts of higher molecular weight paraffin wax produced [1]. Phase equilibrium data of n-alkane systems with different solvents are of importance for the safe and efficient operation of chemical plants. They are necessary for high-pressure polymerization processes and for the design of oil-recovery processes. Besides its importance for technological processes such as crystallization and purification at high pressure, phase equilibrium properties provides a good tool for examining the thermodynamic nature of many systems [11].Recently, the use of phase change material (PCM) thermal energy storage has gained considerable attention because of its high storage density (amount of energy stored per unit mass), and a narrow temperature range for charging and discharging the storage. Paraffin waxes have been used as PCM for many applications because of their advantageous thermal performances and phase behavior [12]. Finally, the control of crystallization processes is a problem of quite general relevance, which appears in many practical fields such as pharmaceutical and specialty chemical industries [13-15]. "Crystal design or engineering" enables, in principle, a direct handling of the structure, size, and shape of crystals entering into the elaboration of materials. Classical means of controlling size, morphology, and polymorphic expression of crystals make use of

### **2. DSC methodology applied to measure liquid-solid phase equilibria of paraffins**

As it was mentioned above, there are many experimental works in literature [3, 14, 16, 20-23, 28-30] reporting the use of DSC to study the paraffins crystallization process. In this section, it is described the DSC methodology to characterize the liquid-solid phase equilibria of paraffins in model systems and crude oil samples. The objective of this section is to provide the details of the DSC technique and the experimental conditions used to get the key properties that characterize the liquid-solid phase equilibria of paraffins.

The measurement principle of differential scanning calorimetry (DSC) is based on the measurement of the difference in the heat flows to the sample crucible and reference crucible. These heat flows are directly proportional to the temperature difference between the furnace and crucible, but inversely proportional to the thermal resistance of the system. In Figure 1 is shown the measuring cell, furnace and liquid nitrogen cooling chamber of the Shimadzu DSC-60A differential scanning calorimeter used in the experiments to be presented in this work.

**Figure 1.** DSC measuring cell and temperature control system (Source: Shimadzu).

256 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The method to obtain the liquid-solid phase equilibrium properties from DSC experiments is explained below. A calibration procedure of the DSC equipment should be performed before carrying out the experiments by using Indium or series of high purity normal paraffins as standard [22]. Each sample (between 10 and 20 mg) is first heated until reaching a temperature higher than expected crystallization onset temperature (WAT) but without reaching the boiling point of the sample. Then, the sample is held isothermally for 1 min., and then cooled to the desired temperature at a pre-defined rate. The cooling/heating rate can be variable; in general low heating/cooling rates would be desirable from an equilibrium point of view [20]. However, by using low cooling rates higher WAT are obtained with a loss of sensitivity to identify the DSC peak onsets, whereas high cooling rates depress measured WAT due to supercooling effects [20]. Differences about ± 1°C on DSC WAT measurements have been observed when using 1, 5 and 10 °C/min as cooling rates in single paraffin solutions [16]; whereas for crude oil mixtures and by using low cooling rates of 0.1 to 1 °C/min, differences about ± 1-2°C were reported [31] Therefore, in the experiments presented in the following sections, we employ a heating/cooling rate of 5 °C/min because it provided sufficient experimental speed and sensitivity to identify onsets of the exo and endothermic peaks. In order to delete any thermal history effects, two heating/cooling cycles are employed, so that crystallization and melting properties are obtained from the second cycle. The crystallization onset temperature (WAT) is determined as the onset of the exothermal peak during the cooling process corresponding to the liquid–solid transition. Under heating conditions, the melting temperature is recorded as the onset of the endothermal peak, whereas the wax disappearance temperature (WDT), temperature at which the last precipitated paraffin re-dissolves in the oil or solution, can be recorded as the endset of the solid–liquid endotherm. Finally, due to that the total energy released during cooling or heating process is proportional to the area between the base line and the exothermal peak or endothermal peak, respectively, the enthalpies of crystallization and melting of the waxy model systems are calculated from the integration of heat flow curve.

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 257

*Percent crystallinity = [ΔHm / ΔHm°] x 100* (1)

where *ΔHm* is the melting enthalpy of the mixture measured by DSC and *ΔHm°* is the melting

enthalpy of the 100% crystalline solute.

**Figure 2.** Example of DSC measurements on a paraffinic model system.

In Figure 2 is shown the determination of the equilibrium temperatures (WAT and melting temperature) as well as the enthalpies from the DSC thermograms according to the method explained above.

The DSC technique allows also the determination of the wax precipitation or solubility curve (amount of precipitated wax at different temperatures) as it has been reported [18, 28, 32-33]. It is carried out by assuming that the amount or fraction of precipitated wax in the total wax content is proportional to the percent of accumulated heat released in the total heat released (Crystallization enthalpy), thus the amount of precipitated wax at different temperatures can be determined by dividing the accumulated heat released by the heat of crystallization. This procedure is depicted in Figure 3, where the accumulated heat released for the exothermic peak related to the crystallization of the system 6 wt % of C36 in *n*-decane is plotted as an example [28].

Finally, by using DSC data, we can determine the degree of crystallinity for pure solutes in solvent systems or mixtures by using the following equation [28, 34]:

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 257

$$\text{Percent crystallivity} = \{\Delta \mathcal{H}\_m / \Delta \mathcal{H}\_{m^\circ}\} \propto 100 \tag{1}$$

where *ΔHm* is the melting enthalpy of the mixture measured by DSC and *ΔHm°* is the melting enthalpy of the 100% crystalline solute.

Applications of Calorimetry in a Wide Context –

explained above.

is plotted as an example [28].

256 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The method to obtain the liquid-solid phase equilibrium properties from DSC experiments is explained below. A calibration procedure of the DSC equipment should be performed before carrying out the experiments by using Indium or series of high purity normal paraffins as standard [22]. Each sample (between 10 and 20 mg) is first heated until reaching a temperature higher than expected crystallization onset temperature (WAT) but without reaching the boiling point of the sample. Then, the sample is held isothermally for 1 min., and then cooled to the desired temperature at a pre-defined rate. The cooling/heating rate can be variable; in general low heating/cooling rates would be desirable from an equilibrium point of view [20]. However, by using low cooling rates higher WAT are obtained with a loss of sensitivity to identify the DSC peak onsets, whereas high cooling rates depress measured WAT due to supercooling effects [20]. Differences about ± 1°C on DSC WAT measurements have been observed when using 1, 5 and 10 °C/min as cooling rates in single paraffin solutions [16]; whereas for crude oil mixtures and by using low cooling rates of 0.1 to 1 °C/min, differences about ± 1-2°C were reported [31] Therefore, in the experiments presented in the following sections, we employ a heating/cooling rate of 5 °C/min because it provided sufficient experimental speed and sensitivity to identify onsets of the exo and endothermic peaks. In order to delete any thermal history effects, two heating/cooling cycles are employed, so that crystallization and melting properties are obtained from the second cycle. The crystallization onset temperature (WAT) is determined as the onset of the exothermal peak during the cooling process corresponding to the liquid–solid transition. Under heating conditions, the melting temperature is recorded as the onset of the endothermal peak, whereas the wax disappearance temperature (WDT), temperature at which the last precipitated paraffin re-dissolves in the oil or solution, can be recorded as the endset of the solid–liquid endotherm. Finally, due to that the total energy released during cooling or heating process is proportional to the area between the base line and the exothermal peak or endothermal peak, respectively, the enthalpies of crystallization and melting of the waxy model systems are calculated from the integration of heat flow curve.

In Figure 2 is shown the determination of the equilibrium temperatures (WAT and melting temperature) as well as the enthalpies from the DSC thermograms according to the method

The DSC technique allows also the determination of the wax precipitation or solubility curve (amount of precipitated wax at different temperatures) as it has been reported [18, 28, 32-33]. It is carried out by assuming that the amount or fraction of precipitated wax in the total wax content is proportional to the percent of accumulated heat released in the total heat released (Crystallization enthalpy), thus the amount of precipitated wax at different temperatures can be determined by dividing the accumulated heat released by the heat of crystallization. This procedure is depicted in Figure 3, where the accumulated heat released for the exothermic peak related to the crystallization of the system 6 wt % of C36 in *n*-decane

Finally, by using DSC data, we can determine the degree of crystallinity for pure solutes in

solvent systems or mixtures by using the following equation [28, 34]:

**Figure 2.** Example of DSC measurements on a paraffinic model system.

258 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 259

solvents have been reported as a help in both inhibiting wax crystal formation and decreasing the amount of the wax deposited [38]. The experimental studies reported in literature have been carried out evaluating the effect of the solvent on cloud point or wax dissolution temperatures. Nevertheless, the wax gelation and deposition processes are actually originated due to the amount of paraffin crystals formed during cooling below WAT. This makes important to evaluate the influence of solvent on the amount of crystallized paraffin at temperatures below WAT. Therefore, in this section is presented an application of the Differential Scanning Calorimetry (DSC) to study the liquid-solid phase behavior of a high molecular weight *n*-paraffin: hexatriacontane (C36H72), in presence of solvents of different chemical nature in order to get a better understanding of the

Figure 4 shows the DSC thermograms of the crystallization and melting behavior of 6 wt. % of hexatriacontane (C36) in different pure and mixed solvents systems. As can be seen, a single and well defined peak is observed during cooling and heating processes, related to the crystallization and melting of the monodisperse sample of the heavy paraffin C36 in different solvent systems. However, the endothermic peaks seem to be broader than the exothermic, so while the identification of the crystallization onset temperatures was

interactions solute-solvent on the paraffin crystallization mechanism.

straightforward; the melting onset temperatures were difficult to identify.

**Figure 4.** DSC exothermic and endothermic peaks of 6 wt% of C36 in different simple and mixed solvents systems: a) 94% of n-decane, b) 47% n-decane + 47% 1-phenyldodecane, c) 47% n-decane + 47%

xylene and d) 94 % of squalane [28].

**Figure 3.** Determination of wax solubility curve of the system 6 wt.% of C36 in *n*-decane: a) accumulated heat released for the DSC exothermic peak and b) wax solubility curve obtained [28].

### **3. Experimental study of the influence of solvent on paraffin crystallization**

The paraffin crystallization process can be influenced by many factors such as paraffin composition, solvent nature, polidispersity, rate of cooling, pressure, kinetics and presence of impurities [1,9, 14, 28, 30, 35-36], so that a better knowledge of factors affecting wax solubility will also improve the understanding of the wax precipitation phenomena in the petroleum industry described above. The studies about the effect of solvent on solubility of waxes reported in literature [1] have shown that waxes do not exhibit ideal solution behavior when crystallizing and that their solubility in a solvent increases as both the solvent molecular size and solvent solubility parameter decrease. The influence of the shape and size of the solvent on solute–solvent interaction and on the n-alkanes solubility has been also described in literature, hence it has been reported that globular or spherical solvents destroy the conformational order in liquid long-chain hydrocarbons [28, 37]. Aromatic solvents have been reported as a help in both inhibiting wax crystal formation and decreasing the amount of the wax deposited [38]. The experimental studies reported in literature have been carried out evaluating the effect of the solvent on cloud point or wax dissolution temperatures. Nevertheless, the wax gelation and deposition processes are actually originated due to the amount of paraffin crystals formed during cooling below WAT. This makes important to evaluate the influence of solvent on the amount of crystallized paraffin at temperatures below WAT. Therefore, in this section is presented an application of the Differential Scanning Calorimetry (DSC) to study the liquid-solid phase behavior of a high molecular weight *n*-paraffin: hexatriacontane (C36H72), in presence of solvents of different chemical nature in order to get a better understanding of the interactions solute-solvent on the paraffin crystallization mechanism.

Applications of Calorimetry in a Wide Context –

258 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 3.** Determination of wax solubility curve of the system 6 wt.% of C36 in *n*-decane: a) accumulated

The paraffin crystallization process can be influenced by many factors such as paraffin composition, solvent nature, polidispersity, rate of cooling, pressure, kinetics and presence of impurities [1,9, 14, 28, 30, 35-36], so that a better knowledge of factors affecting wax solubility will also improve the understanding of the wax precipitation phenomena in the petroleum industry described above. The studies about the effect of solvent on solubility of waxes reported in literature [1] have shown that waxes do not exhibit ideal solution behavior when crystallizing and that their solubility in a solvent increases as both the solvent molecular size and solvent solubility parameter decrease. The influence of the shape and size of the solvent on solute–solvent interaction and on the n-alkanes solubility has been also described in literature, hence it has been reported that globular or spherical solvents destroy the conformational order in liquid long-chain hydrocarbons [28, 37]. Aromatic

heat released for the DSC exothermic peak and b) wax solubility curve obtained [28].

**3. Experimental study of the influence of solvent on paraffin** 

**crystallization** 

Figure 4 shows the DSC thermograms of the crystallization and melting behavior of 6 wt. % of hexatriacontane (C36) in different pure and mixed solvents systems. As can be seen, a single and well defined peak is observed during cooling and heating processes, related to the crystallization and melting of the monodisperse sample of the heavy paraffin C36 in different solvent systems. However, the endothermic peaks seem to be broader than the exothermic, so while the identification of the crystallization onset temperatures was straightforward; the melting onset temperatures were difficult to identify.

**Figure 4.** DSC exothermic and endothermic peaks of 6 wt% of C36 in different simple and mixed solvents systems: a) 94% of n-decane, b) 47% n-decane + 47% 1-phenyldodecane, c) 47% n-decane + 47% xylene and d) 94 % of squalane [28].

260 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Crystallization and melting properties of the model systems investigated are shown in Table 1. The influence of the solvent aromaticity over the solution of C36 in *n*-decane was studied by adding mono-aromatic solvents: xylene and 1-phenyldodecane. The data show clearly the effect of the solvent chemistry on those properties. Lower values of crystallization and melting enthalpies are obtained in presence of aromatic solvents. The magnitude of the enthalpies decrease is related to the aromaticity of the solvent mixture, where greater aromaticity causes a greater diminishing of crystallization and melting enthalpies. Hence, the aromatic single rings interspersed among hexatriacontane molecules hinder their interactions, preventing an efficient ordering during cooling, then the paraffin crystal networks of a solid phase formed in such circumstance result significantly less ordered, as indicated by the lower values of the crystallinity index calculated from DSC data (see Table 2) for the model systems with aromatic solvents.

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 261

A way to explain the depressing effect of aromatic solvents over the enthalpies of crystallization and melting is through the entropy change that suffers the system during liquid - solid phase transition. It can be assumed that magnitude of the entropy change in the crystallization and melting processes for a paraffinic – aromatic mixture is lower than that for a 100% aliphatic system, like the C36 - n-decane system, because of the poor crystal network ordering of the solid phase formed in presence of aromatic solvents, which is reflected in the lower values of their crystallinity index. On another hand, a crystal network with greater disorder introduced by the aromatic molecules of the solvent is weaker, so its melting temperature tends to be lower. The WAT is also lowered due to the presence of aromatic solvents; however, in the case of the 1-phenyldodecane, a less aromatic solvent than xylene and with a greater molecular weight than decane, its aliphatic chain of 12 carbons has a significant "ordering" effect in the paraffinic crystal network that surpasses the effect of its aromatic rings regards to the depressing of the WAT and melting

In contrast, by changing the solvent system from n-decane to squalane (a C24 aliphatic chain with six methyl branches), the WAT is significantly increased to 54.5 °C with a dramatic depression of the enthalpy of crystallization. This behavior is influenced by the size and structure of the solvent, in a similar way to that observed for the 1-phenyldodecane – ndecane solvent system. The methyl branches of the C24 iso-paraffin inhibits the efficient ordering of C36 molecules during crystallization process, forming a less ordered solid phase than that formed in C36-decane system, which is reflected in the low enthalpy of crystallization measured (6.36 J/g), on the other hand, the highest WAT observed is a consequence of the greater size of squalane with respect to decane. In fact, as has been reported, solubility decreases (greater WAT) as the solvent size increases due to the inability of the bigger solvent molecule to effectively contact and solvate the solute [1]. Furthermore, despite the disorder in the crystalline arrangement caused by the six methyl branches of the squalane, the effect of its size (24 carbon length) results in the highest values of both

Table 1 shows also the WDT of C36 in different solvents during melting process. Under ideal conditions, the values of WAT and WDT should be similar; however, as has been reported [22] differences between both values can be attributed to the experimental uncertainty and kinetic effects (e.g. supercooling). Our DSC results showed differences in the range between 0.88-5.38 °C which could be attributed to the heating/cooling rate used of 5 °C/min. The effect of solvent chemistry on WDT of C36 was similar to that observed for the melting

The results presented before showed a significant influence of solvent chemistry on crystallization and melting of C36; however, in order to get a better understanding of the paraffin crystallization process in presence of solvents of different chemical structure at temperatures below WAT, solubility curves were obtained by using the DSC data as can be seen in Figure 5. As expected, the crystallization process of C36 in squalane starts before respect to the other systems, as a consequence of solvent chain length, followed by the other

temperature observed with the xylene.

temperature and enthalpy of melting.

temperature discussed above.

mixtures according to their respective WATs.


a Calculated as the aromaticity factor of aromatic solvent multiplied by its molar fraction in the mixture, where aromaticity factor of the xylene and 1-phenyldodecane are 0.75 and 0.333 respectively.

**Table 1.** Crystallization and melting properties of the system 6 % of C36 in different solvents systems [28]


<sup>a</sup>ΔT = Onset - Endset

b For a cooling rate = 5 °C/min

c For a melting enthalpy of hexatriacontane = 172.9 J/g [39]

**Table 2.** DSC crystallization data of the system 6 % of C36 in different solvent systems [28]

A way to explain the depressing effect of aromatic solvents over the enthalpies of crystallization and melting is through the entropy change that suffers the system during liquid - solid phase transition. It can be assumed that magnitude of the entropy change in the crystallization and melting processes for a paraffinic – aromatic mixture is lower than that for a 100% aliphatic system, like the C36 - n-decane system, because of the poor crystal network ordering of the solid phase formed in presence of aromatic solvents, which is reflected in the lower values of their crystallinity index. On another hand, a crystal network with greater disorder introduced by the aromatic molecules of the solvent is weaker, so its melting temperature tends to be lower. The WAT is also lowered due to the presence of aromatic solvents; however, in the case of the 1-phenyldodecane, a less aromatic solvent than xylene and with a greater molecular weight than decane, its aliphatic chain of 12 carbons has a significant "ordering" effect in the paraffinic crystal network that surpasses the effect of its aromatic rings regards to the depressing of the WAT and melting temperature observed with the xylene.

Applications of Calorimetry in a Wide Context –

2) for the model systems with aromatic solvents.

Solvent System Onset Crystallization

For a melting enthalpy of hexatriacontane = 172.9 J/g [39]

Enthalpy of Crystallization (J/g)

aromaticity factor of the xylene and 1-phenyldodecane are 0.75 and 0.333 respectively.

Temperature (°C)

(°C)

Solvent System WAT

47% n-decane +

47% n-decane + 47% 1 phenyldodecane

47% n-decane + 47%

47% n-decane + 47%

<sup>a</sup>ΔT = Onset - Endset b For a cooling rate = 5 °C/min

c

[28]

260 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Crystallization and melting properties of the model systems investigated are shown in Table 1. The influence of the solvent aromaticity over the solution of C36 in *n*-decane was studied by adding mono-aromatic solvents: xylene and 1-phenyldodecane. The data show clearly the effect of the solvent chemistry on those properties. Lower values of crystallization and melting enthalpies are obtained in presence of aromatic solvents. The magnitude of the enthalpies decrease is related to the aromaticity of the solvent mixture, where greater aromaticity causes a greater diminishing of crystallization and melting enthalpies. Hence, the aromatic single rings interspersed among hexatriacontane molecules hinder their interactions, preventing an efficient ordering during cooling, then the paraffin crystal networks of a solid phase formed in such circumstance result significantly less ordered, as indicated by the lower values of the crystallinity index calculated from DSC data (see Table

> Melting Temperature (°C)

94 % n-decane 43.2 13.54 30.52 12.48 45.6 0

94 % squalane 54.5 6.36 37.1 12.56 52.89 0 a Calculated as the aromaticity factor of aromatic solvent multiplied by its molar fraction in the mixture, where

**Table 1.** Crystallization and melting properties of the system 6 % of C36 in different solvents systems

94 % n-decane 43.2 32.4 10.08 2.16 7.21

1-phenyldodecane 47.5 22.5 25 5 5.83 94 % squalane 54.5 41.08 13.42 2.68 7.26

**Table 2.** DSC crystallization data of the system 6 % of C36 in different solvent systems [28]

xylene 37.5 23.5 14 2.8 5.38

47% xylene 37.5 8.05 11.96 9.31 37.92 0.43

47.5 10.66 20.25 10.09 41.82 0.12

Endset Crystallization Temperature (°C)

Enthalpy of Melting (J/g)

WDT (°C)

ΔTa (°C)

Δt b (min)

DSC Crystallinity c (%)

Solvent system aromaticity a

In contrast, by changing the solvent system from n-decane to squalane (a C24 aliphatic chain with six methyl branches), the WAT is significantly increased to 54.5 °C with a dramatic depression of the enthalpy of crystallization. This behavior is influenced by the size and structure of the solvent, in a similar way to that observed for the 1-phenyldodecane – ndecane solvent system. The methyl branches of the C24 iso-paraffin inhibits the efficient ordering of C36 molecules during crystallization process, forming a less ordered solid phase than that formed in C36-decane system, which is reflected in the low enthalpy of crystallization measured (6.36 J/g), on the other hand, the highest WAT observed is a consequence of the greater size of squalane with respect to decane. In fact, as has been reported, solubility decreases (greater WAT) as the solvent size increases due to the inability of the bigger solvent molecule to effectively contact and solvate the solute [1]. Furthermore, despite the disorder in the crystalline arrangement caused by the six methyl branches of the squalane, the effect of its size (24 carbon length) results in the highest values of both temperature and enthalpy of melting.

Table 1 shows also the WDT of C36 in different solvents during melting process. Under ideal conditions, the values of WAT and WDT should be similar; however, as has been reported [22] differences between both values can be attributed to the experimental uncertainty and kinetic effects (e.g. supercooling). Our DSC results showed differences in the range between 0.88-5.38 °C which could be attributed to the heating/cooling rate used of 5 °C/min. The effect of solvent chemistry on WDT of C36 was similar to that observed for the melting temperature discussed above.

The results presented before showed a significant influence of solvent chemistry on crystallization and melting of C36; however, in order to get a better understanding of the paraffin crystallization process in presence of solvents of different chemical structure at temperatures below WAT, solubility curves were obtained by using the DSC data as can be seen in Figure 5. As expected, the crystallization process of C36 in squalane starts before respect to the other systems, as a consequence of solvent chain length, followed by the other mixtures according to their respective WATs.

262 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 263

Asphaltene sample

*AsphIri AsphPC* 

heteroaromatic and napthenic ring plus relatively short paraffinic branches [8]. Some authors have proposed that asphaltenes form aggregates with a core formed by aromatic regions, and aliphatic chains on the periphery interacting with the surrounding oil [40-41]. The aliphatic portions of the asphaltene permit an interaction of asphaltenes with waxes. A handful of studies have evaluated the asphaltene-wax interactions and their effect on wax crystallization and gelation properties [28-30, 42-45]. The study of the influence of the asphaltenes and their chemical nature on the wax crystallization phenomena of paraffinic model systems; is presented in this section. DSC measurements allowed getting crystallization properties of paraffinic model systems in presence of asphaltenes of different

The effect of asphaltenes was studied on liquid-solid equilibrium of the binary system: tetracosane (C24H50) - octacosane (C28H58). The composition used in these model systems was 15 and 10 wt% of C24 and C28 respectively in the following solvent systems: a) 75% of decane, b) mixture of 37.5 % of decane + 37.5 % of xylene and c) mixture of 37.5 % of decane + 37.0 % of xylene + 0.5 % of asphaltenes. The asphaltene samples used in this study, labeled as AsphPC and AsphIri, were extracted from two Mexican crude oils of the southern region. These asphaltenes of different chemical nature were characterized by using elemental analysis, vapor pressure osmometry, 1H and 13C NMR spectroscopy in order to get their molecular parameters. Details of the experimental techniques used for the characterization of these asphaltenes and their effect on phase-equilibrium and rheological properties of waxy model systems have been reported recently in literature [28, 30]. Some of the molecular parameters of these asphaltenes are shown in Table 3. As can be seen, the AsphPC asphaltenes are more aromatic than AsphIri asphaltenes, and its aromatic core is also bigger and more condensed, whereas the aromatic core of AsphIri asphaltenes is richer in alkyl substituents comprising methyl groups, alkyl chains and naphthenic rings [30]. DSC exothermic peaks of the model systems are plotted in Figure 6 and their crystallization

RA Aromatic rings 7.09 20.69 *f*<sup>a</sup> Aromaticity factor 0.50 0.67 Condensation index 0.53 0.71

Aromatic substitution index 0.55 0.37

*n*ac Average length of the alkyl chains 11.84 11.12

substituents 5.99 5.47

origin with different molecular structure.

properties are shown in Table 4.

Symbol Definition

*<sup>n</sup>*Average number of carbon atoms per alkyl

**Table 3.** Molecular parameters of AsphPC and AsphIri asphaltenes [30]

**Figure 5.** DSC Solubility curves of 6 wt % of C36 in different simple and mixed solvents systems [28].

The chemical structure of the solvent affects significantly the crystallization rate of the Hexatriacontane C36. Table 2 shows that the crystallization process is slower for the systems with aromatic solvents. An evident consequence of this is the fact that lower amounts of solids are formed in these systems with respect to the decane system below its WAT as can be observed in Figure 5; this can be attributed to the aromatic ring interfering with the normal crystal growth, retarding the conformational ordering of C36 molecules in the solid phase created.

The degree of crystallinity obtained by DSC for the solid phase formed in presence of squalane, shown in Table 2, points out the effect of competition between the size and branching of the aliphatic solvents in the crystallinity of the solid phases formed. Due to the greater size of squalane with regard to the *n*-decane, it would be expected a greater crystallinity index for the solid phase formed in presence of squalane; however its ramifications limit the possibility of achieving an efficient conformational ordering of the crystal network in the solid phase, which results in a crystallinity index value similar to that obtained for the *n*-decane system.

The results presented in this section showed that the solvent aromaticity was a key factor that results in inhibition of the paraffin crystallization process, decreasing WAT, by promoting the creation of a solid phase partially disordered due to the presence of aromatic single rings interspersed among paraffin molecules hindering their efficient ordering during the cooling process.

### **4. DSC study of the effect of asphaltenes on liquid-solid phase equilibria**

Asphaltenes are the most heavy and polar fraction in the crude oil. The asphaltene fraction is formed by many series of relatively large molecules containing aromatic rings, several heteroaromatic and napthenic ring plus relatively short paraffinic branches [8]. Some authors have proposed that asphaltenes form aggregates with a core formed by aromatic regions, and aliphatic chains on the periphery interacting with the surrounding oil [40-41]. The aliphatic portions of the asphaltene permit an interaction of asphaltenes with waxes. A handful of studies have evaluated the asphaltene-wax interactions and their effect on wax crystallization and gelation properties [28-30, 42-45]. The study of the influence of the asphaltenes and their chemical nature on the wax crystallization phenomena of paraffinic model systems; is presented in this section. DSC measurements allowed getting crystallization properties of paraffinic model systems in presence of asphaltenes of different origin with different molecular structure.

Applications of Calorimetry in a Wide Context –

phase created.

0

1

2

3

Wt % solid

4

5

6

7

obtained for the *n*-decane system.

the cooling process.

262 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 5.** DSC Solubility curves of 6 wt % of C36 in different simple and mixed solvents systems [28].

The chemical structure of the solvent affects significantly the crystallization rate of the Hexatriacontane C36. Table 2 shows that the crystallization process is slower for the systems with aromatic solvents. An evident consequence of this is the fact that lower amounts of solids are formed in these systems with respect to the decane system below its WAT as can be observed in Figure 5; this can be attributed to the aromatic ring interfering with the normal crystal growth, retarding the conformational ordering of C36 molecules in the solid

20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60

Temperature (°c)

Decane (Reference) Decane-Xylene Decane-1-Phenyl dodecane

Squalane

The degree of crystallinity obtained by DSC for the solid phase formed in presence of squalane, shown in Table 2, points out the effect of competition between the size and branching of the aliphatic solvents in the crystallinity of the solid phases formed. Due to the greater size of squalane with regard to the *n*-decane, it would be expected a greater crystallinity index for the solid phase formed in presence of squalane; however its ramifications limit the possibility of achieving an efficient conformational ordering of the crystal network in the solid phase, which results in a crystallinity index value similar to that

The results presented in this section showed that the solvent aromaticity was a key factor that results in inhibition of the paraffin crystallization process, decreasing WAT, by promoting the creation of a solid phase partially disordered due to the presence of aromatic single rings interspersed among paraffin molecules hindering their efficient ordering during

**4. DSC study of the effect of asphaltenes on liquid-solid phase equilibria** 

Asphaltenes are the most heavy and polar fraction in the crude oil. The asphaltene fraction is formed by many series of relatively large molecules containing aromatic rings, several The effect of asphaltenes was studied on liquid-solid equilibrium of the binary system: tetracosane (C24H50) - octacosane (C28H58). The composition used in these model systems was 15 and 10 wt% of C24 and C28 respectively in the following solvent systems: a) 75% of decane, b) mixture of 37.5 % of decane + 37.5 % of xylene and c) mixture of 37.5 % of decane + 37.0 % of xylene + 0.5 % of asphaltenes. The asphaltene samples used in this study, labeled as AsphPC and AsphIri, were extracted from two Mexican crude oils of the southern region. These asphaltenes of different chemical nature were characterized by using elemental analysis, vapor pressure osmometry, 1H and 13C NMR spectroscopy in order to get their molecular parameters. Details of the experimental techniques used for the characterization of these asphaltenes and their effect on phase-equilibrium and rheological properties of waxy model systems have been reported recently in literature [28, 30]. Some of the molecular parameters of these asphaltenes are shown in Table 3. As can be seen, the AsphPC asphaltenes are more aromatic than AsphIri asphaltenes, and its aromatic core is also bigger and more condensed, whereas the aromatic core of AsphIri asphaltenes is richer in alkyl substituents comprising methyl groups, alkyl chains and naphthenic rings [30]. DSC exothermic peaks of the model systems are plotted in Figure 6 and their crystallization properties are shown in Table 4.



264 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 265

without asphaltenes. For another hand, the crystallization heat increases significantly in presence of AsphIri asphaltenes, whereas diminishes moderately in presence of AsphPC asphaltenes. These results make evident the effect of the chemical nature of different asphaltenes over the crystallization behavior of paraffinic systems. A greater abundance of aliphatic chains in AsphIri asphaltenes permits a better interaction with the paraffins of the C24-C28 system promoting co-crystallization phenomena, where the asphaltenes are partially integrated to the crystal network and probably acting as nucleation sites, causing a slight increasing of WAT. Moreover, the partial immobilization of the paraffins engaged in the interactions with the asphaltene alkyl chains may promote a "*quasicrystallization*" phenomenon of the paraffins in the asphaltene network, such interaction results in exothermic effects as has been reported in literature [46, 47], which explains the significant increasing of crystallization heat of the model system with AsphIri asphaltenes as observed in Table 4. On the other hand, the most aromatic asphaltenes (AsphPC) with a bigger and more condensed aromatic core and with a smaller amount of aliphatic substituents inhibit in some extent the paraffin-asphaltene interactions so that they cannot be incorporated to the paraffin crystal structure hindering nucleation process and crystal network growth, which results in a WAT decreasing with a lower crystallization enthalpy due to the formation of a

The wax solubility curves of these systems are plotted in Figure 7, as can be seen the effect of solvent and asphaltenes of different chemical nature is evident. Regarding to the C24 - C28 mixture in *n*-decane, the presence of xylene reduces moderately both the amount of solid formed and the WAT, although the temperature interval of their solubility curves are very similar. However, the effect of asphaltenes on wax solubility curve is very significant considering its low concentration in the model system (0.5%), particularly in the case of the more aromatic AsphPC asphaltene. As in the case of C36 in different solvents, the rate of wax precipitation for the C24-C28 mixture in xylene is significantly affected by the presence of a small amount of highly aromatic compounds such as the asphaltenes. The data in Table 4 shows also that the presence of asphaltenes in the paraffinic system increases around 25% the time required to precipitate the total of paraffins (Δt) for a cooling rate of 5°C/ min.

These results showed that asphaltenes are practically acting in this system as inhibitors of the paraffins precipitation. When the asphaltenes have a structure highly condensed with a certain degree of aromatic substitution, that allows some kind of interaction with the paraffins, the inhibition effect is greater due the steric interference and the disorder generated in the paraffinic network which difficult the molecular recognition among paraffin molecules avoiding the growth of stable crystalline networks and therefore the formation of the solid phase. Otherwise a less condensed aromatic structure with a greater substitution degree have a better interaction with paraffins and thus, it could play a role as nucleation site increasing both WAT and the amount of solid phase formed, at least in a certain temperature range as can be observed in Figure 7, but even in such case the disruptive effect that introduces the aromatic core of the asphaltenes prevails inhibiting the crystallization process, as it was observed for the model system with the AsphIri

asphaltenes. These phenomena are sketched in Figure 8.

disordered solid phase.

**Figure 6.** DSC exothermic peaks of the binary system C24-C28 in different solvent systems and with asphaltenes of different chemical nature [28].


<sup>a</sup>ΔT = WAT - Endset; b For a cooling rate = 5 °C / min

**Table 4.** DSC crystallization data of the binary system C24-C28 in different solvent systems and with asphaltenes [28]

As can be observed, the presence of an aromatic solvent as the xylene decreases slightly both WAT and crystallization enthalpy due to the disorder-effects generated by the aromaticity as was discussed before. However, crystallization properties were notably affected by the presence of asphaltenes where their chemical nature played an important role. It has been reported that flocculated asphaltenes providing nucleation sites for waxes increase WAT [44], but also it has been reported [30] that asphaltenes decreased very slightly the WAT. According with other studies [45] the effect of the asphaltenes on the WAT depends of the aggregation state of the asphaltenes.

In these model systems, the results obtained showed a slight increasing of WAT due to presence of the aliphatic asphaltenes (AsphIri) and a decreasing in presence of the more aromatic asphaltenes (AsphPC) with respect to the C24-C28 in decane-xylene model system without asphaltenes. For another hand, the crystallization heat increases significantly in presence of AsphIri asphaltenes, whereas diminishes moderately in presence of AsphPC asphaltenes. These results make evident the effect of the chemical nature of different asphaltenes over the crystallization behavior of paraffinic systems. A greater abundance of aliphatic chains in AsphIri asphaltenes permits a better interaction with the paraffins of the C24-C28 system promoting co-crystallization phenomena, where the asphaltenes are partially integrated to the crystal network and probably acting as nucleation sites, causing a slight increasing of WAT. Moreover, the partial immobilization of the paraffins engaged in the interactions with the asphaltene alkyl chains may promote a "*quasicrystallization*" phenomenon of the paraffins in the asphaltene network, such interaction results in exothermic effects as has been reported in literature [46, 47], which explains the significant increasing of crystallization heat of the model system with AsphIri asphaltenes as observed in Table 4. On the other hand, the most aromatic asphaltenes (AsphPC) with a bigger and more condensed aromatic core and with a smaller amount of aliphatic substituents inhibit in some extent the paraffin-asphaltene interactions so that they cannot be incorporated to the paraffin crystal structure hindering nucleation process and crystal network growth, which results in a WAT decreasing with a lower crystallization enthalpy due to the formation of a disordered solid phase.

Applications of Calorimetry in a Wide Context –

asphaltenes of different chemical nature [28].

0

0.2

0.4

0.6

Normalized exothermic heat ( J / g. s)

0.8

1

1.2

Solvent System WAT

<sup>a</sup>ΔT = WAT - Endset; b For a cooling rate = 5 °C / min

aggregation state of the asphaltenes.

asphaltenes [28]

264 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 6.** DSC exothermic peaks of the binary system C24-C28 in different solvent systems and with

30 25 20 15 10 5 0

Temperature (°C)

**Table 4.** DSC crystallization data of the binary system C24-C28 in different solvent systems and with

As can be observed, the presence of an aromatic solvent as the xylene decreases slightly both WAT and crystallization enthalpy due to the disorder-effects generated by the aromaticity as was discussed before. However, crystallization properties were notably affected by the presence of asphaltenes where their chemical nature played an important role. It has been reported that flocculated asphaltenes providing nucleation sites for waxes increase WAT [44], but also it has been reported [30] that asphaltenes decreased very slightly the WAT. According with other studies [45] the effect of the asphaltenes on the WAT depends of the

In these model systems, the results obtained showed a slight increasing of WAT due to presence of the aliphatic asphaltenes (AsphIri) and a decreasing in presence of the more aromatic asphaltenes (AsphPC) with respect to the C24-C28 in decane-xylene model system

(°C) Enthalpy of Crystallization (J/g) Endset

Decane

Decane-Xylene

Decane-Xylene + AsphIri Decane-Xylene + AsphPC

Decane 26.5 37.09 7 19.5 3.9 Decane-Xylene 24.81 36.51 6.09 18.72 3.74 Decane-Xylene + AsphIri 25.66 58.42 1 24.66 4.93 Decane-Xylene + AsphPC 21.77 33.01 0.53 21.24 4.24

(°C)

ΔTa (°C)

Δtb (min) The wax solubility curves of these systems are plotted in Figure 7, as can be seen the effect of solvent and asphaltenes of different chemical nature is evident. Regarding to the C24 - C28 mixture in *n*-decane, the presence of xylene reduces moderately both the amount of solid formed and the WAT, although the temperature interval of their solubility curves are very similar. However, the effect of asphaltenes on wax solubility curve is very significant considering its low concentration in the model system (0.5%), particularly in the case of the more aromatic AsphPC asphaltene. As in the case of C36 in different solvents, the rate of wax precipitation for the C24-C28 mixture in xylene is significantly affected by the presence of a small amount of highly aromatic compounds such as the asphaltenes. The data in Table 4 shows also that the presence of asphaltenes in the paraffinic system increases around 25% the time required to precipitate the total of paraffins (Δt) for a cooling rate of 5°C/ min.

