You can put your MOUNT lines here. 
@ECHO OFF 
MOUNT c C:\ 
c:
```
**Table 2.** A sample of Dos-emulator DOSBox version 0.74 configuration file description (as shown in autoexec area only)

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 through a whole text-file for GP because of a purpose for a title and axis captions.

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 rapid setting for similar graph format preparations.

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 because of keeping the safety-connection between the live data and the GPR file.

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 and #3 should be with differential calculation for #3 minus #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 GP directory.

Applications of Calorimetry in a Wide Context – 356 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In the Fig. 14., a Interfile Calculation Parameters and style-menu displayed, red-mark of TEST01 (Src. file # 2) on left-y-axis and white-mark of TEST00 (Src. file # 1) on left-y-axis, meanwhile blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis. The aim of this computation is to process the file #3 minus #2 based rule on column X date for Temperature region. Finally a result of the processed data has been shown as blue-mark beside on right-y-axis.

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 357

**Figure 11.** At first, column structure menu indicates the live date column structure

**Figure 12.** Second, load file name menu indicates the live date formatted general-purpose text-style

pursuant to table 3a,3b

**Figure 9.** 2-Dimension Graph Plotter GP.EXE version 4.13-PC/AT and Dos-emulator DOSBox version 0.74 are both free software in English supported to calculate the differential exothermic heat data using DSC included relaxation processes for example, scanning 1st run to 2nd run.

GP.EXE: http://www.vector.co.jp/soft/dos/business/se004831.html GP.EXE samples :http://www.vector.co.jp/soft/dos/business/se010753.html

**Figure 10.** Typical samples of 2-Dimension Graph Plotter GP.EXE. A left chart is the typical Gaussian differentiation sample, 1st derivative and 2nd one and experimental data and calculation. A right chart is the typical Ahhrenius-type plot with inversed horizontal axis together with logarithm vertical axis. Green colour cross line indicator means the across point both live-data and translated-data.

**Figure 11.** At first, column structure menu indicates the live date column structure

beside on right-y-axis.

356 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In the Fig. 14., a Interfile Calculation Parameters and style-menu displayed, red-mark of TEST01 (Src. file # 2) on left-y-axis and white-mark of TEST00 (Src. file # 1) on left-y-axis, meanwhile blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis. The aim of this computation is to process the file #3 minus #2 based rule on column X date for Temperature region. Finally a result of the processed data has been shown as blue-mark

**Figure 9.** 2-Dimension Graph Plotter GP.EXE version 4.13-PC/AT and Dos-emulator DOSBox version 0.74 are both free software in English supported to calculate the differential exothermic heat data using

**Figure 10.** Typical samples of 2-Dimension Graph Plotter GP.EXE. A left chart is the typical Gaussian differentiation sample, 1st derivative and 2nd one and experimental data and calculation. A right chart is the typical Ahhrenius-type plot with inversed horizontal axis together with logarithm vertical axis.

Green colour cross line indicator means the across point both live-data and translated-data.

DSC included relaxation processes for example, scanning 1st run to 2nd run.

GP.EXE: http://www.vector.co.jp/soft/dos/business/se004831.html

GP.EXE samples :http://www.vector.co.jp/soft/dos/business/se010753.html

**Figure 12.** Second, load file name menu indicates the live date formatted general-purpose text-style pursuant to table 3a,3b

358 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 359

**Figure 13.** Third, load parameter's file menu indicates organized graph structure

**Figure 14.** Forth, *an Interfile Calculation Parameters and* style-menu displayed, red-mark of TEST01 (Src. file # 2) on left-y-axis and white-mark of TEST00 (Src. file # 1) on left-y-axis, meanwhile blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis. In the figure, a highlight area of green, the

In the Fig. 15., Left and right axis, so called Y-axis Plotting Parameters are shown relation to Fig.14. For Src. file #1 and 2 are to belong to left-y-axis named A of Y-axis and further

letter of the 2 means the #2 file that selected for Src. file #3 minus #2.

calculated Src. file #3 minus #2 is to belong to right-y-axis named B.


b

**Table 3.** a. Typical numerical example for differential calculation with random number generator only onside x-axis formatted for GP.exe as data filename TEST01.TXT b. Typical numerical example for differential calculation formatted for GP.exe as data filename TEST00.TXT

**Figure 13.** Third, load parameter's file menu indicates organized graph structure

358 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

a

b

**Table 3.** a. Typical numerical example for differential calculation with random number generator only onside x-axis formatted for GP.exe as data filename TEST01.TXT b. Typical numerical example for

differential calculation formatted for GP.exe as data filename TEST00.TXT

**Figure 14.** Forth, *an Interfile Calculation Parameters and* style-menu displayed, red-mark of TEST01 (Src. file # 2) on left-y-axis and white-mark of TEST00 (Src. file # 1) on left-y-axis, meanwhile blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis. In the figure, a highlight area of green, the letter of the 2 means the #2 file that selected for Src. file #3 minus #2.

In the Fig. 15., Left and right axis, so called Y-axis Plotting Parameters are shown relation to Fig.14. For Src. file #1 and 2 are to belong to left-y-axis named A of Y-axis and further calculated Src. file #3 minus #2 is to belong to right-y-axis named B.

360 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 361

In the Fig. 17., It is the most important method for calculating of relaxation process. Text-fire save-menu using blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis should be describe for example as file name TEST04.TXT in write-data filename input region. Then the TEST04.TXT should be on further calculation process to equation (5) ,

**Figure 17.** Seventh, text-fire save-menu using blue-mark of TEST00 minus TEST01 (Src. file #3 minus

In the Fig. 18., PostScript-file save-menu using a PostScript-file driver of PS.DLL, that include gpat431.lzh archive, displayed in Plot Parameters panel. Furthermore the useful information, if it assumed to be a 01.ps as saved file name for presented graph design, it would be transformed from PostScript-file to PDF-file, for example, from 01.ps to assumed 01gw.pdf, to be free to use a program ghostscript ver. 9.04. It should be typed on commandline supported by each OS in current directory of 01.ps (not use the command-line in

"C:\Program Files\gs\gs9.04\bin\gswin32c.exe" -dNOPAUSE -dBATCH – sDEVICE = pdfwrite -r600 –sOutputFile = 01gw.pdf -c 300000

Assumed 01gw.pdf would be a graph with super-resolution quality attaching suitable for all kind of publications. For example, it could be transformed from their PDF to wordprocessor MS-Word, to be free to use a program such as "Acrobat Reader", and it should be typing keys of Control-a, then Zoom up to around 200%, then Control-c, after then in word-

#2) on right-y-axis as file name TEST04.TXT displayed in write-data panel

DOSBox ) as:

setvmthreshold save pop -f 01.ps

processor to be also typing keys Control-v for universal use.

*t*=1(s) , then should be normalized and multiplied by inverse reactor summation.

**Figure 15.** Fifth, Y-axis Plotting Parameters are shown. For Src. file #1 and 2 are to belong to left-y-axis named A and Src. file #3 minus #2 (calculated data) is to belong to right-y-axis named B

In the Fig. 16., Plotting green cross-line indicator means the calculated Src. file #3 minus #2 dots. Fig. 10s are also the similar for usage of cross-line indicator.

**Figure 16.** Sixth, Plotting green cross-line indicator means the calculated Src. file #3 minus #2 dots

In the Fig. 17., It is the most important method for calculating of relaxation process. Text-fire save-menu using blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis should be describe for example as file name TEST04.TXT in write-data filename input region. Then the TEST04.TXT should be on further calculation process to equation (5) , *t*=1(s) , then should be normalized and multiplied by inverse reactor summation.

Applications of Calorimetry in a Wide Context –

360 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 15.** Fifth, Y-axis Plotting Parameters are shown. For Src. file #1 and 2 are to belong to left-y-axis

In the Fig. 16., Plotting green cross-line indicator means the calculated Src. file #3 minus #2

**Figure 16.** Sixth, Plotting green cross-line indicator means the calculated Src. file #3 minus #2 dots

named A and Src. file #3 minus #2 (calculated data) is to belong to right-y-axis named B

dots. Fig. 10s are also the similar for usage of cross-line indicator.

**Figure 17.** Seventh, text-fire save-menu using blue-mark of TEST00 minus TEST01 (Src. file #3 minus #2) on right-y-axis as file name TEST04.TXT displayed in write-data panel

In the Fig. 18., PostScript-file save-menu using a PostScript-file driver of PS.DLL, that include gpat431.lzh archive, displayed in Plot Parameters panel. Furthermore the useful information, if it assumed to be a 01.ps as saved file name for presented graph design, it would be transformed from PostScript-file to PDF-file, for example, from 01.ps to assumed 01gw.pdf, to be free to use a program ghostscript ver. 9.04. It should be typed on commandline supported by each OS in current directory of 01.ps (not use the command-line in DOSBox ) as:

```
"C:\Program Files\gs\gs9.04\bin\gswin32c.exe" -dNOPAUSE -dBATCH –
sDEVICE = pdfwrite -r600 –sOutputFile = 01gw.pdf -c 300000 
setvmthreshold save pop -f 01.ps
```
Assumed 01gw.pdf would be a graph with super-resolution quality attaching suitable for all kind of publications. For example, it could be transformed from their PDF to wordprocessor MS-Word, to be free to use a program such as "Acrobat Reader", and it should be typing keys of Control-a, then Zoom up to around 200%, then Control-c, after then in wordprocessor to be also typing keys Control-v for universal use.

Numerical Solutions for Structural

Relaxation of Amorphous Alloys Studied by Activation Energy Spectrum Model 363

Edamatsu' GP.EXE that was designed until 1999 to make smart graphs for publication with powerful data analysis ability such as numerical complex differentiation. And now it is shown that the GP.EXE has been useful for genuine data processing even in the 2012's

The author was favoured to have the assistance of Dr. I. A. Figueroa in Universidad Nacional Autonoma de Mexico who contributed an experimental circumstance to the accomplishment of the amorphous sample preparations in the University of Sheffield UK. The author also would like to express the appreciation to Dr. Sergio Gonzalez Sanchez (Universitat Autonoma de Barcelona), Mr. P. J. J. Hawksworth and Dr. I. Todd in the University of Sheffield. The author is indebted to Professor H. A. Davies for drawing his

[1] Brochure for the Nanotechnology and Materials Technology Development Department, on March (2008), The New Energy and Industrial Technology Development Organization (NEDO) in Japan, processing technology for metallic glasses, p.61-62,

[2] I.A. Figueroa, R. Rawal, P. Stewart, P.A. Carroll, H.A. Davies, H. Jones and I. Todd,

[3] I.A. Figueroa, H.A. Davies, I. Todd and K. Yamada, Advanced Engineering Materials,

[4] K. Yamada, Y. Iijima and K. Fukamichi: Defect and Diffusion Forum, Vols. 143-147

[6] Y. Takahara, A. Morita, T. Takeda and H. Matsuda: J. Japan Inst. Metals, Vol. 54 (1990)

[7] K. Yamada, M. Ito, M. Tatsumiya, Y. Iijima and K. Fukamichi: Defect and Diffusion

[8] K. Yamada, K. Fukamichi and Y. Iijima: J. Magn. Soc. Jpn., Vol.22 Suppl. S2 (1998), pp.

[5] K. Yamada, Y. Iijima and K. Fukamichi: J. Mater. Res., Vol. 8 (1993), pp.2231-2238

[9] K. Yamada et al, Defect and Diffusion Forum Vols. 283-286 (2009), pp 533-538

http:// www.nedo.go.jp/ kankobutsu/ pamphlets/ nano/ nano\_e2008.pdf

Journal of Non-Crystalline Solids, Vol. 353 (2007), pp. 839-841

generation.