These results showed that asphaltenes are practically acting in this system as inhibitors of the paraffins precipitation. When the asphaltenes have a structure highly condensed with a certain degree of aromatic substitution, that allows some kind of interaction with the paraffins, the inhibition effect is greater due the steric interference and the disorder generated in the paraffinic network which difficult the molecular recognition among paraffin molecules avoiding the growth of stable crystalline networks and therefore the formation of the solid phase. Otherwise a less condensed aromatic structure with a greater substitution degree have a better interaction with paraffins and thus, it could play a role as nucleation site increasing both WAT and the amount of solid phase formed, at least in a certain temperature range as can be observed in Figure 7, but even in such case the disruptive effect that introduces the aromatic core of the asphaltenes prevails inhibiting the crystallization process, as it was observed for the model system with the AsphIri asphaltenes. These phenomena are sketched in Figure 8.

266 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 267

**5. Wax precipitation study in crude oils by DSC measurements** 

melting point was recorded as their endothermic peak temperature.

in precipitation of solid particles of wax.

not well defined, with an onset around 20.8°C.

In Figure 9 are shown the DSC thermograms of crude oils during cooling process. As it has been reported [22], during cooling, a decrease of the solvating power of the oil matrix results

The thermograms of crude oils RDO1 and RDO2 show one well defined exothermal peak from which the WAT can be easily determined 19.2 and 18.5°C respectively. In contrast the thermogram of crude oil J32 presents two exothermal peaks, first one well defined, a liquidsolid phase transition whose onset corresponding to a WAT of 28°C and a second one broad

Other methods were employed to determine the WAT of the crude oil samples, these experimental techniques were fourier transform infrared spectroscopy (FT-IR), rheometry and densitometry. Figure 10 shows the WAT determination by these methods described briefly below. FT-IR method is based on the fact that the absorbance between the wave numbers 735 and 715 cm-1 attributed to the rocking vibrations of the long chain methylene (LCM) groups (the major component of the solid wax formed in crude oils), has been found

With the ongoing trend in deep water developments, flow assurance has become a major technical and economic issue. The avoidance or remediation of wax deposition is one key aspect of flow assurance [3-4, 6-7]. In order to develop solutions to the wax deposition problem is necessary to get a deep understanding of the crystallization phenomena in which the crude oil composition, particularly the content of high molecular weight paraffins and asphaltenes have a significant impact [29]. Comparison of experimental methods for measurement of wax precipitation in crude oils have been reported in literature [5, 21, 24-27, 29], where wax detection limits vary depending on the measurement technique, oil composition, thermal history, time of measurement and fluid properties related to crystal nucleation and growth [27]. In this section is presented a characterization of the wax precipitation phenomena in crude oils by using DSC measurements. Wax appearance temperature is measured by using DSC and these results are compared with those obtained by using other techniques such as rheometry, spectroscopy and densitometry in order to show advantages and disadvantages of the use of DSC method to measure liquid-solid phase equilibria of waxes in crude oils. The importance to get the wax melting temperature and crystallinity degree by DSC is analyzed also as key parameters to evaluate the propensity of crude oils to present wax precipitation problems during crude oil production and transporting. Three Mexican crude oils of the southern region labeled as RDO1, RDO2 and J32 are studied in this work. Crude oils RDO1 and RDO2 present wax precipitation and deposition problems during their production and transportation, whereas crude oil J32 presents a severe asphaltene precipitation and deposition problem along the well during primary production. The cloud point temperatures of the crude oils and the crystallization and melting properties of their isolated waxes were determined by using the DSC method according to the procedures and conditions described and presented in section II of this chapter. However, in these experiments for waxes, under heating conditions, the wax

**Figure 7.** Wax solubility curves of the binary system C24-C28 in different solvent systems and with asphaltenes of different chemical nature [28].

**Figure 8.** Schematic representation of the "Steric effect" of asphaltenes of different chemical nature on paraffin crystallization.

### **5. Wax precipitation study in crude oils by DSC measurements**

Applications of Calorimetry in a Wide Context –

asphaltenes of different chemical nature [28].

0

5

10

15

Wt % Solid

20

25

30

paraffin crystallization.

266 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 7.** Wax solubility curves of the binary system C24-C28 in different solvent systems and with

0 5 10 15 20 25 30

Decane Decane-Xylene Decane-Xylene + AsfIri Decane-Xylene + AsfPC

Temperature (°C)

**Figure 8.** Schematic representation of the "Steric effect" of asphaltenes of different chemical nature on

With the ongoing trend in deep water developments, flow assurance has become a major technical and economic issue. The avoidance or remediation of wax deposition is one key aspect of flow assurance [3-4, 6-7]. In order to develop solutions to the wax deposition problem is necessary to get a deep understanding of the crystallization phenomena in which the crude oil composition, particularly the content of high molecular weight paraffins and asphaltenes have a significant impact [29]. Comparison of experimental methods for measurement of wax precipitation in crude oils have been reported in literature [5, 21, 24-27, 29], where wax detection limits vary depending on the measurement technique, oil composition, thermal history, time of measurement and fluid properties related to crystal nucleation and growth [27]. In this section is presented a characterization of the wax precipitation phenomena in crude oils by using DSC measurements. Wax appearance temperature is measured by using DSC and these results are compared with those obtained by using other techniques such as rheometry, spectroscopy and densitometry in order to show advantages and disadvantages of the use of DSC method to measure liquid-solid phase equilibria of waxes in crude oils. The importance to get the wax melting temperature and crystallinity degree by DSC is analyzed also as key parameters to evaluate the propensity of crude oils to present wax precipitation problems during crude oil production and transporting. Three Mexican crude oils of the southern region labeled as RDO1, RDO2 and J32 are studied in this work. Crude oils RDO1 and RDO2 present wax precipitation and deposition problems during their production and transportation, whereas crude oil J32 presents a severe asphaltene precipitation and deposition problem along the well during primary production. The cloud point temperatures of the crude oils and the crystallization and melting properties of their isolated waxes were determined by using the DSC method according to the procedures and conditions described and presented in section II of this chapter. However, in these experiments for waxes, under heating conditions, the wax melting point was recorded as their endothermic peak temperature.

In Figure 9 are shown the DSC thermograms of crude oils during cooling process. As it has been reported [22], during cooling, a decrease of the solvating power of the oil matrix results in precipitation of solid particles of wax.

The thermograms of crude oils RDO1 and RDO2 show one well defined exothermal peak from which the WAT can be easily determined 19.2 and 18.5°C respectively. In contrast the thermogram of crude oil J32 presents two exothermal peaks, first one well defined, a liquidsolid phase transition whose onset corresponding to a WAT of 28°C and a second one broad not well defined, with an onset around 20.8°C.

Other methods were employed to determine the WAT of the crude oil samples, these experimental techniques were fourier transform infrared spectroscopy (FT-IR), rheometry and densitometry. Figure 10 shows the WAT determination by these methods described briefly below. FT-IR method is based on the fact that the absorbance between the wave numbers 735 and 715 cm-1 attributed to the rocking vibrations of the long chain methylene (LCM) groups (the major component of the solid wax formed in crude oils), has been found

268 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

to increase with a decrease in temperature due to the formation of a solid phase [48]. Below the WAT, the higher absorptive of the solid phase made up of LCM grups, contributes strongly to the total absorbance, which gives rise a change in the slope of the plot of the area of the absorbance peak (735 to 715 cm-1) of each FT-IR spectrum as a function of the temperature. The temperature where the change in slope occurs is recorded as the WAT as observed in Figure 10 a). Rheometric WAT measurements were carried on the basis that petroleum fluids exhibit non-Newtonian behavior below WAT and Newtonian behavior above the WAT which follows the Arrhenius temperature dependence:

$$
\mu = \mathcal{A} \ e^{\to x/RT} \tag{2}
$$

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 269

**Figure 10.** WAT determination by using different experimental methods: a) FT-IR WAT determination for crude oil RDO1, b) Rheometric WAT measurement for crude oil RDO2 from Arrhenius plot and c)

Density-Temperature profile for crude oil RDO1 [29].

where µ is the Newtonian dynamic viscosity, *A* is the Arrhenius pre-exponential factor, *Ea* is the activation energy of viscous flow, *R* is the universal gas constant and *T* is the absolute temperature. The formation and growing of solid wax crystals dispersed in the crude oil medium causes a viscosity increasing during a cooling process [35]. In this way, from viscosity-temperature curves, WAT is recorded as the temperature of the deviation of the Arrhenius law as it is shown in Figure 10 b). Finally, the WAT determination by using densitometry method is carried out by identifying the temperature at which a sharp change in the slope of density – temperature curve obtained during a cooling process that become evident the onset of wax crystallization as can be observed in Figure 10 c).

**Figure 9.** Exothermic peaks from DSC Thermograms of crude oils during cooling [29].

268 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

above the WAT which follows the Arrhenius temperature dependence:

evident the onset of wax crystallization as can be observed in Figure 10 c).

Crude oil RDO1

Crude oil RDO2

Crude oil J32

EXO

Heat Flow (mW)

**Figure 9.** Exothermic peaks from DSC Thermograms of crude oils during cooling [29].

to increase with a decrease in temperature due to the formation of a solid phase [48]. Below the WAT, the higher absorptive of the solid phase made up of LCM grups, contributes strongly to the total absorbance, which gives rise a change in the slope of the plot of the area of the absorbance peak (735 to 715 cm-1) of each FT-IR spectrum as a function of the temperature. The temperature where the change in slope occurs is recorded as the WAT as observed in Figure 10 a). Rheometric WAT measurements were carried on the basis that petroleum fluids exhibit non-Newtonian behavior below WAT and Newtonian behavior

 *µ = A e Ea / RT* (2)

where µ is the Newtonian dynamic viscosity, *A* is the Arrhenius pre-exponential factor, *Ea* is the activation energy of viscous flow, *R* is the universal gas constant and *T* is the absolute temperature. The formation and growing of solid wax crystals dispersed in the crude oil medium causes a viscosity increasing during a cooling process [35]. In this way, from viscosity-temperature curves, WAT is recorded as the temperature of the deviation of the Arrhenius law as it is shown in Figure 10 b). Finally, the WAT determination by using densitometry method is carried out by identifying the temperature at which a sharp change in the slope of density – temperature curve obtained during a cooling process that become

Título del eje

4 6 8 10 12 14 16 18 20 22 24 26 28 30 Temperature (ºC)

WAT

WAT

WAT Solid-solid phase transition

Cooling

**Figure 10.** WAT determination by using different experimental methods: a) FT-IR WAT determination for crude oil RDO1, b) Rheometric WAT measurement for crude oil RDO2 from Arrhenius plot and c) Density-Temperature profile for crude oil RDO1 [29].

Table 5 shows the WAT measurements by using the different techniques for the crude oils investigated in this work. According to these results, good agreement is obtained between DSC and FT-IR method in the WAT measurement, whereas Rheometry method apparently overestimated cloud point for crude oils RDO1 and RDO2 and underestimate it in the case of crude oil J32. WAT detection difficulties related with effects of crude oil composition were found when using Densitometry method where the uncertainty associated with the WAT measurement was high.

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 271

WAX RDO 1 WAX RDO 2 WAX J32

**Wax RDO1 RDO2 J32** 

to minimize the propensity of crude oil J32 to present wax precipitation problems during production and transportation, despite of its highest both crystallization temperature whereas crude oils RDO1 y RDO2, whose wax fractions have the highest melting temperatures present wax precipitation and deposition problems in the well head and downstream. A correlation between temperatures and enthalpies of melting was observed in waxes analyzed by DSC, wax RDO1 with highest melting temperature (45.8 °C) has also the highest melting enthalpy (112.89 J/g). This correlation found in this work is in agreement with previous results reported in literature [50]. Finally in Figure 13 is plotted the relationship between wax melting temperature and wax crystallinity, where a good correlation can be observed. In fact and as expected, the lowest degree of crystallinity of wax J32 indicates that its crystal structure is weaker and less stable, with a higher disorder degree, and thus making it easier to melt as pointed out its lower melting temperature.

**Figure 11.** Exo and endothermic peaks from DSC thermograms of waxes [29].

Crystallization Temperature (°C) 50.1 52.3 60.2 Crystallization Enthalpy (J/g) 110.8 107.11 82.29 Melting Temperature (°C) 45.8 43.6 35.9 Enthalpy of melting (J/g) 112.89 110.56 102.13 DSC Crystallinity (%) 70.29 68.84 62.46

100 80 60 40 20 0 -20

Temperature (ºC)

**Property** 

EXO


Heat Flow (Mw)

**Table 6.** Crystallization and melting properties of waxes [29]


\*Not detectable

**Table 5.** WAT measurements of crude oils [29]

The good agreement between DSC and FT-IR methods can be explained in terms of their high sensitivity to the energetic variations related to the phase transition phenomena of paraffins. The Rheometry and Densitometry methods, however, need that a critical amount of solid wax come out of solution to produce a detectable change in the rheological properties or density of the crude oil sample and thus to identify the WAT. On the other hand, the WAT values of the crude oils RDO, measured by the rheometric technique were higher than DSC values ; hence liquid-liquid demixing effects not detected by DSC and FT-IR methods during cooling can have a significant impact on rheological behavior of crude oil samples resulting in an overestimation of WAT by the rheometric technique.

Waxes isolated from crude oils were also analyzed by DSC experiments in order to get their crystallization and melting properties. Figure 11 shows the exothermic and endothermic peaks obtained from DSC thermograms of the crude oil waxes. As can be observed, during cooling and heating, a single and well-resolved peak was obtained for each of the RDO1 and RDO2 waxes, whereas exo and endothermic peaks of Wax J32 were broader and partially well defined between 60 and 6 °C.

The crystallization and melting properties of waxes characterized by DSC are shown in Table 6. It can be seen that wax J32 has the highest crystallization temperature (60.2 °C) followed by wax RDO2 (52.3 °C) and wax RDO1 (50.1 °C). In the case of crystallization enthalpies, the lowest was obtained for wax J32 and the highest for wax RDO1. As expected and due to the crystallizing materials that form the waxy deposits are primarily *n*-alkanes, there is a correlation between wax crystallization temperature and crude oil WAT (see Figure 12).

The wax melting temperature is an important parameter that can be used to define the temperature at which pipe walls or storage facilities may need to be heated in order to remove solid deposits [49]. The lowest melting temperature found in wax J32 (35.9 °C) helps to minimize the propensity of crude oil J32 to present wax precipitation problems during production and transportation, despite of its highest both crystallization temperature whereas crude oils RDO1 y RDO2, whose wax fractions have the highest melting temperatures present wax precipitation and deposition problems in the well head and downstream. A correlation between temperatures and enthalpies of melting was observed in waxes analyzed by DSC, wax RDO1 with highest melting temperature (45.8 °C) has also the highest melting enthalpy (112.89 J/g). This correlation found in this work is in agreement with previous results reported in literature [50]. Finally in Figure 13 is plotted the relationship between wax melting temperature and wax crystallinity, where a good correlation can be observed. In fact and as expected, the lowest degree of crystallinity of wax J32 indicates that its crystal structure is weaker and less stable, with a higher disorder degree, and thus making it easier to melt as pointed out its lower melting temperature.

Applications of Calorimetry in a Wide Context –

WAT measurement was high.

**Table 5.** WAT measurements of crude oils [29]

well defined between 60 and 6 °C.

Crude oil

\*Not detectable

Figure 12).

270 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

WAT (°C)

Table 5 shows the WAT measurements by using the different techniques for the crude oils investigated in this work. According to these results, good agreement is obtained between DSC and FT-IR method in the WAT measurement, whereas Rheometry method apparently overestimated cloud point for crude oils RDO1 and RDO2 and underestimate it in the case of crude oil J32. WAT detection difficulties related with effects of crude oil composition were found when using Densitometry method where the uncertainty associated with the

DSC Rheometry Densitometry FT-IR Average

RDO1 19.2 32.1 27 18.8 24.2 ± 26.5 RDO2 18.5 28.4 21 16.5 21.1 ± 24.6 J32 28 16.3 \*ND 30.7 25 ± 30.6

The good agreement between DSC and FT-IR methods can be explained in terms of their high sensitivity to the energetic variations related to the phase transition phenomena of paraffins. The Rheometry and Densitometry methods, however, need that a critical amount of solid wax come out of solution to produce a detectable change in the rheological properties or density of the crude oil sample and thus to identify the WAT. On the other hand, the WAT values of the crude oils RDO, measured by the rheometric technique were higher than DSC values ; hence liquid-liquid demixing effects not detected by DSC and FT-IR methods during cooling can have a significant impact on rheological behavior of crude

Waxes isolated from crude oils were also analyzed by DSC experiments in order to get their crystallization and melting properties. Figure 11 shows the exothermic and endothermic peaks obtained from DSC thermograms of the crude oil waxes. As can be observed, during cooling and heating, a single and well-resolved peak was obtained for each of the RDO1 and RDO2 waxes, whereas exo and endothermic peaks of Wax J32 were broader and partially

The crystallization and melting properties of waxes characterized by DSC are shown in Table 6. It can be seen that wax J32 has the highest crystallization temperature (60.2 °C) followed by wax RDO2 (52.3 °C) and wax RDO1 (50.1 °C). In the case of crystallization enthalpies, the lowest was obtained for wax J32 and the highest for wax RDO1. As expected and due to the crystallizing materials that form the waxy deposits are primarily *n*-alkanes, there is a correlation between wax crystallization temperature and crude oil WAT (see

The wax melting temperature is an important parameter that can be used to define the temperature at which pipe walls or storage facilities may need to be heated in order to remove solid deposits [49]. The lowest melting temperature found in wax J32 (35.9 °C) helps

oil samples resulting in an overestimation of WAT by the rheometric technique.

(°C)

Deviation (%)

**Figure 11.** Exo and endothermic peaks from DSC thermograms of waxes [29].


**Table 6.** Crystallization and melting properties of waxes [29]

272 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 273

In this chapter we have showed the usefulness of the DSC technique on the characterization of the liquid-solid phase equilibrium of paraffins. It was shown that DSC is an experimental method widely used due to its simplicity, accuracy and fast response to monitor phase transitions. Good capabilities and advantages of the DSC method were shown in order to carry out relevant studies on thermodynamic properties of paraffins. In this chapter it was shown that DSC measurements allowed elucidating the interactions of paraffins with solvents and asphaltenes of different chemical nature during the crystallization and melting phenomena. DSC technique was very useful on the characterization of the wax precipitation phenomena in crude oils due to its high sensitivity and reliability for the identification of phase transitions and crystallinity measurement, which allows evaluating tendency of crude oils to present wax precipitation problems in production and transporting operations. Finally, in order to develop solutions to the wax formation problems presented in some industrial sectors such as petroleum industry is necessary to get a deep understanding of the paraffin crystallization phenomena where the DSC method can give us valuable information

**6. Conclusions** 

as was shown in this chapter.

Luis Alberto Alcazar-Vara and Eduardo Buenrostro-Gonzalez

*Instituto Mexicano del Petróleo, Programa Académico de Posgrado. Eje Central Lázaro Cárdenas,* 

The authors express gratitude to the Instituto Mexicano del Petróleo (IMP) for both providing facilities and granting permission to publish results. L.A.A.V thanks CONACYT and the Programa Académico de Posgrado of IMP for the economic support granted during his Ph.D. studies. The authors thank to Mr. J.A. Garcia-Martinez from IMP for his excellent

[1] Jennings DW, Weispfennig K (2005) Experimental solubility data of various n-alkane waxes: Effects of alkane chain length, alkane odd versus even carbon number structures

[2] Burger ED, Perkins TK, Striegler JH (1981) Studies of Wax Deposition in the Trans.

[3] Rønningsen HP, Bjørndal B, Hansen AB, Pedersen WB (1991) Wax precipitation from North Sea oils. 1. Crystallization and dissolution temperature, and Newtonian and non-

and solvent chemistry on solubility. Fluid Phase Equilibria. 227:27–35.

**Author details** 

**Acknowledgement** 

**7. References** 

assistance on asphaltenes characterization.

Alaska Pipeline. J. Petroleum Tech. 33:1075-86.

Newtonian flow properties. Energy & Fuels. 5:895–908.

*México, D.F.* 

**Figure 12.** Corrrelation between DSC crystallization temperatures of crude oils and their wax fraction

**Figure 13.** Corrrelation between wax melting temperature and crystallinity.

As conclusions of this section is established that from the methods presented here for the WAT determination, DSC technique is recommended for the identification of phase transitions in crude oils due to its high sensitivity and reliability. Crude oils RDO1 and RDO2, whose wax fractions have the highest melting temperatures and crystallinity degree present wax precipitation and deposition problems in the well head and downstream, whereas the crude oil J32 that has the wax fraction with the lowest melting temperature and crystallinity degree do not present wax deposition problems during production. DSC measurements allowed identifying key parameters useful to evaluate the wax precipitation in crude oil samples.

### **6. Conclusions**

Applications of Calorimetry in a Wide Context –

DSC Crystallization temperature

(ºC)

272 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

18.5 °C 19.2 °C

<sup>50</sup>°<sup>C</sup> <sup>52</sup>°<sup>C</sup>

**Figure 13.** Corrrelation between wax melting temperature and crystallinity.

in crude oil samples.

Melting temperature (°C)

**Figure 12.** Corrrelation between DSC crystallization temperatures of crude oils and their wax fraction

RDO 1 RDO 2 J32

Crude oil Wax

28 °C

Wax melting temperature

Wax Crystallinity (%)

60 °C

DSC crystallinity (%)

As conclusions of this section is established that from the methods presented here for the WAT determination, DSC technique is recommended for the identification of phase transitions in crude oils due to its high sensitivity and reliability. Crude oils RDO1 and RDO2, whose wax fractions have the highest melting temperatures and crystallinity degree present wax precipitation and deposition problems in the well head and downstream, whereas the crude oil J32 that has the wax fraction with the lowest melting temperature and crystallinity degree do not present wax deposition problems during production. DSC measurements allowed identifying key parameters useful to evaluate the wax precipitation

RDO1 RDO2 J32

Crude oil wax

In this chapter we have showed the usefulness of the DSC technique on the characterization of the liquid-solid phase equilibrium of paraffins. It was shown that DSC is an experimental method widely used due to its simplicity, accuracy and fast response to monitor phase transitions. Good capabilities and advantages of the DSC method were shown in order to carry out relevant studies on thermodynamic properties of paraffins. In this chapter it was shown that DSC measurements allowed elucidating the interactions of paraffins with solvents and asphaltenes of different chemical nature during the crystallization and melting phenomena. DSC technique was very useful on the characterization of the wax precipitation phenomena in crude oils due to its high sensitivity and reliability for the identification of phase transitions and crystallinity measurement, which allows evaluating tendency of crude oils to present wax precipitation problems in production and transporting operations. Finally, in order to develop solutions to the wax formation problems presented in some industrial sectors such as petroleum industry is necessary to get a deep understanding of the paraffin crystallization phenomena where the DSC method can give us valuable information as was shown in this chapter.

### **Author details**

Luis Alberto Alcazar-Vara and Eduardo Buenrostro-Gonzalez *Instituto Mexicano del Petróleo, Programa Académico de Posgrado. Eje Central Lázaro Cárdenas, México, D.F.* 

### **Acknowledgement**

The authors express gratitude to the Instituto Mexicano del Petróleo (IMP) for both providing facilities and granting permission to publish results. L.A.A.V thanks CONACYT and the Programa Académico de Posgrado of IMP for the economic support granted during his Ph.D. studies. The authors thank to Mr. J.A. Garcia-Martinez from IMP for his excellent assistance on asphaltenes characterization.

### **7. References**


274 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[4] Leontaritis KJ (1995) The Asphaltene and Wax Deposition Envelopes. The Symposium on Thermodynamics of Heavy Oils and Asphaltenes, Area 16C of Fuels and Petrochemical Division, AIChE Spring National Meeting and Petroleum Exposition, Houston, Texas, March 19-23.

Liquid-Solid Phase Equilibria of Paraffinic Systems by DSC Measurements 275

[20] Hammami A, Ratulowski J, Coutinho JAP (2003) Cloud Points: Can We Measure or

[21] Hammami A, Raines MA (1999) Paraffin Deposition from Crude Oils: Comparison of

[22] Hansen AB, Larsen E, Pedersen WB, Nielsen AB (1991) Wax precipitation from North Sea crude oils. 3. Precipitation and dissolution of wax studied by differential scanning

[23] Guo X, Pethica BA, Huang JS, Adamson DH, Prud'homme RK (2006) Effect of Cooling Rate on Crystallization of Model Waxy Oils with Microcrystalline Poly(ethylene

[24] Monger-McClure TG, Tackett JE, Merrill LS (1999) Comparisons of Cloud Point Measurement and Paraffin Prediction Methods .SPE Production & Facilities. 14(1):4–10. [25] Lira-Galeana C, Hammami A (2000) Wax Precipitation from Petroleum Fluids: A Review. in: Asphaltenes and Asphalts 2. Yen TF, Chilingarian G eds. Elsevier Science

[26] Leontaritis KJ, Leontaritis JD (2003) Cloud Point and Wax Deposition Measurement Techniques. SPE Paper No. 80267, SPE International Symposium on Oilfield Chemistry,

[27] Coutinho JAP, Daridon JL (2005) The Limitations of the Cloud Point Measurement Techniques and the Influence of the Oil Composition on its Detection. Petroleum

[28] Alcazar-Vara LA, Buenrostro-Gonzalez E (2012) Experimental Study of the Influence of Solvent and Asphaltenes on Liquid-Solid Phase Behavior of Paraffinic Model Systems by using DSC and FT-IR Techniques. Journal of Thermal Analysis and Calorimetry.

[29] Alcazar-Vara LA, Buenrostro-Gonzalez E (2011) Characterization of the Wax Precipitation in Mexican Crude Oils. Fuel Processing Technology. 92(1): 2366–2374. [30] Alcazar-Vara LA, Garcia-Martinez JA, Buenrostro-Gonzalez E (2012) Effect of Asphaltenes on Equilibrium and Rheological Properties of Waxy Model Systems. Fuel.

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[32] Han S, Huang Z, Senra M, Hoffmann R, Fogler HS (2010) Method to Determine the Wax Solubility Curve in Crude Oil from Centrifugation and High Temperature Gas

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**Chapter 12** 

© 2013 Steinmann et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

and reproduction in any medium, provided the original work is properly cited.

**Thermal Analysis of Phase Transitions** 

**and Crystallization in Polymeric Fibers** 

W. Steinmann, S. Walter, M. Beckers, G. Seide and T. Gries

Each year about 50 Million tons polymer is processed to fibers worldwide [1]. Polymeric fibers are manufactured into all sorts of daily as well as industrial goods [2, 3]. The most prominent materials are thermoplastic among which poly(ethylene terephtalat) (PET), polyamides (PA) and polypropylene (PP) make up the largest fraction [4]. Other thermoplastic polymers such as poly(vinylidene fluoride) (PVDF) belong to niche markets

The most distinctive property of synthetic fiber materials which separates them from other polymeric products is the strong anisotropic material structure. Geometrically this is characterized by a rather high aspect ratio of diameter to length which can reach several magnitudes of order in filament fibers. An exemplary PET textile multi-filament bundle of 300 single filaments in one flat yarn weighs around 100 g per 10.000 meters length (100 dtex). This yields in a single filament diameter of roughly 3 µm. A common industrial bobbin holds up to 25 kg of a virtually endless length of yarn, which in this case would be 2.5 million meters. The predominant cross section is circular in shape. Nonetheless, depending on the fiber application other cross-sections are possible and also common [3,4]. On a structural level the strong anisotropic character of a thermoplastic fiber is mainly caused and influenced by the production process. Hence, the spinning process of thermoplastic fibers shall be explained briefly. Next to the direct spinning process in which the polymer is directly processed to fibers right after the polymerization process, the most common process is the extruder based fiber production. The polymer granules are heated and transferred into a molten state inside the extruder [8]. The melt is then conveyed into a gear pump which ensures a constant flow of mass. This constant polymer flow then is being pressed through filtration layers and finally extruded through capillaries. Following the extrusion the polymer is drawn down vertically and solidifies while cooling from extrusion

Additional information is available at the end of the chapter

with highly specialized applications [5-7].

http://dx.doi.org/10.5772/54063

**1. Introduction** 


## **Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers**

W. Steinmann, S. Walter, M. Beckers, G. Seide and T. Gries

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54063

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

24:2213-2220.

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Fuels. 23(4):2056-2064.

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Mechanical Gelation. Ind. Eng. Chem. Res. 44:7242-7254.

Journal of Chemical Thermodynamics. 37:1276-1287.

Reservoirs. Energy & Fuels. 21(5):2785-2794.

Spectroscopy. Energy & Fuels. 15:756–763.

[49] Flow assurance design guideline (2001) Deepstar IV project.

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[35] Paso K, Senra M, Yi Y, Sastry AM, Fogler HS (2005) Paraffin Polydispersity Facilitates

[36] Vieira LC, Buchuid MB, Lucas EF (2010) Effect of Pressure on the Crystallization of Crude Oil Waxes. II. Evaluation of Crude Oils and Condensate. Energy & Fuels.

[37] Domanska U, Morawski P (2005) Influence of Size and Shape Effects on the High-Pressure Solubility of n-Alkanes: Experimental Data, Correlation and Prediction.

[38] Rakotosaona R, Bouroukba M, Petitjean D, Dirand M (2008) Solubility of a Petroleum Wax with an Aromatic Hydrocarbon in a Solvent. Energy & Fuels. 22:784–789. [39] Dirand M, Bouroukba M, Chevallier V, Petitjean D, Behar E, Ruffier-Meray V (2002) Normal Alkanes, Multialkane Synthetic Model Mixtures, and Real Petroleum Waxes: Crystallographic Structures. Thermodynamic Properties and Crystallization. J. Chem.

[40] Mullins OC, Betancourt SS, Cribbs ME, Dubost FX, Creek JL, Andrews AB, Venkataramanan L (2007) The Colloidal Structure of Crude Oil and the Structure of Oil

[41] Carbognani L, Rogel E (2003) Solid Petroleum Asphaltenes Seem Surrounded by Alkyl

[42] Garcia MD, Carbognani L (2001) Asphaltene-Paraffin Structural Interactions. Effect on

[43] Venkatesan R, Ostlund JA, Chawla H, Wattana P, Nyden M, Fogler HS (2003) The Effect of Asphaltenes on the Gelation of Waxy Oils. Energy & Fuels. 17(6):1630-1640. [44] Kriz P, Andersen SI (2005) Effect of Asphaltenes on Crude Oil Wax Crystallization.

[45] Tinsley JF, Jahnke JP, Dettman HD, Prud'home RK (2009) Waxy Gels with Asphaltenes 1: Characterization of Precipitation, Gelation, Yield Stress, and Morphology. Energy &

[46] Mahmoud R, Gierycz P, Solimando R, Rogalski M (2005) Calorimetric Probing of n-

[47] Stachowiak C, Viguie J-R, Grolier J-P, Rogalski M (2005) Effect of n-Alkanes on

[48] Roehner RM, Hanson FV (2001) Determination of Wax Precipitation Temperature and Amount of Precipitated Solid Wax versus Temperature for Crude Oils using FT-IR

[50] Alghanduri LM, Elgarni MM, Daridon JL, Coutinho JAP (2010) Characterization of

Alkane-Petroleum Asphaltene Interactions. Energy & Fuels. 19:2474 –2479.

Asphaltene Structuring in Petroleum Oils. Langmuir. 21:4824-4829.

Each year about 50 Million tons polymer is processed to fibers worldwide [1]. Polymeric fibers are manufactured into all sorts of daily as well as industrial goods [2, 3]. The most prominent materials are thermoplastic among which poly(ethylene terephtalat) (PET), polyamides (PA) and polypropylene (PP) make up the largest fraction [4]. Other thermoplastic polymers such as poly(vinylidene fluoride) (PVDF) belong to niche markets with highly specialized applications [5-7].

The most distinctive property of synthetic fiber materials which separates them from other polymeric products is the strong anisotropic material structure. Geometrically this is characterized by a rather high aspect ratio of diameter to length which can reach several magnitudes of order in filament fibers. An exemplary PET textile multi-filament bundle of 300 single filaments in one flat yarn weighs around 100 g per 10.000 meters length (100 dtex). This yields in a single filament diameter of roughly 3 µm. A common industrial bobbin holds up to 25 kg of a virtually endless length of yarn, which in this case would be 2.5 million meters. The predominant cross section is circular in shape. Nonetheless, depending on the fiber application other cross-sections are possible and also common [3,4].

On a structural level the strong anisotropic character of a thermoplastic fiber is mainly caused and influenced by the production process. Hence, the spinning process of thermoplastic fibers shall be explained briefly. Next to the direct spinning process in which the polymer is directly processed to fibers right after the polymerization process, the most common process is the extruder based fiber production. The polymer granules are heated and transferred into a molten state inside the extruder [8]. The melt is then conveyed into a gear pump which ensures a constant flow of mass. This constant polymer flow then is being pressed through filtration layers and finally extruded through capillaries. Following the extrusion the polymer is drawn down vertically and solidifies while cooling from extrusion

© 2013 Steinmann et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

temperature down to the ambient air temperature. Usually the fibers are drawn down mechanically by rollers [4,8]. Figure 1 illustrates a classical melt spinning line. The polymer granules are feed through a hopper (A) into an extruder (B). The molten polymer is transported through heated pipes (C) to a gear pump (D). The gear pump feeds the spin pack (E) in which several layers of filtration are placed. The polymer is then extruded through capillaries and exits the spinpack into the quenching zone (F) where a laminar air flow ensures constant cooling conditions. After solidification and before touching the first roller or godet (H) the filaments are usually coated with a spin finish (G).

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 279

This is usually realized by heated rollers, so that the fibers heat up before and after drawing when in contact with the surface of the rollers. Other principles can facilitate chamber ovens, contact heating plates or overheated steam. The process parameters of the drawing state also have a significant influence on the material structure, the orientation state and also the relaxation state. For example do fibers which are drawn and not properly heat-set a high

In both cases the melt drawing as well as the solid state drawing the macromolecules are oriented along the fiber axis (see figure 2). This results in a unique morphology and crystalline structure which can be found only in fibrous materials in this highly oriented state [9,11]. Although there remains some controversy and vivid discussion about the resulting crystalline structure, scientist and researchers agree in the fact that the highly elongated material exhibits deformed crystallites as well as a highly ordered amorphous

For the description of the crystalline structure, most commonly the Stacked-Lamellae and the Shih-Kebab models are quoted [14]. This is usually based on small angle x-ray scattering data, which however do not provide a real image of the structure [15]. A closed theory about the development of the various morphologies is not available. For the thermo-dynamical

Elongated states cannot be discussed within the equilibrium thermodynamics, because of the missing isotropic character of the morphology. Nonetheless, an adoption of the equilibrium theories through consideration of anisotropic influences in analogy to the electro-magnetic field theory is possible [16,17]. In literature [16] within the discussion of entropy elasticity it is described that elongation of a melt through an outside force results in an increase of the free energy of the material. Thus a deformation will result in an increased Gibbs energy ΔGm in spinning and thus will significantly influence the crystallization of the

*G HT S <sup>m</sup>* (1)

degree of shrinkage which is usually unacceptable for most applications [2,4].

**Figure 2.** Model for the morphology in a polymeric fiber in allusion to [14]

description of the crystallization the Gibbs free energy is used [16]:

phase in the non crystalline regions.

polymer [16].

The most important process parameters of the melt spinning process are: the extrusion temperature TExtrusion; the mass flow through each single capillary mThroughput; the density of the melt ρMelt; the cross-sectional area of the capillary ACapillary; the viscosity η of the melt at the local temperature and the draw down speed v. Of course, there are numerous other parameters that affect the process such as the surface quality of the capillary walls, the form of the capillary rim, the ambient air profile consisting of flow direction, speed and temperature and others. For a basic comprehension these are neglected at this point. There is large number of extensive publications on these aspects available such as [9-13].

**Figure 1.** Schematic overview of a conventional melt spinning line

The cooling of the material from melt to ambient temperature takes place under tremendous stretching stress, which is characterized by the ratio between draw down and melt extrusion speed. This is commonly referred to as melt draw ratio (MDR). This melt draw ratio can vary between small one digit figures for rather thick filaments, e.g. fishing line applications, up to values well beyond 100 for fine filaments with diameters in the range of 1 to 50 µm. In most applications the fibers undergo a consecutive stretching or drawing stage after solidification. Thus this is called solid-state-drawing (SSD). Herein the filament is usually run between two rollers whereas the second roller is run at a higher speed than the first one. The speed ratio of the two rollers is referred to as the solid state draw ratio (SSDR) [2,11,12]. Usually, the solid-state-drawing is usually performed under elevated temperature levels. This is usually realized by heated rollers, so that the fibers heat up before and after drawing when in contact with the surface of the rollers. Other principles can facilitate chamber ovens, contact heating plates or overheated steam. The process parameters of the drawing state also have a significant influence on the material structure, the orientation state and also the relaxation state. For example do fibers which are drawn and not properly heat-set a high degree of shrinkage which is usually unacceptable for most applications [2,4].

**Figure 2.** Model for the morphology in a polymeric fiber in allusion to [14]

Applications of Calorimetry in a Wide Context –

278 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

roller or godet (H) the filaments are usually coated with a spin finish (G).

large number of extensive publications on these aspects available such as [9-13].