*Japan* 

**Author details** 

Kazu-masa Yamada

**Acknowledgement** 

attention to presented researches.

Vol. 9 (2007), pp. 496-499

pp. 752-757 (in Japanese)

Forum, Vols. 194-199 (2001), pp.815-820

(1997), pp.765-770

97-100

**6. References** 

*Hakodate National College of Technology,* 

*Department of Electrical and Electronic Engineering,* 

**Figure 18.** Final, PostScript-file save-menu using a PS.DLL PostScript-file driver displayed in Plot Parameters panel. If it assumed to be a 01.ps as saved file name, it would be transformed from PostScript-fire to PDF-file, for example, from 01.ps to assumed 01gw.pdf, to be free to use a program ghostscript ver. 9.04. It should be typed on command-line as:

**"C:\Program Files\gs\gs9.04\bin\gswin32c.exe" -dNOPAUSE -dBATCH -sDEVICE=pdfwrite -r600 -sOutputFile=01gw.pdf -c 300000 setvmthreshold save pop -f 01.ps**

### **5. Conclusion**

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 have been observed through the process of numerical-based discussion. It is so called rapid-type clarification between the temperature range *T*2 and *T*1 for almost around narrow 100 K region. In other words, even the above mentioned narrow temperature range induced the "reversible" phenomena, and it has been also observed in the anneal process of scan #1 to #n, repeatedly.

After it has been difficult in general to calculate numerical differences between any kinds of DSC live data. Because it has the time-domain problem for stepping accuracy and speed on temperature column region. So in second half of this paper, it was tutorial to short course calculation method for the differences using the freeware in Tohoku University Prof. K. Edamatsu' GP.EXE that was designed until 1999 to make smart graphs for publication with powerful data analysis ability such as numerical complex differentiation. And now it is shown that the GP.EXE has been useful for genuine data processing even in the 2012's generation.

### **Author details**

Applications of Calorimetry in a Wide Context –

362 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 18.** Final, PostScript-file save-menu using a PS.DLL PostScript-file driver displayed in Plot Parameters panel. If it assumed to be a 01.ps as saved file name, it would be transformed from PostScript-fire to PDF-file, for example, from 01.ps to assumed 01gw.pdf, to be free to use a program

**"C:\Program Files\gs\gs9.04\bin\gswin32c.exe" -dNOPAUSE -dBATCH -sDEVICE=pdfwrite -r600** 

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 have been observed through the process of numerical-based discussion. It is so called rapid-type clarification between the temperature range *T*2 and *T*1 for almost around narrow 100 K region. In other words, even the above mentioned narrow temperature range induced the "reversible" phenomena, and it has been

After it has been difficult in general to calculate numerical differences between any kinds of DSC live data. Because it has the time-domain problem for stepping accuracy and speed on temperature column region. So in second half of this paper, it was tutorial to short course calculation method for the differences using the freeware in Tohoku University Prof. K.

ghostscript ver. 9.04. It should be typed on command-line as:

**5. Conclusion** 

**-sOutputFile=01gw.pdf -c 300000 setvmthreshold save pop -f 01.ps**

also observed in the anneal process of scan #1 to #n, repeatedly.

Kazu-masa Yamada *Hakodate National College of Technology, Department of Electrical and Electronic Engineering, Japan* 

### **Acknowledgement**

The author was favoured to have the assistance of Dr. I. A. Figueroa in Universidad Nacional Autonoma de Mexico who contributed an experimental circumstance to the accomplishment of the amorphous sample preparations in the University of Sheffield UK. The author also would like to express the appreciation to Dr. Sergio Gonzalez Sanchez (Universitat Autonoma de Barcelona), Mr. P. J. J. Hawksworth and Dr. I. Todd in the University of Sheffield. The author is indebted to Professor H. A. Davies for drawing his attention to presented researches.

### **6. References**


Applications of Calorimetry in a Wide Context – 364 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[10] J. A. Leake, E. Woldt, and J. E. Evetts, Mater. Sci. Eng. , Vol. 97 (1988), pp. 469-472 [11] M. R. J. Gibbs, J. E. Evetts and J. A. Leake, J. Mater. Sci., Vol. 18 (1983), pp. 278-288 [12] W. Primak: Phys. Rev. Vol. 100 (1955) pp. 1677-1689

**Chapter 16** 

© 2013 Plano 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,

**Thermal Analysis of Sulfur and Selenium** 

**Compounds with Multiple Applications,** 

Thermal methodologies are analytical and quantitative methods capable of providing reliable, fast and reproducible results. Thermogravimetry (TG), Differential Scanning Calorimetry (DSC) and Isothermal Titration Calorimetry (ITC) techniques are the chosen

ITC is the most quantitative means available for measuring the thermodynamic properties of a protein-protein interaction. So, ITC is the calorimetric approach most used to investigate biomolecular interactions. ITC measures the binding equilibrium directly by determining the heat evolved on association of a ligand with its binding partner. In a single experiment, the values of the binding constant (Ka), the stoichiometry (n) and the enthalpy of binding (Δ*H*b) are determined. The free energy and entropy of binding are determined from the association constant. The temperature dependence of the Δ*H*b parameter, measured by performing the titration at varying temperatures, describes the Δ*C*p term. Furthermore, binding of proteins and small molecules to nucleic acids is of course critical to all organisms, playing a role in replication, transcription, translation and DNA repair processes to name just a few. Protein association with nucleic acids has therefore been the subject of much study throughout the years, and ITC has been one of the most common tools used for such investigations. When used in conjunction with complementary techniques such as X-ray crystallography, ITC can provide an informative thermodynamic account of these systems [1]. Besides, ITC is a useful technique in the protein-lipid interactions studies, and two examples in 2008 were the study of the effect of cholesterol on an amphibian antimicrobial peptide interaction with membranes [2], and analysis of the interaction of mammalian bonemarrow derived peptides with model and natural membranes [3]. Finally, ITC is a powerful tool for the pursuit of higher affinity drugs with improved binding specificities [4]. In its

Daniel Plano, Juan Antonio Palop and Carmen Sanmartín

**Including Anticancer Drugs** 

Additional information is available at the end of the chapter

methods for several physicochemical determinations.

http://dx.doi.org/10.5772/53048

**1. Introduction** 

## **Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs**

Daniel Plano, Juan Antonio Palop and Carmen Sanmartín

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53048

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

364 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[12] W. Primak: Phys. Rev. Vol. 100 (1955) pp. 1677-1689

[10] J. A. Leake, E. Woldt, and J. E. Evetts, Mater. Sci. Eng. , Vol. 97 (1988), pp. 469-472 [11] M. R. J. Gibbs, J. E. Evetts and J. A. Leake, J. Mater. Sci., Vol. 18 (1983), pp. 278-288

> Thermal methodologies are analytical and quantitative methods capable of providing reliable, fast and reproducible results. Thermogravimetry (TG), Differential Scanning Calorimetry (DSC) and Isothermal Titration Calorimetry (ITC) techniques are the chosen methods for several physicochemical determinations.

> ITC is the most quantitative means available for measuring the thermodynamic properties of a protein-protein interaction. So, ITC is the calorimetric approach most used to investigate biomolecular interactions. ITC measures the binding equilibrium directly by determining the heat evolved on association of a ligand with its binding partner. In a single experiment, the values of the binding constant (Ka), the stoichiometry (n) and the enthalpy of binding (Δ*H*b) are determined. The free energy and entropy of binding are determined from the association constant. The temperature dependence of the Δ*H*b parameter, measured by performing the titration at varying temperatures, describes the Δ*C*p term. Furthermore, binding of proteins and small molecules to nucleic acids is of course critical to all organisms, playing a role in replication, transcription, translation and DNA repair processes to name just a few. Protein association with nucleic acids has therefore been the subject of much study throughout the years, and ITC has been one of the most common tools used for such investigations. When used in conjunction with complementary techniques such as X-ray crystallography, ITC can provide an informative thermodynamic account of these systems [1]. Besides, ITC is a useful technique in the protein-lipid interactions studies, and two examples in 2008 were the study of the effect of cholesterol on an amphibian antimicrobial peptide interaction with membranes [2], and analysis of the interaction of mammalian bonemarrow derived peptides with model and natural membranes [3]. Finally, ITC is a powerful tool for the pursuit of higher affinity drugs with improved binding specificities [4]. In its

© 2013 Plano 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.

simplest form, ITC is a rapid and convenient method for measuring affinities of new leads and optimized compounds. In addition, however, ITC is particularly useful in providing information about the mode of binding. The use of ITC as a general tool in drug design and characterization is exemplified in a study by McKew *et al*. [5] who demonstrated the efficacy of ITC for studying three classes of inhibitor to the cytosolic amphitropic enzyme phospholipase A2 alpha (cPLA2a).

Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs 367

Another application of thermal analysis is to study the chemical structure and the structure rearrangements in metallic complexes. The VA main group metal compounds including inorganic and metallorganic complex have showed interesting physical properties, medical and material functions. Some bismuth complexes can be used in medicine, microbiology and pharmacology [16-18]. Two studies with thiourea complexes of antimony and bismuth have evidenced several structure rearrangements or phase transformations for these complexes

Several studies have been carried out in order to determine the specific and thermodynamic constants of methionine, which is one of the nine essential amino acids needed by human

Chalcogenide semiconductors have been proposed for phase change nonvolatile random access memories, which is becoming the next generation for memory technology [23]. So, the proper description of thermal behavior of semiconducting chalcogenide glasses is crucial to understand their properties and functions. One of the crucial techniques to study the

Among the chalcogenide systems, selenium and selenium based glassy alloys have been intensively studied due to their wide technical applications, especially in the field of electronics and optoelectronics. A recent study has used the DTA technique to study the glass transition kinetics of the two binary Se-In alloys in comparison with that of pure Se. The glass transition temperature was found to be shifting to a higher value with increasing of heating rates and indium content. It was observed an increase of the stability parameters accompanied with the introduction of In into the Se matrix [24]. Another interesting Se based glassy alloys are Se-Sb alloys owing to their electrical, optical dielectric and thermal properties. Mehta *et al*. have reported the thermal characterization with calorimetric measurements for some Se-Sb alloys [25]. They reported the Hruby number, which is the strong indicator of glass forming tendency, thermal stability parameter and the values of

Selenium-tellurium thin films have attractive semiconductors for device application. Se-Te form a continuous series of solid solution and the Se-Te system has an intermediate behavior between pure Se and pure Te. The addition of Te has a catalytic effect on the crystallization of Se. In 2009, the crystallization parameters of the bulk Se-Te chalcogenide glass have been studied using DSC [26]. The values of glass transition temperature, onset crystallization temperature, peak crystallization temperature and enthalpy released with and without laser irradiation for different exposure time have been studied. The films showed indirect allowed interband transition that is influenced by the laser irradiation.

Ternary systems of chalcogenide glasses containing metal elements possess unique optical, electrical and physicochemical properties [27]. The most popular metal is silver and its addition into chalcogenide glasses leads to a drastic change in the physical and chemical

beings and contains a sulfur atom, and 2-mecaptonicotinic acid complexes [21, 22].

glass transition kinetics is the differential thermal analysis (DTA) and DSC.

from 100 to 170 ºC [19, 20].

**2.2. Glass materials** 

crystallization enthalpy and entropy.