**Figure 1.** Schematic overview of a conventional melt spinning line

temperature down to the ambient air temperature. Usually the fibers are drawn down mechanically by rollers [4,8]. Figure 1 illustrates a classical melt spinning line. The polymer granules are feed through a hopper (A) into an extruder (B). The molten polymer is transported through heated pipes (C) to a gear pump (D). The gear pump feeds the spin pack (E) in which several layers of filtration are placed. The polymer is then extruded through capillaries and exits the spinpack into the quenching zone (F) where a laminar air flow ensures constant cooling conditions. After solidification and before touching the first

The most important process parameters of the melt spinning process are: the extrusion temperature TExtrusion; the mass flow through each single capillary mThroughput; the density of the melt ρMelt; the cross-sectional area of the capillary ACapillary; the viscosity η of the melt at the local temperature and the draw down speed v. Of course, there are numerous other parameters that affect the process such as the surface quality of the capillary walls, the form of the capillary rim, the ambient air profile consisting of flow direction, speed and temperature and others. For a basic comprehension these are neglected at this point. There is

The cooling of the material from melt to ambient temperature takes place under tremendous stretching stress, which is characterized by the ratio between draw down and melt extrusion speed. This is commonly referred to as melt draw ratio (MDR). This melt draw ratio can vary between small one digit figures for rather thick filaments, e.g. fishing line applications, up to values well beyond 100 for fine filaments with diameters in the range of 1 to 50 µm. In most applications the fibers undergo a consecutive stretching or drawing stage after solidification. Thus this is called solid-state-drawing (SSD). Herein the filament is usually run between two rollers whereas the second roller is run at a higher speed than the first one. The speed ratio of the two rollers is referred to as the solid state draw ratio (SSDR) [2,11,12]. Usually, the solid-state-drawing is usually performed under elevated temperature levels. In both cases the melt drawing as well as the solid state drawing the macromolecules are oriented along the fiber axis (see figure 2). This results in a unique morphology and crystalline structure which can be found only in fibrous materials in this highly oriented state [9,11]. Although there remains some controversy and vivid discussion about the resulting crystalline structure, scientist and researchers agree in the fact that the highly elongated material exhibits deformed crystallites as well as a highly ordered amorphous phase in the non crystalline regions.

For the description of the crystalline structure, most commonly the Stacked-Lamellae and the Shih-Kebab models are quoted [14]. This is usually based on small angle x-ray scattering data, which however do not provide a real image of the structure [15]. A closed theory about the development of the various morphologies is not available. For the thermo-dynamical description of the crystallization the Gibbs free energy is used [16]:

$$
\Delta G\_m = \Delta H - T \cdot \Delta S \tag{1}
$$

Elongated states cannot be discussed within the equilibrium thermodynamics, because of the missing isotropic character of the morphology. Nonetheless, an adoption of the equilibrium theories through consideration of anisotropic influences in analogy to the electro-magnetic field theory is possible [16,17]. In literature [16] within the discussion of entropy elasticity it is described that elongation of a melt through an outside force results in an increase of the free energy of the material. Thus a deformation will result in an increased Gibbs energy ΔGm in spinning and thus will significantly influence the crystallization of the polymer [16].

280 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

For the ideal Gaussian polymer chain this energy contribution corresponds with a reduction of entropy δSΔL in the elongated state [11]:

$$
\Delta G\_{m,\Delta L} = \Delta H - T \cdot (\Delta S - \delta S\_{\Delta L}) \tag{2}
$$

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 281

**Figure 3.** Schematic set up of differential scanning calorimetry

to provide valid and reliable experimental results.

insight can be gained [22].

**3. Sample preparation** 

necessary for sample preparation.

In a special form of differential scanning calorimetry a temperature-modulation is used. Usually one pre-defined frequency is used for temperature modulation [23,24]. The special TOPEM® (Mettler Toledo brand name) technique developed by Mettler Toledo allows the frequency-independent separation of reversing and non-reversing components of the heat flow by analyzing the impulse response of the sample to a pulse of stochastically varied length. Therefore a separation of overlapping effects is possible. Due to this separation extra

The process of sample preparation is of significant importance for the success of experimental investigation of polymeric fibers and has to be handled with great care. Additionally, different aspects of preparation have to be considered simultaneously in order

Before beginning with the experimental procedure itself, several aspects have to be dealt with. In general, both granules and fibers are treated in the same manner: The samples have to be reduced to small pieces so that they fit into the crucibles. In this context it is inevitably necessary to consider that the preparation method directly influences the results which are provided by differential scanning calorimetry. Therefore optimum conditions and parameters have to be found in order to determine certain effects (such as glass transition, crystallization or melting). Otherwise these effects still would be observable but not as good as if the optimum conditions were adjusted. Figure 4 conveys an idea which steps are

The sample has to be reduced to small pieces in order to perform the experiments. Therefore it is possible to alter the form and size of these pieces which yields different results. For example, the reduction to smaller pieces results in different observations concerning the gained thermogram. Usage of a sample with reduced size leads to a decrease of the peak and a lowered melting point. Therefore one can conclude that the mechanical aspect of preparation cannot be neglected and has to be treated carefully. Figures 5 a) and b) deliver an impression which mechanical appearance of the sample has to be chosen in the best case.

This change in entropy causes an increase of the crystallization temperature as well as an enhancement of crystallization rates. For polymorphic materials simple extensions of this theory are given in [18,19]. The different morphological phases are described through varying energy levels which depend on temperature and state of elongation and strain [19,20]. Depending on the process parameters and the material properties these phenomena are more or less prominent and detectable. Since the degree of crystallinity, the degree of orientation within the molecular structure and tendency of a material to crystallize when stored at temperatures above the glass transition temperature, thermal analysis is one key analytical method to investigate fiber materials, processes and fiber product properties.

### **2. Experimental method**

The following text deals with the experimental investigation of polymeric materials. In this context the method of differential scanning calorimetry (DSC) is described and it will be pointed out what the general procedure is like and which experimental parameters have to be considered.

Differential scanning calorimetry follows the principle of the measurement of heat flow differences. By performing DSC a sample whose temperature is increased gradually and then subsequently cooled down is investigated and finally compared to a reference probe. Therefore it is possible to determine enthalpies and melting points of an arbitrary polymeric fiber. In this context a variation of the involved parameters offers a possibility to draw conclusions about underlying properties such as equilibrium values but concerning the execution of the experiment all of the possibly modifiable parameters have to be regarded carefully to perform DSC correctly. In order to perform DSC a furnace which can be heated up and cooled down homogenously is required. Inside this oven there are two mountings for the samples and each mounting is equipped with a high-sensitive temperature sensor [21,23,24]. The general set up is depicted in figure 3.

One mounting (left mounting in figure 3) is for the crucible which contains the prepared sample. The lid of the crucible has at least one hole to allow an exchange with the surrounding atmosphere. Furthermore, pressure build-up in the crucibles is prevented if parts of the sample vaporize.The other mounting (right mounting in figure 3) is for an empty crucible which functions as a reference. Due to the usage of such a reference only effects caused by the sample itself are observable in the final thermogram. The oven is purged with a gas (sample gas), so that transitions and chemical reactions in different atmospheres can be examined. To avoid oxidation processes a protective gas (e.g. N2 or Ar) can be used to create an atmosphere around the sample during the process of DSC. Otherwise, air or oxygen can be selected. Furthermore, the space around the oven is purged with a protective gas (N2)to avoid ice formation at low temperatures [21-24].

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 281

**Figure 3.** Schematic set up of differential scanning calorimetry

In a special form of differential scanning calorimetry a temperature-modulation is used. Usually one pre-defined frequency is used for temperature modulation [23,24]. The special TOPEM® (Mettler Toledo brand name) technique developed by Mettler Toledo allows the frequency-independent separation of reversing and non-reversing components of the heat flow by analyzing the impulse response of the sample to a pulse of stochastically varied length. Therefore a separation of overlapping effects is possible. Due to this separation extra insight can be gained [22].

### **3. Sample preparation**

Applications of Calorimetry in a Wide Context –

of entropy δSΔL in the elongated state [11]:

**2. Experimental method** 

[21,23,24]. The general set up is depicted in figure 3.

be considered.

280 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

For the ideal Gaussian polymer chain this energy contribution corresponds with a reduction

, ( ) *G HT S S m L <sup>L</sup>*

This change in entropy causes an increase of the crystallization temperature as well as an enhancement of crystallization rates. For polymorphic materials simple extensions of this theory are given in [18,19]. The different morphological phases are described through varying energy levels which depend on temperature and state of elongation and strain [19,20]. Depending on the process parameters and the material properties these phenomena are more or less prominent and detectable. Since the degree of crystallinity, the degree of orientation within the molecular structure and tendency of a material to crystallize when stored at temperatures above the glass transition temperature, thermal analysis is one key analytical method to investigate fiber materials, processes and fiber product properties.

The following text deals with the experimental investigation of polymeric materials. In this context the method of differential scanning calorimetry (DSC) is described and it will be pointed out what the general procedure is like and which experimental parameters have to

Differential scanning calorimetry follows the principle of the measurement of heat flow differences. By performing DSC a sample whose temperature is increased gradually and then subsequently cooled down is investigated and finally compared to a reference probe. Therefore it is possible to determine enthalpies and melting points of an arbitrary polymeric fiber. In this context a variation of the involved parameters offers a possibility to draw conclusions about underlying properties such as equilibrium values but concerning the execution of the experiment all of the possibly modifiable parameters have to be regarded carefully to perform DSC correctly. In order to perform DSC a furnace which can be heated up and cooled down homogenously is required. Inside this oven there are two mountings for the samples and each mounting is equipped with a high-sensitive temperature sensor

One mounting (left mounting in figure 3) is for the crucible which contains the prepared sample. The lid of the crucible has at least one hole to allow an exchange with the surrounding atmosphere. Furthermore, pressure build-up in the crucibles is prevented if parts of the sample vaporize.The other mounting (right mounting in figure 3) is for an empty crucible which functions as a reference. Due to the usage of such a reference only effects caused by the sample itself are observable in the final thermogram. The oven is purged with a gas (sample gas), so that transitions and chemical reactions in different atmospheres can be examined. To avoid oxidation processes a protective gas (e.g. N2 or Ar) can be used to create an atmosphere around the sample during the process of DSC. Otherwise, air or oxygen can be selected. Furthermore, the space around the oven is purged

with a protective gas (N2)to avoid ice formation at low temperatures [21-24].

(2)

The process of sample preparation is of significant importance for the success of experimental investigation of polymeric fibers and has to be handled with great care. Additionally, different aspects of preparation have to be considered simultaneously in order to provide valid and reliable experimental results.

Before beginning with the experimental procedure itself, several aspects have to be dealt with. In general, both granules and fibers are treated in the same manner: The samples have to be reduced to small pieces so that they fit into the crucibles. In this context it is inevitably necessary to consider that the preparation method directly influences the results which are provided by differential scanning calorimetry. Therefore optimum conditions and parameters have to be found in order to determine certain effects (such as glass transition, crystallization or melting). Otherwise these effects still would be observable but not as good as if the optimum conditions were adjusted. Figure 4 conveys an idea which steps are necessary for sample preparation.

The sample has to be reduced to small pieces in order to perform the experiments. Therefore it is possible to alter the form and size of these pieces which yields different results. For example, the reduction to smaller pieces results in different observations concerning the gained thermogram. Usage of a sample with reduced size leads to a decrease of the peak and a lowered melting point. Therefore one can conclude that the mechanical aspect of preparation cannot be neglected and has to be treated carefully. Figures 5 a) and b) deliver an impression which mechanical appearance of the sample has to be chosen in the best case.

282 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 283

explanation for this phenomenon is that stripes offer an increased contact surface whereas knots melt discontinuously. Additionally, this result is independent on the volume of the crucible. In figures 5 c) and d) a similar thermogram is presented but the volume of the crucible is doubled (from 20 µL to 40 µL) and what is apparent here is the fact that again the short fiber chops provide the steadiest graph. Additionally, one can conclude that only the usage of the crucible with 20 µL volume delivers reliable results due to the fact that for the 40 µL crucible the graph inside the thermogram is rather uneven. This effect is caused by the better heat contact in the smaller crucibles, since the lid is pressed to the bottom of the

Concerning the weighted portion another remarkable effect can be observed: The peak height increases whereas the peak width drastically increases (see figure 6). Furthermore the onset temperature also increases logarithmically as a function of the sample mass. Nevertheless this result is rather obvious due to the fact that for the melting process of a sample with increased weight a higher amount of energy is required than for a sample with less weight. Concerning the interpretation of the results an advantage of less sample weight is that the peak sharpness is increased and therefore overlapping effects can be observed easier. In this context it is necessary to keep in mind that it is possible that thermal events that cause only little effects might be missed. These observations are depicted in the following diagram (figure 6), where the double peak during melting of polypropylene gets

**Figure 6.** Normalized thermograms for different sample weight of polypropylene fibers

To illustrate the effects caused by the variation of different parameters, several thermograms are shown in the following paragraph. All these thermograms refer to the investigation of fibers and as an example polypropylene (PP) was used. Firstly, the heating rated is varied as

Analysis of the thermogram presented above conveys that the alteration of the heating rate causes a strong effect on the results delivered by differential scanning calorimetry. With all other parameters remaining constant the peak height and width increases with increasing

crucible during the preparation process.

more separated for lower sample masses.

**4. Influence of experimental parameters** 

it is depicted in figure 7 a).

**Figure 4.** Preparation of fiber samples for DSC:

a) Determination of the empty weight of the crucible


**Figure 5.** Effect of preparation conditions and crucible size

a) Heating process with crucible volume of 20 µl,

b) Cooling process with crucible volume of 20 µl,

c) Heating process with crucible volume of 40 µl,

d) Cooling process with crucible volume of 40 µl.

Obviously, best results will be achieved if the sample is manufactured into short fiber chops (stripes). Especially knots cause irregularities as an unsteady graph in the thermogram. The explanation for this phenomenon is that stripes offer an increased contact surface whereas knots melt discontinuously. Additionally, this result is independent on the volume of the crucible. In figures 5 c) and d) a similar thermogram is presented but the volume of the crucible is doubled (from 20 µL to 40 µL) and what is apparent here is the fact that again the short fiber chops provide the steadiest graph. Additionally, one can conclude that only the usage of the crucible with 20 µL volume delivers reliable results due to the fact that for the 40 µL crucible the graph inside the thermogram is rather uneven. This effect is caused by the better heat contact in the smaller crucibles, since the lid is pressed to the bottom of the crucible during the preparation process.

Concerning the weighted portion another remarkable effect can be observed: The peak height increases whereas the peak width drastically increases (see figure 6). Furthermore the onset temperature also increases logarithmically as a function of the sample mass. Nevertheless this result is rather obvious due to the fact that for the melting process of a sample with increased weight a higher amount of energy is required than for a sample with less weight. Concerning the interpretation of the results an advantage of less sample weight is that the peak sharpness is increased and therefore overlapping effects can be observed easier. In this context it is necessary to keep in mind that it is possible that thermal events that cause only little effects might be missed. These observations are depicted in the following diagram (figure 6), where the double peak during melting of polypropylene gets more separated for lower sample masses.

**Figure 6.** Normalized thermograms for different sample weight of polypropylene fibers

#### **4. Influence of experimental parameters**

Applications of Calorimetry in a Wide Context –

**Figure 4.** Preparation of fiber samples for DSC: a) Determination of the empty weight of the crucible

**Figure 5.** Effect of preparation conditions and crucible size

Obviously, best results will be achieved if the sample is manufactured into short fiber chops (stripes). Especially knots cause irregularities as an unsteady graph in the thermogram. The

a) Heating process with crucible volume of 20 µl, b) Cooling process with crucible volume of 20 µl, c) Heating process with crucible volume of 40 µl, d) Cooling process with crucible volume of 40 µl.

b) Reduction of the fiber to small pieces c) Insertion of the crucible into cavity d) Determination of the total weight.

282 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

To illustrate the effects caused by the variation of different parameters, several thermograms are shown in the following paragraph. All these thermograms refer to the investigation of fibers and as an example polypropylene (PP) was used. Firstly, the heating rated is varied as it is depicted in figure 7 a).

Analysis of the thermogram presented above conveys that the alteration of the heating rate causes a strong effect on the results delivered by differential scanning calorimetry. With all other parameters remaining constant the peak height and width increases with increasing heating rate. Moreover, a double peak is of importance. Phase transitions only occur or can be separated from the melting process if lower heating rates are used. For high heating rates they cannot be observed.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 285

Noticeable is also the double peak when low heating rates were used. During the melting process of fibers it is likely that a phase transition from α- to γ-phase takes place [28]. The obversation of this transition is depending on the choice of the heating rate because it is possible that the material melts directly or the effect is superimposed by others. Due to the fact that a characteristic amount of energy is necessary, it is possible to observe this transition as a peak in the thermogram if the heating rate is chosen correctly. After complete transition to γ-phase the sample will melt completely and another peak is observable in the thermogram. Now the distance between these mentioned peaks is depending on the heating rate and if this rate is adjusted inappropriately both effects are no longer separate from each other. Another possibility is that no phase transition occurs because the temperature is risen

quickly enough to start the melting process directly.

**Figure 8.** Normalized thermograms for different a) heating and b) cooling rates for PP

heating rate of 0 °C/min from the peaks for known heating rates.

rate as it is depicted in figure 9 a).

another remarkable effect can be observed:

necessary to choose a heating rate above 25 °C/min.

In the thermogram (figure 8 b)) the variation of the cooling rate is presented for PP. With increasing cooling rates the crystallization peak and its width increases. As reasonably expected the crystallization procedure is slower for higher cooling rates. The actual crystallization peak is determined by extrapolating a virtual crystallization peak for a

As the previous results were gained from investigations of PP similar experiments were performed for PA6 (BASF Ultramid B24N03 [26]). Beginning with a variation of the heating

Similar to PP the peak width and height is increased for higher heating rates. In this case

With heating rates higher than 25 °C/min a glass transition is starting below 50°C. This indicates that if heating rates below 25 °C/min were chosen this kinetic transition causes a too small effect and is therefore not visible. If the heating rate is then increased further another peak becomes observable. What is visible here is a phase transition from γ- to αphase between 120 °C and 160°C [29]. For the observation of these two effects, it is therefore

**Figure 7.** a) normalized thermograms for different heating rates for polypropylene fibers b) normalized thermograms for different cooling rates of polypropylene granule

Secondly, the variation of the cooling rate is also important as it is depicted in figure 7 b). Beside other observations it is very obvious that the crystallization peak is shifted in positive temperature direction with decreasing cooling rates and the absolute height of the peak is also decreasing. Apparently the correct choice of the cooling rate is as important as it is for the heating rate for the analysis of crystallization processes. By taking into account different cooling rates and extrapolating the peak temperature to isothermal conditions (not measurable in DSC), the true crystallization point can be evaluated.

### **4.1. Fibers from commodity polymers**

All results provided by the last paragraph yield that the alteration of heating and cooling rate causes a strong effect on the results of DSC. Due to this fact it is vital for the success of the analysis to consider the effect of the altering of especially those parameters mentioned above on the properties of a polymeric material which are in the center of interest. Among others the properties crystallization, melting and glass transition shall usually be investigated. In order to support the successful performance of DSC several hints and recommendations for various polymers will be presented in this paragraph. Typical commodity polymers are polypropylene (PP) [25], polyamide (PA6) [26] and polyethylene terephthalate (PET) [27]. In the following paragraph the effects of variations of heating and cooling rate on these polymers will be examined and presented.

Starting with PP (LyondellBasell Moplen HP561R [25]), in the following thermogram the results of DSC with different heating rates are depicted (figure 8 a)).

With increasing heating rate an increase of the peak height and width is noticeable. Additionally, the experiment's velocity is decreasing and the melting process starts earlier. Noticeable is also the double peak when low heating rates were used. During the melting process of fibers it is likely that a phase transition from α- to γ-phase takes place [28]. The obversation of this transition is depending on the choice of the heating rate because it is possible that the material melts directly or the effect is superimposed by others. Due to the fact that a characteristic amount of energy is necessary, it is possible to observe this transition as a peak in the thermogram if the heating rate is chosen correctly. After complete transition to γ-phase the sample will melt completely and another peak is observable in the thermogram. Now the distance between these mentioned peaks is depending on the heating rate and if this rate is adjusted inappropriately both effects are no longer separate from each other. Another possibility is that no phase transition occurs because the temperature is risen quickly enough to start the melting process directly.

Applications of Calorimetry in a Wide Context –

they cannot be observed.

284 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 7.** a) normalized thermograms for different heating rates for polypropylene fibers

Secondly, the variation of the cooling rate is also important as it is depicted in figure 7 b). Beside other observations it is very obvious that the crystallization peak is shifted in positive temperature direction with decreasing cooling rates and the absolute height of the peak is also decreasing. Apparently the correct choice of the cooling rate is as important as it is for the heating rate for the analysis of crystallization processes. By taking into account different cooling rates and extrapolating the peak temperature to isothermal conditions (not

All results provided by the last paragraph yield that the alteration of heating and cooling rate causes a strong effect on the results of DSC. Due to this fact it is vital for the success of the analysis to consider the effect of the altering of especially those parameters mentioned above on the properties of a polymeric material which are in the center of interest. Among others the properties crystallization, melting and glass transition shall usually be investigated. In order to support the successful performance of DSC several hints and recommendations for various polymers will be presented in this paragraph. Typical commodity polymers are polypropylene (PP) [25], polyamide (PA6) [26] and polyethylene terephthalate (PET) [27]. In the following paragraph the effects of variations of heating and

Starting with PP (LyondellBasell Moplen HP561R [25]), in the following thermogram the

With increasing heating rate an increase of the peak height and width is noticeable. Additionally, the experiment's velocity is decreasing and the melting process starts earlier.

b) normalized thermograms for different cooling rates of polypropylene granule

measurable in DSC), the true crystallization point can be evaluated.

cooling rate on these polymers will be examined and presented.

results of DSC with different heating rates are depicted (figure 8 a)).

**4.1. Fibers from commodity polymers** 

heating rate. Moreover, a double peak is of importance. Phase transitions only occur or can be separated from the melting process if lower heating rates are used. For high heating rates

**Figure 8.** Normalized thermograms for different a) heating and b) cooling rates for PP

In the thermogram (figure 8 b)) the variation of the cooling rate is presented for PP. With increasing cooling rates the crystallization peak and its width increases. As reasonably expected the crystallization procedure is slower for higher cooling rates. The actual crystallization peak is determined by extrapolating a virtual crystallization peak for a heating rate of 0 °C/min from the peaks for known heating rates.

As the previous results were gained from investigations of PP similar experiments were performed for PA6 (BASF Ultramid B24N03 [26]). Beginning with a variation of the heating rate as it is depicted in figure 9 a).

Similar to PP the peak width and height is increased for higher heating rates. In this case another remarkable effect can be observed:

With heating rates higher than 25 °C/min a glass transition is starting below 50°C. This indicates that if heating rates below 25 °C/min were chosen this kinetic transition causes a too small effect and is therefore not visible. If the heating rate is then increased further another peak becomes observable. What is visible here is a phase transition from γ- to αphase between 120 °C and 160°C [29]. For the observation of these two effects, it is therefore necessary to choose a heating rate above 25 °C/min.

Applications of Calorimetry in a Wide Context – 286 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In analogy the cooling rate is varied as it is depicted in figure 9 b). Similar to PP, the crystallization peak shifts to lower temperatures for higher heating rates and true crystallization point can be gained by an extrapolation of the peak temperature. The glass transition point cannot be observed since the actual state of the polymer chains is frozen in during cooling and changes in heat capacity will only be visible by heating up the sample again. Furthermore, the phase transition is also not visible since the material crystallizes in the α phase.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 287

shortly after glass transition, indicating that the elongated state of the amorphous polymers chains was frozen in during the rapid cooling in the spinning process. At high heating rates another effect can be observed: after the glass transition and relaxation second crystallization occurs, which pronounces the quenching of the material during the spinning process. After heating over the glass transition point, the mobility of the amorphous or mesomorphous polymer chains increase so that the already present crystallites can grow.

Secondly, the cooling rate is changed for PET sample fibers (figure 10 b)). The analysis of this diagram yields similar results as for the investigation of PP and PA6. With increased cooling rates higher and broader crystallization peaks become visible. Additionally, these

Using the results from the previous paragraph, one can conclude that the appropriate choice of heating and cooling rates is essential for the experiment's success. Therefore, the following table contains valuable information concerning the right choice of these rates in order to gain maximum benefit from performing differential scanning calorimetry of commodity polymers. In this context it is necessary to consider that with too high heating

**Polymer Process Effect Temperatures Rates**  PP Heating Phase transition (α →γ) 156 – 162 °C < 25 °C/min PP Heating Melting 162 – 170 °C all PP Cooling Crystallization 100 – 125 °C all

PA6 Heating Glass transition 50 – 60 °C > 25 °C/min PA6 Heating Phase transition (γ →α) 100 – 170 °C > 10 °C/min PA6 Heating Melting 200 – 240 °C all PA6 Cooling Crystallization 160 – 200 °C all

PET Heating Glass transition with relaxation 70 – 90 °C > 25 °C/min PET Heating Crystallization 90 – 160 °C > 10 °C/min PET Heating Melting 220 – 270 °C all PET Cooling Crystallization 190 °C – 240 °C all

Poly(vinylidene fluoride) is a thermoplastic, semicrystalline fluoropolymer with the monomer unit [CF2-CH2]. Due to the high fluorine content, it exhibits excellent chemical stability [30]. Furthermore, the polar side groups are responsible for the piezoelectric, pyroelectric and ferroelectric properties of the material, which are only present in one

peaks are shifted to lower temperatures with increased cooling rates.

rates some effects may superimpose and therefore might not be visible.

**Table 1.** Recommendations for the right choice of heating and cooling rates

**5. Poly(vinylidene fluoride) fibers** 

**4.2. Recommendations** 

**Figure 9.** Normalized thermograms for different a) heating and b) cooling rates for PA6

Finally, DSC is performed for PET (Invista Polyester Chips 4048 [27]) and again heating and cooling rates are varied. Firstly, the heating rate is altered (figure 10 a)).

**Figure 10.** Normalized thermograms for different a) heating and b) cooling rates for PET

Again, the peak width and height increases with higher heating rates. But the glass transition is in this case even more remarkable: Beginning with a heating rate of 25 °C/min this transition becomes visible and is much more pronounced than it was in the investigation of PA6, since the mobilization of polymer chains during the transition has a larger influence on the heat capacity. Furthermore, a relaxation process can be observed shortly after glass transition, indicating that the elongated state of the amorphous polymers chains was frozen in during the rapid cooling in the spinning process. At high heating rates another effect can be observed: after the glass transition and relaxation second crystallization occurs, which pronounces the quenching of the material during the spinning process. After heating over the glass transition point, the mobility of the amorphous or mesomorphous polymer chains increase so that the already present crystallites can grow.

Secondly, the cooling rate is changed for PET sample fibers (figure 10 b)). The analysis of this diagram yields similar results as for the investigation of PP and PA6. With increased cooling rates higher and broader crystallization peaks become visible. Additionally, these peaks are shifted to lower temperatures with increased cooling rates.

### **4.2. Recommendations**

Applications of Calorimetry in a Wide Context –

the α phase.

286 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 9.** Normalized thermograms for different a) heating and b) cooling rates for PA6

**Figure 10.** Normalized thermograms for different a) heating and b) cooling rates for PET

Again, the peak width and height increases with higher heating rates. But the glass transition is in this case even more remarkable: Beginning with a heating rate of 25 °C/min this transition becomes visible and is much more pronounced than it was in the investigation of PA6, since the mobilization of polymer chains during the transition has a larger influence on the heat capacity. Furthermore, a relaxation process can be observed

cooling rates are varied. Firstly, the heating rate is altered (figure 10 a)).

Finally, DSC is performed for PET (Invista Polyester Chips 4048 [27]) and again heating and

In analogy the cooling rate is varied as it is depicted in figure 9 b). Similar to PP, the crystallization peak shifts to lower temperatures for higher heating rates and true crystallization point can be gained by an extrapolation of the peak temperature. The glass transition point cannot be observed since the actual state of the polymer chains is frozen in during cooling and changes in heat capacity will only be visible by heating up the sample again. Furthermore, the phase transition is also not visible since the material crystallizes in

> Using the results from the previous paragraph, one can conclude that the appropriate choice of heating and cooling rates is essential for the experiment's success. Therefore, the following table contains valuable information concerning the right choice of these rates in order to gain maximum benefit from performing differential scanning calorimetry of commodity polymers. In this context it is necessary to consider that with too high heating rates some effects may superimpose and therefore might not be visible.


**Table 1.** Recommendations for the right choice of heating and cooling rates

### **5. Poly(vinylidene fluoride) fibers**

Poly(vinylidene fluoride) is a thermoplastic, semicrystalline fluoropolymer with the monomer unit [CF2-CH2]. Due to the high fluorine content, it exhibits excellent chemical stability [30]. Furthermore, the polar side groups are responsible for the piezoelectric, pyroelectric and ferroelectric properties of the material, which are only present in one crystalline phase of the polymorphic material, the so called β phase [31,32]. In total, four different crystalline phases can occur [33]. An overview of the crystalline phases, together with the conditions for their formation, is given in table 2.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 289

Conventional and temperature modulated DSC are carried out on a DSC 1 from Mettler Toledo, Greifensee, Switzerland, equipped with a FRS5 sensor having 56 thermocouples. During the experiments, heating and cooling rates were varied between 1 °C/min and 20 °C/min in a temperature range between -90 °C and 250 °C, which corresponds to 50 °C below the glass transition and 70 °C above the melting point. As checked by thermogravimetric analysis, no weight loss and therefore no polymer degradation occurs in this temperature region during the relevant residence times. For the temperature modulated DSC analysis, TOPEM® technique by Mettler Toledo was used, where the constant heating rate was modulated with heat pulses of 0.5 °C height and stochastically varied length between 15 and 30 s (corresponds to 33.3 and 16.6 MHz). Experimental conditions for DSC

**Parameter Value Unit**  Starting temperature -90 °C End temperature 250 °C Heating / cooling rate 1 / 2 / 5 / 10 / 20 °C/min Constant heating / cooling rate (TOPEM®) 0.5 / 1 / 2 °C/min Heat pulse height (TOPEM®) 0.5 °C Heat pulse length (TOPEM®) 15 - 30 s Crucible size (granule) 40 µl Crucible size (fiber) 20 µl Purge gas volume rate 50 ml/min

Results of thermal analysis are compared to the polymer structure and polymer chain orientation, which are determined by wide angle x-ray diffraction (WAXD). Here, a 2D image plate system IPDS II from STOE & Cie GmbH, Darmstadt, Germany, is used for simultaneous analysis of structure and texture. Since the three most important crystalline forms of PVDF α, β and γ have unique diffraction patterns, the method can be easily used to identify the phases. By additional experiments with a heating chamber and heating rates similar to DSC, the underlying phase transitions can be assigned directly to their thermal effect. Since β phase formation can be achieved by mechanical stress, thermal properties of the material are further correlated to dynamic mechanical analysis (DMA), which is carried out on a DMA/SDTA861e by Mettler Toledo. Here, mechanical relaxation processes determined from the phase shift tan(δ) between storage and loss modulus are correlated to

In this chapter, some information about the thermal properties and the crystallization behavior of the raw material (Solvay Solef® PVDF 1006 [43]) will be given, which can be

**6. Experimental details** 

analysis are summarized in table 3.

**Table 3.** Parameters for DSC experiments

their contributions to heat flow.

**7. Properties of raw material** 


**Table 2.** Crystalline phases of poly(vinylidene fluoride) [34-37]

If the material is present in the β phase, it can be used to create sensors or actuators, which are commonly used in the form of films in microphones, hydrophones or headphones. Here, the necessary process conditions (drawing of the films or high electric fields) for the β phase formation are well known [31,38].

In the case of fibers, the material could potentially be used as sensor or actuators. Possible applications include direction sensitive and spatially resolved strain measurement, which is useful for health monitoring in medical / smart textiles or structural health monitoring in fiber reinforced composites. However, suitable process conditions for fiber spinning, drawing and further processing steps have to be found, whereas β phase crystallites have to be formed and not be destroyed along the process chain [39-42]. Therefore, methods of thermal analysis were developed to identify the presence of the β phase, which are validated by additional X-ray diffraction measurements (WAXD) and dynamic mechanical analysis (DMA) [40,42]. In the following section of this chapter, these methods and their validation will be demonstrated, and they will be applied to gather information about phase transitions during melt spinning, drawing and heat treatment. Therefore, thermal analysis is a powerful tool for process analysis and the development of a process chain for the creation of piezoelectric sensor fibers.

### **6. Experimental details**

Applications of Calorimetry in a Wide Context –

**Crystalline phase** 

288 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

with the conditions for their formation, is given in table 2.

**Table 2.** Crystalline phases of poly(vinylidene fluoride) [34-37]

formation are well known [31,38].

of piezoelectric sensor fibers.

**Molecular conformation** 

crystalline phase of the polymorphic material, the so called β phase [31,32]. In total, four different crystalline phases can occur [33]. An overview of the crystalline phases, together

**Crystalline unit cell** 

<sup>α</sup> TGTG' non-polar Cooled from melt,

<sup>β</sup> TT polar (high) Mechanical stress,

<sup>γ</sup> TTTGTTTG' non-polar Heat treatment, cast

δ TGTG' polar (low) Electric field

If the material is present in the β phase, it can be used to create sensors or actuators, which are commonly used in the form of films in microphones, hydrophones or headphones. Here, the necessary process conditions (drawing of the films or high electric fields) for the β phase

In the case of fibers, the material could potentially be used as sensor or actuators. Possible applications include direction sensitive and spatially resolved strain measurement, which is useful for health monitoring in medical / smart textiles or structural health monitoring in fiber reinforced composites. However, suitable process conditions for fiber spinning, drawing and further processing steps have to be found, whereas β phase crystallites have to be formed and not be destroyed along the process chain [39-42]. Therefore, methods of thermal analysis were developed to identify the presence of the β phase, which are validated by additional X-ray diffraction measurements (WAXD) and dynamic mechanical analysis (DMA) [40,42]. In the following section of this chapter, these methods and their validation will be demonstrated, and they will be applied to gather information about phase transitions during melt spinning, drawing and heat treatment. Therefore, thermal analysis is a powerful tool for process analysis and the development of a process chain for the creation

**(a-b-projection) Polarity Conditions for** 

**formation** 

cast from solution

high electric field

from solution

Conventional and temperature modulated DSC are carried out on a DSC 1 from Mettler Toledo, Greifensee, Switzerland, equipped with a FRS5 sensor having 56 thermocouples. During the experiments, heating and cooling rates were varied between 1 °C/min and 20 °C/min in a temperature range between -90 °C and 250 °C, which corresponds to 50 °C below the glass transition and 70 °C above the melting point. As checked by thermogravimetric analysis, no weight loss and therefore no polymer degradation occurs in this temperature region during the relevant residence times. For the temperature modulated DSC analysis, TOPEM® technique by Mettler Toledo was used, where the constant heating rate was modulated with heat pulses of 0.5 °C height and stochastically varied length between 15 and 30 s (corresponds to 33.3 and 16.6 MHz). Experimental conditions for DSC analysis are summarized in table 3.


**Table 3.** Parameters for DSC experiments

Results of thermal analysis are compared to the polymer structure and polymer chain orientation, which are determined by wide angle x-ray diffraction (WAXD). Here, a 2D image plate system IPDS II from STOE & Cie GmbH, Darmstadt, Germany, is used for simultaneous analysis of structure and texture. Since the three most important crystalline forms of PVDF α, β and γ have unique diffraction patterns, the method can be easily used to identify the phases. By additional experiments with a heating chamber and heating rates similar to DSC, the underlying phase transitions can be assigned directly to their thermal effect. Since β phase formation can be achieved by mechanical stress, thermal properties of the material are further correlated to dynamic mechanical analysis (DMA), which is carried out on a DMA/SDTA861e by Mettler Toledo. Here, mechanical relaxation processes determined from the phase shift tan(δ) between storage and loss modulus are correlated to their contributions to heat flow.

### **7. Properties of raw material**

In this chapter, some information about the thermal properties and the crystallization behavior of the raw material (Solvay Solef® PVDF 1006 [43]) will be given, which can be

#### Applications of Calorimetry in a Wide Context – 290 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

later on compared to changes in the fiber material. A typical DSC thermogram (with heating and cooling rate of 10 °C/min) of PVDF quiescently cooled from the melt (with a cooling rate of 1 °C/min) can be found in figure 11. As indicated in the figure, the melting and crystallization peak can be identified clearly.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 291

**Figure 13.** a) Diffraction pattern of melt spun PVDF fiber (winding speed 2.500 m/min),

Here, also the same effect on the melting peak (shift to the first part) can be found.

Depending on the heating rate, the melting behavior changes in the fiber material. After the melting peak, a second peak occurs (figure 14 a)). By further analysis (section "phase transitions during heat treatment"), this peak correlates to the melting of the γ phase, which is converted from α phase during the heating process. This peak gets larger for lower heating rates, since the process of γ phase conversion has more time to take place. Further evidence for changes in this kinetics can be found in the shape of the melting peak, whereas the first part of the peak becomes larger for lower heating rates. Furthermore, γ phase formation is more promoted in fibers produced with higher winding speeds (figure 14 b)).

b) Diffraction pattern of a drawn PVDF fiber (DR = 1.5, drawing TD = 140 °C),

c) Diffraction pattern of a thermally treated PVDF fiber (T = 165 °C).

**Figure 14.** Melting behavior of melt spun PVDF fibers:

a) as a function of the heating rate, b) as a function of the take up velocity.

**Figure 11.** DSC thermogram (heating and cooling) for PVDF bulk material

The endothermal peak correlates to the melting of the material, which takes place in the temperature region between 165 and 180 °C. During the cooling phase, the crystallization (exothermal peak) takes place between 150 and 140 °C. When compared to X-ray data and polarizing microscopy, this behavior can be assigned to a non-textured α phase (figure 12 a), orientation factor f = 0) with spherulitic morphology (figure 12 b)). The material properties are summarized in table 4.

**Figure 12.** a) Diffraction pattern of quiescently cooled PVDF sample, b) Polarizing microscopy image of quiescently cooled PVDF sample.

### **8. Influence of the spinning process**

PVDF fibers (multifilaments) are produced in an industrially relevant high speed spinning process. The winding speed is varied between 100 and 2.500 m/min, which correlates to a melt draw ratio of 40 respectively 100. Due to this high draw ratios, polymer chains are oriented and orientation induced crystallization takes place. However, mechanical stress is relatively low during the melt drawing, so that the material crystallizes in a textured α phase (orientation factor f ≈ 1). This information can be extracted from the X-ray data (figure 13 a)).

**Figure 13.** a) Diffraction pattern of melt spun PVDF fiber (winding speed 2.500 m/min), b) Diffraction pattern of a drawn PVDF fiber (DR = 1.5, drawing TD = 140 °C), c) Diffraction pattern of a thermally treated PVDF fiber (T = 165 °C).

Depending on the heating rate, the melting behavior changes in the fiber material. After the melting peak, a second peak occurs (figure 14 a)). By further analysis (section "phase transitions during heat treatment"), this peak correlates to the melting of the γ phase, which is converted from α phase during the heating process. This peak gets larger for lower heating rates, since the process of γ phase conversion has more time to take place. Further evidence for changes in this kinetics can be found in the shape of the melting peak, whereas the first part of the peak becomes larger for lower heating rates. Furthermore, γ phase formation is more promoted in fibers produced with higher winding speeds (figure 14 b)). Here, also the same effect on the melting peak (shift to the first part) can be found.

**Figure 14.** Melting behavior of melt spun PVDF fibers:

Applications of Calorimetry in a Wide Context –

crystallization peak can be identified clearly.

are summarized in table 4.

13 a)).

290 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 11.** DSC thermogram (heating and cooling) for PVDF bulk material

**Figure 12.** a) Diffraction pattern of quiescently cooled PVDF sample, b) Polarizing microscopy image of quiescently cooled PVDF sample.

**8. Influence of the spinning process** 

later on compared to changes in the fiber material. A typical DSC thermogram (with heating and cooling rate of 10 °C/min) of PVDF quiescently cooled from the melt (with a cooling rate of 1 °C/min) can be found in figure 11. As indicated in the figure, the melting and

The endothermal peak correlates to the melting of the material, which takes place in the temperature region between 165 and 180 °C. During the cooling phase, the crystallization (exothermal peak) takes place between 150 and 140 °C. When compared to X-ray data and polarizing microscopy, this behavior can be assigned to a non-textured α phase (figure 12 a), orientation factor f = 0) with spherulitic morphology (figure 12 b)). The material properties

PVDF fibers (multifilaments) are produced in an industrially relevant high speed spinning process. The winding speed is varied between 100 and 2.500 m/min, which correlates to a melt draw ratio of 40 respectively 100. Due to this high draw ratios, polymer chains are oriented and orientation induced crystallization takes place. However, mechanical stress is relatively low during the melt drawing, so that the material crystallizes in a textured α phase (orientation factor f ≈ 1). This information can be extracted from the X-ray data (figure

b) as a function of the take up velocity.

a) as a function of the heating rate,

Typical values for thermal and structural properties for a melt spun fiber can be found in table 4. Even though the material is cooled down with about 1.000.000 °C/min during fiber spinning, the melting enthalpy is exactly in the same range compared to the slowly cooled sample. This emphasizes the strong enhancement of crystallization rates due to the uniaxial orientation in the spinning process.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 293

**Figure 16.** Relaxation processes at different drawing temperatures (draw ratio DR = 1.4)

**Figure 17.** Phase shift tan(δ) in dynamic mechanical response of the material

phase formation. The properties of all fibers are summarized in the table 4.

When compared to X-ray diffraction measurements, β phase amount is drastically increased without affecting overall crystallinity if the fibers are drawn above the relaxation temperature. Therefore, the relaxation process takes place in the α phase and promotes β

temperature.

Both peaks correlate a relaxation process, which can be found in DMA measurements, which are displayed in figure 17. Here, glass transitions can be identified easily. Another relaxation process (known as αc relaxation in other types of polymers [44]) can be found at 55 °C (α phase) and at 60 °C (β phase), so there is clear evidence for a heat contribution to DSC measurements of this relaxation process. A reason for the occurrence of the first peak in coldly drawn fibers is a drawing temperature below the relaxation temperature, so that more energy is stored in the material and released when heated above glass transition

### **9. Influence of the drawing process**

In the drawing process, a plastic deformation of the material in the solid state takes place, whereas the drawing ratio DR and drawing temperature TD can be varied. Starting from the standard process (DR = 1.4, TD = 140 °C), drawing ratio and temperature are varied separately between 1.0 and 1.6 as well as 40 °C and 160 °C respectively. The effect of both parameters on the melting behavior is displayed in figure 15.

**Figure 15.** a) Changes in the melting peak as a function of draw ratio, b) Changes in the melting peak as a function of drawing temperature.

A main effect of the drawing process is a modification of the melting peak, whereas peak temperature shifts to lower temperatures with higher drawing ratios (168 °C for the highest draw ratio compared to 173 °C for an as-spun fiber). In the X-ray diffraction pattern (figure 13 b)), the formation of β phase can be identified, so that the modification of the melting peak correlates to this crystalline phase. Like in the undrawn fiber, the peak coming from γ phase melting can also be found. The same effect can be found by increasing the drawing temperature. The underlying phase transitions during the melting process will be described in detail in the next section. At lower temperature regions, further peaks can be found (figure 16) depending on the drawing temperature. For low temperatures, a signature close after the glass transition point (-35 °C) can be found. A second peak can be found at higher temperatures, which is present in all fibers. For undrawn fibers, the peak temperature is around 55 °C and for drawn fibers about 5 °C higher.

**Figure 16.** Relaxation processes at different drawing temperatures (draw ratio DR = 1.4)

orientation in the spinning process.

**9. Influence of the drawing process** 

parameters on the melting behavior is displayed in figure 15.

**Figure 15.** a) Changes in the melting peak as a function of draw ratio, b) Changes in the melting peak as a function of drawing temperature.

around 55 °C and for drawn fibers about 5 °C higher.

292 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Typical values for thermal and structural properties for a melt spun fiber can be found in table 4. Even though the material is cooled down with about 1.000.000 °C/min during fiber spinning, the melting enthalpy is exactly in the same range compared to the slowly cooled sample. This emphasizes the strong enhancement of crystallization rates due to the uniaxial

In the drawing process, a plastic deformation of the material in the solid state takes place, whereas the drawing ratio DR and drawing temperature TD can be varied. Starting from the standard process (DR = 1.4, TD = 140 °C), drawing ratio and temperature are varied separately between 1.0 and 1.6 as well as 40 °C and 160 °C respectively. The effect of both

A main effect of the drawing process is a modification of the melting peak, whereas peak temperature shifts to lower temperatures with higher drawing ratios (168 °C for the highest draw ratio compared to 173 °C for an as-spun fiber). In the X-ray diffraction pattern (figure 13 b)), the formation of β phase can be identified, so that the modification of the melting peak correlates to this crystalline phase. Like in the undrawn fiber, the peak coming from γ phase melting can also be found. The same effect can be found by increasing the drawing temperature. The underlying phase transitions during the melting process will be described in detail in the next section. At lower temperature regions, further peaks can be found (figure 16) depending on the drawing temperature. For low temperatures, a signature close after the glass transition point (-35 °C) can be found. A second peak can be found at higher temperatures, which is present in all fibers. For undrawn fibers, the peak temperature is Both peaks correlate a relaxation process, which can be found in DMA measurements, which are displayed in figure 17. Here, glass transitions can be identified easily. Another relaxation process (known as αc relaxation in other types of polymers [44]) can be found at 55 °C (α phase) and at 60 °C (β phase), so there is clear evidence for a heat contribution to DSC measurements of this relaxation process. A reason for the occurrence of the first peak in coldly drawn fibers is a drawing temperature below the relaxation temperature, so that more energy is stored in the material and released when heated above glass transition temperature.

**Figure 17.** Phase shift tan(δ) in dynamic mechanical response of the material

When compared to X-ray diffraction measurements, β phase amount is drastically increased without affecting overall crystallinity if the fibers are drawn above the relaxation temperature. Therefore, the relaxation process takes place in the α phase and promotes β phase formation. The properties of all fibers are summarized in the table 4.

294 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry


Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 295

For an interpretation of the results, the highly oriented crystalline structures have to be taken into account. They were formed far from equilibrium and therefore must contribute to the non-reversing heat flow. On the other side, energy stored in the solidified amorphous parts due to short-range bonding to neighbor polymer chains contributes to the reversing heat flow. However, also crystalline phases contribute to the reversing heat flow if time scale of the phase transitions is larger than the pulse length applied to the sample. In total, 3 (α phase fiber) or 4 (β phase fiber) transformations in the crystalline regions take place. The same amount of phase transitions can also be found in X-ray measurements. The additional peak in the β phase fibers is caused by a reconversion to the α phase. After this transition, the changes in the crystalline structure are the same for both fibers, starting from α phase conversion to γ phase, going on with the melting of the remaining α crystallites and finally ending with the melting of the γ phase. Since the melting of the α phase takes place shortly after the conversion to γ phase, the amount of γ phase (compare to figure 14) strongly depends on the heating rate. All phase transitions during heat treatment are summarized in

**Transition Temperature range (peak) Heat flow**  β →α 165 °C – 170 °C (168 °C) endothermal α →γ 166 °C – 173 °C (171 °C) exothermal α melt → 173 °C – 180 °C (176 °C) endothermal γ melt → 180 °C – 190 °C (185 °C) endothermal

For the selection of the right process settings for the production of piezoelectric fibers, it is necessary to get an overview of all phase transitions which can occur in the processes (melt spinning, solid state drawing and heat treatment/polarization). All these transitions were

Melt

Melt spinning Drawing Heat treatment

phase

Cooling T < 160 °C

> Heating T > 166 °C

phase

Heating T > 180°C

**Table 5.** Summary of phase transitions in PVDF fibers during heat treatment

described in the previous sections and are summarized in figure 19.

Heating T > 173 °C

Mechanical stress

**Figure 19.** Overview of phase transitions in poly(vinylidene fluoride) fibers

**11. Overview over phase transitions** 

Heating T > 165°C

phase

table 5.

**Table 4.** Thermal and structural properties of PVDF (\*: not detectable since determined by process)

### **10. Phase transitions during heat treatment**

Heat treatment is important in the further processing of the fibers. If they are to be used as piezoelectric sensors, a polarization process has to take place at elevated temperatures without having a reconversion of β phase to α phase. To identify such a transition and explain phase transformations during the melting procedure of the material, temperature modulated measurements can be used. However, the occurrence of different crystalline phases has to be validated X-ray measurements of heated fibers. The results for temperature modulated measurements (TOPEM ®) are displayed in figure 18 for a undrawn and a highly drawn fiber, whereas heat flow is separated into reversing and non-reversing parts.

**Figure 18.** TOPEM ® results with constant heating rate of 2 °C/min (melting peak):

a) PVDF fiber containing α phase,

b) PVDF fiber containing β phase.

For an interpretation of the results, the highly oriented crystalline structures have to be taken into account. They were formed far from equilibrium and therefore must contribute to the non-reversing heat flow. On the other side, energy stored in the solidified amorphous parts due to short-range bonding to neighbor polymer chains contributes to the reversing heat flow. However, also crystalline phases contribute to the reversing heat flow if time scale of the phase transitions is larger than the pulse length applied to the sample. In total, 3 (α phase fiber) or 4 (β phase fiber) transformations in the crystalline regions take place. The same amount of phase transitions can also be found in X-ray measurements. The additional peak in the β phase fibers is caused by a reconversion to the α phase. After this transition, the changes in the crystalline structure are the same for both fibers, starting from α phase conversion to γ phase, going on with the melting of the remaining α crystallites and finally ending with the melting of the γ phase. Since the melting of the α phase takes place shortly after the conversion to γ phase, the amount of γ phase (compare to figure 14) strongly depends on the heating rate. All phase transitions during heat treatment are summarized in table 5.


**Table 5.** Summary of phase transitions in PVDF fibers during heat treatment

### **11. Overview over phase transitions**

Applications of Calorimetry in a Wide Context –

Morphology spherulitic /

**10. Phase transitions during heat treatment** 

non-reversing parts.

a) PVDF fiber containing α phase, b) PVDF fiber containing β phase.

294 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Parameter Value Value Value Unit**  Type of material Granules Melt spun fiber Drawn fiber - Relaxation temperature range - 36 - 65 40 - 71 °C Relaxation temperature peak - 55 60 °C Relaxation enthalpy - 1.6 1.3 J/g Melting range 168 - 180 168 - 185 165 - 185 °C Melting peak temperature 174 173 168 °C Melting enthalpy 49.6 48.2 45.8 J/g Crystallization range 140 - 150 -\* -\* °C Crystallization peak temperature 145 -\* -\* °C Crystallization enthalpy 50.0 -\* -\* J/g Crystalline phase α α β -

non-textured

**Figure 18.** TOPEM ® results with constant heating rate of 2 °C/min (melting peak):

**Table 4.** Thermal and structural properties of PVDF (\*: not detectable since determined by process)

Heat treatment is important in the further processing of the fibers. If they are to be used as piezoelectric sensors, a polarization process has to take place at elevated temperatures without having a reconversion of β phase to α phase. To identify such a transition and explain phase transformations during the melting procedure of the material, temperature modulated measurements can be used. However, the occurrence of different crystalline phases has to be validated X-ray measurements of heated fibers. The results for temperature modulated measurements (TOPEM ®) are displayed in figure 18 for a undrawn and a highly drawn fiber, whereas heat flow is separated into reversing and

textured textured -

For the selection of the right process settings for the production of piezoelectric fibers, it is necessary to get an overview of all phase transitions which can occur in the processes (melt spinning, solid state drawing and heat treatment/polarization). All these transitions were described in the previous sections and are summarized in figure 19.

**Figure 19.** Overview of phase transitions in poly(vinylidene fluoride) fibers

Applications of Calorimetry in a Wide Context – 296 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

After melt spinning, the fibers should be drawn at high ratios (close to maximum elongation) to form as much β phase fraction as possible. Drawing temperature should be at least above 55 °C to enhance β phase formation and prevent relaxation processes. For further polarization processes, temperature should be kept below 160 °C to keep the material in the β phase. For the process development, calorimetric measurements are of great value to identify the phase transitions, so that they can be realized in the process by choosing the right parameters. Furthermore, thermal analysis is of great value for further quality control, since the present crystalline phases can be detected by a simple method (compared to techniques like X-ray diffraction).

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 297

Furthermore, the values determined at low frequencies can be considered as the DC

Depending on the type of polymer, CNT can influence the crystallization process in two different ways. Both effects will be described in this section with the help of the examples polypropylene (PP, Basell Moplen HP561R [25]) and polyamide 6 (PA6, BASF B24N03 [26]). In PP (compare figure 20 a)), crystallization peak shifts to higher temperatures with increasing amount of CNT. This effect has two reasons. First, the high thermal conductivity of CNT allows the latent heat to be transferred faster from the polymer to the surrounding medium, to that sample temperature is closer to the reference temperature compared to unmodified samples. However, this effect shifts the peak only about 0.5 °C per w% CNT added to the polymer. The more dominant effect is the acting of CNT as foreign substance in the polymer, on which crystal nuclei can be formed at higher temperatures. After this nucleation, crystallites can grow in the usual way. By adding only 1 w% of CNT, this effect

The effect in PA6 is different (see figure 20 b)). The form of the crystallization peak changes to that a double peak can be found. Here, the part of the peak at lower temperatures (which is also shifted compared to unmodified material), has the same origin like in PP. Here also higher crystallization temperature is caused by enhanced thermal conductivity and crystal nucleation on the CNT. The part of the peak at higher temperatures is caused by another effect, the direct crystal growth on the CNT. The particles act as nuclei for the polymer chains and the crystallites can grow at higher temperatures, since no undercooling is needed

The type of crystallization process has a large influence on the electrical properties of the material, especially on the percolation threshold. A comparison of the electrical properties of the two polymers can be found in figure 21 a). The percolation threshold is the value for CNT concentration, where the specific resistivity drastically decreases over several orders of magnitude. Above the threshold, resistivity only decreases slowly due to the higher amount

conductivity of the material.

**14. Compounding in different polymer matrices** 

shifts the melting peak by 5 °C to higher temperatures.

**Figure 20.** Effect of CNT on polymer crystallization (cooling rate 10 °C/min):

for crystal growth compared to nucleation.

a) Polypropylene (PP), b) Polyamide 6 (PA6).

### **12. Carbon nanotube composite fibers**

Carbon nanotubes (CNT) are allotropes of pure carbon in a form of a cylindrical structure. Depending on the number of graphite sheets forming the tube, they are divided into single wall (SW-CNT) and multi wall carbon nanotubes (MW-CNT). Beside excellent mechanical properties, CNT offer high electrical and thermal conductivity. When added to a polymer matrix, their properties are partially transferred to the polymer nanocomposite material [45]. In the case of mechanical reinforcement, an increase of Young's modulus can be observed in many polymer matrices [45,46]. One of the most interesting aspects is the formation of electrical conductive paths, so called percolative networks, in otherwise insulating materials [45,47]. Compared to other conductive fillers like carbon black (CB), the amount of CNT for reaching electrical conductivity is extremely low, whereas percolation thresholds below 0.1 % were observed [48].

However, not only the desired material properties in solid state change by the additivation of CNT. The nanoparticles interact with the polymer matrix and influence the rheological properties of the polymer melt, but also the crystallization behavior [46]. Especially in the melt spinning process, process settings have to be adjusted to allow the production of CNT modified nanocomposite fibers [49-53]. Therefore, the nancomposites have to be analyzed by DSC to understand the effects of CNT on the different polymer matrices, so that the right process parameters for fiber production can be found. Furthermore, thermal analysis provides useful information about the functional properties of the material, since crystallization conditions have a large influence on the electrical conductivity.

### **13. Experimental conditions**

For each polymer, conventional DSC was carried out at least 50 °C below the glass transition (except of polyethylene, where glass transition is too low) and 50 °C above the melting point. Heating rate was varied between 2 °C and 20 °C, whereas results with 5 °C/min are shown in this chapter, since all effects to be demonstrated can be found at this heating rate.

Electrical properties of the composite materials where checked with a LCR meter, whereas the materials were tested in a frequency range between 1 Hz and 100 kHz. By checking AC conductivity, effects of partially not connected conductive networks can be found. Furthermore, the values determined at low frequencies can be considered as the DC conductivity of the material.

### **14. Compounding in different polymer matrices**

Applications of Calorimetry in a Wide Context –

(compared to techniques like X-ray diffraction).

**12. Carbon nanotube composite fibers** 

% were observed [48].

**13. Experimental conditions** 

296 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

After melt spinning, the fibers should be drawn at high ratios (close to maximum elongation) to form as much β phase fraction as possible. Drawing temperature should be at least above 55 °C to enhance β phase formation and prevent relaxation processes. For further polarization processes, temperature should be kept below 160 °C to keep the material in the β phase. For the process development, calorimetric measurements are of great value to identify the phase transitions, so that they can be realized in the process by choosing the right parameters. Furthermore, thermal analysis is of great value for further quality control, since the present crystalline phases can be detected by a simple method

Carbon nanotubes (CNT) are allotropes of pure carbon in a form of a cylindrical structure. Depending on the number of graphite sheets forming the tube, they are divided into single wall (SW-CNT) and multi wall carbon nanotubes (MW-CNT). Beside excellent mechanical properties, CNT offer high electrical and thermal conductivity. When added to a polymer matrix, their properties are partially transferred to the polymer nanocomposite material [45]. In the case of mechanical reinforcement, an increase of Young's modulus can be observed in many polymer matrices [45,46]. One of the most interesting aspects is the formation of electrical conductive paths, so called percolative networks, in otherwise insulating materials [45,47]. Compared to other conductive fillers like carbon black (CB), the amount of CNT for reaching electrical conductivity is extremely low, whereas percolation thresholds below 0.1

However, not only the desired material properties in solid state change by the additivation of CNT. The nanoparticles interact with the polymer matrix and influence the rheological properties of the polymer melt, but also the crystallization behavior [46]. Especially in the melt spinning process, process settings have to be adjusted to allow the production of CNT modified nanocomposite fibers [49-53]. Therefore, the nancomposites have to be analyzed by DSC to understand the effects of CNT on the different polymer matrices, so that the right process parameters for fiber production can be found. Furthermore, thermal analysis provides useful information about the functional properties of the material, since

For each polymer, conventional DSC was carried out at least 50 °C below the glass transition (except of polyethylene, where glass transition is too low) and 50 °C above the melting point. Heating rate was varied between 2 °C and 20 °C, whereas results with 5 °C/min are shown in this chapter, since all effects to be demonstrated can be found at this heating rate. Electrical properties of the composite materials where checked with a LCR meter, whereas the materials were tested in a frequency range between 1 Hz and 100 kHz. By checking AC conductivity, effects of partially not connected conductive networks can be found.

crystallization conditions have a large influence on the electrical conductivity.

Depending on the type of polymer, CNT can influence the crystallization process in two different ways. Both effects will be described in this section with the help of the examples polypropylene (PP, Basell Moplen HP561R [25]) and polyamide 6 (PA6, BASF B24N03 [26]).

In PP (compare figure 20 a)), crystallization peak shifts to higher temperatures with increasing amount of CNT. This effect has two reasons. First, the high thermal conductivity of CNT allows the latent heat to be transferred faster from the polymer to the surrounding medium, to that sample temperature is closer to the reference temperature compared to unmodified samples. However, this effect shifts the peak only about 0.5 °C per w% CNT added to the polymer. The more dominant effect is the acting of CNT as foreign substance in the polymer, on which crystal nuclei can be formed at higher temperatures. After this nucleation, crystallites can grow in the usual way. By adding only 1 w% of CNT, this effect shifts the melting peak by 5 °C to higher temperatures.

The effect in PA6 is different (see figure 20 b)). The form of the crystallization peak changes to that a double peak can be found. Here, the part of the peak at lower temperatures (which is also shifted compared to unmodified material), has the same origin like in PP. Here also higher crystallization temperature is caused by enhanced thermal conductivity and crystal nucleation on the CNT. The part of the peak at higher temperatures is caused by another effect, the direct crystal growth on the CNT. The particles act as nuclei for the polymer chains and the crystallites can grow at higher temperatures, since no undercooling is needed for crystal growth compared to nucleation.

**Figure 20.** Effect of CNT on polymer crystallization (cooling rate 10 °C/min): a) Polypropylene (PP), b) Polyamide 6 (PA6).

The type of crystallization process has a large influence on the electrical properties of the material, especially on the percolation threshold. A comparison of the electrical properties of the two polymers can be found in figure 21 a). The percolation threshold is the value for CNT concentration, where the specific resistivity drastically decreases over several orders of magnitude. Above the threshold, resistivity only decreases slowly due to the higher amount of conductive filler. For polypropylene, the threshold can be found at 3 w% compared to 7 w% for polyamide 6.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 299

As described above, CNT have a major influence on the crystallization behavior in the different polymers. Even though the material is cooled down much faster during melt spinning and orientation induced crystallization is dominating the structure formation in the material, crystallization phenomena are drastically altered due to the presence of the nanoparticles. An example for the changes in the crystallization of polypropylene can be found in figure 22. If the material is heated above the relaxation point (approx. 50 °C), recrystallization phenomena can be found in the unmodified fibers. If CNT are doped to the PP matrix, no recrystallization peak can be found. Since the melting enthalpy is constant for different CNT fractions compared to the raw material (after recrystallization), it can be concluded that crystallization rates are enhanced by the presence of the particles. This observation is correlating with the fact, that the material cannot be drawn at high ratios in

**Figure 22.** Changes in the melting behavior as a function of CNT concentration in polypropylene fibers

In polyamide 6, the thermal property affected mostly is the glass transition. This effect is displayed in figure 23. By adding higher amounts of CNT, the glass transition temperature shifts to higher values. Thus a TG of 60 °C is reached for a concentration of 10 w% compared to 52 °C for the same type of unmodified material. Since polymer crystallites grow on the CNT surface, the material is the polymer matrix has a better chemical bonding to the nanoparticles and the polymer chain mobility is lowered due to their presence. Therefore, more energy is needed to mobilize the polymer chains resulting in a higher glass transition

**15. Influence of the spinning process** 

the molten state if CNT are present.

spun with a winding speed of 50 m/min

temperature.

For polypropylene, CNT act as nucleation seeds, but the material has no chemical affinity to the nanoparticles. Therefore CNT try to form aggregates in the polymer matrix, which can build conductive paths through the whole fiber. The region between the aggregates is then filled by PP crystallites during the crystallization process. Because of the separation of the different regions, only lower amount of CNT is needed to form conductive paths. Therefore, the dynamic percolation threshold defined by the crystallization process is significantly lower than it would be for a uniform distribution of the particles in the fiber. This behavior can be observed with transmission electron microscopy (figure 21 b)).

For polyamide 6, where polymer crystallites directly grow on the particles, a chemical affinity between the components is given and single CNT are separated by the polymer matrix (see figure 21 c)). Therefore, CNT are well distributed in the polymer and the percolation threshold is defined by the geometry of the nanoparticles (length and diameter) as well as their orientation to the fiber matrix. Single CNT in PA6 can be oriented better compared to the aggregates in PP, so that the resistivity of a fiber is highly sensitive to the process parameters in the spinning and drawing process.

b) Transmission electron microscopy image of 10 w% CNT in PP,

c) Transmission electron microscopy image of 5 w% CNT in PA6.

#### **15. Influence of the spinning process**

Applications of Calorimetry in a Wide Context –

7 w% for polyamide 6.

(PP and PA6),

298 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

can be observed with transmission electron microscopy (figure 21 b)).

process parameters in the spinning and drawing process.

b) Transmission electron microscopy image of 10 w% CNT in PP, c) Transmission electron microscopy image of 5 w% CNT in PA6.

of conductive filler. For polypropylene, the threshold can be found at 3 w% compared to

For polypropylene, CNT act as nucleation seeds, but the material has no chemical affinity to the nanoparticles. Therefore CNT try to form aggregates in the polymer matrix, which can build conductive paths through the whole fiber. The region between the aggregates is then filled by PP crystallites during the crystallization process. Because of the separation of the different regions, only lower amount of CNT is needed to form conductive paths. Therefore, the dynamic percolation threshold defined by the crystallization process is significantly lower than it would be for a uniform distribution of the particles in the fiber. This behavior

For polyamide 6, where polymer crystallites directly grow on the particles, a chemical affinity between the components is given and single CNT are separated by the polymer matrix (see figure 21 c)). Therefore, CNT are well distributed in the polymer and the percolation threshold is defined by the geometry of the nanoparticles (length and diameter) as well as their orientation to the fiber matrix. Single CNT in PA6 can be oriented better compared to the aggregates in PP, so that the resistivity of a fiber is highly sensitive to the

**Figure 21.** a) Electrical conductivity as a function of CNT weight fraction in different polymer matrices

As described above, CNT have a major influence on the crystallization behavior in the different polymers. Even though the material is cooled down much faster during melt spinning and orientation induced crystallization is dominating the structure formation in the material, crystallization phenomena are drastically altered due to the presence of the nanoparticles. An example for the changes in the crystallization of polypropylene can be found in figure 22. If the material is heated above the relaxation point (approx. 50 °C), recrystallization phenomena can be found in the unmodified fibers. If CNT are doped to the PP matrix, no recrystallization peak can be found. Since the melting enthalpy is constant for different CNT fractions compared to the raw material (after recrystallization), it can be concluded that crystallization rates are enhanced by the presence of the particles. This observation is correlating with the fact, that the material cannot be drawn at high ratios in the molten state if CNT are present.

**Figure 22.** Changes in the melting behavior as a function of CNT concentration in polypropylene fibers spun with a winding speed of 50 m/min

In polyamide 6, the thermal property affected mostly is the glass transition. This effect is displayed in figure 23. By adding higher amounts of CNT, the glass transition temperature shifts to higher values. Thus a TG of 60 °C is reached for a concentration of 10 w% compared to 52 °C for the same type of unmodified material. Since polymer crystallites grow on the CNT surface, the material is the polymer matrix has a better chemical bonding to the nanoparticles and the polymer chain mobility is lowered due to their presence. Therefore, more energy is needed to mobilize the polymer chains resulting in a higher glass transition temperature.

300 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 301

major changes in the phase separation behavior, but without changing the crystallization process by the nanotubes. Possible reasons for the broadening are more diverse sizes of regions of LDPE in PP, which tend to crystallize at different temperatures. Further evidence of the aggregation of CNT in PP can be found in the melting process. While the form of melting peak of LDPE is not changed at all, the PP changes from a double peak to a single peak. Since the occurrence of the double peak indicates a phase transformation before the actual melting procedure, it can be concluded that the present crystalline phase (α phase) is stabilized by the presence of CNT and the nanotubes are situated in the PP phase of the

As stated above, the choice of the base polymer as well as the melt spinning of the fibers has a large influence on the electrical conductivity. The base materials can be classified into two groups. In polymers like polypropylene, CNT act as nucleation seeds. The particles can aggregate and easily form conductive paths, so that a low percolation threshold can be observed. This class of materials is very useful for the production of electrically conductive fibers with high spinning speeds, since electrical conductivity is less affected by the spinning process and possible mechanical treatment during the use of the fibers. For polymers like polyamide 6, crystallites grow on the surface of CNT, so that particles are separated and the percolation threshold is higher. Since single CNT can be oriented easily, the spinning and drawing process has a larger influence on the conductivity. This makes the processing of the materials more instable. However, they can potentially be used to create sensors, whereas

**17. Impact on the development of electrically conductive fibers** 

mechanical stress and deformation can be detected by changes in the resistivity.

given and the temperature ranges for these effects are indicated.

Taking into account the unique morphology of polymeric fibers, special analysis methods are needed for the development of new materials and processes. Due to high deformation of the molten polymer in the spinning process as well as the solid-state deformation during drawing, the polymer chains are highly oriented along the fiber axis. Differential scanning calorimetry, especially with temperature modulation, is one of the most important tools for fiber development. It can be used for a fundamental study of new materials and their behavior during spinning and processing as well as quality control of commidity polymers. For the analysis of commodity polymers, the effect of sample preparation and experimental parameters is demonstrated. For the preparation of samples, small crucibles with fibers cut into small pieces are useful to measure thermograms with clearly visible effects. The choice of parameters has a large influence on the thermal effects observable in the results. Depending on the heating and cooling rate, effects like glass transition, structural phase transitions, melting and crystallization can be revealed from the thermograms. For the observation of these effects in the most common fiber polymers (polypropylene, polyamide 6 and poly(ethylene terephthalate)), recommendations for experimental parameters are

blend system.

**18. Conclusion** 

**Figure 23.** Changes in the glass transition as a function of CNT concentration in polyamide 6 fibers spun with a winding speed of 50 m/min

### **16. Effects in blend systems**

In blend systems, two or more polymers are mixed together without forming a mutual polymer chain. If both components are not compatible with each other, they are separated in the fiber material, but influence each other [54]. Depending on the chemical structure of the polymers, CNT are attracted more by one of the components and aggregate in this material. This effect will be explained on a mixture of polypropylene (PP, LyondellBasell Moplen HP561R [25]) and low-density polyethylene (LDPE, LyondellBasell Lupolen 1800S [55]). The crystallization and melting behavior can be found in figure 24. In the crystallization process, the PP peak shifts by the additivation of CNT, which indicates the nucleation of PP

**Figure 24.** Effect in blend systems of polypropylene / polyethylene (1:1, heating/coolingrate 5 °C/min) as a function of CNT concentration:

a) Crystallization phenomena during cooling of bulk material,

b) Melting phenomena during heating of fibers.

on the CNT and therefore the presence of nanotubes in this polymer. For LDPE, there is no temperature shift of the crystallization peak. However, the peak gets broader. This indicates major changes in the phase separation behavior, but without changing the crystallization process by the nanotubes. Possible reasons for the broadening are more diverse sizes of regions of LDPE in PP, which tend to crystallize at different temperatures. Further evidence of the aggregation of CNT in PP can be found in the melting process. While the form of melting peak of LDPE is not changed at all, the PP changes from a double peak to a single peak. Since the occurrence of the double peak indicates a phase transformation before the actual melting procedure, it can be concluded that the present crystalline phase (α phase) is stabilized by the presence of CNT and the nanotubes are situated in the PP phase of the blend system.

### **17. Impact on the development of electrically conductive fibers**

As stated above, the choice of the base polymer as well as the melt spinning of the fibers has a large influence on the electrical conductivity. The base materials can be classified into two groups. In polymers like polypropylene, CNT act as nucleation seeds. The particles can aggregate and easily form conductive paths, so that a low percolation threshold can be observed. This class of materials is very useful for the production of electrically conductive fibers with high spinning speeds, since electrical conductivity is less affected by the spinning process and possible mechanical treatment during the use of the fibers. For polymers like polyamide 6, crystallites grow on the surface of CNT, so that particles are separated and the percolation threshold is higher. Since single CNT can be oriented easily, the spinning and drawing process has a larger influence on the conductivity. This makes the processing of the materials more instable. However, they can potentially be used to create sensors, whereas mechanical stress and deformation can be detected by changes in the resistivity.

### **18. Conclusion**

Applications of Calorimetry in a Wide Context –

spun with a winding speed of 50 m/min

**16. Effects in blend systems** 

as a function of CNT concentration:

b) Melting phenomena during heating of fibers.

a) Crystallization phenomena during cooling of bulk material,

300 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 23.** Changes in the glass transition as a function of CNT concentration in polyamide 6 fibers

In blend systems, two or more polymers are mixed together without forming a mutual polymer chain. If both components are not compatible with each other, they are separated in the fiber material, but influence each other [54]. Depending on the chemical structure of the polymers, CNT are attracted more by one of the components and aggregate in this material. This effect will be explained on a mixture of polypropylene (PP, LyondellBasell Moplen HP561R [25]) and low-density polyethylene (LDPE, LyondellBasell Lupolen 1800S [55]). The crystallization and melting behavior can be found in figure 24. In the crystallization process, the PP peak shifts by the additivation of CNT, which indicates the nucleation of PP

**Figure 24.** Effect in blend systems of polypropylene / polyethylene (1:1, heating/coolingrate 5 °C/min)

on the CNT and therefore the presence of nanotubes in this polymer. For LDPE, there is no temperature shift of the crystallization peak. However, the peak gets broader. This indicates Taking into account the unique morphology of polymeric fibers, special analysis methods are needed for the development of new materials and processes. Due to high deformation of the molten polymer in the spinning process as well as the solid-state deformation during drawing, the polymer chains are highly oriented along the fiber axis. Differential scanning calorimetry, especially with temperature modulation, is one of the most important tools for fiber development. It can be used for a fundamental study of new materials and their behavior during spinning and processing as well as quality control of commidity polymers.

For the analysis of commodity polymers, the effect of sample preparation and experimental parameters is demonstrated. For the preparation of samples, small crucibles with fibers cut into small pieces are useful to measure thermograms with clearly visible effects. The choice of parameters has a large influence on the thermal effects observable in the results. Depending on the heating and cooling rate, effects like glass transition, structural phase transitions, melting and crystallization can be revealed from the thermograms. For the observation of these effects in the most common fiber polymers (polypropylene, polyamide 6 and poly(ethylene terephthalate)), recommendations for experimental parameters are given and the temperature ranges for these effects are indicated.

The development of new spinning processes is demonstrated for poly(vinylidene fluoride), whereas DSC can be used to detect the formation of the piezoelectric β phase. With the help of temperature modulated DSC compared to X-ray diffraction and dynamic mechanical analysis, a process chain for the generation of piezoelectric sensor fibers with possible spinning and drawing parameters was developed. Since the formation of the piezoelectric crystallites can be detected by DSC, it is powerful tool for future development of piezoelectric sensors and actuators.

Thermal Analysis of Phase Transitions and Crystallization in Polymeric Fibers 303

[5] Walter S, Steinmann W, Gries T, Seide G, Schenuit H, Roth G (2010) Production of textile fabrics from PVDF multifilament yarns with textile titer. Technical Textiles. j. 53:

[6] Walter S, Steinmann W, Gries T, Roth G, Seide G, Schenuit H. Tools for savers of life : production of warp-knitted fabrics from PVDF multifilament yarns of textile fineness.

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Electrically conductive nanocomposites based on carbon nanotubes are used as an example for the development of new materials. The presence of nanoparticles influences the crystallization process dependent on the chemical structure of the polymer matrix, whereas two different mechanisms can be detected. The resulting structure then determines the percolation threshold for electrical conductivity. If polymer crystallites can directly grow on the CNT, the particles are separated and percolation threshold is only determined by the particle geometry and orientation. In the other case, the affinity of the polymer chains to the CNT is lower, so that they act as nucleation seeds. CNT can then aggregate and form conductive paths. Due to the higher separation of the two components, percolation threshold is lower.

### **Author details**

W. Steinmann\* , S. Walter, M. Beckers, G. Seide and T. Gries *Institut für Textiltechnik (ITA) der RWTH Aachen University, Aachen, Germany* 

### **Acknowledgement**

Special thanks to the Deutsche Forschungsgemeinschaft (German research foundation, DFG) for funding the project GR 1311/10-2.

### **19. References**


<sup>\*</sup> Corresponding Author


piezoelectric sensors and actuators.

threshold is lower.

**Author details** 

W. Steinmann\*

*Aachen, Germany* 

**19. References** 

Corresponding Author

 \*

**Acknowledgement** 

for funding the project GR 1311/10-2.

München: Hanser. 880 p.

Technik. Weinheim: Wiley

Chemical Fibers International. j. 61: 122.

302 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

, S. Walter, M. Beckers, G. Seide and T. Gries

*Institut für Textiltechnik (ITA) der RWTH Aachen University,* 

The development of new spinning processes is demonstrated for poly(vinylidene fluoride), whereas DSC can be used to detect the formation of the piezoelectric β phase. With the help of temperature modulated DSC compared to X-ray diffraction and dynamic mechanical analysis, a process chain for the generation of piezoelectric sensor fibers with possible spinning and drawing parameters was developed. Since the formation of the piezoelectric crystallites can be detected by DSC, it is powerful tool for future development of

Electrically conductive nanocomposites based on carbon nanotubes are used as an example for the development of new materials. The presence of nanoparticles influences the crystallization process dependent on the chemical structure of the polymer matrix, whereas two different mechanisms can be detected. The resulting structure then determines the percolation threshold for electrical conductivity. If polymer crystallites can directly grow on the CNT, the particles are separated and percolation threshold is only determined by the particle geometry and orientation. In the other case, the affinity of the polymer chains to the CNT is lower, so that they act as nucleation seeds. CNT can then aggregate and form conductive paths. Due to the higher separation of the two components, percolation

Special thanks to the Deutsche Forschungsgemeinschaft (German research foundation, DFG)

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**Section 5** 

**Indirect Calorimetry to Measure Energy** 

**Expenditure** 

**Indirect Calorimetry to Measure Energy Expenditure** 

Applications of Calorimetry in a Wide Context –

Rotterdam: LyondellBasell.

306 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[55] LyondellBasell (2011) Product Date and Technical Information Moplen HP561R.