TG is mainly employed to study thermal stability, kinetic parameters and degradation processes for a wide range of materials. DSC allows characterizing protein stability and folding, drug-protein interactions, as well as heat capacity, vapor pressures and polymorphism. Moreover, it has been pointed out the usefulness of DSC technique as a potential tool for the early diagnosis, monitoring and screening of cancer patients [6].

### **2. Application of thermal analysis to sulfur and selenium compounds with multiple applications**

Sulfur (S) and selenium (Se) compounds present several applications in a great variety of fields. We consider the anticancer activity of these compounds as the most important application due to the burden, costs and mortality rates caused by cancer disease. Thus, we will treat in depth the application of thermal techniques to these anticancer compounds in the following section.

Due to the vast applications of S and Se compounds and to the great structural variability in each of these applications, the S and Se compounds are going to be classified according to their structural features.

### **2.1. Coordinated compounds**

The study of the degradation process is one of the most common utility for thermal techniques in the study of metal complex derivatives. Coordination compounds with dithiocarbamates have attracted attention because of their potential biological activity [7-10]. In 2006, a novel dithiocarbamate ligand L (triammonium-*N*-dithiocarboxyiminodiacetate) was synthesized and the thermal decomposition of its cooper (II), niquel (II) and palladium (II) was studied by DSC and thermogravimetry [11]. The authors showed that thermal stability of (NH4)3L is low and its decomposition starts with evaporation of an ammonia molecule. Of the three complexes, Cu(H2L)2 is the least thermally stable. Thermal decomposition of the complexes most likely begins with decarboxylation. It is endothermic up to 500 K, but exothermic oxidation processes are observed above this temperature. Thermal decomposition of the cooper (II) complex is accompanied by its melting and with an exothermic structural rearrangement [11]. During the last two years, these thermal techniques have been used to study the stability and to characterize the degradation process of several dithiocarbamate complexes [12-14]. On the other hand, a study of the degradation process for three novel selenocyanato complexes has been published recently [15]. The authors demonstrated that all compounds decompose in a single heating step without the formation of ligand-deficient intermediates.

Another application of thermal analysis is to study the chemical structure and the structure rearrangements in metallic complexes. The VA main group metal compounds including inorganic and metallorganic complex have showed interesting physical properties, medical and material functions. Some bismuth complexes can be used in medicine, microbiology and pharmacology [16-18]. Two studies with thiourea complexes of antimony and bismuth have evidenced several structure rearrangements or phase transformations for these complexes from 100 to 170 ºC [19, 20].

Several studies have been carried out in order to determine the specific and thermodynamic constants of methionine, which is one of the nine essential amino acids needed by human beings and contains a sulfur atom, and 2-mecaptonicotinic acid complexes [21, 22].

### **2.2. Glass materials**

Applications of Calorimetry in a Wide Context –

phospholipase A2 alpha (cPLA2a).

**with multiple applications** 

the following section.

their structural features.

**2.1. Coordinated compounds** 

formation of ligand-deficient intermediates.

366 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

simplest form, ITC is a rapid and convenient method for measuring affinities of new leads and optimized compounds. In addition, however, ITC is particularly useful in providing information about the mode of binding. The use of ITC as a general tool in drug design and characterization is exemplified in a study by McKew *et al*. [5] who demonstrated the efficacy of ITC for studying three classes of inhibitor to the cytosolic amphitropic enzyme

TG is mainly employed to study thermal stability, kinetic parameters and degradation processes for a wide range of materials. DSC allows characterizing protein stability and folding, drug-protein interactions, as well as heat capacity, vapor pressures and polymorphism. Moreover, it has been pointed out the usefulness of DSC technique as a

potential tool for the early diagnosis, monitoring and screening of cancer patients [6].

**2. Application of thermal analysis to sulfur and selenium compounds** 

Sulfur (S) and selenium (Se) compounds present several applications in a great variety of fields. We consider the anticancer activity of these compounds as the most important application due to the burden, costs and mortality rates caused by cancer disease. Thus, we will treat in depth the application of thermal techniques to these anticancer compounds in

Due to the vast applications of S and Se compounds and to the great structural variability in each of these applications, the S and Se compounds are going to be classified according to

The study of the degradation process is one of the most common utility for thermal techniques in the study of metal complex derivatives. Coordination compounds with dithiocarbamates have attracted attention because of their potential biological activity [7-10]. In 2006, a novel dithiocarbamate ligand L (triammonium-*N*-dithiocarboxyiminodiacetate) was synthesized and the thermal decomposition of its cooper (II), niquel (II) and palladium (II) was studied by DSC and thermogravimetry [11]. The authors showed that thermal stability of (NH4)3L is low and its decomposition starts with evaporation of an ammonia molecule. Of the three complexes, Cu(H2L)2 is the least thermally stable. Thermal decomposition of the complexes most likely begins with decarboxylation. It is endothermic up to 500 K, but exothermic oxidation processes are observed above this temperature. Thermal decomposition of the cooper (II) complex is accompanied by its melting and with an exothermic structural rearrangement [11]. During the last two years, these thermal techniques have been used to study the stability and to characterize the degradation process of several dithiocarbamate complexes [12-14]. On the other hand, a study of the degradation process for three novel selenocyanato complexes has been published recently [15]. The authors demonstrated that all compounds decompose in a single heating step without the Chalcogenide semiconductors have been proposed for phase change nonvolatile random access memories, which is becoming the next generation for memory technology [23]. So, the proper description of thermal behavior of semiconducting chalcogenide glasses is crucial to understand their properties and functions. One of the crucial techniques to study the glass transition kinetics is the differential thermal analysis (DTA) and DSC.

Among the chalcogenide systems, selenium and selenium based glassy alloys have been intensively studied due to their wide technical applications, especially in the field of electronics and optoelectronics. A recent study has used the DTA technique to study the glass transition kinetics of the two binary Se-In alloys in comparison with that of pure Se. The glass transition temperature was found to be shifting to a higher value with increasing of heating rates and indium content. It was observed an increase of the stability parameters accompanied with the introduction of In into the Se matrix [24]. Another interesting Se based glassy alloys are Se-Sb alloys owing to their electrical, optical dielectric and thermal properties. Mehta *et al*. have reported the thermal characterization with calorimetric measurements for some Se-Sb alloys [25]. They reported the Hruby number, which is the strong indicator of glass forming tendency, thermal stability parameter and the values of crystallization enthalpy and entropy.

Selenium-tellurium thin films have attractive semiconductors for device application. Se-Te form a continuous series of solid solution and the Se-Te system has an intermediate behavior between pure Se and pure Te. The addition of Te has a catalytic effect on the crystallization of Se. In 2009, the crystallization parameters of the bulk Se-Te chalcogenide glass have been studied using DSC [26]. The values of glass transition temperature, onset crystallization temperature, peak crystallization temperature and enthalpy released with and without laser irradiation for different exposure time have been studied. The films showed indirect allowed interband transition that is influenced by the laser irradiation.

Ternary systems of chalcogenide glasses containing metal elements possess unique optical, electrical and physicochemical properties [27]. The most popular metal is silver and its addition into chalcogenide glasses leads to a drastic change in the physical and chemical properties of the material, for instance, it increases the conductivity by several orders of magnitude and decreases the slope of frequency dependence of alternating current (AC) conductivity. A study conducted by Ogusu *et al*. carried out DSC, X-ray diffraction (XRD) and Raman scattering measurements for Agx(As0.4Se0.6)100-x glasses with x = 0-35 at.% in order to investigate the crystallization kinetics and the local structure [28]. The DSC curves of the samples with Ag content x = 15-35 at.% were obtained at various heating rates for different Ag contents and two or three exothermic peaks for the crystallization were found depending on the Ag content. Furthermore, the dimension of crystal growth of sample particles and activation energy were determined using Matusita´s equation to analyze the DSC data. It was found that the surface and bulk crystallization take place depending on the Ag content and peak crystallization temperatures [28].

Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs 369

selenite are used for coloring glasses, enamel and glazes. On the basis of MnSeO3, two manganese selenides (α-MnSe and MnSe2) were obtained having very interesting semiconductor properties [36]. Vlaev *et al*. have studied the crystallization fields of manganese(II) selenites in the system MnSeO3-SeO2-H2O in the temperature interval 25-300 ºC and characterized the observed phases [37]. Previously to this article, the same author reported the crystallization fields and the characterization of the observed phases for the system NiSeO3-SeO2-H2O [38]. Another article studied the phase equilibrium in the system CdO-SeO2-H2O at 25 and 100ºC and the thermolysis mechanism of the compounds

The ytterbium selenites can serve as initial substances for obtaining selenides and oxyselenides having valuable photoconductive and superconductive properties. So, Gospodinov *et al*. have studied the solubility isotherm of the three-component system Yb2O3-SeO2-H20 at 100 ºC [39]. Furthermore, they have performed simultaneous TG and DTA curves of the compounds obtained in its fields of crystallization and the mechanism of

Alkali metal sulfates, selenite and phosphate tellurate compounds having the formula M2XO4Te(OH)6, where M is the metal and X is S, Se or P, form a broad families with interesting properties, such as superprotonic conduction and ferroelectricity [40-42]. So, synthesis, calorimetric and conductivity studies of new mixed solution of rubidium sulfate

In the last two years, several thermal and structural investigations on crystal structures with thiourea have been carried out. The thermal decomposition of crystal structures with bisthiourea derivatives has been studied by TG-DSC [45]. Another study reported the growth and characterization of a new non-linear organometallic crystal (potassium thiourea thiocyanide or PTT) [46]. The TG curve showed the complete decomposition of PTT between

Some selenoesters present promising photophysical properties for optical device applications such as emissive liquid crystal displays (LCDs), polarized organic lasers and anisotropic Light-emitting diodes (LEDs). Rampon *et al*. have reported the synthesis and the study of the liquid crystalline and fluorescent properties of novel selenoesters [47]. So, these compounds were fluorescent in the blue region and exhibited their stability and liquid crystalline properties over a large range of temperatures. Moreover, these compounds

Cooper chalcogenides are considered as promising in electronic technology due to their physicochemical properties [48, 49]. Chrissofis *et al*. [50] have reported the thermal behavior of samples with very slight divergence from stoichiometry (Cu2-xSe). Also, they have studied the nature of the transformation with non-isothermal measurements at different heating and

selenate tellurate [43] and thallium selenate tellurate [44] have been carried out.

176 and 1000 ºC in three steps with corresponding three DTA peaks.

obtained.

the thermal decomposition [39].

**2.4. Miscellaneous compounds** 

showed a rich phase polymorphism.

cooling rates.

Glassy selenium has low sensitivity and thermal instability. These properties can be improved by alloying of some elements into selenium matrix, such as arsenic [29] and antimony [30, 31]. The proper description of thermal behavior of these glasses is important for understanding their properties and applications. Recently, the thermal properties and structure of AsxSe100-x and SbxSe100-x glass-forming systems (x = 0, 1, 2, 4, 8 and 16) were reported by conventional and StepScan DSC and Raman spectroscopy [32]. Among these thermal properties, the authors studied the glass transition temperature and the crystallization of undercooled melts. So, the glass transition temperature for AsxSe100-x system increases almost linearly with increasing As content from 40 up to 93 ºC, because the glass structure becomes more stable due to cross-linking of Se chains by As. Nevertheless, the glass transition temperature of SbxSe100-x changes only slightly from 40 to 48 ºC [32]. Concerning to the study of crystallization of undercooled melts, it was found that only selenium crystallizes from undercooled melts of As-Se system and its tendency to crystallize decreases markedly with increasing As content, for arsenic content higher than 4 at.% no crystallization was observed. In the case of Sb-Se system Sb2Se3 crystallizes in the first step followed by trigonal selenium crystallization from non-stoichiometric undercooled melt [32].