**Chapter 13** 

© 2013 Rosado et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Energy Expenditure Measured by Indirect** 

Eliane Lopes Rosado, Vanessa Chaia Kaippert and Roberta Santiago de Brito

Obesity is a multifactorial disease characterized by excessive deposition of fat in adipose tissue, which may be due to excessive energy intake, and or changes in body energy

Mika Horie et al [2] demonstrated that obese women had higher total energy expenditure (TEE), compared with normal weight. However, this increase may be due to increased basal metabolic rate (BMR) due to higher fat-free mass (FFM) and energy demand during physical activity. However, Melo et al [3] found that obese individuals are economical, the metabolic point of view. Therefore, the energy expenditure (EE) per kilogram of body weight at the

The low metabolic rate, expressed relative to FFM seems to be a risk factor for weight gain [4]. In a prospective study in Pima Indians, Ravussin et al. [5] showed that both the low resting metabolic rate (RMR) and low TEE increased risk of weight gain. The basal energy expenditure (BEE) and resting (REE) can be obtained through BMR and RMR, respectively,

There are several methods for the assessment of EE with different levels of precision, including indirect calorimetry, which measures the metabolic rate by the determination of oxygen consumption (O2) (with a spirometer), the production of carbon dioxide (CO2) and excretion of urinary nitrogen, for a given period of time [6]. This technique relies on the fact that all the O2 consumed and CO2 produced is due to the oxidation of the three major energy

Recognizing the need to estimate EE in institutions that have no indirect calorimetry, researchers have proposed the use of specific equations, developed from calorimetry studies in groups of individuals with similar clinical characteristics [8]. Although the estimate of EE

and reproduction in any medium, provided the original work is properly cited.

**Calorimetry in Obesity** 

http://dx.doi.org/10.5772/55605

**1. Introduction** 

Additional information is available at the end of the chapter

expenditure, resulting in positive energy balance [1].

give time is lower in obese individuals.

multiplied by 24 hours (1440 minutes).

substrates, which are fats, carbohydrates and proteins [7].

## **Energy Expenditure Measured by Indirect Calorimetry in Obesity**

Eliane Lopes Rosado, Vanessa Chaia Kaippert and Roberta Santiago de Brito

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/55605

### **1. Introduction**

Obesity is a multifactorial disease characterized by excessive deposition of fat in adipose tissue, which may be due to excessive energy intake, and or changes in body energy expenditure, resulting in positive energy balance [1].

Mika Horie et al [2] demonstrated that obese women had higher total energy expenditure (TEE), compared with normal weight. However, this increase may be due to increased basal metabolic rate (BMR) due to higher fat-free mass (FFM) and energy demand during physical activity. However, Melo et al [3] found that obese individuals are economical, the metabolic point of view. Therefore, the energy expenditure (EE) per kilogram of body weight at the give time is lower in obese individuals.

The low metabolic rate, expressed relative to FFM seems to be a risk factor for weight gain [4]. In a prospective study in Pima Indians, Ravussin et al. [5] showed that both the low resting metabolic rate (RMR) and low TEE increased risk of weight gain. The basal energy expenditure (BEE) and resting (REE) can be obtained through BMR and RMR, respectively, multiplied by 24 hours (1440 minutes).

There are several methods for the assessment of EE with different levels of precision, including indirect calorimetry, which measures the metabolic rate by the determination of oxygen consumption (O2) (with a spirometer), the production of carbon dioxide (CO2) and excretion of urinary nitrogen, for a given period of time [6]. This technique relies on the fact that all the O2 consumed and CO2 produced is due to the oxidation of the three major energy substrates, which are fats, carbohydrates and proteins [7].

Recognizing the need to estimate EE in institutions that have no indirect calorimetry, researchers have proposed the use of specific equations, developed from calorimetry studies in groups of individuals with similar clinical characteristics [8]. Although the estimate of EE

is the most common method, the predictive equations might generate errors [9]. Shetty [10] considers that the equations used to estimate the BEE in normal weight adults have reasonable precision (coefficient of variation 8%).

Energy Expenditure Measured by Indirect Calorimetry in Obesity 311

According to Green (1994) [19], this technique is based on the principles that there are no considerable reserves of O2 in the body, the O2 uptake reflects the oxidation of nutrients, that all the chemical energy in the body comes from the oxidation of carbohydrates, fats and proteins, and that the ratio of O2 consumption and CO2 produced for the oxidation of these macronutrients are fixed. After determining the concentration of O2 inspired and CO2 expired, the calculation of RMR can be done with the equation of Weir (1949) [20, 21].

Given the difficulties associated with urine collection 24 hours, and found little difference between the results using the complete formula and simplified (2%), many authors have chosen to use the equation of Weir (1949) disregarding urinary losses of nitrogen [22].

The amount of O2 used for oxidation and CO2 production will depend on the substrate being oxidized. The respiratory quotient (RQ = Volume CO2/Volume O2) varies with the nutrients are being oxidized [14]. The table below describes the values of RQ complexes

> 0.85 Oxidation of a mixed diet 1.0 Carboydrate oxidation

The RQ is divided into non-protein RQ, which reflects the participation of carbohydrates and fats, and protein RQ, which represents the use of proteins. The rate of protein oxidation is obtained by determining the amount of nitrogen excreted in the urine during the test [7, 8].

The evaluation of RMR should only be initiated after a period of rest to minimize possible effects of recent physical activities such as dressing, driving or walking. In practice, it is recommended around twenty minutes of rest, for longer periods can cause the individual to

During the measurement of RMR, the ambient temperature should be maintained in the neutral thermal zone, ie between 25 and 26°C, by Henry & Emery (1986) [14]. In order to evaluate the effects of temperature on EE, Dauncey (1981) [23] subjected women to direct calorimetry for thirty (30) hours at 22°C and 28°C. The evaluation of the RMR morning for 30 minutes, after twelve hours of fasting, demonstrated that the production of heat at the lowest temperature (22°C) was significantly greater (mean of 11 ± 3.2%) compared to the higher temperature (28ºC). Wahrlich & Anjos (2001) [14] point out that at ambient temperatures below the neutral zone, the use of protective clothing may be sufficient to

**RQ Interpretation** 0.67 Ethanol oxidation 0.71 Fat oxidation 0.82 Protein oxidation

1.0 – 1.2 Lipogenesis

**Table 1.** Values for interpretation of respiratory quotient (RQ) according to substrate

corresponding to the use of energy substrates [22].

Adapted of Materese (1997) [22].

sleep or get impatient [14].

prevent the increase in EE caused by the cold.

oxidation.

In clinical practice it is impracticable to measure the calorimetric methods for EE, so the international use of the equations was recommended, modified from a compilation of data carried out by Schofield [11]. Studies conducted in different ethnic groups found that these equations provide high BEE estimates, particularly for residents in the tropics [12-14]. Wahrlich and Anjos [14] confer these differences to the fact that equations have been developed mostly from population samples of North America and Europe which show differences in body composition, and live in different environmental conditions.

It is known that in populations with severe obesity is actually more difficult to fit the equations, because there is the difficulty in choosing the weight to be applied in the equation, which may influence a lot the results [15]. The use of current weight leads to the overestimation of the results independent of the equation to be applied, and the use of ideal or adjusted weight can result in the underestimation of energy needs [16].

Considering that obesity is a chronic disease of epidemiological importance, nutritional intervention studies have been developed in order to propose strategies for the prevention and treatment of this disease. The chronic imbalance between energy intake and EE results in positive energy balance and body weight gain. One way of evaluating the influence of dietary components in the EE, it through the measurement of energy metabolism by indirect calorimetry.

Obesity is also considered multifactorial, with genetic and environmental causes. In this sense, also studied the influence of candidate genes to obesity in metabolic variables, and indirect calorimetry is used in these studies.

The purpose of this chapter is to assess the importance of indirect calorimetry in the assessment of EE in obese individuals, both in study of nutrition intervention and influence of genes in EE, and in the validation and adequacy of existing prediction equations, which were not created for this population.

### **2. Indirect calorimetry**

Indirect calorimetry remains a gold standard in measuring EE in the clinical settings. Indirect calorimetry offers a scientifically-based approach to customize a patient's energy needs and nutrient delivery to maximize the benefits of nutrition therapy. With recent advances in technology, indirect calorimeters are easier to operate, more portable, and affordable. Increased utilization of indirect calorimetry would facilitate individualized patient care and should lead to improved treatment outcomes [17].

Indirect calorimetry is considered a standard method, after validation by comparison with the direct calorimetry [18], however, its use is restricted to research due to the demanding cost and time for its conclusion [14], requiring the use of prediction equations in clinical practice.

According to Green (1994) [19], this technique is based on the principles that there are no considerable reserves of O2 in the body, the O2 uptake reflects the oxidation of nutrients, that all the chemical energy in the body comes from the oxidation of carbohydrates, fats and proteins, and that the ratio of O2 consumption and CO2 produced for the oxidation of these macronutrients are fixed. After determining the concentration of O2 inspired and CO2 expired, the calculation of RMR can be done with the equation of Weir (1949) [20, 21].

Given the difficulties associated with urine collection 24 hours, and found little difference between the results using the complete formula and simplified (2%), many authors have chosen to use the equation of Weir (1949) disregarding urinary losses of nitrogen [22].

The amount of O2 used for oxidation and CO2 production will depend on the substrate being oxidized. The respiratory quotient (RQ = Volume CO2/Volume O2) varies with the nutrients are being oxidized [14]. The table below describes the values of RQ complexes corresponding to the use of energy substrates [22].


Adapted of Materese (1997) [22].

Applications of Calorimetry in a Wide Context –

calorimetry.

practice.

reasonable precision (coefficient of variation 8%).

indirect calorimetry is used in these studies.

were not created for this population.

**2. Indirect calorimetry** 

310 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

is the most common method, the predictive equations might generate errors [9]. Shetty [10] considers that the equations used to estimate the BEE in normal weight adults have

In clinical practice it is impracticable to measure the calorimetric methods for EE, so the international use of the equations was recommended, modified from a compilation of data carried out by Schofield [11]. Studies conducted in different ethnic groups found that these equations provide high BEE estimates, particularly for residents in the tropics [12-14]. Wahrlich and Anjos [14] confer these differences to the fact that equations have been developed mostly from population samples of North America and Europe which show

It is known that in populations with severe obesity is actually more difficult to fit the equations, because there is the difficulty in choosing the weight to be applied in the equation, which may influence a lot the results [15]. The use of current weight leads to the overestimation of the results independent of the equation to be applied, and the use of ideal

Considering that obesity is a chronic disease of epidemiological importance, nutritional intervention studies have been developed in order to propose strategies for the prevention and treatment of this disease. The chronic imbalance between energy intake and EE results in positive energy balance and body weight gain. One way of evaluating the influence of dietary components in the EE, it through the measurement of energy metabolism by indirect

Obesity is also considered multifactorial, with genetic and environmental causes. In this sense, also studied the influence of candidate genes to obesity in metabolic variables, and

The purpose of this chapter is to assess the importance of indirect calorimetry in the assessment of EE in obese individuals, both in study of nutrition intervention and influence of genes in EE, and in the validation and adequacy of existing prediction equations, which

Indirect calorimetry remains a gold standard in measuring EE in the clinical settings. Indirect calorimetry offers a scientifically-based approach to customize a patient's energy needs and nutrient delivery to maximize the benefits of nutrition therapy. With recent advances in technology, indirect calorimeters are easier to operate, more portable, and affordable. Increased utilization of indirect calorimetry would facilitate individualized

Indirect calorimetry is considered a standard method, after validation by comparison with the direct calorimetry [18], however, its use is restricted to research due to the demanding cost and time for its conclusion [14], requiring the use of prediction equations in clinical

patient care and should lead to improved treatment outcomes [17].

differences in body composition, and live in different environmental conditions.

or adjusted weight can result in the underestimation of energy needs [16].

**Table 1.** Values for interpretation of respiratory quotient (RQ) according to substrate oxidation.

The RQ is divided into non-protein RQ, which reflects the participation of carbohydrates and fats, and protein RQ, which represents the use of proteins. The rate of protein oxidation is obtained by determining the amount of nitrogen excreted in the urine during the test [7, 8].

The evaluation of RMR should only be initiated after a period of rest to minimize possible effects of recent physical activities such as dressing, driving or walking. In practice, it is recommended around twenty minutes of rest, for longer periods can cause the individual to sleep or get impatient [14].

During the measurement of RMR, the ambient temperature should be maintained in the neutral thermal zone, ie between 25 and 26°C, by Henry & Emery (1986) [14]. In order to evaluate the effects of temperature on EE, Dauncey (1981) [23] subjected women to direct calorimetry for thirty (30) hours at 22°C and 28°C. The evaluation of the RMR morning for 30 minutes, after twelve hours of fasting, demonstrated that the production of heat at the lowest temperature (22°C) was significantly greater (mean of 11 ± 3.2%) compared to the higher temperature (28ºC). Wahrlich & Anjos (2001) [14] point out that at ambient temperatures below the neutral zone, the use of protective clothing may be sufficient to prevent the increase in EE caused by the cold.

312 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Compher et al. (2006) [24] conducted a systematic literature review to determine the optimal conditions for obtaining reliable measures of RMR by indirect calorimetry. Based on this survey, the following information was highlighted by the authors: 1) food, ethanol, caffeine and nicotine affect RMR for a variable number of hours after consumption, so its use should be controlled prior to measurement, 2) daily activities increased the RMR, however, a short rest period (20 minutes) before the test is sufficient, 3) moderate or vigorous physical activities presented most impact on the metabolism and therefore should be avoided in hours prior to measurement of RMR; 4 ) the measure with a duration of ten minutes with the first five minutes disregarded, and the remaining five minutes with a coefficient of variation of up to 10% guarantee accurate measurements of RMR, 5) the trial site should be physically comfortable and should be evaluated for ten to twenty minutes of rest before the start of measurement.

Energy Expenditure Measured by Indirect Calorimetry in Obesity 313

necessary to know its methodological features and its theoretical and practical limitations. Indirect calorimetry measures the rate of REE, the major component of the TEE. Coupling the measurement of body composition to that of REE expands the diagnostic potential of indirect calorimetry. Once the lean and fat compartments have been measured, it is possible to establish on the basis of REE whether an individual is hyper- or hypometabolic. The

Although the basic principles of indirect calorimetry are well established, it is important to recognize that there are several potential pitfalls in the methodology and data interpretation that must be appreciated to properly understand and apply the results derived from this technique. One must recognize that the fundamental measurement provided by indirect calorimetry is the net disappearance rate of a substrate regardless of the metabolic interconversions that the substrate may undergo before its disappearance from its metabolic pool. Under most circumstances, direct oxidation represents the major route by which a substrate disappears from its metabolic pool, and the two terms are often used interchangeably. However, under conditions when rates of gluconeogenesis, ketogenesis, or lipogenesis are elevated, the presumed equivalence between oxidation and disappearance may no longer apply, even though the actual measurements derived from indirect calorimetry remain valid. When indirect calorimetry is combined with other in vivo metabolic techniques (e.g., the insulin clamp or radioisotope turnover methods) it can provide a powerful tool for noninvasively examining complex metabolic processes [27].

Indirect calorimetry can also evaluate BEE. The main difference between REE and BEE is that REE is measured after the individual dislocation to the exam site, necessitating the prior resting period of 30 minutes to neutralize the effects of the physical activity performed [28].

Kross et al [30] evaluated the accuracy of multiple regression equations to estimate REE in critically ill patients, especially for obese patients. A total of 927 patients were identified, including 401 obese patients. There were bias and poor agreement between measured REE and REE predicted by the Harris-Benedict, Owen, American College of Chest Physicians, and Mifflin equations (p > 0.05). There was poor agreement between measured and predicted REE by the Ireton-Jones equation, stratifying by sex. Ireton-Jones was the only equation that was unbiased for men and those in weight categories 1 and 2. In all cases except Ireton-Jones, predictive equations underestimated measured REE. The authors concluded that none of these equations accurately estimated measured REE in this group of mechanically ventilated patients, most underestimating energy needs. The authors concluded that is necessary to develop predictive equations for adequate assessment of

clinical applications are practically unlimited [26].

Study found that REE is 10-15% higher than the BEE [29].

**3. Utilization of indirect calorimetry in obesity** 

**3.1. Evaluation of prediction equations** 

energy needs.

For research on assessment of RMR recommended: fasting for at least 6 hours, abstaining from caffeine during the night, nicotine and alcohol for at least 2 hours, of moderate physical activity for at least 2 hours, and vigorous physical activity for 14 hours [24].

In relation to the proper position for holding the indirect calorimetry, the authors emphasize that the most important is to ensure that each individual is physically comfortable during the test, and that measures are always taken in the same position. However, they warn that some positions require increased muscle tone and, therefore, could influence the measurement of RMR, and for research that has attempted to evaluate the RMR should keep the individual in the supine posture with or slightly higher [24].

The time required for obtaining an accurate measurement of RMR is only about five to ten minutes, discarding the first five minutes, provided that no changes occur in over 10% VO2 and VCO2 and 5% in RQ. Accordingly, one measure would be sufficient to describe the RMR for twenty-four hours. However, if you cannot guarantee the stability of the readings, the combination of two or three repetitions increase the precision of the measurements for the extrapolation to twenty-four hours [8, 24].

For studies involving analysis of the thermic effect of food (TEF), the indirect calorimetry should be conducted for a period of 6 hours, as measured by shorter periods are not able to fully assess the TEF [24].

With regard to environmental characteristics, it is recommended that the room temperature is comfortable, that is, between 20 and 25°C, the environment is quiet, with soft lighting and humidity control [24].

In females, should be avoided that the energy metabolism assessments are performed during the luteal phase because this phase of the menstrual cycle are described changes such as water retention, increased of body weight and energy demand, changes in lipid profile and metabolism of some nutrients (vitamin D, calcium, magnesium and iron), emotional hypersensitivity, aches and changes in eating behavior [25].

So, indirect calorimetry is a simple and affordable tool for measuring EE and for quantifying the utilization of macronutrients. Its use is becoming increasingly widespread, but it is necessary to know its methodological features and its theoretical and practical limitations. Indirect calorimetry measures the rate of REE, the major component of the TEE. Coupling the measurement of body composition to that of REE expands the diagnostic potential of indirect calorimetry. Once the lean and fat compartments have been measured, it is possible to establish on the basis of REE whether an individual is hyper- or hypometabolic. The clinical applications are practically unlimited [26].

Although the basic principles of indirect calorimetry are well established, it is important to recognize that there are several potential pitfalls in the methodology and data interpretation that must be appreciated to properly understand and apply the results derived from this technique. One must recognize that the fundamental measurement provided by indirect calorimetry is the net disappearance rate of a substrate regardless of the metabolic interconversions that the substrate may undergo before its disappearance from its metabolic pool. Under most circumstances, direct oxidation represents the major route by which a substrate disappears from its metabolic pool, and the two terms are often used interchangeably. However, under conditions when rates of gluconeogenesis, ketogenesis, or lipogenesis are elevated, the presumed equivalence between oxidation and disappearance may no longer apply, even though the actual measurements derived from indirect calorimetry remain valid. When indirect calorimetry is combined with other in vivo metabolic techniques (e.g., the insulin clamp or radioisotope turnover methods) it can provide a powerful tool for noninvasively examining complex metabolic processes [27].

Indirect calorimetry can also evaluate BEE. The main difference between REE and BEE is that REE is measured after the individual dislocation to the exam site, necessitating the prior resting period of 30 minutes to neutralize the effects of the physical activity performed [28]. Study found that REE is 10-15% higher than the BEE [29].

### **3. Utilization of indirect calorimetry in obesity**

### **3.1. Evaluation of prediction equations**

Applications of Calorimetry in a Wide Context –

start of measurement.

312 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Compher et al. (2006) [24] conducted a systematic literature review to determine the optimal conditions for obtaining reliable measures of RMR by indirect calorimetry. Based on this survey, the following information was highlighted by the authors: 1) food, ethanol, caffeine and nicotine affect RMR for a variable number of hours after consumption, so its use should be controlled prior to measurement, 2) daily activities increased the RMR, however, a short rest period (20 minutes) before the test is sufficient, 3) moderate or vigorous physical activities presented most impact on the metabolism and therefore should be avoided in hours prior to measurement of RMR; 4 ) the measure with a duration of ten minutes with the first five minutes disregarded, and the remaining five minutes with a coefficient of variation of up to 10% guarantee accurate measurements of RMR, 5) the trial site should be physically comfortable and should be evaluated for ten to twenty minutes of rest before the

For research on assessment of RMR recommended: fasting for at least 6 hours, abstaining from caffeine during the night, nicotine and alcohol for at least 2 hours, of moderate

In relation to the proper position for holding the indirect calorimetry, the authors emphasize that the most important is to ensure that each individual is physically comfortable during the test, and that measures are always taken in the same position. However, they warn that some positions require increased muscle tone and, therefore, could influence the measurement of RMR, and for research that has attempted to evaluate the RMR should keep

The time required for obtaining an accurate measurement of RMR is only about five to ten minutes, discarding the first five minutes, provided that no changes occur in over 10% VO2 and VCO2 and 5% in RQ. Accordingly, one measure would be sufficient to describe the RMR for twenty-four hours. However, if you cannot guarantee the stability of the readings, the combination of two or three repetitions increase the precision of the measurements for the

For studies involving analysis of the thermic effect of food (TEF), the indirect calorimetry should be conducted for a period of 6 hours, as measured by shorter periods are not able to

With regard to environmental characteristics, it is recommended that the room temperature is comfortable, that is, between 20 and 25°C, the environment is quiet, with soft lighting and

In females, should be avoided that the energy metabolism assessments are performed during the luteal phase because this phase of the menstrual cycle are described changes such as water retention, increased of body weight and energy demand, changes in lipid profile and metabolism of some nutrients (vitamin D, calcium, magnesium and iron), emotional

So, indirect calorimetry is a simple and affordable tool for measuring EE and for quantifying the utilization of macronutrients. Its use is becoming increasingly widespread, but it is

physical activity for at least 2 hours, and vigorous physical activity for 14 hours [24].

the individual in the supine posture with or slightly higher [24].

hypersensitivity, aches and changes in eating behavior [25].

extrapolation to twenty-four hours [8, 24].

fully assess the TEF [24].

humidity control [24].

Kross et al [30] evaluated the accuracy of multiple regression equations to estimate REE in critically ill patients, especially for obese patients. A total of 927 patients were identified, including 401 obese patients. There were bias and poor agreement between measured REE and REE predicted by the Harris-Benedict, Owen, American College of Chest Physicians, and Mifflin equations (p > 0.05). There was poor agreement between measured and predicted REE by the Ireton-Jones equation, stratifying by sex. Ireton-Jones was the only equation that was unbiased for men and those in weight categories 1 and 2. In all cases except Ireton-Jones, predictive equations underestimated measured REE. The authors concluded that none of these equations accurately estimated measured REE in this group of mechanically ventilated patients, most underestimating energy needs. The authors concluded that is necessary to develop predictive equations for adequate assessment of energy needs.

314 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Ullah et al [31] compared measured REE using the bedside with indirect calorimetry commonly used prediction equations, considering that the accuracy of prediction equations for estimating REE in morbidly obese patients is unclear. A total of 31 morbidly obese patients (46 kg/m2) were studied. Pre-operative REE with indirect calorimetry was measured and compared with estimated REE using the Harris-Benedict and Schofield equations. All patients subsequently underwent a Roux-en-Y gastric bypass and were repeated measurements at six weeks and three months following surgery. The equations overestimated REE by 10% and 7%, by Harris-Benedict and Schofield equations, respectively. After weight loss the difference between the estimated and measured REE reduced to 1.3%. The accuracy improved after surgery induced weight loss, confirming their validity for the normal weight population. The study demonstrated that indirect calorimetry should be used in morbid obesity.

Energy Expenditure Measured by Indirect Calorimetry in Obesity 315

body weight (1.873 + 484 kcal / day and 1798 + 495 kcal / day for HB and indirect calorimetry, respectively). However, the authors emphasize the need to employ the indirect calorimetry for the determination of EE of obese, because despite the similarity found between the absolute REE measured by indirect calorimetry and the prediction equation, there are significant ranges of variability, suggesting that the ideal method and more

**3.2. Evaluation of the effect of nutritional interventions and obesity candidate** 

Study with 60 obese women (34.59 ± 7.56 years) was conducted in order to evaluate the influence of fat diet and peroxisome proliferator-activated (PPAR2) and β2-adrenergic receptor genes on energy metabolism. It was found that polymorphism in PPARgamma2 resulted in increased in fat oxidation, regardless of genotype of β2-adrenergic receptor gene. Polyunsaturated fatty acids (PUFA) intake can assist in weight loss, but the genotype of the

The same research group developed another study with sixty obese women (30–46 years) which were divided into two groups depending on the genotype of PPAR2 (Pro12Pro and Pro-12Ala/Ala12Ala). At baseline and after two nutritional (short- or long-term) interventions, measurement of anthropometrical and body composition (bioelectrical impedance) variables, dietary assessments, energy metabolism (indirect calorimetry) measurements as well as biochemical and molecular (PPAR2 genotype) analyses were performed. All women received a high-fat test meal to determine the post-prandial metabolism (short term) and an energy-restricted diet for 10 weeks to determine the effect of diet in long term. The Pro12Ala polymorphism in the PPAR2 gene influenced energy metabolism in the assayed short- and long-term situations since the response to both nutritional interventions differed according to the genotype. The results suggest that fat oxidation and EE may be lower in Pro12Pro carriers compared to Pro12Ala/Ala12Ala genotypes, while in obese women with Pro12Ala/Ala12Ala polymorphisms in the PPAR2 gene fat oxidation was negatively correlated with the monounsaturated fatty acids (MUFA)

The difference in structure of fatty acids, including the chain length, degree of unsaturation and the position of the double bond, can affect the rate of oxidation of fatty acids. Medium chain saturated fatty acids (MCSFA) are more easily oxidized than the long chain saturated fatty acids (LCSFA), while unsaturated fatty acids (UFA) are more easily oxidized compared

Using indirect calorimetry studies also indicate that the PUFA shows a higher oxidation compared to SFA, both in men and in obese normal [37, 38]. Piers et al (2002) [39] found that changes in the type of fat dietary may have a beneficial effect on reducing body weight in men who consume high fat content, since the oxidation rate postprandial (assessed by Indirect calorimetry) of nutrient is increased after a high MUFA meal, compared with the

accurate to obtain the actual REE in this population is the indirect calorimetry.

genes assessed determines the type of fat that should be ingested [34].

to saturated chain acids (SFA) with the same chain length [36].

**genes in energy expenditure** 

and PUFA (%) intake [35].

SFA.

Cross-sectional study developed by our research group (unpublished data) with 92 women (35.60 ± 6.66 years) with excess body weight (34.41 ± 4.71 kg/m2), Brazilian and Spanish. This study assessed the women in a metabolic unit, after fasting for 12 hours without performing strenuous physical activity in the last 24 hours and with minimal effort. The evaluation was performed using the open-circuit respiratory hood with indirect calorimetry (Deltatrac Metabolic Monitor-R3D) [6]. For the calculation of EE, it was used the values of the following volumes; inspired O2 (VO2), expired CO2 (VCO2) (ml / min) and urinary nitrogen [6-28], obtained by the calorimeter. In Brazilian women, it was found that the estimates obtained by Harris-Benedict, Shofield, FAO / WHO /ONU and Henry & Rees did not differ from REE of indirect calorimetry, which presented higher values than the equations proposed by Owen, Mifflin-St Jeor and Oxford. In Spanish women, also the equations proposed by Owen, Mifflin-St Jeor and Oxford presented EE lower than the indirect calorimetry, while the other equations did not differ from the indirect calorimetry. Both are women, Brasilian and Spanish, the best equations were FAO / WHO / ONU, Harris-Benedict Shofield and Henry & Rees.

Study aimed to validate the published predictive equations for REE in 76 normal weight (44.8 kg, 19.0 kg/m2) and 52 obese (64.0 kg, 25.9 kg/m2) Korean children and adolescents in the 7-18 years old age group. The open-circuit indirect calorimetry using a ventilated hood system was used to measure REE. Sixteen REE predictive equations were included, which were based on weight and/or height of children and adolescents, or which were commonly used in clinical settings despite its use based on adults. For the obese group, the Molnar, Mifflin, Liu, and Harris-Benedict equations provided the accurate predictions of > 70% (87%, 79% 77%, and 73%, respectively). On the other hand, for non-obese group, only the Molnar equation had a high level of accuracy (bias of 0.6%, RMSPE of 90.4 kcal/d, and accurate prediction of 72%). The accurate prediction of the Schofield (W/WH), WHO (W/WH), and Henry (W/WH) equations was less than 60% for all groups [32].

Alves et al. (2009) [33] compared the RMR obtained by indirect calorimetry with predict equations (Harris-Benedict (HB) and Ireton-Jones (IJ)) in 44 patients with excess body weight. The nearest RMR in fasting was obtained with the equation HB using the current body weight (1.873 + 484 kcal / day and 1798 + 495 kcal / day for HB and indirect calorimetry, respectively). However, the authors emphasize the need to employ the indirect calorimetry for the determination of EE of obese, because despite the similarity found between the absolute REE measured by indirect calorimetry and the prediction equation, there are significant ranges of variability, suggesting that the ideal method and more accurate to obtain the actual REE in this population is the indirect calorimetry.

Applications of Calorimetry in a Wide Context –

should be used in morbid obesity.

Shofield and Henry & Rees.

314 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Ullah et al [31] compared measured REE using the bedside with indirect calorimetry commonly used prediction equations, considering that the accuracy of prediction equations for estimating REE in morbidly obese patients is unclear. A total of 31 morbidly obese patients (46 kg/m2) were studied. Pre-operative REE with indirect calorimetry was measured and compared with estimated REE using the Harris-Benedict and Schofield equations. All patients subsequently underwent a Roux-en-Y gastric bypass and were repeated measurements at six weeks and three months following surgery. The equations overestimated REE by 10% and 7%, by Harris-Benedict and Schofield equations, respectively. After weight loss the difference between the estimated and measured REE reduced to 1.3%. The accuracy improved after surgery induced weight loss, confirming their validity for the normal weight population. The study demonstrated that indirect calorimetry

Cross-sectional study developed by our research group (unpublished data) with 92 women (35.60 ± 6.66 years) with excess body weight (34.41 ± 4.71 kg/m2), Brazilian and Spanish. This study assessed the women in a metabolic unit, after fasting for 12 hours without performing strenuous physical activity in the last 24 hours and with minimal effort. The evaluation was performed using the open-circuit respiratory hood with indirect calorimetry (Deltatrac Metabolic Monitor-R3D) [6]. For the calculation of EE, it was used the values of the following volumes; inspired O2 (VO2), expired CO2 (VCO2) (ml / min) and urinary nitrogen [6-28], obtained by the calorimeter. In Brazilian women, it was found that the estimates obtained by Harris-Benedict, Shofield, FAO / WHO /ONU and Henry & Rees did not differ from REE of indirect calorimetry, which presented higher values than the equations proposed by Owen, Mifflin-St Jeor and Oxford. In Spanish women, also the equations proposed by Owen, Mifflin-St Jeor and Oxford presented EE lower than the indirect calorimetry, while the other equations did not differ from the indirect calorimetry. Both are women, Brasilian and Spanish, the best equations were FAO / WHO / ONU, Harris-Benedict

Study aimed to validate the published predictive equations for REE in 76 normal weight (44.8 kg, 19.0 kg/m2) and 52 obese (64.0 kg, 25.9 kg/m2) Korean children and adolescents in the 7-18 years old age group. The open-circuit indirect calorimetry using a ventilated hood system was used to measure REE. Sixteen REE predictive equations were included, which were based on weight and/or height of children and adolescents, or which were commonly used in clinical settings despite its use based on adults. For the obese group, the Molnar, Mifflin, Liu, and Harris-Benedict equations provided the accurate predictions of > 70% (87%, 79% 77%, and 73%, respectively). On the other hand, for non-obese group, only the Molnar equation had a high level of accuracy (bias of 0.6%, RMSPE of 90.4 kcal/d, and accurate prediction of 72%). The accurate prediction of the Schofield (W/WH), WHO (W/WH), and

Alves et al. (2009) [33] compared the RMR obtained by indirect calorimetry with predict equations (Harris-Benedict (HB) and Ireton-Jones (IJ)) in 44 patients with excess body weight. The nearest RMR in fasting was obtained with the equation HB using the current

Henry (W/WH) equations was less than 60% for all groups [32].

### **3.2. Evaluation of the effect of nutritional interventions and obesity candidate genes in energy expenditure**

Study with 60 obese women (34.59 ± 7.56 years) was conducted in order to evaluate the influence of fat diet and peroxisome proliferator-activated (PPAR2) and β2-adrenergic receptor genes on energy metabolism. It was found that polymorphism in PPARgamma2 resulted in increased in fat oxidation, regardless of genotype of β2-adrenergic receptor gene. Polyunsaturated fatty acids (PUFA) intake can assist in weight loss, but the genotype of the genes assessed determines the type of fat that should be ingested [34].

The same research group developed another study with sixty obese women (30–46 years) which were divided into two groups depending on the genotype of PPAR2 (Pro12Pro and Pro-12Ala/Ala12Ala). At baseline and after two nutritional (short- or long-term) interventions, measurement of anthropometrical and body composition (bioelectrical impedance) variables, dietary assessments, energy metabolism (indirect calorimetry) measurements as well as biochemical and molecular (PPAR2 genotype) analyses were performed. All women received a high-fat test meal to determine the post-prandial metabolism (short term) and an energy-restricted diet for 10 weeks to determine the effect of diet in long term. The Pro12Ala polymorphism in the PPAR2 gene influenced energy metabolism in the assayed short- and long-term situations since the response to both nutritional interventions differed according to the genotype. The results suggest that fat oxidation and EE may be lower in Pro12Pro carriers compared to Pro12Ala/Ala12Ala genotypes, while in obese women with Pro12Ala/Ala12Ala polymorphisms in the PPAR2 gene fat oxidation was negatively correlated with the monounsaturated fatty acids (MUFA) and PUFA (%) intake [35].

The difference in structure of fatty acids, including the chain length, degree of unsaturation and the position of the double bond, can affect the rate of oxidation of fatty acids. Medium chain saturated fatty acids (MCSFA) are more easily oxidized than the long chain saturated fatty acids (LCSFA), while unsaturated fatty acids (UFA) are more easily oxidized compared to saturated chain acids (SFA) with the same chain length [36].

Using indirect calorimetry studies also indicate that the PUFA shows a higher oxidation compared to SFA, both in men and in obese normal [37, 38]. Piers et al (2002) [39] found that changes in the type of fat dietary may have a beneficial effect on reducing body weight in men who consume high fat content, since the oxidation rate postprandial (assessed by Indirect calorimetry) of nutrient is increased after a high MUFA meal, compared with the SFA.

316 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Casas-Agustench et al (2009) [40] aimed to compare the acute effects of three fatty meals with different fat quality on postprandial thermogenesis and substrate oxidation. Evaluated twenty-nine healthy men aged between 18 and 30 years in randomized crossover trial, comparing the thermogenic effects of three isocaloric meals: high in PUFA from walnuts, high in MUFA from olive oil, and high in SFA from fat-rich dairy products. Indirect calorimetry was used to determine RMR, RQ, 5-H postprandial EE and substrate oxidation. Five hours postprandial thermogenesis was higher by 28% after the high PUFA meal (p = 0.039) and by 23% higher after the high MUFA meal (p = 0.035), compared with the high SFA meal. Increased fat oxidation rates no significantly after the two meals rich in UFA and decreased non significantly after the high SFA meal. Postprandial RQ, carbohydrate and protein oxidation measures were similar among meals. The authors concluded that fat quality determined the thermogenic response to a fatty meal but clear effects on substrate oxidation.

Energy Expenditure Measured by Indirect Calorimetry in Obesity 317

fat-rich meal in both groups (*p* < 0.01). CHO oxidation rate increased in both groups after consumption of the CHO-rich meal (*p* < 0.001). Oxidation rates of protein, fat, and CHO during the experiment were not significantly different between lean and obese participants. In conclusion, it was verified that meal-induced thermogenesis and macronutrient oxidation rates were not significantly different between lean and obese women after consumption of a

In a parallel-arm, long-term feeding trial, 24 lean and 24 overweight participants received a daily peanut oil load in a milk shake equivalent to 30% of their REE for eight weeks to evaluate the effects of peanut oil intake on appetite, EE (indirect calorimetry at baseline and week 8), body composition, and lipid profile. Energy intake increased significantly in the overweight but not in the lean participants. A statistically significant body weight gain (median 2.35 kg) was also observed among the overweight subjects, although this corresponded to only 43% of the theoretical weight gain. In the overweight participants, the REE was significantly increased by 5% over the intervention, but no significant difference was observed in the lean subjects. As expected, REE was significantly higher in the overweight than in the lean participants. No marked differences of appetite were observed over time in either group or between overweight and lean participants. These data indicate that ingestion of peanut oil elicits a weaker compensatory dietary response among overweight compared with lean individuals. Body weight increased, albeit less than

The effects of a moderate-fat diet, high in MUFAs, and a low-fat (LF) diet on EE and macronutrient oxidation before and after a 6-mo controlled dietary intervention were compared. Twenty-seven overweight (body mass index 28.1 + 0.4 kg/m2) nondiabetic subjects (18–36 years) followed an 8-wk low-calorie diet and a 2-wk weight-stabilizing diet and then were randomly assigned to a MUFA (*n* = 12) or LF (*n =* 15) diet for 6 mo. Substrate oxidation and 24-h EE were measured by whole-body indirect calorimetry. The first measurement (0 mo) was taken during the weight-stabilizing diet, and the second measurement was taken after the 6-mo intervention. A tendency was seen toward a lower 24-h EE with the MUFA than with the LF diet (*p* = 0.0675), but this trend did not remain after adjustment for the initial loses of fat mass and FFM (*p* = 0.2963). Meal-induced thermogenesis was significantly (*p* < 0.05) lower with the MUFA than with the LF diet. Despite a slightly lower meal-induced thermogenesis, the MUFA diet had an effect on 24-h EE that was not significantly different from that of the LF diet after a 6-mo controlled

Study with 24 healthy, overweight men (body mass index between 25 and 31 kg/m2) compared the effects of diets rich in medium-chain triglycerides (MCTs) or long-chain triglycerides (LCTs) on body composition, EE, substrate oxidation, subjective appetite, and *ad libitum* energy intake. At baseline and after four weeks of each dietary intervention, EE was measured using indirect calorimetry. Average EE was 0.04 + 0.02 kcal/min greater (*p* < 0.05) on day 2 and 0.03 + 0.02 kcal/min (not significant) on day 28 with functional oil (64.7% MCT oil) compared with olive oil consumption. Similarly, average fat oxidation was greater (*p* = 0.052) with functional oil compared with olive oil intake on day 2 but not day 28.

CHO-rich or a fat-rich meal [42].

theoretically predicted [43].

dietary intervention [44].

Another study was conducted to evaluate whether postprandial abnormalities of EE and / or lipid oxidation are present in healthy, normal-weight individuals with a strong family history of obesity and thus at high risk to become obese. They conducted a case-control study. A total of 16 healthy young men participated in the study. Eight individuals had both parents overweight (father's and mother's body mass index > 25 kg / m2) and eight had both parents with normal body weight (father's and mother's body mass index < 25 kg / m2). The group of individuals with overweight parents was similar to that with normal-weight parents (control group) in terms of body mass index and FFM. EE was measured by indirect calorimetry, and blood samples were taken for the evaluation of metabolic variables in the fasting state and every hour for 8 h after a standard fat-rich meal (protein 15%, 34% carbohydrate, 51 fat %, 4090 kJ). Fasting and postprandial EE, and fasting fat and carbohydrate oxidation were both in similar groups. On the contrary, postprandial carbohydrate oxidation (incremental area under curve) was significantly higher and that of fat oxidation lower in the group of individuals with overweight parents. They concluded that normal-weight individuals with a strong family history of obesity present a reduced fat oxidation in the postprandial period. These metabolic characteristics may be considered the early predictors of weight gain and are genetically determined probably [41].

Differences in meal-induced thermogenesis and macronutrient oxidation between lean (*n =*  19) and obese (*n =* 22) women after consumption of two different isocaloric meals, one rich in carbohydrate (CHO) and one rich in fat were examined. Women were studied on two occasions, one week apart. In one visit they consumed a CHO-rich meal and in the other visit a fat-rich meal. The two meals were isocaloric and were given in random order. REE and macronutrient oxidation rates were measured and calculated in the fasting state and every hour for 3 h after meal consumption. Meal-induced thermogenesis was not different between lean and obese subjects after the CHO-rich (*p =* 0.89) or fat-rich (*p =* 0.32) meal, but it was significantly higher after the CHO-rich compared with the fat-rich meal in the lean and the obese individuals (*p* < 0.05). Protein oxidation rate increased slightly but significantly after the test meals in both groups (*p* < 0.01). Fat oxidation rate decreased after consumption of the CHO-rich meal (*p* < 0.001), whereas it increased after consumption of the fat-rich meal in both groups (*p* < 0.01). CHO oxidation rate increased in both groups after consumption of the CHO-rich meal (*p* < 0.001). Oxidation rates of protein, fat, and CHO during the experiment were not significantly different between lean and obese participants. In conclusion, it was verified that meal-induced thermogenesis and macronutrient oxidation rates were not significantly different between lean and obese women after consumption of a CHO-rich or a fat-rich meal [42].

Applications of Calorimetry in a Wide Context –

oxidation.

316 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Casas-Agustench et al (2009) [40] aimed to compare the acute effects of three fatty meals with different fat quality on postprandial thermogenesis and substrate oxidation. Evaluated twenty-nine healthy men aged between 18 and 30 years in randomized crossover trial, comparing the thermogenic effects of three isocaloric meals: high in PUFA from walnuts, high in MUFA from olive oil, and high in SFA from fat-rich dairy products. Indirect calorimetry was used to determine RMR, RQ, 5-H postprandial EE and substrate oxidation. Five hours postprandial thermogenesis was higher by 28% after the high PUFA meal (p = 0.039) and by 23% higher after the high MUFA meal (p = 0.035), compared with the high SFA meal. Increased fat oxidation rates no significantly after the two meals rich in UFA and decreased non significantly after the high SFA meal. Postprandial RQ, carbohydrate and protein oxidation measures were similar among meals. The authors concluded that fat quality determined the thermogenic response to a fatty meal but clear effects on substrate

Another study was conducted to evaluate whether postprandial abnormalities of EE and / or lipid oxidation are present in healthy, normal-weight individuals with a strong family history of obesity and thus at high risk to become obese. They conducted a case-control study. A total of 16 healthy young men participated in the study. Eight individuals had both parents overweight (father's and mother's body mass index > 25 kg / m2) and eight had both parents with normal body weight (father's and mother's body mass index < 25 kg / m2). The group of individuals with overweight parents was similar to that with normal-weight parents (control group) in terms of body mass index and FFM. EE was measured by indirect calorimetry, and blood samples were taken for the evaluation of metabolic variables in the fasting state and every hour for 8 h after a standard fat-rich meal (protein 15%, 34% carbohydrate, 51 fat %, 4090 kJ). Fasting and postprandial EE, and fasting fat and carbohydrate oxidation were both in similar groups. On the contrary, postprandial carbohydrate oxidation (incremental area under curve) was significantly higher and that of fat oxidation lower in the group of individuals with overweight parents. They concluded that normal-weight individuals with a strong family history of obesity present a reduced fat oxidation in the postprandial period. These metabolic characteristics may be considered the

early predictors of weight gain and are genetically determined probably [41].

Differences in meal-induced thermogenesis and macronutrient oxidation between lean (*n =*  19) and obese (*n =* 22) women after consumption of two different isocaloric meals, one rich in carbohydrate (CHO) and one rich in fat were examined. Women were studied on two occasions, one week apart. In one visit they consumed a CHO-rich meal and in the other visit a fat-rich meal. The two meals were isocaloric and were given in random order. REE and macronutrient oxidation rates were measured and calculated in the fasting state and every hour for 3 h after meal consumption. Meal-induced thermogenesis was not different between lean and obese subjects after the CHO-rich (*p =* 0.89) or fat-rich (*p =* 0.32) meal, but it was significantly higher after the CHO-rich compared with the fat-rich meal in the lean and the obese individuals (*p* < 0.05). Protein oxidation rate increased slightly but significantly after the test meals in both groups (*p* < 0.01). Fat oxidation rate decreased after consumption of the CHO-rich meal (*p* < 0.001), whereas it increased after consumption of the In a parallel-arm, long-term feeding trial, 24 lean and 24 overweight participants received a daily peanut oil load in a milk shake equivalent to 30% of their REE for eight weeks to evaluate the effects of peanut oil intake on appetite, EE (indirect calorimetry at baseline and week 8), body composition, and lipid profile. Energy intake increased significantly in the overweight but not in the lean participants. A statistically significant body weight gain (median 2.35 kg) was also observed among the overweight subjects, although this corresponded to only 43% of the theoretical weight gain. In the overweight participants, the REE was significantly increased by 5% over the intervention, but no significant difference was observed in the lean subjects. As expected, REE was significantly higher in the overweight than in the lean participants. No marked differences of appetite were observed over time in either group or between overweight and lean participants. These data indicate that ingestion of peanut oil elicits a weaker compensatory dietary response among overweight compared with lean individuals. Body weight increased, albeit less than theoretically predicted [43].

The effects of a moderate-fat diet, high in MUFAs, and a low-fat (LF) diet on EE and macronutrient oxidation before and after a 6-mo controlled dietary intervention were compared. Twenty-seven overweight (body mass index 28.1 + 0.4 kg/m2) nondiabetic subjects (18–36 years) followed an 8-wk low-calorie diet and a 2-wk weight-stabilizing diet and then were randomly assigned to a MUFA (*n* = 12) or LF (*n =* 15) diet for 6 mo. Substrate oxidation and 24-h EE were measured by whole-body indirect calorimetry. The first measurement (0 mo) was taken during the weight-stabilizing diet, and the second measurement was taken after the 6-mo intervention. A tendency was seen toward a lower 24-h EE with the MUFA than with the LF diet (*p* = 0.0675), but this trend did not remain after adjustment for the initial loses of fat mass and FFM (*p* = 0.2963). Meal-induced thermogenesis was significantly (*p* < 0.05) lower with the MUFA than with the LF diet. Despite a slightly lower meal-induced thermogenesis, the MUFA diet had an effect on 24-h EE that was not significantly different from that of the LF diet after a 6-mo controlled dietary intervention [44].

Study with 24 healthy, overweight men (body mass index between 25 and 31 kg/m2) compared the effects of diets rich in medium-chain triglycerides (MCTs) or long-chain triglycerides (LCTs) on body composition, EE, substrate oxidation, subjective appetite, and *ad libitum* energy intake. At baseline and after four weeks of each dietary intervention, EE was measured using indirect calorimetry. Average EE was 0.04 + 0.02 kcal/min greater (*p* < 0.05) on day 2 and 0.03 + 0.02 kcal/min (not significant) on day 28 with functional oil (64.7% MCT oil) compared with olive oil consumption. Similarly, average fat oxidation was greater (*p* = 0.052) with functional oil compared with olive oil intake on day 2 but not day 28.

318 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Consumption of a diet rich in MCTs results in greater loss of adipose tissue compared with LCTs, perhaps due to increased EE and fat oxidation observed with MCT intake [45].

Energy Expenditure Measured by Indirect Calorimetry in Obesity 319

TEE - energy expenditure TEF - thermic effect of food UFA - unsaturated fatty acids

VO2 - inspired O2 VCO2 - expired CO2

**Author details** 

**Acknowledgement** 

**5. References** 

15(11):2546-8.

63(6):879-83.

37(3):287-301.

Eliane Lopes Rosado, Vanessa Chaia Kaippert and Roberta Santiago de Brito

Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG).

We thank the Federal University of Viçosa and Navarra University.

and non-white severely obese women. Nutr Hosp. 24(6):676-81.

body-weight gain. N Engl J Med 1988;318(8):467-72.

previous work. Hum Nutr Clin Nutr. 39 suppl 1:5-41.

utilization in man. Ann Rev Nutr. 7:187-208.

Review. J Am Diet Assoc. 105:775-89.

*Nutrição e Dietética Departament, Federal University of Rio de Janeiro, Rio de Janeiro, Brasil* 

This work was supported by Conselho Nacional de Pesquisa (CNPq) and Fundação de

[1] Flatt J-P (2007) Differences in Basal Energy Expenditure and Obesity. Obesity.

[2] Mika Horie L, González MC, Raslan M, torrinhas R, Rodrigues NL, Verotti CC, Cecconello I, Heymsfield SB, Waitzberg DL (2009) Resting energy expenditure in white

[3] Melo CM, Tirapegui J, Ribeiro SML (2008) Gasto energético corporal: conceitos, formas de avaliação e sua relação com a obesidade. Arq Bras Endocrinol Metab. 52(3):452-464. [4] Astrup A, Buemann B, Toubro S, Ranneries C, Raben A (1996) Low resting metabolic rate in subjects predisposed to obesity: a role for thyroid status. Am J Clin Nutr.

[5] Ravussin E, Lillioja S, Knowler WC, Christin L, Freymond D, Abbott WG, Boyce V, Howard BV, Bogardus C (1988) Reduced rate of energy expenditure as a risk factor for

[6] Ferrannini E (1988) The theoretical bases of indirect calorimetry: a review. Metabolism.

[7] Jéquier E, Acheson K, Schutz Y (1987) Assessment of energy expenditure and fuel

[9] Frankenfield D, Roth-Yousey L, Compher C (2005) Comparison of Predictive Equations for Resting Metabolic Rate in Healthy Nonobese and Obese Adults: A Systematic

[10] Shetty P (2005) Energy requirements of adults. Public Health Nutrition. 8(7A):994–1009. [11] Schofield WN (1985) Predicting basal metabolic rate, new standards and review of

[8] Diener JRC (1997) Calorimetria indireta. Rev Ass Med Brasil. 43(3):245-53.

A controlled randomized dietary trial was conducted with 26 overweight or moderately obese men and women (body mass index 28-33 kg/m2) to test the hypothesis that n-3 polyunsaturated fatty acids (n-3-PUFA) lower body weight and fat mass by reducing appetite and *ad libitum* food intake and/or by increasing EE. Diets were administered in an isocaloric fashion for 2 weeks followed by 12 weeks of *ad libitum* intake. The n-3-PUFA and control diets were identical in all regards except for the fatty acid composition. Both groups lost similar amounts of weight when these diets were consumed *ad libitum* for 12 weeks [mean (SD): -3.5 (3.7) kg in the control group vs. -2.8 (3.7) kg in the n-3-PUFA group, F(1,24) = 13.425, *p* = 0.001 for time effect; F(1,24) = 0.385, *p* = 0.541 for time × group interaction]. No differences were founds between the n-3-PUFA and control groups with regard to appetite as measured by visual analogue scale, *ad libitum* food intake or, REE as measured by indirect calorimetry, diurnal plasma leptin concentrations, or fasting ghrelin concentrations. These results suggest that dietary n-3-PUFA do not play an important role in the regulation of food intake, EE, or body weight in humans [46].

### **4. Conclusion**

Indirect calorimetry is useful technique in the metabolic evaluation of obese individuals. Despite some methodological limitations, is still the best way to estimate this variable in this population, which is useful both in studies of dietary intervention, intended to propose new strategies for prevention and treatment of obesity, and for validation of predictive equations for energy expenditure in this population.

### **Abbreviations**

BEE - basal energy expenditure CHO – carbohydrate EE - energy expenditure FFM - fat-free mass LCSFA - long chain saturated fatty acids LCT - long-chain triglycerides LF – low-fat MCSFA - Medium chain saturated fatty acids MCT - medium-chain triglycerides MUFA - monounsaturated fatty acids PPAR2 - peroxisome proliferator-activated PUFA - polyunsaturated fatty acids REE – resting energy expenditure RMR - resting metabolic rate RQ - respiratory quotient SFA – saturated fatty acids

TEE - energy expenditure TEF - thermic effect of food UFA - unsaturated fatty acids VO2 - inspired O2 VCO2 - expired CO2

### **Author details**

Applications of Calorimetry in a Wide Context –

food intake, EE, or body weight in humans [46].

for energy expenditure in this population.

LCSFA - long chain saturated fatty acids

MCSFA - Medium chain saturated fatty acids

**4. Conclusion** 

**Abbreviations** 

CHO – carbohydrate EE - energy expenditure FFM - fat-free mass

LF – low-fat

BEE - basal energy expenditure

LCT - long-chain triglycerides

MCT - medium-chain triglycerides MUFA - monounsaturated fatty acids PPAR2 - peroxisome proliferator-activated

PUFA - polyunsaturated fatty acids REE – resting energy expenditure RMR - resting metabolic rate RQ - respiratory quotient SFA – saturated fatty acids

318 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Consumption of a diet rich in MCTs results in greater loss of adipose tissue compared with

A controlled randomized dietary trial was conducted with 26 overweight or moderately obese men and women (body mass index 28-33 kg/m2) to test the hypothesis that n-3 polyunsaturated fatty acids (n-3-PUFA) lower body weight and fat mass by reducing appetite and *ad libitum* food intake and/or by increasing EE. Diets were administered in an isocaloric fashion for 2 weeks followed by 12 weeks of *ad libitum* intake. The n-3-PUFA and control diets were identical in all regards except for the fatty acid composition. Both groups lost similar amounts of weight when these diets were consumed *ad libitum* for 12 weeks [mean (SD): -3.5 (3.7) kg in the control group vs. -2.8 (3.7) kg in the n-3-PUFA group, F(1,24) = 13.425, *p* = 0.001 for time effect; F(1,24) = 0.385, *p* = 0.541 for time × group interaction]. No differences were founds between the n-3-PUFA and control groups with regard to appetite as measured by visual analogue scale, *ad libitum* food intake or, REE as measured by indirect calorimetry, diurnal plasma leptin concentrations, or fasting ghrelin concentrations. These results suggest that dietary n-3-PUFA do not play an important role in the regulation of

Indirect calorimetry is useful technique in the metabolic evaluation of obese individuals. Despite some methodological limitations, is still the best way to estimate this variable in this population, which is useful both in studies of dietary intervention, intended to propose new strategies for prevention and treatment of obesity, and for validation of predictive equations

LCTs, perhaps due to increased EE and fat oxidation observed with MCT intake [45].

Eliane Lopes Rosado, Vanessa Chaia Kaippert and Roberta Santiago de Brito *Nutrição e Dietética Departament, Federal University of Rio de Janeiro, Rio de Janeiro, Brasil* 

### **Acknowledgement**

This work was supported by Conselho Nacional de Pesquisa (CNPq) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG).

We thank the Federal University of Viçosa and Navarra University.

### **5. References**


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**Section 6** 

**Applications of Calorimetry into Propellants,** 

**Alloys, Mixed Oxides and Lipids** 


**Applications of Calorimetry into Propellants, Alloys, Mixed Oxides and Lipids** 

Applications of Calorimetry in a Wide Context –

11(3):395-402.

322 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and women: a randomized controlled trial. Nutr Metab. 6:24.

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**Chapter 14** 

© 2013 Gonçalves et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Thermal Decomposition Kinetics** 

**on Ammonium Perchlorate – AP/HTPB Binder** 

Despite the widespread use and long investigative history of ammonium perchlorate(AP) fuel mixtures, it still can be said that AP alone and AP/HTPB (hydroxyl-terminatedpolybutadiene) composites remain among the most confounding materials in the research setting [1]. Since the physical structure of composite propellants like the AP/HTPB composite is heterogeneous, the combustion wave structure appears to be also heterogeneous. During the combustion, at the burning surface, the decomposed gases from the ammonium perchlorate particles and fuel binder (HTPB) are interdiffused and produce diffusion flame streams. Due this, the flame structure of AP composite propellants is

Ammonium perchlorate (NH4ClO4) is a powerful oxidizer salt largely used in solid propellant formulations for application in airspace and defense materials industries. It is obtained by reaction between ammonia and perchloric acid, or by double decomposition between an ammonium salt and sodium perchlorate, and crystallizes with romboedric structure in room temperature and pressure, with relative density of 1.95 [2] Similarly to most ammonium salts, AP thermal decomposition occurs before its fusion. When submitted to a low heating rate, decomposes releasing gases chlorine, nitrogen and oxygen and water in the vapor state; while with a high heating rate stimulus there are instant reactions with

During the combustion process of AP crystals at high pressures, is possible to observe the formation of a tiny layer of ammonium perchlorate in liquid phase at the grain surface [3],

and reproduction in any medium, provided the original work is properly cited.

**of Aged Solid Propellant Based** 

R. F. B. Gonçalves, J. A. F. F. Rocco and K. Iha

Additional information is available at the end of the chapter

complex and locally three-dimensional in shape.

followed by a region where it is presented in gaseous phase.

http://dx.doi.org/10.5772/52109

**1. Introduction** 

high energy release.

## **Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder**

R. F. B. Gonçalves, J. A. F. F. Rocco and K. Iha

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/52109

### **1. Introduction**

Despite the widespread use and long investigative history of ammonium perchlorate(AP) fuel mixtures, it still can be said that AP alone and AP/HTPB (hydroxyl-terminatedpolybutadiene) composites remain among the most confounding materials in the research setting [1]. Since the physical structure of composite propellants like the AP/HTPB composite is heterogeneous, the combustion wave structure appears to be also heterogeneous. During the combustion, at the burning surface, the decomposed gases from the ammonium perchlorate particles and fuel binder (HTPB) are interdiffused and produce diffusion flame streams. Due this, the flame structure of AP composite propellants is complex and locally three-dimensional in shape.

Ammonium perchlorate (NH4ClO4) is a powerful oxidizer salt largely used in solid propellant formulations for application in airspace and defense materials industries. It is obtained by reaction between ammonia and perchloric acid, or by double decomposition between an ammonium salt and sodium perchlorate, and crystallizes with romboedric structure in room temperature and pressure, with relative density of 1.95 [2] Similarly to most ammonium salts, AP thermal decomposition occurs before its fusion. When submitted to a low heating rate, decomposes releasing gases chlorine, nitrogen and oxygen and water in the vapor state; while with a high heating rate stimulus there are instant reactions with high energy release.

During the combustion process of AP crystals at high pressures, is possible to observe the formation of a tiny layer of ammonium perchlorate in liquid phase at the grain surface [3], followed by a region where it is presented in gaseous phase.

© 2013 Gonçalves et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

According to Beckstead and Puduppakkam [4], the combustion of a monopropellant can be divided in three regions (condensed, liquid-gas two-phase region and gas region). The twophase region consists of liquid and gaseous species resulting from the melting and/or decomposition of the solid phase. The precise division between the two-phase and gasphase region (i.e. the 'burning surface') is not well defined due to chemical reactions, bubbles, and condensed material being convected away from the surface. In the gas phase region of a monopropellant, the flame is essentially premixed. The species emanating from the surface react with each other and/or decompose to form other species. A wide variety of reactions involving many species occur in the gas flame until equilibrium is reached in the final flame zone.

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 327

↓ HCl + 2 O2

NH4ClO4 → NH3 + HClO4

These oxygen molecules will be used as oxidizer in binders combustion, when the AP is

The combustion mechanism of AP has been studied and modified. The table below shows the elementary reactions which take part on the combustion process. This mechanism was proposed by Gross [6], according to literature data. It is very interesting the analysis of the combustion for its close relation to the thermal decomposition. When high pressure or high temperatures are used, the material suffers combustion instead of thermal decomposition, i.e. there's a higher velocity of decomposition and higher energy release, but the process is

Reaction **A b Ea**  HClO4=ClO3+OH 1.00E+14 0.0 3.91E+04 HClO4+HNO=ClO3+H2O+NO 1.50E+13 0.0 6.00E+03 ClO3=ClO+O2 1.70E+13 0.5 0,00E+00 Cl2+O2+M=ClO2+Cl+M 6.00E+08 0.0 1.12E+04 ClO+NO=Cl+NO2 6.78E+12 0.0 3.11E+02 ClO+ClOH=Cl2+HO2 1.00E+11 0.0 1.00E+04 ClOH+OH=ClO+H2O 1.80E+13 0.0 0,00E+00 HCl+OH=Cl+H2O 5.00E+11 0.0 7.50E+02 Cl2+H=HCl+Cl 8.40E+13 0.0 1.15E+03 ClO+NH3=ClOH+NH2 6.00E+11 0.5 6.40E+03 NH3+Cl=NH2+HCl 4.50E+11 0.5 1.00E+02 NH3+OH=NH2+H2O 5.00E+07 1.6 9.55E+02 NH2+O2=HNO+OH 3.00E+09 0.0 0,00E+00 NH2+NO=H2O+N2 6.20E+15 -1.3 0,00E+00 HNO+OH=NO+H2O 1.30E+07 1.9 -9.50E+02 HNO+O2=NO2+OH 1.50E+13 0.0 1.00E+04 HNO+H=H2+NO 4.50E+11 0.7 6.60E+02 NO+H+M=HNO+M 8.90E+19 -1.3 7.40E+02 HO2+N2=HNO+NO 2.70E+10 0.5 4.18E+04 NO+HO2=NO2+OH 2.11E+12 0.0 4.80E+02 H+NO2=NO+OH 3.47E+14 0.0 1.48E+03 H2+OH=H2O+H 2.16E+08 1.5 3.43E+03

*k* = *A Tb* exp(-*E/RT*). Units: *A* (mol-cm-s-K), *E* (J/mol).

used in a composite propellant or even when is burning by itself.

usually incomplete.

**Table 1.** AP combustion mechanism

Thermal decomposition of AP, as its combustion processes, have been experimentally studied and reported in the literature. The thermal decomposition of AP may be observed by differential thermal analysis (DTA) and thermal gravimetry (TG), in the figure below [5]. A heating rate of 0.33 K/s was used on the analysis.

**Figure 1.** TG and DTA of AP decomposition [5]

The phase transition from orthorhombic to cubic crystal lattice (ΔH = -85 kJ/kg) is represented by the endothermic peak on 520 K. The exothermic events on 607 K and 720 K are due to the proper decomposition of the AP crystal in ammonia and perchloric acid, followed by the formation of chloridric acid and oxygen (decomposition of HClO4), according to the reactions below.

$$\begin{array}{c} \text{NH4ClO}\_{4} \begin{array}{c} \text{-NH3} + \text{HClO}\_{4} \\ \downarrow \\ \text{HCl} \\ + \\ 2 \text{ O}\_{2} \end{array} \end{array}$$

These oxygen molecules will be used as oxidizer in binders combustion, when the AP is used in a composite propellant or even when is burning by itself.

The combustion mechanism of AP has been studied and modified. The table below shows the elementary reactions which take part on the combustion process. This mechanism was proposed by Gross [6], according to literature data. It is very interesting the analysis of the combustion for its close relation to the thermal decomposition. When high pressure or high temperatures are used, the material suffers combustion instead of thermal decomposition, i.e. there's a higher velocity of decomposition and higher energy release, but the process is usually incomplete.


**Table 1.** AP combustion mechanism

Applications of Calorimetry in a Wide Context –

A heating rate of 0.33 K/s was used on the analysis.

**Figure 1.** TG and DTA of AP decomposition [5]

according to the reactions below.

final flame zone.

326 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

According to Beckstead and Puduppakkam [4], the combustion of a monopropellant can be divided in three regions (condensed, liquid-gas two-phase region and gas region). The twophase region consists of liquid and gaseous species resulting from the melting and/or decomposition of the solid phase. The precise division between the two-phase and gasphase region (i.e. the 'burning surface') is not well defined due to chemical reactions, bubbles, and condensed material being convected away from the surface. In the gas phase region of a monopropellant, the flame is essentially premixed. The species emanating from the surface react with each other and/or decompose to form other species. A wide variety of reactions involving many species occur in the gas flame until equilibrium is reached in the

Thermal decomposition of AP, as its combustion processes, have been experimentally studied and reported in the literature. The thermal decomposition of AP may be observed by differential thermal analysis (DTA) and thermal gravimetry (TG), in the figure below [5].

The phase transition from orthorhombic to cubic crystal lattice (ΔH = -85 kJ/kg) is represented by the endothermic peak on 520 K. The exothermic events on 607 K and 720 K are due to the proper decomposition of the AP crystal in ammonia and perchloric acid, followed by the formation of chloridric acid and oxygen (decomposition of HClO4),

*k* = *A Tb* exp(-*E/RT*). Units: *A* (mol-cm-s-K), *E* (J/mol).

Based on combustion mechanisms, the burning process may be simulated and analyzed by some specific softwares. In a previous work [7], these simulations were done, considering a perfectly stirred reactor, different internal pressures and a specific temperature profile. The combustion simulation results may be observed in the figure below, which show the behavior of AP combustion with different internal pressures of the combustion chamber.

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 329

for each component decomposition and their interactions in chamber, as well as the formation and decomposition of new intermediary species, especially in the flame region. The proposed mechanism for AP-HTPB combustion may be observed in Table 2 below.

> Reaction A b Ea Cl2+O2+M=ClO2+Cl+M 6.00E+08 0 1.12E+04 ClO+NO=Cl+NO2 6.78E+12 0 3.11E+02 HCl+OH=Cl+H2O 5.00E+11 0 7.50E+02 Cl2+H=HCl+Cl 8.40E+13 0 1.15E+03 NH3+Cl=NH2+HCl 4.50E+11 0.5 1.00E+02 NH3+OH=NH2+H2O 5.00E+07 1.6 9.55E+02 NH2+O2=HNO+OH 3.00E+09 0 0.00E+00 NH2+NO=H2O+N2 6.20E+15 -1.3 0.00E+00 HNO+OH=NO+H2O 1.30E+07 1.9 -9.50E+02 HNO+O2=NO2+OH 1.50E+13 0 1.00E+04 HNO+H=H2+NO 4.50E+11 0.7 6.60E+02 NO+H+M=HNO+M 8.90E+19 -1.3 7.40E+02 HO2+N2=HNO+NO 2.70E+10 0.5 4.18E+04 NO+HO2=NO2+OH 2.11E+12 0 4.80E+02 H+NO2=NO+OH 3.47E+14 0 1.48E+03 H2+OH=H2O+H 2.16E+08 1.5 3.43E+03 CH4+Cl=CH3+HCl 2.50E+13 0 3.83E+03 CH4+H=CH3+H2 6.60E+08 1.6 1.08E+04 CH4+OH=CH3+H2O 1.00E+08 1.6 3.12E+03 CH3+H+M=CH4+M 1.27E+16 -0.6 3.83E+02 CO+OH=CO2+H 4.76E+07 1.2 7.00E+01 CO+ClO=CO2+Cl 3.00E+12 0 1.00E+03 CO+ClO2=CO2+ClO 1.00E+10 0 0.00E+00 H+O2=O+OH 8.30E+13 0 1.44E+04 CH2+H2=CH3+H 5.00E+05 2 7.23E+03 CH2+H+M=CH3+M 2.50E+16 -0.8 0.00E+00 CH4+O=CH3+OH 1.02E+09 1.5 6.00E+02 OH+CH3=CH2+H2O 5.60E+07 1.6 5.42E+03 C2H4+O2=2CO+2H2 1.80E+14 0 3.55E+04 NH2+NO2=2HNO 1.40E+12 0 0.00E+00 NH2+ClO=HNO+HCl 2.50E+12 0 0.00E+00 O2+HNO=NO+HO2 1.00E+13 0 1.30E+04 H+Cl+M=HCl+M 5.30E+21 -2 -2.00E+03 Cl+Cl+M=Cl2+M 3.34E+14 0 -1.80E+03 Cl+HO2=ClO+OH 2.47E+13 0 8.94E+02 ClO+O=Cl+O2 6.60E+13 0 4.40E+02 H+HCl=Cl+H2 7.94E+12 0 3.40E+03 HCl+O=Cl+OH 2.30E+11 0.6 9.00E+02

**Figure 2.** AP combustion at a) 1 atm; b) 5 atm; c) 30 atm and d) 60 atm.

The "elbows" appear due to the increase of the occurrence of intermediate reactions in the flame zone. This phenomenon generates a great variation on the mole fractions of intermediates (as the high temperature enhance the speed of the slower reactions, generating more radicals), which modify the concentration of the main species (specially in the flame zone), so the different slope is observed. As the pressure in the combustion chamber increases, there is an approximation of the flame to the material's surface and accentuation of the "elbows" presented on the flame region, indicating the influence of the speed increase of elementary reactions in the decomposition process of the material in study. This gain in chemical speed reactions may be converted in gain in thrust of rocket motors and specific impulse of solid propellant grains.

When a composite propellant is used, like AP-HTPB, the combustion process depends on the diffusion of the gases generated on the initial decomposition of the oxidizer, which surrounds the binder molecules at the burning surface. The combustion mechanism has higher complexity as new components are added, because there are the elementary reactions


for each component decomposition and their interactions in chamber, as well as the formation and decomposition of new intermediary species, especially in the flame region. The proposed mechanism for AP-HTPB combustion may be observed in Table 2 below.

Applications of Calorimetry in a Wide Context –

328 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 2.** AP combustion at a) 1 atm; b) 5 atm; c) 30 atm and d) 60 atm.

motors and specific impulse of solid propellant grains.

The "elbows" appear due to the increase of the occurrence of intermediate reactions in the flame zone. This phenomenon generates a great variation on the mole fractions of intermediates (as the high temperature enhance the speed of the slower reactions, generating more radicals), which modify the concentration of the main species (specially in the flame zone), so the different slope is observed. As the pressure in the combustion chamber increases, there is an approximation of the flame to the material's surface and accentuation of the "elbows" presented on the flame region, indicating the influence of the speed increase of elementary reactions in the decomposition process of the material in study. This gain in chemical speed reactions may be converted in gain in thrust of rocket

When a composite propellant is used, like AP-HTPB, the combustion process depends on the diffusion of the gases generated on the initial decomposition of the oxidizer, which surrounds the binder molecules at the burning surface. The combustion mechanism has higher complexity as new components are added, because there are the elementary reactions

Based on combustion mechanisms, the burning process may be simulated and analyzed by some specific softwares. In a previous work [7], these simulations were done, considering a perfectly stirred reactor, different internal pressures and a specific temperature profile. The combustion simulation results may be observed in the figure below, which show the behavior of AP combustion with different internal pressures of the combustion chamber.

Applications of Calorimetry in a Wide Context – 330 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 331

 N2 O2 Cl2 H2 O HCl CO CO2

Similarly, the combustion process of ammonium perchlorate formulated with hydroxyl terminated polybutadiene was simulated in a perfect stirred reactor (with 70/30 proportion),

0 1 2 3 4 5 6 7 8 9 10

Distance from the burning surface (mm)

The combustion process of AP/HTPB has presented invariable with pressure. This behavior should be attributed to the homogeneous dispersion of AP admist the binder, in the solid phase, and to the lack of this species in relation to the binder (generating lower concentrations of O2 than necessary). Also, in the gas phases, it is assumed that all of the liquid AP and HTPB present on the condensed phase decompose to form gaseous species;

In this simulation, the oxygen molar fraction suffers a decrease (and cancels), according to the reactions with HTPB decomposition products, for the formation of carbon monoxide and dioxide. Also, it is interesting to highlight that in this case the carbon monoxide molar fraction suffers a decrease, because the restriction of oxidizer species makes that the oxygen presented in CO to be also used as oxidizing source, viewing the reactive behavior of this specie. In this simulation, the molar fractions of CO and CO2 are not null initially, because given the system temperature, HTPB suffers an initial decomposition that should not be

There is always the premise in all simulations and all studies that the materials are in a perfect state, flawless. Unfortunately, this is not the reality in most industries or laboratories, when there's low turnover. Therefore, the materials may suffer many different changes in

with variations in the internal chamber pressure (Figure 3 below).

0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35 0,40 0,45 0,50

**Figure 3.** AP/HTPB combustion [7]

evaporation is not included.

discarded, generating both carbon oxides.

their structure or properties. The main one is the aging process.

Mole Fraction


**Table 2.** AP-HTPB combustion mechanisma

*k* = *A Tb* exp(-*E/RT*). Units: *A* (mol-cm-s-K), *E* (J/mol).

M: any metal surface or metallic additive used only as support or catalyst a Kinetic data composed of [8]

Similarly, the combustion process of ammonium perchlorate formulated with hydroxyl terminated polybutadiene was simulated in a perfect stirred reactor (with 70/30 proportion), with variations in the internal chamber pressure (Figure 3 below).

**Figure 3.** AP/HTPB combustion [7]

Applications of Calorimetry in a Wide Context –

**Table 2.** AP-HTPB combustion mechanisma

a Kinetic data composed of [8]

330 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Cl2+O=Cl+ClO 2.51E+12 0 2.72E+03 N2O+M=N2+O+M 6.20E+14 0 5.61E+04 N2O+OH=N2+HO2 2.00E+12 0 2.11E+04 N2O+O=NO+NO 2.90E+13 0 2.32E+04 N2O+O=N2+O2 1.40E+12 0 1.08E+04 N2O+H=N2+OH 4.40E+14 0 1.89E+04 2H+M<=>H2+M 1.00E+18 -1 0.00E+00 2H+H2<=>2H2 9.00E+16 -0.6 0.00E+00 2H+H2O<=>H2+H2O 6.00E+19 -1.3 0.00E+00 2H+CO2<=>H2+CO2 5.50E+20 -2 0.00E+00 ClO2+NO=ClO+NO2 1.00E+11 0 0.00E+00 Cl+ClO2=ClO+ClO 5.00E+13 0 6.00E+03 ClO+ClO=Cl2+O2 1.00E+11 0 0.00E+00 Cl+HO2=HCl+O2 1.80E+13 0 0.00E+00 Cl+O2+M=ClO2+M 8.00E+06 0 5.20E+03 NO2+O=NO+O2 1.00E+13 0 6.00E+02 HNO+HNO=H2O+N2O 3.95E+12 0 5.00E+03 NO2+NO2=NO+NO+O2 1.00E+14 0 2.50E+04 Cl+N2O=ClO+N2 1.20E+14 0 3.35E+04 OH+OH=H2O+O 6.00E+08 1.3 0.00E+00 NH2+NO2=H2O+N2O 4.50E+11 0 0.00E+00 HNO+NH2=NH3+NO 5.00E+11 0.5 1.00E+03 ClO+HNO=HCl+NO2 3.00E+12 0 0.00E+00 HCl+HO2=ClO+H2O 3.00E+12 0 0.00E+00 NH2+NO=H+N2+OH 6.30E+19 -2.5 1.90E+03 NH2+OH=H2O+NH 4.00E+06 2 1.00E+03 NH2+NH2=NH+NH3 5.00E+13 0 1.00E+04 NH+NO=N2+OH 1.00E+13 0 0.00E+00 NH+NO=H+N2+O 2.30E+13 0 0.00E+00 Cl+NH2=HCl+NH 5.00E+10 0.5 0.00E+00 ClO2+NH=ClO+HNO 1.00E+14 0 0.00E+00 N+NO2=NO+NO 1.00E+14 0 0.00E+00 N+N2O=N2+NO 5.00E+13 0 0.00E+00 NH+OH=H2O+N 5.00E+11 0.5 2.00E+03 NH+OH=H2+NO 1.60E+12 0.6 1.50E+03 NH+NH2=N+NH3 1.00E+13 0 2.00E+03 HO2+CH3<=>O2+CH4 1.00E+12 0 0.00E+00 CH2+CH4<=>2CH3 2.46E+06 2 8.27E+03

*k* = *A Tb* exp(-*E/RT*). Units: *A* (mol-cm-s-K), *E* (J/mol).

M: any metal surface or metallic additive used only as support or catalyst

The combustion process of AP/HTPB has presented invariable with pressure. This behavior should be attributed to the homogeneous dispersion of AP admist the binder, in the solid phase, and to the lack of this species in relation to the binder (generating lower concentrations of O2 than necessary). Also, in the gas phases, it is assumed that all of the liquid AP and HTPB present on the condensed phase decompose to form gaseous species; evaporation is not included.

In this simulation, the oxygen molar fraction suffers a decrease (and cancels), according to the reactions with HTPB decomposition products, for the formation of carbon monoxide and dioxide. Also, it is interesting to highlight that in this case the carbon monoxide molar fraction suffers a decrease, because the restriction of oxidizer species makes that the oxygen presented in CO to be also used as oxidizing source, viewing the reactive behavior of this specie. In this simulation, the molar fractions of CO and CO2 are not null initially, because given the system temperature, HTPB suffers an initial decomposition that should not be discarded, generating both carbon oxides.