Another technologically important ternary system of chalcogen elements are the infrared transmitting glasses based on Ge-Sb-Se because they are good transmitters of radiation in the 2-16 µm wavelength region. The applications include fabrication of optical components like IR lenses, windows and filter used in thermal imaging systems. The Sb-Ge-Se films result sensitive for the UV exhibit mechanical, optical and structural changes [33, 34]. An understanding of the glass forming tendency and crystallization kinetics in these chalcogenide materials is very important to develop them for applications based on the amorphous to crystallization phase change and vice versa. So, one report evaluated the glass-forming ability of some alloys in SbxGe25-xSe75 (0 ≤ x ≤ 10) system by using various thermal stability criteria, based on characteristic temperatures [35]. It was observed that the thermal stability decrease with increasing Sb content in the glassy system.

### **2.3. Inorganic mixtures**

Several reports have been published concerning to the solubility and thermal characterization of various metal-selenite systems. For example, some manganese(II) selenite are used for coloring glasses, enamel and glazes. On the basis of MnSeO3, two manganese selenides (α-MnSe and MnSe2) were obtained having very interesting semiconductor properties [36]. Vlaev *et al*. have studied the crystallization fields of manganese(II) selenites in the system MnSeO3-SeO2-H2O in the temperature interval 25-300 ºC and characterized the observed phases [37]. Previously to this article, the same author reported the crystallization fields and the characterization of the observed phases for the system NiSeO3-SeO2-H2O [38]. Another article studied the phase equilibrium in the system CdO-SeO2-H2O at 25 and 100ºC and the thermolysis mechanism of the compounds obtained.

The ytterbium selenites can serve as initial substances for obtaining selenides and oxyselenides having valuable photoconductive and superconductive properties. So, Gospodinov *et al*. have studied the solubility isotherm of the three-component system Yb2O3-SeO2-H20 at 100 ºC [39]. Furthermore, they have performed simultaneous TG and DTA curves of the compounds obtained in its fields of crystallization and the mechanism of the thermal decomposition [39].

Alkali metal sulfates, selenite and phosphate tellurate compounds having the formula M2XO4Te(OH)6, where M is the metal and X is S, Se or P, form a broad families with interesting properties, such as superprotonic conduction and ferroelectricity [40-42]. So, synthesis, calorimetric and conductivity studies of new mixed solution of rubidium sulfate selenate tellurate [43] and thallium selenate tellurate [44] have been carried out.

### **2.4. Miscellaneous compounds**

Applications of Calorimetry in a Wide Context –

368 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Ag content and peak crystallization temperatures [28].

selenium crystallization from non-stoichiometric undercooled melt [32].

thermal stability decrease with increasing Sb content in the glassy system.

**2.3. Inorganic mixtures** 

properties of the material, for instance, it increases the conductivity by several orders of magnitude and decreases the slope of frequency dependence of alternating current (AC) conductivity. A study conducted by Ogusu *et al*. carried out DSC, X-ray diffraction (XRD) and Raman scattering measurements for Agx(As0.4Se0.6)100-x glasses with x = 0-35 at.% in order to investigate the crystallization kinetics and the local structure [28]. The DSC curves of the samples with Ag content x = 15-35 at.% were obtained at various heating rates for different Ag contents and two or three exothermic peaks for the crystallization were found depending on the Ag content. Furthermore, the dimension of crystal growth of sample particles and activation energy were determined using Matusita´s equation to analyze the DSC data. It was found that the surface and bulk crystallization take place depending on the

Glassy selenium has low sensitivity and thermal instability. These properties can be improved by alloying of some elements into selenium matrix, such as arsenic [29] and antimony [30, 31]. The proper description of thermal behavior of these glasses is important for understanding their properties and applications. Recently, the thermal properties and structure of AsxSe100-x and SbxSe100-x glass-forming systems (x = 0, 1, 2, 4, 8 and 16) were reported by conventional and StepScan DSC and Raman spectroscopy [32]. Among these thermal properties, the authors studied the glass transition temperature and the crystallization of undercooled melts. So, the glass transition temperature for AsxSe100-x system increases almost linearly with increasing As content from 40 up to 93 ºC, because the glass structure becomes more stable due to cross-linking of Se chains by As. Nevertheless, the glass transition temperature of SbxSe100-x changes only slightly from 40 to 48 ºC [32]. Concerning to the study of crystallization of undercooled melts, it was found that only selenium crystallizes from undercooled melts of As-Se system and its tendency to crystallize decreases markedly with increasing As content, for arsenic content higher than 4 at.% no crystallization was observed. In the case of Sb-Se system Sb2Se3 crystallizes in the first step followed by trigonal

Another technologically important ternary system of chalcogen elements are the infrared transmitting glasses based on Ge-Sb-Se because they are good transmitters of radiation in the 2-16 µm wavelength region. The applications include fabrication of optical components like IR lenses, windows and filter used in thermal imaging systems. The Sb-Ge-Se films result sensitive for the UV exhibit mechanical, optical and structural changes [33, 34]. An understanding of the glass forming tendency and crystallization kinetics in these chalcogenide materials is very important to develop them for applications based on the amorphous to crystallization phase change and vice versa. So, one report evaluated the glass-forming ability of some alloys in SbxGe25-xSe75 (0 ≤ x ≤ 10) system by using various thermal stability criteria, based on characteristic temperatures [35]. It was observed that the

Several reports have been published concerning to the solubility and thermal characterization of various metal-selenite systems. For example, some manganese(II) In the last two years, several thermal and structural investigations on crystal structures with thiourea have been carried out. The thermal decomposition of crystal structures with bisthiourea derivatives has been studied by TG-DSC [45]. Another study reported the growth and characterization of a new non-linear organometallic crystal (potassium thiourea thiocyanide or PTT) [46]. The TG curve showed the complete decomposition of PTT between 176 and 1000 ºC in three steps with corresponding three DTA peaks.