There is always the premise in all simulations and all studies that the materials are in a perfect state, flawless. Unfortunately, this is not the reality in most industries or laboratories, when there's low turnover. Therefore, the materials may suffer many different changes in their structure or properties. The main one is the aging process.

332 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The aging process is one of the most significant factors responsible for changes in the activation energy of solid propellants (usually reduction). This phenomenon can be defined as the growth of cross bonds in the polyurethane chain, altering the mechanical properties of traction resistance and elongation, in comparison of the properties just after the fabrication [9]. This aging process can be responsible for the appearance of failures and cracks in the grains, which compromise the propellant performance.

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 333

The polyurethane network was obtained by curing HTPB polymer samples with IPDI (isophore diisocianate) at an [NCO]/[OH] equivalent ratio of 0.95, at 338 K for 120 h. The NCO/OH ratio is defined as the equivalent ratio between the materials containing NCO (IPDI) groups and those containing OH groups (HTPB) and it affects the mechanical properties of cured composite propellant [13,14]. The chemical composition of the propellant was (weight) binder 22% and others 78%. The synthetic aging process was conducted by exposing the propellant formulation to a temperature of 338 K for 300 days.

DSC curves were obtained on a model DSC50 Shimadzu in the temperature range of 298-773 K, under dynamic nitrogen atmosphere (ca. 50 mL/min). Sample masses were about 1.5 mg, and each sample was heated in hermetically sealed aluminum pans. Seven different heating rates were used for the non-aged samples: 10.0, 15.0, 20.0, 30.0, 35.0, 40.0 and 45.0 K min-1; for the aged samples, three different heat rates were used: 30, 35 and 40 K min-1. DSC system

The method used in the analysis of composite samples was based on DSC experiments in which the temperatures of the extrapolated onset of the thermal decomposition process and the temperatures of maximum heat flow were determined from the resulting measured curves for exothermic reactions. DSC curves at different heating rates, , for non-aged and

In order to determine the kinetic parameters of the degradation step Ozawa and Kissinger's methods were applied. They were both derived from the basic kinetic equations for heterogeneous chemical reactions and therefore have a wide application, as it is not necessary to know the reaction order [19] or the conversional function to determine the kinetic parameters. The activation energy determined by applying these methods is the sum of activation energies of chemical reactions and physical processes in thermal

The temperatures of exothermic peaks, Tp, can be used to calculate the kinetic parameters by the Ozawa method [16,17]. These parameters are the activation energy, Ea, and the pre-

A linear relationship between the heating rate (log ) and the reciprocal of the absolute

where a and b are the parameters of the linear equation: a is -0.4567E/R (slope) and b is a

Assuming that the rate constant follows the Arrhenius law and that the exothermic reaction can be considered as a single step process, the conversion at the maximum conversion rate is invariant with the heating rate when this is linear. Having in account such assumptions, eq.

log ß = a.Tp-1 + b (1)

temperature, Tp-1, may be found and the following linear equation can be established:

was calibrated with indium (m.p.= 429.6 K; Hfus=28.54 Jg-1) and zinc (m.p.= 692.6 K).

aged composite samples are shown in Figs. 4 and 5, respectively.

decomposition and therefore it is called apparent.

constant (linear coefficient). R is the gas constant.

exponential factor, A, relatives to the decomposition process.

**2.2. Kinetic approach** 

The AP/HTPB composite decomposition and the combustion mechanism have been extensively investigated in the last decades and the appearance of advanced methods of diagnostics, like flash pyrolysis, thermogravimetry and differential scanning calorimetry, led to the ressurgence of the interest. These methods are widely used for the investigation of thermal decomposition of organic materials [10], polymers [11,12], composites [13] and explosives [14].

Kissinger [15] and Ozawa [16] and Flynn [17] demonstrated that differential scanning calorimetry (DSC) technique, based on the linear relation between peak temperature and heating rate, can be used to determine the kinetics parameters of a thermal decomposition (activation energy, rate constant). The Ozawa method is one of the most popular methods for estimating activation energies by linear heating rate and it is the so-called isoconversional method. Thermal analysis cannot be used to elucidate the complete mechanism of a thermal degradation but the dynamic analysis has been frequently used to study the overall thermal degradation kinetics of polymers and composites because it gives reliable information on the frequency factor(A), the activation energy (E) and the overall reaction order [18].

In the present work, the differential scanning calorimetry (DSC) technique and the Ozawa dynamic method were used to determine the kinetic parameters of the aged and non-aged solid propellant, AP/HTPB, thermal decomposition. The Kissinger method for obtaining the activation energy value was also employed for a comparison purpose.

### **2. Experimental**

### **2.1. Materials and apparatus**

AP was obtained from Avibras Indústria Aeroespacial S.A.; HTPB from Petroflex Industry S.A., a subsidiary of Petrobras – Petróleo do Brasil S.A.; IPDI from Merck; DOA from Elekeiroz S.A.. The composite propellant was produced in a batch process of 5 kg mass (pilot plant) using a planetary mixer under vacuum atmosphere during 2 hours. All raw materials are incorporated in HTPB polyol, starting with AP that was classified to a medium size of 300 micrometers. When all ingredients are added to the HTPB polyol, the IPDI curing agent can be mixed to the liquid propellant. The propellant curing process was conducted in a temperature of 60 Celsius during a 120 hs period time.

The synthetic aging process was conducted by exposing the cured propellant formulation to a temperature of 338 K for 300 days in a muffle (FNT-F3-T 6600W) that was monitored day by day during this period.

The polyurethane network was obtained by curing HTPB polymer samples with IPDI (isophore diisocianate) at an [NCO]/[OH] equivalent ratio of 0.95, at 338 K for 120 h. The NCO/OH ratio is defined as the equivalent ratio between the materials containing NCO (IPDI) groups and those containing OH groups (HTPB) and it affects the mechanical properties of cured composite propellant [13,14]. The chemical composition of the propellant was (weight) binder 22% and others 78%. The synthetic aging process was conducted by exposing the propellant formulation to a temperature of 338 K for 300 days.

DSC curves were obtained on a model DSC50 Shimadzu in the temperature range of 298-773 K, under dynamic nitrogen atmosphere (ca. 50 mL/min). Sample masses were about 1.5 mg, and each sample was heated in hermetically sealed aluminum pans. Seven different heating rates were used for the non-aged samples: 10.0, 15.0, 20.0, 30.0, 35.0, 40.0 and 45.0 K min-1; for the aged samples, three different heat rates were used: 30, 35 and 40 K min-1. DSC system was calibrated with indium (m.p.= 429.6 K; Hfus=28.54 Jg-1) and zinc (m.p.= 692.6 K).

### **2.2. Kinetic approach**

Applications of Calorimetry in a Wide Context –

explosives [14].

reaction order [18].

**2. Experimental** 

**2.1. Materials and apparatus** 

by day during this period.

332 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

grains, which compromise the propellant performance.

The aging process is one of the most significant factors responsible for changes in the activation energy of solid propellants (usually reduction). This phenomenon can be defined as the growth of cross bonds in the polyurethane chain, altering the mechanical properties of traction resistance and elongation, in comparison of the properties just after the fabrication [9]. This aging process can be responsible for the appearance of failures and cracks in the

The AP/HTPB composite decomposition and the combustion mechanism have been extensively investigated in the last decades and the appearance of advanced methods of diagnostics, like flash pyrolysis, thermogravimetry and differential scanning calorimetry, led to the ressurgence of the interest. These methods are widely used for the investigation of thermal decomposition of organic materials [10], polymers [11,12], composites [13] and

Kissinger [15] and Ozawa [16] and Flynn [17] demonstrated that differential scanning calorimetry (DSC) technique, based on the linear relation between peak temperature and heating rate, can be used to determine the kinetics parameters of a thermal decomposition (activation energy, rate constant). The Ozawa method is one of the most popular methods for estimating activation energies by linear heating rate and it is the so-called isoconversional method. Thermal analysis cannot be used to elucidate the complete mechanism of a thermal degradation but the dynamic analysis has been frequently used to study the overall thermal degradation kinetics of polymers and composites because it gives reliable information on the frequency factor(A), the activation energy (E) and the overall

In the present work, the differential scanning calorimetry (DSC) technique and the Ozawa dynamic method were used to determine the kinetic parameters of the aged and non-aged solid propellant, AP/HTPB, thermal decomposition. The Kissinger method for obtaining the

AP was obtained from Avibras Indústria Aeroespacial S.A.; HTPB from Petroflex Industry S.A., a subsidiary of Petrobras – Petróleo do Brasil S.A.; IPDI from Merck; DOA from Elekeiroz S.A.. The composite propellant was produced in a batch process of 5 kg mass (pilot plant) using a planetary mixer under vacuum atmosphere during 2 hours. All raw materials are incorporated in HTPB polyol, starting with AP that was classified to a medium size of 300 micrometers. When all ingredients are added to the HTPB polyol, the IPDI curing agent can be mixed to the liquid propellant. The propellant curing process was conducted in

The synthetic aging process was conducted by exposing the cured propellant formulation to a temperature of 338 K for 300 days in a muffle (FNT-F3-T 6600W) that was monitored day

activation energy value was also employed for a comparison purpose.

a temperature of 60 Celsius during a 120 hs period time.

The method used in the analysis of composite samples was based on DSC experiments in which the temperatures of the extrapolated onset of the thermal decomposition process and the temperatures of maximum heat flow were determined from the resulting measured curves for exothermic reactions. DSC curves at different heating rates, , for non-aged and aged composite samples are shown in Figs. 4 and 5, respectively.

In order to determine the kinetic parameters of the degradation step Ozawa and Kissinger's methods were applied. They were both derived from the basic kinetic equations for heterogeneous chemical reactions and therefore have a wide application, as it is not necessary to know the reaction order [19] or the conversional function to determine the kinetic parameters. The activation energy determined by applying these methods is the sum of activation energies of chemical reactions and physical processes in thermal decomposition and therefore it is called apparent.

The temperatures of exothermic peaks, Tp, can be used to calculate the kinetic parameters by the Ozawa method [16,17]. These parameters are the activation energy, Ea, and the preexponential factor, A, relatives to the decomposition process.

A linear relationship between the heating rate (log ) and the reciprocal of the absolute temperature, Tp-1, may be found and the following linear equation can be established:

$$\log \mathfrak{E} = \mathbf{a}. \mathrm{T}\_{\mathbb{P}}^{-1} + \mathbf{b} \tag{1}$$

where a and b are the parameters of the linear equation: a is -0.4567E/R (slope) and b is a constant (linear coefficient). R is the gas constant.

Assuming that the rate constant follows the Arrhenius law and that the exothermic reaction can be considered as a single step process, the conversion at the maximum conversion rate is invariant with the heating rate when this is linear. Having in account such assumptions, eq. 334 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

(1) may be applied to the exothermic peak maximum temperature considering different heating rates [15,19]. Thus carrying out several experiments at different heating rates a plot of log ß vs 1/Tp may be done and the activation energy can be estimated directly from the slope of the curve using the following equation derived [14] from the eq.(1):

$$\mathbf{E}\mathbf{a} = -2.19\,\mathrm{R}\,\mathrm{[d}\,\log\,\mathrm{\mathfrak{d}\,\mathrm{/}\,\mathrm{d}^{\circ}\,\mathrm{T}\_{\mathbb{P}}\,\mathrm{^{\circ}}]}\tag{2}$$

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 335

**Figure 4.** Constant heating rate TGA plots – Flynn & Wall method [20]

to calculate the activation energy.

**3. Results and discussion** 

min-1 for the aged ones.

From this curve is possible to construct a ln β vs 1/T plot. The slope of this new curve is used

The activation energy and kinetic parameters of thermal decomposition of propellant samples were calculated by Ozawa method using DSC curves at different heating rates: 10.0, 15.0, 20.0, 30.0, 35.0, 40.0 and 45.0 K min-1 for the non-aged ones and 30.0, 35.0 and 40.0 K

where - d log ß/ d Tp-1 = parameter a (eq.1).

With the same above assumptions, the Kissinger method8 may be used to calculate the activation energy and the pre-exponential factor from the maximum rate condition which will occur at the maximum exothermic peak temperature, Tp.

The Kissinger method is based on the plot of ln (/Tp2) vs. 1/Tp. Activation energy is calculated from the slope of the curve using the following equation:

$$\mathbf{Ea} = \mathbf{R} \text{ d}[\ln \| \mathbf{B} / \mathbf{T}\_{\mathbb{P}} \mathbf{2} \| \text{ / [d (1/\mathbf{T}\_{\mathbb{P}})]} \text{} \tag{3}$$

Once time E is known the values of pre-exponential factor, A, are calculated with the equation:

$$\mathbf{A} = \left( \emptyset \to \exp \, \mathrm{Ea/RT\_{\mathbb{P}}} \right) / \mathrm{RT\_{\mathbb{P}}}^2 \tag{4}$$

The temperature dependence of the specific rate constant k is described by the Arrhenius equation:

$$\mathbf{k} = \mathbf{A} \exp\left(-\mathbf{Ea/RT\_{\mathbb{P}}}\right) \tag{5}$$

The kinetic Shimadzu software, based on the Ozawa method, feed with the exothermic peak temperatures and the heating rate data, gives the Arrhenius kinetic parameters (Ea, A) relative to the thermal decomposition of composite and, consequently, with the eq. (5) the overall rate constant can be calculated.

There's also a possibility of using Flynn and Wall methodology with TGA analysis (constant heating rate TGA) [17], once it requires less experimental time, although this method is limited to single-step decompositions and first order kinetics. The approaches are the following:

This first approach requires at least three determinations at different heating rates (Fig. 4 below), following the Arrhenius equation:

 <sup>1</sup> *d E <sup>n</sup> A.exp dt RT* , where α represents the fraction of decomposition and *n* is the

reaction order.

Re-arranging, the equation turns to:

$$E\alpha = \left(\frac{-R}{c}\right) \frac{d\ln\beta}{d\left(\frac{1}{T}\right)}, \text{ where c is a constant for n=1.}$$

**Figure 4.** Constant heating rate TGA plots – Flynn & Wall method [20]

From this curve is possible to construct a ln β vs 1/T plot. The slope of this new curve is used to calculate the activation energy.

#### **3. Results and discussion**

Applications of Calorimetry in a Wide Context –

where - d log ß/ d Tp-1 = parameter a (eq.1).

overall rate constant can be calculated.

below), following the Arrhenius equation:

, where c is a constant for n=1.

<sup>1</sup> *d E <sup>n</sup> A.exp dt RT*

ln 1

*T*

Re-arranging, the equation turns to:

equation:

equation:

following:

reaction order.

*R d <sup>E</sup>*

 

*<sup>c</sup> <sup>d</sup>*

334 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

will occur at the maximum exothermic peak temperature, Tp.

calculated from the slope of the curve using the following equation:

slope of the curve using the following equation derived [14] from the eq.(1):

(1) may be applied to the exothermic peak maximum temperature considering different heating rates [15,19]. Thus carrying out several experiments at different heating rates a plot of log ß vs 1/Tp may be done and the activation energy can be estimated directly from the

With the same above assumptions, the Kissinger method8 may be used to calculate the activation energy and the pre-exponential factor from the maximum rate condition which

The Kissinger method is based on the plot of ln (/Tp2) vs. 1/Tp. Activation energy is

Once time E is known the values of pre-exponential factor, A, are calculated with the

The temperature dependence of the specific rate constant k is described by the Arrhenius

The kinetic Shimadzu software, based on the Ozawa method, feed with the exothermic peak temperatures and the heating rate data, gives the Arrhenius kinetic parameters (Ea, A) relative to the thermal decomposition of composite and, consequently, with the eq. (5) the

There's also a possibility of using Flynn and Wall methodology with TGA analysis (constant heating rate TGA) [17], once it requires less experimental time, although this method is limited to single-step decompositions and first order kinetics. The approaches are the

This first approach requires at least three determinations at different heating rates (Fig. 4

Ea = - 2.19 R [d log ß/ d Tp-1] (2)

Ea = R d[ln /Tp2] / [d (1/Tp)] (3)

A = ( E exp Ea/RTp) / RTp2 (4)

k = A exp ( -Ea/RTp) (5)

, where α represents the fraction of decomposition and *n* is the

The activation energy and kinetic parameters of thermal decomposition of propellant samples were calculated by Ozawa method using DSC curves at different heating rates: 10.0, 15.0, 20.0, 30.0, 35.0, 40.0 and 45.0 K min-1 for the non-aged ones and 30.0, 35.0 and 40.0 K min-1 for the aged ones.

336 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 337

The exothermic events have different maximum temperatures in both cases; the higher the

heating rate, higher is the maximum temperature of the peak.

**Figure 7.** Ozawa plot for AP/HTPB samples at 10, 15, 20, 30, 35, 40 and 45 K min–1

**Figure 8.** Ozawa plot for aged AP/HTPB samples at 30, 35 and 40 K min–1

**Figure 5.** DSC curves of thermal decomposition of non-aged composite samples, AP/HTPB, at the heating rates: 10, 20, 30, 35 and 40 K min–1 and TG curve with a heating rate of 30 K min–1

**Figure 6.** DSC curves of thermal decomposition of aged composite samples, AP/HTPB, at the heating rates: 30, 35 and 40 K min–1

The exothermic events have different maximum temperatures in both cases; the higher the heating rate, higher is the maximum temperature of the peak.

Applications of Calorimetry in a Wide Context –

336 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 5.** DSC curves of thermal decomposition of non-aged composite samples, AP/HTPB, at the

**Figure 6.** DSC curves of thermal decomposition of aged composite samples, AP/HTPB, at the heating

rates: 30, 35 and 40 K min–1

heating rates: 10, 20, 30, 35 and 40 K min–1 and TG curve with a heating rate of 30 K min–1

**Figure 7.** Ozawa plot for AP/HTPB samples at 10, 15, 20, 30, 35, 40 and 45 K min–1

**Figure 8.** Ozawa plot for aged AP/HTPB samples at 30, 35 and 40 K min–1

The DSC curves are presented in Figs. 5 and 6. The DSC curves show that the first stage is endothermic and the second stage is exothermic. The endothermic event is quite similar for the different heating rates used and it shows the same peak temperature. This event occurs around 520 K and it was not considered because it represents a phase transition of ammonium perchlorate (AP) from the orthorhombic to the cubic form [21,22]. Together with DSC curves obtained for different heating rates (non-aged samples), Fig. 1, the TG curve for 30.0 K min-1 was included to show that in the region corresponding to the endothermic peak (DSC curves) there is no any weight loss or, at least, it is imperceptible and, the same behavior was observed in all of other TG curves for different heating rates.

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 339

Cohen [24] studied the kinetics of the surface pyrolysis of HTPB and, assuming zero-order kinetics, they found the activation energy of 71 kJ mol-1. Comparison between the activation energies for the propellant decomposition and the activation energies for decomposition of individual ammonium perchlorate (AP) or/and HTPB binder suggests that the overall kinetics of the mass loss is determined by the reaction between the binder and the

Ammonium perchlorate is widely used as an oxidizer in energetic composites and it is one of the most important raw materials in propellant formulations where it represents at least 80 % of total mass of composite solid propellants, so its contribution on the thermal decomposition behavior of propellant samples is always very important. The addition of burning rates catalysts like Fe2O3 on the propellant formulation alters the thermal decomposition behavior of AP, and consequently the thermal decomposition behavior of the propellant. Shin-Ming [22] showed that the presence of these catalysts compounds reduce the maximum decomposition reaction temperature in

Another important aspect of DSC curves is the correlation of maximum temperature of exothermic peak obtained for each heating rate applied to the composite sample during the experiments. This correlation can be used to determine the burning rate characteristics of a composite solid propellant with a specific formulation. The burning rate characteristics are an important ballistic parameter of the energetic composite like solid propellant. Xiao-Bin [25] showed that the burning rates of propellants were very closely related to the exothermic peak temperature of ammonium nitrate (AN) that is used as an oxidizer in smokeless

In the present work, the DSC curves at different heating rates were obtained for original and synthetically aged samples that have the same raw materials and with the same manufacture process. These conditions are necessary because differences in the raw materials, as ammonium perchlorate (AP) particle size, can affect the thermal decomposition behavior of the composite. In other words, the decomposition mechanism of AP powder of

For energetic materials like composite solid propellant, it is critical to use the minimum sample size and low heating rates to avoid the risks to potential damage of the DSC cell resulting in DSC curves with a lot of interferences caused by the detonation behavior of composite samples. In opposition to this criteria, in this study, high heating rates were used (10.0 to 45.0 K min-1), but to compensate this condition very low sample sizes were used ( 1.5 mg). Despite these heating rates are not close to the rocket motor chamber conditions (heating rates estimated as 106 K s-1) the slower heating rates used in this work allow one to

decomposition products of AP[24].

AP samples.

propellant formulation.

**4. Conclusions** 

fine particle size differs that of AP of larger particle size.

get a better insight into the reaction kinetics mechanisms.

Figures 7 and 8 show the plot of log vs the reciprocal of the absolute temperature relative to each maximum of the exothermic stage. The values of the activation energy were found to be 134.5 kJ mol-1 (non-aged samples) and 79.0 kJ mol-1 (aged samples). Sell et al.[23] using thermogravimetry at heating rates between 0.5 and 10 K min-1 studied the decomposition kinetics of the AP/HTPB propellant samples with isoconversional method and the calculated activation energies are between 100 and 230 kJ mol-1.

From the slope of Kissinger plot (ln (/Tp2) vs. 1/Tp) and eq. (3) the activation energy was also calculated and is 126.2 kJ mol-1 for the non-aged samples, therefore quite similar to that obtained using the Ozawa method.

The thermal decomposition of solid composite propellant is a multistep process and the reaction mechanism changes with the temperature and, consequently, the activation energy varies with the extent of the reaction. DSC data are used to estimate the activation energies of thermal decomposition of propellant samples because the global decomposition reaction is taken in account. Implicit in any discussion about the decomposition is the fact that the overall process is complex, and any derived rate parameters do not correspond to an elementary single step. TG/DTG results are in agreement with this assumption.

The pre-exponential factor was found to be 2.04 1010 min-1 (non-aged samples) and 1.29.106 min-1 (aged samples) and the reaction orders for the global composite decomposition were estimated in 0.7 (non-aged) and 0.6 (aged) by the kinetic Shimadzu software based in the Ozawa method. This value is quite different from the Arrhenius assumption where the reaction order is always considered as 1.0. For practical purposes the Arrhenius parameters, like the corrected reaction order, can be used to estimate the overall rate constant (k) for thermal decomposition using the eq. (5).

The differences found in the kinetics parameters between the original and the aged samples, specially the activation energy (Ea), confirm the practical observation that energetic materials like the composites used in solid propellant rocket motors require less energy to start the combustion process as they age. Besides, considering the heating rate of 40 K min-1 for the original and for the aged samples, a reduction in the enthalpy of the decomposition's exothermic phase was observed (2.56 to 1.15 J g-1).

Cohen [24] studied the kinetics of the surface pyrolysis of HTPB and, assuming zero-order kinetics, they found the activation energy of 71 kJ mol-1. Comparison between the activation energies for the propellant decomposition and the activation energies for decomposition of individual ammonium perchlorate (AP) or/and HTPB binder suggests that the overall kinetics of the mass loss is determined by the reaction between the binder and the decomposition products of AP[24].

Ammonium perchlorate is widely used as an oxidizer in energetic composites and it is one of the most important raw materials in propellant formulations where it represents at least 80 % of total mass of composite solid propellants, so its contribution on the thermal decomposition behavior of propellant samples is always very important. The addition of burning rates catalysts like Fe2O3 on the propellant formulation alters the thermal decomposition behavior of AP, and consequently the thermal decomposition behavior of the propellant. Shin-Ming [22] showed that the presence of these catalysts compounds reduce the maximum decomposition reaction temperature in AP samples.

Another important aspect of DSC curves is the correlation of maximum temperature of exothermic peak obtained for each heating rate applied to the composite sample during the experiments. This correlation can be used to determine the burning rate characteristics of a composite solid propellant with a specific formulation. The burning rate characteristics are an important ballistic parameter of the energetic composite like solid propellant. Xiao-Bin [25] showed that the burning rates of propellants were very closely related to the exothermic peak temperature of ammonium nitrate (AN) that is used as an oxidizer in smokeless propellant formulation.

In the present work, the DSC curves at different heating rates were obtained for original and synthetically aged samples that have the same raw materials and with the same manufacture process. These conditions are necessary because differences in the raw materials, as ammonium perchlorate (AP) particle size, can affect the thermal decomposition behavior of the composite. In other words, the decomposition mechanism of AP powder of fine particle size differs that of AP of larger particle size.

### **4. Conclusions**

Applications of Calorimetry in a Wide Context –

338 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

behavior was observed in all of other TG curves for different heating rates.

activation energies are between 100 and 230 kJ mol-1.

obtained using the Ozawa method.

agreement with this assumption.

thermal decomposition using the eq. (5).

exothermic phase was observed (2.56 to 1.15 J g-1).

The DSC curves are presented in Figs. 5 and 6. The DSC curves show that the first stage is endothermic and the second stage is exothermic. The endothermic event is quite similar for the different heating rates used and it shows the same peak temperature. This event occurs around 520 K and it was not considered because it represents a phase transition of ammonium perchlorate (AP) from the orthorhombic to the cubic form [21,22]. Together with DSC curves obtained for different heating rates (non-aged samples), Fig. 1, the TG curve for 30.0 K min-1 was included to show that in the region corresponding to the endothermic peak (DSC curves) there is no any weight loss or, at least, it is imperceptible and, the same

Figures 7 and 8 show the plot of log vs the reciprocal of the absolute temperature relative to each maximum of the exothermic stage. The values of the activation energy were found to be 134.5 kJ mol-1 (non-aged samples) and 79.0 kJ mol-1 (aged samples). Sell et al.[23] using thermogravimetry at heating rates between 0.5 and 10 K min-1 studied the decomposition kinetics of the AP/HTPB propellant samples with isoconversional method and the calculated

From the slope of Kissinger plot (ln (/Tp2) vs. 1/Tp) and eq. (3) the activation energy was also calculated and is 126.2 kJ mol-1 for the non-aged samples, therefore quite similar to that

The thermal decomposition of solid composite propellant is a multistep process and the reaction mechanism changes with the temperature and, consequently, the activation energy varies with the extent of the reaction. DSC data are used to estimate the activation energies of thermal decomposition of propellant samples because the global decomposition reaction is taken in account. Implicit in any discussion about the decomposition is the fact that the overall process is complex, and any derived rate parameters do not correspond to an elementary single step. TG/DTG results are in

The pre-exponential factor was found to be 2.04 1010 min-1 (non-aged samples) and 1.29.106 min-1 (aged samples) and the reaction orders for the global composite decomposition were estimated in 0.7 (non-aged) and 0.6 (aged) by the kinetic Shimadzu software based in the Ozawa method. This value is quite different from the Arrhenius assumption where the reaction order is always considered as 1.0. For practical purposes the Arrhenius parameters, like the corrected reaction order, can be used to estimate the overall rate constant (k) for

The differences found in the kinetics parameters between the original and the aged samples, specially the activation energy (Ea), confirm the practical observation that energetic materials like the composites used in solid propellant rocket motors require less energy to start the combustion process as they age. Besides, considering the heating rate of 40 K min-1 for the original and for the aged samples, a reduction in the enthalpy of the decomposition's For energetic materials like composite solid propellant, it is critical to use the minimum sample size and low heating rates to avoid the risks to potential damage of the DSC cell resulting in DSC curves with a lot of interferences caused by the detonation behavior of composite samples. In opposition to this criteria, in this study, high heating rates were used (10.0 to 45.0 K min-1), but to compensate this condition very low sample sizes were used ( 1.5 mg). Despite these heating rates are not close to the rocket motor chamber conditions (heating rates estimated as 106 K s-1) the slower heating rates used in this work allow one to get a better insight into the reaction kinetics mechanisms.

Applications of Calorimetry in a Wide Context – 340 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The Ozawa and Kissinger methods demonstrated that differential scanning calorimetry technique, based on the linear relation between peak temperature and heating rate, can be used to determine the kinetics parameters of thermal decomposition reaction of energetic materials giving reproducible results.

Thermal Decomposition Kinetics of Aged Solid Propellant Based on Ammonium Perchlorate – AP/HTPB Binder 341

[10] Mathot V B F (2001) New routes for thermal analysis and calorimetry as applied to

[11] Maijling J, Simon P, Khunová V (2002) Optical Transmittance Thermal Analysis of the

[12] de Klerk W P C, Schrader, M A, van der Steen A C (1999) Compatibility Testing of Energetic Materials, Which Technique?, J. Therm. Anal. Cal., Vol. 56, pp. 1123,

[13] Stankovic M, Kapor V, Petrovic S (1999) The Thermal Decomposition of Triple-Base

[14] Jones D E G, Feng H T, Augsten R A, Fouchard R C (1999) Thermal Analysis Studies on

[15] Kissinger H E (1957) Reaction Kinetics in Differential Thermal Analysis, Anal. Chem.,

[16] Ozawa T, Isozaki H, Negishi A (1970) A new type of quantitative differential analysis,

[17] Flynn J H (1966) A quick, direct method for the determination of activation energy from

[18] Park J W, Lee H P, Kim H T, Yoo K O (2000) A kinetic analysis of thermal degradation of polymers using a dynamic method, Polym. Degrad.Stabil., Vol. 67, pp. 535. [19] Ozawa T (2001) Temperature control modes in thermal analysis, J. Therm. Anal. Cal*.*,

[21] Na-Lu L, Tsao-Fa Y (1991) The thermal behavior of porous residual ammonium

[22] Shin-Ming S, Sun-I C, Bor-Horng W (1993) The thermal decomposition of ammonium perchlorate (AP) containing a burning-rate modifier, Thermochim. Acta, Vol. 223, pp.

[23] Sell T, Vyazovkin S, Wight C A (1999) Thermal decomposition kinetics of PBAN-Binder

[24] Cohen N S, Fleming R W, Derr R L (1974) Role of binders in solid propellant

[25] Xiao-Bin Z, Lin-Fa H, Xiao-Ping Z (2000) Thermal decomposition and combustion of GAP/NA/Nitrate Ester propellants, Progress in Astronautics and Aeronautics, AIAA,

[26] Du T (1989) Thermal decomposition studies of solid propellant binder HTPB,

[27] Rocco J A F F, Lima J E S, Frutuoso A G, Iha K, Ionashiro M, Matos J R, Suárez-Iha M E V (2004) Thermal degradation of a composite solid propellant examined by DSC –

and composite solid rocket propellants, Combust. Flame, Vol. 119, pp. 174.

Poly(Ethylene Terephtalate) Foils, J. Therm. Anal. Cal., Vol. 67, pp. 201, 206.

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thermogravimetric data, Thermochim. Acta, Vol. 4, pp. 323.

[20] Sauerbrunn S, Gill P, Decomposition Kinetics using TGA, TA Instruments.

Thermochimica Acta., Vol. 1, No. 6, pp. 545, 553.

percholate, Thermochim. Acta, Vol. 186, pp. 53.

combustion, AIAA Journal, Vol. 6, pp. 212.

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Kinetic study, J. Therm. Anal. Cal., Vol. 75, pp. 551, 557.

1131.

135.

Vol. 185, pp. 413.

Vol. 29, pp. 1702.

Vol. 64, 2001, pp. 109, 126.

The DSC curves do not show any interference and the kinetic data obtained using the maximum temperatures (reciprocal, in K-1) and the respective heating rates are very close to the results found in the literature, at very lower heating rates [26-29].

### **Author details**

R. F. B. Gonçalves, J. A. F. F. Rocco and K. Iha *Instituto Tecnológico de Aeronáutica, CTA, São José dos Campos, S.P., Brasil* 

### **Acknowledgement**

The authors gratefully acknowledge financial support from FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) and CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) for the fundings and investiments.

### **5. References**


[10] Mathot V B F (2001) New routes for thermal analysis and calorimetry as applied to polymeric systems, J. Therm. Anal. Cal., Vol. 64, pp. 15, 35.

Applications of Calorimetry in a Wide Context –

materials giving reproducible results.

R. F. B. Gonçalves, J. A. F. F. Rocco and K. Iha

**Author details** 

**Acknowledgement** 

**5. References** 

340 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

the results found in the literature, at very lower heating rates [26-29].

*Instituto Tecnológico de Aeronáutica, CTA, São José dos Campos, S.P., Brasil* 

Científico e Tecnológico) for the fundings and investiments.

Astronautics and Aeronautics, AIAA, Vol.185, pp. 3.

[5] Kubota N (2002) Propellants and Explosives, Wiley-VCH.

Combustion Science, 33, 497.

[3] Boggs T L (1970) AIAA Journal, 8, 5, 867.

26th Joint Propulsion Conference.

Thermochimica Acta, Vol. 384, pp. 343, 349.

The Ozawa and Kissinger methods demonstrated that differential scanning calorimetry technique, based on the linear relation between peak temperature and heating rate, can be used to determine the kinetics parameters of thermal decomposition reaction of energetic

The DSC curves do not show any interference and the kinetic data obtained using the maximum temperatures (reciprocal, in K-1) and the respective heating rates are very close to

The authors gratefully acknowledge financial support from FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) and CNPq (Conselho Nacional de Desenvolvimento

[1] Brill T B, Budenz B T (2000) Flash Pyrolysis of Ammonium Perchlorate-Hydroxyl-Terminated-Polybutadiene Mixtures Including Selected Additives, Progress in

[2] Beckstead M W, Puduppakkam K, Thakre P, Yang V (2007) Progress in Energy and

[4] Beckstead M W, Puduppakkam K V (2004) Modeling and Simulation of Combustion of Solid Propellant Ingredients Using Detailed Chemical Kinetics, 40th

[6] Gross M L (2007) Two-dimensional modeling of AP/HTPB utilizing a vorticity

[7] Gonçalves R F B, Rocco J A F F, Machado F B C, Iha K (2012) Ammonium perchlorate and ammonium perchlorate-hydroxyl terminated polybutadiene simulated combustion,

[8] Korobeinichev O, Ermolin N, Chernov A, Emel'yanov I (1990) AIAA/SAE/ASME/ASEE

[9] Celina M, Minier L, Assink, R (2002) Development and application tool characterize the oxidative degradation of AP/HTPB/Al propellants in a propellant reability study,

AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit.

formulation and one-dimensional modeling of AP and ADN.

Journal of Aerospace Technology and Management, v 4, n1.


	- [28] Andrade J, Frutuoso A G, Iha K, Rocco J A F F, Bezerra E M, Matos J R, Suárez-Iha M E V (2008) Estudo da decomposição térmica de propelente sólido compósito de baixa emissão de fumaça, Quim. Nova, Vol. 31, No. 2, pp. 301-305.

**Chapter 15** 

© 2013 Yamada, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

**Numerical Solutions for Structural** 

**Studied by Activation Energy Spectrum Model** 

What is the physical process which is producing the general characteristic of glass? It is said that the transformation of the liquid-system to glass one is a final theme in physics through into the twenty-first century. Furthermore, the development of amorphous-material devices and specimen modification methods is closely related with the obviousness of high thermal

The aim of this research is to clarify numerical solutions for nano-structure relaxation processes focusing on the activation energy in transition metal (ie Cu, Fe) based amorphous alloys. Activation energy for structural relaxation process in a metal type amorphous ternary and quaternary alloys, with cross sections of typically 0.03 mm x 2.0 mm, prepared by chill-block melt spinning has been investigated by Differential Scanning Calorimetry (DSC) with a cyclically heating technique [1,2,3]. Activation energies for structural relaxation with a spatial quantity in amorphous materials have been discussed by use of a total relaxed ratio function that depends on annealing temperature and time. In the present work in amorphous ternary and quaternary alloys, the distributions for the Activation Energy Spectrum (AES) with derivative-type relaxed ratio function were observed. Another result has been also established that the "reversible" AES model energy distribution though the cyclically nano-structural relaxations were in good agreement with the presented

There has been recently considerable that the glassy alloys are representative of the bulk formed ultra-fine structure [1]. Particularly Cu has been shown to be good base element for bulk glass-forming alloy with fully glassy sections recently by use of die injection casting [2,3]. Binary Cu - (Zr or Hf) alloys have been found to form an amorphous phase over a

experimental results of transition metal based amorphous alloys.

**Relaxation of Amorphous Alloys** 

Additional information is available at the end of the chapter

Kazu-masa Yamada

http://dx.doi.org/10.5772/53723

stability and stability of relaxation.

**1. Introduction** 

[29] Andrade J, Iha K, Rocco J A F F, Bezerra E M (2007) Análise térmica aplicada ao estudo de materiais energéticos, Quim. Nova, Vol. 30, No. 4, pp. 952, 956.

## **Numerical Solutions for Structural Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model**

Kazu-masa Yamada

Applications of Calorimetry in a Wide Context –

342 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

emissão de fumaça, Quim. Nova, Vol. 31, No. 2, pp. 301-305.

de materiais energéticos, Quim. Nova, Vol. 30, No. 4, pp. 952, 956.

[28] Andrade J, Frutuoso A G, Iha K, Rocco J A F F, Bezerra E M, Matos J R, Suárez-Iha M E V (2008) Estudo da decomposição térmica de propelente sólido compósito de baixa

[29] Andrade J, Iha K, Rocco J A F F, Bezerra E M (2007) Análise térmica aplicada ao estudo

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53723

### **1. Introduction**

What is the physical process which is producing the general characteristic of glass? It is said that the transformation of the liquid-system to glass one is a final theme in physics through into the twenty-first century. Furthermore, the development of amorphous-material devices and specimen modification methods is closely related with the obviousness of high thermal stability and stability of relaxation.

The aim of this research is to clarify numerical solutions for nano-structure relaxation processes focusing on the activation energy in transition metal (ie Cu, Fe) based amorphous alloys. Activation energy for structural relaxation process in a metal type amorphous ternary and quaternary alloys, with cross sections of typically 0.03 mm x 2.0 mm, prepared by chill-block melt spinning has been investigated by Differential Scanning Calorimetry (DSC) with a cyclically heating technique [1,2,3]. Activation energies for structural relaxation with a spatial quantity in amorphous materials have been discussed by use of a total relaxed ratio function that depends on annealing temperature and time. In the present work in amorphous ternary and quaternary alloys, the distributions for the Activation Energy Spectrum (AES) with derivative-type relaxed ratio function were observed. Another result has been also established that the "reversible" AES model energy distribution though the cyclically nano-structural relaxations were in good agreement with the presented experimental results of transition metal based amorphous alloys.

There has been recently considerable that the glassy alloys are representative of the bulk formed ultra-fine structure [1]. Particularly Cu has been shown to be good base element for bulk glass-forming alloy with fully glassy sections recently by use of die injection casting [2,3]. Binary Cu - (Zr or Hf) alloys have been found to form an amorphous phase over a

wide composition range. However, addition of Ti in both these binary systems greatly increased the glass forming ability (GFA), with the critical diameter for fully amorphous rods being at least 4 mm for Cu60Zr30Ti10, Cu60Hf20Ti20 and Cu55Hf25Ti20 [2,3]. Meanwhile the understanding of the structural relaxation process is essential in the development of stability for amorphous alloys, as well as in establishing stable working temperature to avoid the degradation of strength. Therefore, high thermal stability of quasi-stable amorphous materials for Cu based alloys. The atomic mechanism of diffusion in amorphous alloys is still poorly understood as compared to that in crystalline alloys. However, measurements of diffusivity in amorphous alloys have been limited so far because of the experimental difficulties of measuring the very small diffusion coefficients, usually less than 10-17 m2s-1, which are typical of amorphous alloys below their crystallization temperatures [4,5].

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 345

study the structural relaxation is important to investigate the constitutional property of the amorphous alloys. Furthermore, the structural relaxation is closely connected with the stability of specific examples related to the bulk glass-forming amorphous alloy. It is also

Consider the population of an assembly of reaction centre for structural relaxation, that is to say isolated double wells potential model (or so called Two Level System, TLS) as shown in Fig. 1[9]. A relaxation centre which is isolated and in a particular structural configuration, permits an atom to be either in a higher energy position at state 0 or in a lower energy position at state 1 in Fig. 1. The axis of abscissas is the configuration variable for relaxation processes, and the position 1/2 on the axis in Fig.1 is the saddle point for the energy wall

**Figure 1.** Schematic illustrations of relaxation centre and energy levels for the corresponding two level

necessary to know this property from a viewpoint of the application development.

between the position 0 and 1.

system

In the present work, using Differential Scanning Calorimetry (DSC) thermal analysis has been made to determine the activation processes [6,7,8], and to evaluate whether it represents the thermodynamically stable form of CuHfTi and CuHfTi-B glass-forming amorphous alloys.

### **2. Experimental procedure**

Cu-based alloy ingots of composition Cu60Hf20Ti20, (Cu60Hf22Ti18)0.99B1 and (Cu60Hf22Ti18)0.97B3 were prepared by arc-melting mixtures in an argon gas atmosphere purified with a Ti getter. The alloy compositions represent the nominal values but the weight losses in melting were negligible. The alloy ingots were inverted on the hearth and re-melted several times, to ensure compositional homogeneity. Ribbon samples of each alloy, with cross sections of typically 0.03 mm \* 2.0 mm, were produced by chill-block melt spinning in a sealed inactive gas atmosphere. The amorphous state of the specimen of the ribbon samples was confirmed by X-ray diffraction.

The endothermic/exothermic heats for relaxation process were measured by differential scanning calorimetry (DSC) of DSC3100s of MacScience Co., Ltd (Bruker Japan Co., Ltd.) at a constant heating rate of 1.00 K/s. And the ordered specimens were prepared by annealing used in the electric furnace of the DSC. Pre-annealing and following long-time main annealing by a DSC furnace are at a 700 K for 1800 s and at a 580 K for 6000 s, respectively. The maximum temperature of 700 K is enough to suppress the crystallization and to measure optimistically the structural relaxation for these three kinds of specimen [9].

### **2.1. Theory with DSC annealing process**

Due to insufficient data of thermal stability of amorphous alloys, the following points are left as future problems. Even bulk glass-forming alloy, also amorphous alloys is a nonequilibrium state. The certain overall atoms in an amorphous alloy are in non-stable state rather than in the stable crystalline state. Therefore, not only crystallization over a certain wide temperature range but also re-arrangement of atoms occurs. The structural relaxation process is one of the essential phenomena in some non-equilibrium materials. Thereby, to study the structural relaxation is important to investigate the constitutional property of the amorphous alloys. Furthermore, the structural relaxation is closely connected with the stability of specific examples related to the bulk glass-forming amorphous alloy. It is also necessary to know this property from a viewpoint of the application development.

Applications of Calorimetry in a Wide Context –

amorphous alloys.

by X-ray diffraction.

**2. Experimental procedure** 

**2.1. Theory with DSC annealing process** 

344 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

wide composition range. However, addition of Ti in both these binary systems greatly increased the glass forming ability (GFA), with the critical diameter for fully amorphous rods being at least 4 mm for Cu60Zr30Ti10, Cu60Hf20Ti20 and Cu55Hf25Ti20 [2,3]. Meanwhile the understanding of the structural relaxation process is essential in the development of stability for amorphous alloys, as well as in establishing stable working temperature to avoid the degradation of strength. Therefore, high thermal stability of quasi-stable amorphous materials for Cu based alloys. The atomic mechanism of diffusion in amorphous alloys is still poorly understood as compared to that in crystalline alloys. However, measurements of diffusivity in amorphous alloys have been limited so far because of the experimental difficulties of measuring the very small diffusion coefficients, usually less than 10-17 m2s-1,

which are typical of amorphous alloys below their crystallization temperatures [4,5].

In the present work, using Differential Scanning Calorimetry (DSC) thermal analysis has been made to determine the activation processes [6,7,8], and to evaluate whether it represents the thermodynamically stable form of CuHfTi and CuHfTi-B glass-forming

Cu-based alloy ingots of composition Cu60Hf20Ti20, (Cu60Hf22Ti18)0.99B1 and (Cu60Hf22Ti18)0.97B3 were prepared by arc-melting mixtures in an argon gas atmosphere purified with a Ti getter. The alloy compositions represent the nominal values but the weight losses in melting were negligible. The alloy ingots were inverted on the hearth and re-melted several times, to ensure compositional homogeneity. Ribbon samples of each alloy, with cross sections of typically 0.03 mm \* 2.0 mm, were produced by chill-block melt spinning in a sealed inactive gas atmosphere. The amorphous state of the specimen of the ribbon samples was confirmed

The endothermic/exothermic heats for relaxation process were measured by differential scanning calorimetry (DSC) of DSC3100s of MacScience Co., Ltd (Bruker Japan Co., Ltd.) at a constant heating rate of 1.00 K/s. And the ordered specimens were prepared by annealing used in the electric furnace of the DSC. Pre-annealing and following long-time main annealing by a DSC furnace are at a 700 K for 1800 s and at a 580 K for 6000 s, respectively. The maximum temperature of 700 K is enough to suppress the crystallization and to

Due to insufficient data of thermal stability of amorphous alloys, the following points are left as future problems. Even bulk glass-forming alloy, also amorphous alloys is a nonequilibrium state. The certain overall atoms in an amorphous alloy are in non-stable state rather than in the stable crystalline state. Therefore, not only crystallization over a certain wide temperature range but also re-arrangement of atoms occurs. The structural relaxation process is one of the essential phenomena in some non-equilibrium materials. Thereby, to

measure optimistically the structural relaxation for these three kinds of specimen [9].

Consider the population of an assembly of reaction centre for structural relaxation, that is to say isolated double wells potential model (or so called Two Level System, TLS) as shown in Fig. 1[9]. A relaxation centre which is isolated and in a particular structural configuration, permits an atom to be either in a higher energy position at state 0 or in a lower energy position at state 1 in Fig. 1. The axis of abscissas is the configuration variable for relaxation processes, and the position 1/2 on the axis in Fig.1 is the saddle point for the energy wall between the position 0 and 1.

**Figure 1.** Schematic illustrations of relaxation centre and energy levels for the corresponding two level system

On the population of an assembly of this model, activation energy spectrum (AES) in structural relaxation processes, J. A. Leake, J. E. Evetts and M. R. J. Gibbs [10,11] describe the phenomena of physical available and variable property with good agreement between the theory and the experimentation. The theory assumes exponent factor nearly equal onedimension for chemical reaction kinetics of Jhonson-Mehl-Avrami (JMA) equation.

Therefore, the theoretical model for the relaxation process in amorphous materials on the basis of a spectrum of available processes with a distribution of activation energy was proposed. In their model, the total change in the measured property, *ΔP* is given by

$$
\Delta P = \int\_0^E p(E)dE\tag{1}
$$

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 347

In the range of activation energy *E* to *E*+d*E* during the structural relaxation process, the total available property *p*0(*E*) changes such as

$$p(E)\text{d}E = p\_0(E)\left[1 - \exp\left\{-\nu\_0 t \exp\left(-\frac{E}{kT}\right)\right\}\right]\text{d}E\tag{2}$$

where *ν*0 is an order of the Debye frequency ( *ν*<sup>0</sup> 1012 Hz) . Primak [12] rewrites Eq. (2) as

$$p(E) = p\_0(E)\,\theta\left(E, T, t\right),\tag{3}$$

where *θ*( *E*, *T*, *t* ) is defined as the characteristic annealing function. Thus, the function of *θ*( *E*, *T*, *t* ) is a measure of the proportion of available processes at the energy *E*. Proportion as *θ*( *E*, *T*, *t* ) has contributed to the relaxation property after the time *t* at the annealing temperature *T*. The form of *θ*( *E*, *T*, *t* ) is given in Fig. 2 (a) and (b) .

In the another paper [9], in a process for most simplifying assumption, the function *θ*( *E*, *T*, *t* ) can be replaced by step function at an energy *E*0(*T*, *t*) as

$$E\_0 = kT \ln\left(\nu\_0 t\right) \tag{4}$$

These *E*0 forms are given in Fig. 2 (c, d, e, f, g, h, i), then *E*0 changes from 0 to 1 over one-step meanwhile *θ* (*E*) changes over a narrow range of *E* and *T*. If in the simplified calculations, the *E*0 should have been applied. On the other hand, in the present work for calculation using specific 1st derivative-type relaxation ratio, as follows.

$$\frac{d\theta\left(E,T,t\right)}{dE} = \left\{\nu\_0 t \exp\left(-\frac{E}{kT}\right)\right\} \left(-\frac{E}{kT}\right) \exp\left\{-\nu\_0 t \exp\left(-\frac{E}{kT}\right)\right\} \tag{5}$$

The (5) function is shown in Fig 3 (a), on the contrary the derivative of *E*0(*T*) is shown in Fig 3 (b) . So it should be preferred replacement with a better approximation using the function (5). By using simple area summation method, furthermore the normalization for the linear function of S=0.234 T+0.244 in this case as shown in Fig 4 would be applied, we can estimate the actual activation energy spectra distributions using the method of Fig 5. It is so called normalized 1st derivative - type relaxation ratio function in our organized work.

available property *p*0(*E*) changes such as

346 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

0 0 ( )d ( ) 1 exp exp d *<sup>E</sup> pE E p E <sup>t</sup> <sup>E</sup>*

temperature *T*. The form of *θ*( *E*, *T*, *t* ) is given in Fig. 2 (a) and (b) .

*t* ) can be replaced by step function at an energy *E*0(*T*, *t*) as

using specific 1st derivative-type relaxation ratio, as follows.

0 0 *E kT t* ln

On the population of an assembly of this model, activation energy spectrum (AES) in structural relaxation processes, J. A. Leake, J. E. Evetts and M. R. J. Gibbs [10,11] describe the phenomena of physical available and variable property with good agreement between the theory and the experimentation. The theory assumes exponent factor nearly equal one-

Therefore, the theoretical model for the relaxation process in amorphous materials on the basis of a spectrum of available processes with a distribution of activation energy was

<sup>0</sup> ( )d *<sup>E</sup>*

where *ν*0 is an order of the Debye frequency ( *ν*<sup>0</sup> 1012 Hz) . Primak [12] rewrites Eq. (2) as

 <sup>0</sup> *pE p E ETt* () () ,, , 

where *θ*( *E*, *T*, *t* ) is defined as the characteristic annealing function. Thus, the function of *θ*( *E*, *T*, *t* ) is a measure of the proportion of available processes at the energy *E*. Proportion as *θ*( *E*, *T*, *t* ) has contributed to the relaxation property after the time *t* at the annealing

In the another paper [9], in a process for most simplifying assumption, the function *θ*( *E*, *T*,

These *E*0 forms are given in Fig. 2 (c, d, e, f, g, h, i), then *E*0 changes from 0 to 1 over one-step meanwhile *θ* (*E*) changes over a narrow range of *E* and *T*. If in the simplified calculations, the *E*0 should have been applied. On the other hand, in the present work for calculation

> 0 0 , , exp exp exp *d ETt E E <sup>E</sup> t t dE kT kT kT*

The (5) function is shown in Fig 3 (a), on the contrary the derivative of *E*0(*T*) is shown in Fig 3 (b) . So it should be preferred replacement with a better approximation using the function (5). By using simple area summation method, furthermore the normalization for the linear function of S=0.234 T+0.244 in this case as shown in Fig 4 would be applied, we can estimate the actual activation energy spectra distributions using the method of Fig 5. It is so called

normalized 1st derivative - type relaxation ratio function in our organized work.

 

(5)

In the range of activation energy *E* to *E*+d*E* during the structural relaxation process, the total

*P pE E* (1)

(3)

(4)

(2)

*kT*

dimension for chemical reaction kinetics of Jhonson-Mehl-Avrami (JMA) equation.

proposed. In their model, the total change in the measured property, *ΔP* is given by

348 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 349

**Figure 3.** (a). Dependence of the 1st derivation of *θ* ( *E*, *T*, *t*=1 s ) on the activation energy *E* and the temperature *T* . Fig. 3 (a) Derivative type *θ*( *E*, *T*, *t*=1 s ) . Right hand and left hand of charts are the same figure. Additionally right one is shown in grey scale for visible-contrasty (b). Dependence of the 1st derivation of *θ* ( *E*, *T*, *t*=1 s ) on the activation energy *E* and the temperature *T* . Fig. 3 (b) Approximation type *E*0(*T*, *t*=1 s). Right hand and left hand of charts are the same figure. Additionally right one is for visible-contrasty (c). Dependence of the 1st derivation of *θ* ( *E*, *T*=400, 500, 600 and 700K, *t*=1 s ) on the

activation energy *E*.

**Figure 2.** (a). Dependence of the characteristic annealing function *θ*( *E*, *T*, *t*=1s ) on the activation energy *E* and the temperature *T* [9,10]. Fig. 2(a) is used of *θ*( *E*, *T*, *t*=1s ) (b). Dependence of the characteristic annealing function θ( E, T, t=1s ) on the activation energy E and the temperature T [9,10]. Fig. 2(b) is used of θ( E, T, t=1s ) (c). Dependence of the characteristic annealing function *θ*( *E*, *T*, *t*=1s ) on the activation energy *E* and the temperature *T* [9,10]. Fig. 2(c) is used of *E*0(*T*, *t*=1s). Right hand and left hand of charts are the same figure. Additionally right one is shown in grey scale for visible-contrasty (d,e,f,g). Dependence of the characteristic annealing function *θ*( *E*, *T*, *t* ) and step function of threshold *E*0(*T*, *t*) on the horizontal axis of the activation energy *E* [9,10]. Fig. 2(d) at the upper left is used of *θ*( *E*, *T*, *t*=100s ). Fig. 2(e) at the upper right is used of *θ*( *E*, *T*=500K, *t* ). Fig. 2(f) at the lower left is used with step functions superposed on *θ*( *E*, *T*, *t*=100s ). Fig. 2(g) at the lower right is used with step functions superposed on *θ*( *E*, *T*=500K, *t* ) (h, i). Dependence of the simplifying assumption of characteristic annealing function, activation energy *E*0(*T*, *t*) vs the annealing time *t* and the isothermal annealing temperature *T* [9,10]. Fig. 2(h) at the left is used of *E*0(*T*, *t*=1, 10, 102, 103, 104, 105 and 106 s). Fig. 2(i) at the right is used of *E*0(*T*=450, 500, 550, 600, 650, 700, 750 and 800K)

348 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 2.** (a). Dependence of the characteristic annealing function *θ*( *E*, *T*, *t*=1s ) on the activation energy *E* and the temperature *T* [9,10]. Fig. 2(a) is used of *θ*( *E*, *T*, *t*=1s ) (b). Dependence of the characteristic annealing function θ( E, T, t=1s ) on the activation energy E and the temperature T [9,10]. Fig. 2(b) is used of θ( E, T, t=1s ) (c). Dependence of the characteristic annealing function *θ*( *E*, *T*, *t*=1s ) on the activation energy *E* and the temperature *T* [9,10]. Fig. 2(c) is used of *E*0(*T*, *t*=1s). Right hand and left hand of charts are the same figure. Additionally right one is shown in grey scale for visible-contrasty (d,e,f,g). Dependence of the characteristic annealing function *θ*( *E*, *T*, *t* ) and step function of threshold *E*0(*T*, *t*) on the horizontal axis of the activation energy *E* [9,10]. Fig. 2(d) at the upper left is used of *θ*( *E*, *T*, *t*=100s ). Fig. 2(e) at the upper right is used of *θ*( *E*, *T*=500K, *t* ). Fig. 2(f) at the lower left is used with step functions superposed on *θ*( *E*, *T*, *t*=100s ). Fig. 2(g) at the lower right is used with step functions superposed on *θ*( *E*, *T*=500K, *t* ) (h, i). Dependence of the simplifying assumption of characteristic annealing function, activation energy *E*0(*T*, *t*) vs the annealing time *t* and the isothermal annealing temperature *T* [9,10]. Fig. 2(h) at the left is used of *E*0(*T*, *t*=1, 10, 102, 103, 104, 105 and 106 s). Fig. 2(i) at the

right is used of *E*0(*T*=450, 500, 550, 600, 650, 700, 750 and 800K)

**Figure 3.** (a). Dependence of the 1st derivation of *θ* ( *E*, *T*, *t*=1 s ) on the activation energy *E* and the temperature *T* . Fig. 3 (a) Derivative type *θ*( *E*, *T*, *t*=1 s ) . Right hand and left hand of charts are the same figure. Additionally right one is shown in grey scale for visible-contrasty (b). Dependence of the 1st derivation of *θ* ( *E*, *T*, *t*=1 s ) on the activation energy *E* and the temperature *T* . Fig. 3 (b) Approximation type *E*0(*T*, *t*=1 s). Right hand and left hand of charts are the same figure. Additionally right one is for visible-contrasty (c). Dependence of the 1st derivation of *θ* ( *E*, *T*=400, 500, 600 and 700K, *t*=1 s ) on the activation energy *E*.

350 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 351

In the previous paper [9], we discussed at first the AES applied on the Cu-Hf-Ti system,

In Table 1 [2] the glass forming ability (GFA) related to the *T*rg (=*T*g / *T*L) was observed that addition of Ti in Cu-Hf binary systems greatly increased. In this table, they were shown with the critical diameter dC for fully amorphous rods being at least 3 mm for

**Table 1.** Glass forming section thickness and thermal property for Cu60Hf40-XTiX (X=from 5 to 35) alloy

After all, the aim of this research is also to clarify a quantitative evaluation in the structure relaxation processes focusing on the activation energy in Cu60Hf20Ti20 based amorphous

Pre-annealing and main-annealing conditions were completely similar the way as Ref. 9. After that it will be noted that an atom to be in a higher energy position at stage 0 in Fig. 1, endothermic heat occurs at 1st run in the measurement scanning #1 even at 1st run in #2, that is to say the reversible relaxation processes, and the 1st minus 2nd run indicates the endothermic value (the 2nd minus 1st run indicates the exothermic value) that could be calculate the AES distributions that means an atom to be in a higher energy position at stage

The liquidus temperature *T*L has its minimum value for the 20at%Ti alloy in Table 1, probably corresponding to a ternary eutectic system, it is because only this composition has single melting peak in the DTA trace [2]. Thus this is a dominating factor in determining that *T*rg has its maximum value at this composition clearly. The atomic diameter of Ti (0.289nm) is intermediate between those of Cu (0.256nm) and Hf (0.315nm) and, evidently, equal proportions of Hf and Ti result in maximum stabilization of the densely packed liquid

structure [2] and normalized 1st derivative - type relaxation ratio function.

**2.2. Experimental processes with DSC annealing** 

Cu60Hf22.5Ti17.5, Cu60Hf20Ti20 and Cu60Hf17.5Ti22.5 .

because of the following reasons.

series [2]

0 in Fig. 1.

alloys with high GFA series.

**Figure 4.** Dependence of the summation *S* of *1st* derivative type *θ*( *E*, *T*, *t*=1s ) on the temperature *T* . Plots can be replaced by linear function with a good approximation in *S* = 0.234 *T* + 0.244

**Figure 5.** (a). Divided by the *S* = 0.234 *T* + 0.244 of Fig 4 , dependence of the normalized 1st derivative type relaxation ratio function of *θ*( *E*, *T*, *t*=1s ) on the activation energy *E* and the temperature *T* . Right hand and left hand of charts are the same figure. Additionally right one is shown in grey scale for visiblecontrasty (b). Divided by the *S* = 0.234 *T* + 0.244 of Fig 4 , dependence of the normalized 1st derivative type relaxation ratio function of *θ*( *E*, *T*=400, 500, 600 and 700K, *t*=1 s) on the activation energy *E*

### **2.2. Experimental processes with DSC annealing**

Applications of Calorimetry in a Wide Context –

350 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 4.** Dependence of the summation *S* of *1st* derivative type *θ*( *E*, *T*, *t*=1s ) on the temperature *T* .

**Figure 5.** (a). Divided by the *S* = 0.234 *T* + 0.244 of Fig 4 , dependence of the normalized 1st derivative type relaxation ratio function of *θ*( *E*, *T*, *t*=1s ) on the activation energy *E* and the temperature *T* . Right hand and left hand of charts are the same figure. Additionally right one is shown in grey scale for visiblecontrasty (b). Divided by the *S* = 0.234 *T* + 0.244 of Fig 4 , dependence of the normalized 1st derivative type relaxation ratio function of *θ*( *E*, *T*=400, 500, 600 and 700K, *t*=1 s) on the activation energy *E*

Plots can be replaced by linear function with a good approximation in *S* = 0.234 *T* + 0.244

In the previous paper [9], we discussed at first the AES applied on the Cu-Hf-Ti system, because of the following reasons.

In Table 1 [2] the glass forming ability (GFA) related to the *T*rg (=*T*g / *T*L) was observed that addition of Ti in Cu-Hf binary systems greatly increased. In this table, they were shown with the critical diameter dC for fully amorphous rods being at least 3 mm for Cu60Hf22.5Ti17.5, Cu60Hf20Ti20 and Cu60Hf17.5Ti22.5 .


**Table 1.** Glass forming section thickness and thermal property for Cu60Hf40-XTiX (X=from 5 to 35) alloy series [2]

After all, the aim of this research is also to clarify a quantitative evaluation in the structure relaxation processes focusing on the activation energy in Cu60Hf20Ti20 based amorphous alloys with high GFA series.

Pre-annealing and main-annealing conditions were completely similar the way as Ref. 9. After that it will be noted that an atom to be in a higher energy position at stage 0 in Fig. 1, endothermic heat occurs at 1st run in the measurement scanning #1 even at 1st run in #2, that is to say the reversible relaxation processes, and the 1st minus 2nd run indicates the endothermic value (the 2nd minus 1st run indicates the exothermic value) that could be calculate the AES distributions that means an atom to be in a higher energy position at stage 0 in Fig. 1.

The liquidus temperature *T*L has its minimum value for the 20at%Ti alloy in Table 1, probably corresponding to a ternary eutectic system, it is because only this composition has single melting peak in the DTA trace [2]. Thus this is a dominating factor in determining that *T*rg has its maximum value at this composition clearly. The atomic diameter of Ti (0.289nm) is intermediate between those of Cu (0.256nm) and Hf (0.315nm) and, evidently, equal proportions of Hf and Ti result in maximum stabilization of the densely packed liquid structure [2] and normalized 1st derivative - type relaxation ratio function.

352 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 353

In the presented work by use of the AES model, following above-mentioned, activation energies in structural relaxation processes have been determined of composition Cu60Hf20Ti20 and related (Cu60Hf22Ti18)0.99B1 and (Cu60Hf22Ti18)0.97B3 amorphous alloys as shown in Fig. 8.

The maximum energies in AES have similar tendency among three kinds of alloy nearly at 160 kJmol-1 (1.66 eV). Between the three kinds of B for 3, 1 and 0 % alloys, in an energy region less than 160 kJmol-1, AES of only B 3 % alloy is higher than that of B 1% and 0 %.

This suggests that the diffusion path size for the diffusant of Ti that atomic radius is smallest in the metallic compositions and the packing density of the covalent bonding matrix between the boron and metal are dominant in the relaxation processes. Consequently activation energy for the structural relaxation process has been determined in the Cu60Hf20Ti20 with having the highest bulk glass-forming ability in Cu60Hf40-XTiX (X are from 5 to 35 %) alloy series as almost 160 kJmol-1 (1.66 eV) using the normalized derivative - type

**Figure 8.** *In the present work for calculation using specific* normalized *1st derivative - type relaxation ratio function* of *θ*( *E*, *T*, *t*=1s ) , activation energy spectrum distributed in Cu60Hf20Ti20 , (Cu60Hf22Ti18)0.99B1 and

In the Fig. 7., four-leafed schematic illustrations show on the DSC scanning #1, #2, we could evaluate the value included relaxation processes for scanning 1st run then 2nd run, on the other hand we could estimate the value included not relaxation processes for scanning 2nd run then 3rd run that are almost without relaxation. So solving the value should be calculated by DSC exothermic heats of 2nd run minus 1st run. So it is very important to calculate the differences between 2nd and 1st run. But also it is difficult to calculated form the DSC exothermic heats of 2nd run minus 1st run because of the temperature scanning step problem. This section describes the way of calculation how to get the differences

Meanwhile, in an energy region more than 160 kJmol-1, AES of them are similar.

**3. Results through experimental procedure** 

relaxed ratio function [9].

(Cu60Hf22Ti18)0.97B3

(distinction) data.

**4. Calculation technique** 

**Figure 6.** An example of annealing time and temperature history by use in fully electric furnace of the DSC. Specimens were prepared by annealing used in the DSC furnace, pre-annealing and following longtime main-annealing are at 700 K (=*T*2) for 1800 s (=*t*0) and recycled at a 580 K(=*T*1) for 6000 s(=*t*1), respectively. The maximum temperature of *T*2 is enough to suppress the crystallization and to measure optimistically the structural relaxation following the continuous scan #1 1st run to n-th run. The "reversible" phenomena have been observed in the anneal process of scan #2 to scan #n as shown in Fig.7.

**Figure 7.** four-leafed schematic illustrations of reversible phenomena for DSC scanning #1 then #2, and included relaxation processes for scanning 1st run then 2nd run, on the other hand without relaxation processes for scanning 2nd run then 3rd run

### **3. Results through experimental procedure**

Applications of Calorimetry in a Wide Context –

352 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 6.** An example of annealing time and temperature history by use in fully electric furnace of the DSC. Specimens were prepared by annealing used in the DSC furnace, pre-annealing and following longtime main-annealing are at 700 K (=*T*2) for 1800 s (=*t*0) and recycled at a 580 K(=*T*1) for 6000 s(=*t*1), respectively. The maximum temperature of *T*2 is enough to suppress the crystallization and to measure optimistically the structural relaxation following the continuous scan #1 1st run to n-th run. The

"reversible" phenomena have been observed in the anneal process of scan #2 to scan #n as shown in Fig.7.

**Figure 7.** four-leafed schematic illustrations of reversible phenomena for DSC scanning #1 then #2, and included relaxation processes for scanning 1st run then 2nd run, on the other hand without relaxation

processes for scanning 2nd run then 3rd run

In the presented work by use of the AES model, following above-mentioned, activation energies in structural relaxation processes have been determined of composition Cu60Hf20Ti20 and related (Cu60Hf22Ti18)0.99B1 and (Cu60Hf22Ti18)0.97B3 amorphous alloys as shown in Fig. 8.

The maximum energies in AES have similar tendency among three kinds of alloy nearly at 160 kJmol-1 (1.66 eV). Between the three kinds of B for 3, 1 and 0 % alloys, in an energy region less than 160 kJmol-1, AES of only B 3 % alloy is higher than that of B 1% and 0 %. Meanwhile, in an energy region more than 160 kJmol-1, AES of them are similar.

This suggests that the diffusion path size for the diffusant of Ti that atomic radius is smallest in the metallic compositions and the packing density of the covalent bonding matrix between the boron and metal are dominant in the relaxation processes. Consequently activation energy for the structural relaxation process has been determined in the Cu60Hf20Ti20 with having the highest bulk glass-forming ability in Cu60Hf40-XTiX (X are from 5 to 35 %) alloy series as almost 160 kJmol-1 (1.66 eV) using the normalized derivative - type relaxed ratio function [9].

**Figure 8.** *In the present work for calculation using specific* normalized *1st derivative - type relaxation ratio function* of *θ*( *E*, *T*, *t*=1s ) , activation energy spectrum distributed in Cu60Hf20Ti20 , (Cu60Hf22Ti18)0.99B1 and (Cu60Hf22Ti18)0.97B3

### **4. Calculation technique**

In the Fig. 7., four-leafed schematic illustrations show on the DSC scanning #1, #2, we could evaluate the value included relaxation processes for scanning 1st run then 2nd run, on the other hand we could estimate the value included not relaxation processes for scanning 2nd run then 3rd run that are almost without relaxation. So solving the value should be calculated by DSC exothermic heats of 2nd run minus 1st run. So it is very important to calculate the differences between 2nd and 1st run. But also it is difficult to calculated form the DSC exothermic heats of 2nd run minus 1st run because of the temperature scanning step problem. This section describes the way of calculation how to get the differences (distinction) data.

354 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In the Fig. 9., if they were a typical numerical example for differential calculation with supplied as text-type file name, for example, TEST00.TXT of 1th DSC run and TEST01.TXT of 2nd one, it would be transformed from their differential calculation to result numerical data such as TEST04.TXT, to be free to use a program such as GP.EXE ver. 4.13 and DOSBox version 0.74. The 2-Dimension Graph Plotter GP.EXE version 4.13-PC/AT and Dos-emulator DOSBox version 0.74 for all kind of MS-windows OS (another DOSBox version exists for MAC OS probably) are both free software supported in English keyboard peripheral interface. Additionally information, the GP.EXE was built by Prof. Dr. K. Edamatsu( now at riec.tohoku.ac.jp) in 1980-99 year for design to plot scientific/engineering graphs using PCs. Prof. Edamatsu said in his GP's documentation "with GP.EXE, make smart graphs for your presentation and publication. Also, try GP's powerful data analysis capability such as general least-squares fitting, numerical differentiation and integration".

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 355

need to user for non-automatic start of GP. For normal user, it should be ignore the last one. Otherwise all users command the type key of **gp** on DOSBox command line**,** GP.EXE starts

**# Lines in this section will be run at** 

**# You can put your MOUNT lines here.** 

**Table 2.** A sample of Dos-emulator DOSBox version 0.74 configuration file description (as shown in

through a whole text-file for GP because of a purpose for a title and axis captions.

because of keeping the safety-connection between the live data and the GPR file.

rapid setting for similar graph format preparations.

**[autoexec]** 

**startup.** 

**@ECHO OFF MOUNT c C:\** 

**c:** 

and #3 should be with differential calculation for #3 minus #2.

In the Fig. 11., GP.EXE column structure menu indicating live date column was shown. In the case, X, Y, YE of default column structure allow to use a delimiter also space and tabulator key. Live data should be minimum structure of X and Y with delimiter of space key. Meanwhile additional data column if include could be were specially galloped by use of "U" rule for GP column structure. The typical sample structure of live data is shown in Table 3a and 3b. Addition the 1st, 2nd and 3rd line were normally (default) galloped

INIT.GPR and other GPR files would be able to modified by a text-type general-purpose editor, then directory file path, captions and so on in them could be also re-arranged and

Note: GPR file always includes full-Path towards live data, but usually it is NOT often need to full-Path towards them but only Local-Path that means without non-Path description, then some of this full-Path should be deleted by use of a text-type general-purpose editor

In the Fig. 12., load file name menu indicates the live date formatted general-purpose textstyle pursuant to table 3a,3b. As it was shown, 3 files (2 kinds of file) of TEST00.TXT, TEST01.TXT and TEST00.TXT are loaded in the live data tray in GP.EXE for 2 data differential calculations. The file #1 should be without differential calculations. The file #2

In the Fig. 13., load and save parameter's file (GPR of extensions) menu indicates graph structure list organized whole graphic design. Especially GPR file is also plain text-type, so we could arrange them before/afterward by use of a text-type general-purpose editor anytime.

Note: GP.EXE system is so called legacy-DOS, overall generated user filename must be kept the name rule of 8 character letter filename and 3 character letter extensions around in the

anytime.

autoexec area only)

GP directory.

In around 2010 year, the GP.EXE with super high speed and powerful data analysis capability is born-again by use of high performance Dos-emulator DOSBox.

Presented process, to calculate the differential exo/endothermic heat supplied from DSC live scanning environmental with gas flow atmosphere. Overall, Relaxation processes for example has been tutorial as bellow description mainly using the freeware GP.EXE, further only using scanning data 1st run to 2nd run.

In the Fig. 10., for introduction to present calculation technique, typical complex 2-D tutorial graph samples are shown by using GP.EXE. A left chart is the typical Gaussian differentiation tutorial sample, 1st derivative and 2nd one and experimental data and calculation. A right chart is the typical Ahhrenius tutorial plot with inversed horizontal axis with logarithm vertical axis. If you were to use the GP.EXE, you should download from the site of www.vector.co.jp/soft/dos/business/se004831.html.

Then you could get the file of gpat431.lzh, you should make the directory for set the GP.EXE environments. It should be save and destination to (recommended): **C:/prog/gp/gp.exe**, **C:/prog/gp/INIT.GPR**, **C:/prog/gp/DOC**, **C:/prog/gp/ DRIVERS**, etc.

Note: GP.EXE system is so called legacy-DOS, overall generated user filename must be kept the name rule of 8 character letter filename and 3 character letter extensions around in the GP directory.

Addition you could get the file of gpsmp420.lzh of tutorial examples of GPR extension files, you could be easy to get the way the GP.EXE operating. As shown in Fig. 10., the tutorials exist in site of **www.vector.co.jp/soft/dos/business/se010753.html**.

In the Table 2. , Recommended Dos-emulator DOSBox version 0.74 configuration file descriptions are shown. You could edit (ie. MS-Win7) it in Program Menu, DOSBox options, editing the configuration, last lines for "autoexec" region. Addition, **keyb** command needs the user of Japanese JP106 keyboard peripheral interface only (addition the **keyb** program and keyboard-map should also be needed. The **keyb** system's useful information would be gathered in World Wide Web). Meanwhile for in English peripheral US101 user, the **keyb** command should be ignore. Furthermore the last **gp** command in table 2, it should not be need to user for non-automatic start of GP. For normal user, it should be ignore the last one. Otherwise all users command the type key of **gp** on DOSBox command line**,** GP.EXE starts anytime.

Applications of Calorimetry in a Wide Context –

only using scanning data 1st run to 2nd run.

GP directory.

354 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

general least-squares fitting, numerical differentiation and integration".

site of www.vector.co.jp/soft/dos/business/se004831.html.

**C:/prog/gp/INIT.GPR**, **C:/prog/gp/DOC**, **C:/prog/gp/ DRIVERS**, etc.

exist in site of **www.vector.co.jp/soft/dos/business/se010753.html**.

capability is born-again by use of high performance Dos-emulator DOSBox.

In the Fig. 9., if they were a typical numerical example for differential calculation with supplied as text-type file name, for example, TEST00.TXT of 1th DSC run and TEST01.TXT of 2nd one, it would be transformed from their differential calculation to result numerical data such as TEST04.TXT, to be free to use a program such as GP.EXE ver. 4.13 and DOSBox version 0.74. The 2-Dimension Graph Plotter GP.EXE version 4.13-PC/AT and Dos-emulator DOSBox version 0.74 for all kind of MS-windows OS (another DOSBox version exists for MAC OS probably) are both free software supported in English keyboard peripheral interface. Additionally information, the GP.EXE was built by Prof. Dr. K. Edamatsu( now at riec.tohoku.ac.jp) in 1980-99 year for design to plot scientific/engineering graphs using PCs. Prof. Edamatsu said in his GP's documentation "with GP.EXE, make smart graphs for your presentation and publication. Also, try GP's powerful data analysis capability such as

In around 2010 year, the GP.EXE with super high speed and powerful data analysis

Presented process, to calculate the differential exo/endothermic heat supplied from DSC live scanning environmental with gas flow atmosphere. Overall, Relaxation processes for example has been tutorial as bellow description mainly using the freeware GP.EXE, further

In the Fig. 10., for introduction to present calculation technique, typical complex 2-D tutorial graph samples are shown by using GP.EXE. A left chart is the typical Gaussian differentiation tutorial sample, 1st derivative and 2nd one and experimental data and calculation. A right chart is the typical Ahhrenius tutorial plot with inversed horizontal axis with logarithm vertical axis. If you were to use the GP.EXE, you should download from the

Then you could get the file of gpat431.lzh, you should make the directory for set the GP.EXE environments. It should be save and destination to (recommended): **C:/prog/gp/gp.exe**,

Note: GP.EXE system is so called legacy-DOS, overall generated user filename must be kept the name rule of 8 character letter filename and 3 character letter extensions around in the

Addition you could get the file of gpsmp420.lzh of tutorial examples of GPR extension files, you could be easy to get the way the GP.EXE operating. As shown in Fig. 10., the tutorials

In the Table 2. , Recommended Dos-emulator DOSBox version 0.74 configuration file descriptions are shown. You could edit (ie. MS-Win7) it in Program Menu, DOSBox options, editing the configuration, last lines for "autoexec" region. Addition, **keyb** command needs the user of Japanese JP106 keyboard peripheral interface only (addition the **keyb** program and keyboard-map should also be needed. The **keyb** system's useful information would be gathered in World Wide Web). Meanwhile for in English peripheral US101 user, the **keyb** command should be ignore. Furthermore the last **gp** command in table 2, it should not be

```
[autoexec] 