Some selenoesters present promising photophysical properties for optical device applications such as emissive liquid crystal displays (LCDs), polarized organic lasers and anisotropic Light-emitting diodes (LEDs). Rampon *et al*. have reported the synthesis and the study of the liquid crystalline and fluorescent properties of novel selenoesters [47]. So, these compounds were fluorescent in the blue region and exhibited their stability and liquid crystalline properties over a large range of temperatures. Moreover, these compounds showed a rich phase polymorphism.

Cooper chalcogenides are considered as promising in electronic technology due to their physicochemical properties [48, 49]. Chrissofis *et al*. [50] have reported the thermal behavior of samples with very slight divergence from stoichiometry (Cu2-xSe). Also, they have studied the nature of the transformation with non-isothermal measurements at different heating and cooling rates.

Oligothiophenes and polythiophenes are another sulfur compounds that have attracted much attention due to their unusual electric and nonlinear optical properties as interesting materials for organic electronics and optoelectronics, LEDs, field-effect transistors, thin-film transistors… So, the relative stabilities of 2,2´- and 3,3´-bithiophenes (the main building blocks of these conducting organic materials) have been evaluated by experimental thermochemistry [51].

Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs 371

Furthermore, a solid-solid phase transition close to the melting point is only observed in the *L*-cysteine. Additionally, several polymorphic forms have been reported for both compounds. *L*-cysteine crystallizes in the monoclinic and orthorhombic forms and has been structurally characterized [53, 54]. Phase transitions have been detected when lowering the temperatures [55] and also when decreasing pressures up to 4.2 GPa and decreasing to 1-7 GPa [56]. *L*-cystine crystallizes in the tetragonal and hexagonal forms and has also been studied at ambient [57, 58] and at low temperature [59] and at high pressures although no

During the past decade the study of mixed sulfur donor ligand complexes with main group metals has made a progressive development due to the development of new analytical and structural techniques [60-62]. These complexes present potential applications in areas such as fast ion conductivity, photocatalysis and electro-optics, among others as well as several

One of these promising complexes is antimony(III) bis(pyrrolidinedithiocarbamato) alkyldithiocarbonates. The link of two active ligands was the rational design used for the design of these complexes. So, pyrrolidine dithiocarbamates which represent a class of antioxidants mediate a wide variety of effects in biological systems[66]. It is a multipotent synthetic compound well known for its metal chelation property and one of the most potent and specific NF-kB inhibitor [67]. Besides, antimony metal containing compounds are commonly used to treat parasitic infections and exhibit a broad spectrum of chemotherapeutic applications and cytotoxic activities. So, a study has reported the synthesis, spectroscopic, thermal and structural behavior of antimony(III) bis(pyrrolidinedithiocarbamato)alkyldithiocarbonates [12]. Thermogravimetric studies not only allows to determine purity and thermal stability of the complex but also composition of the complex as well which it is observed during different steps of weight losses as a

Another type of complexes with a potent anticancer activity which were designed using the link of two active ligands, are the palladium (II) and platinum (IV) complexes with active sulfur ligands. The use of antitumor drugs based on platinum(II) metal complexes, cisplatin and its analogues carboplatin and oxaliplatin is limited by two factors: installation of tumor drug resistance and severe adverse effects [68, 69]. Therapeutic strategies are oriented towards the development of new platinum- and non-platinum-based antitumor drugs with higher efficiency, reduced general toxicity and broader spectrum of activity [70]. Sulfurcontaining molecules are studied as chemoprotectors in platinum-based chemotherapy. Dithiocarbamates have attracted particular attention for the use of chemical modulation of

The thermal behaviour of Pd(II) complexes with some dithiocarbamate derivatives was studied in order to establish the coordination mode of the ligand, to test the thermal stability [11] or to understand the effect of the alkyl chain attached to the nitrogen atom over the

solid-solid phase transition has been detected.

**3.2. Metal complexes of sulfur compounds** 

fragment formed in different temperature ranges [12].

biochemical applications [63-65].

cisplatin nephrotoxicity [71-73].

### **3. Application of thermal analysis to sulfur and selenium compounds with anticancer activity**

In the last decade, among the wide range of compounds tested as potential anticancer agents, several structurally diverse derivatives that contain a sulfur or selenium template have been reported and have generated growing interest. For that reason, in this chapter we have focused on some relevant thermal studies in sulfur and selenium compounds with anticancer activity.

### **3.1. Sulfur amino acids and cysteine cathepsins.**

The human family of cysteine cathepsins are a family of lysosomal proteases and has 11 members (cysteine cathepsin B, C, F, H, K, L, O, S, V, W and X), which share a conserved active site that is formed by cysteine, histidine and asparagine residues. Cysteine cathepsins are often upregulated in various human cancers, and have been implicated in distinct tumorigenic processes such as angiogenesis, proliferation, apoptosis and invasion. During cancer progression, cathepsins are often translocated to the cell surface of tumor cells or are secreted into the extracellular milieu, where they can promote tumor invasion through several possible mechanisms. Causal roles for cysteine cathepsins in cancer have been demonstrated by pharmacological and genetic techniques. This includes functional downregulation of cysteine cathepsin activity by increasing expression of endogenous inhibitors and administration of small-molecule cysteine protease inhibitors. Besides, causal roles for specific cysteine cathepsins in cancer have been demonstrated by downregulating their expression or crossing mouse models of cancer with mice in which the cysteine cathepsin has been genetically ablated. These studies have identified roles for cysteine cathepsins in both tumor cells and tumor-associated cells such as endothelial cells and macrophages.

Taking into account the causal roles for cysteine cathepsins, which present a cysteine residue in the active site, in cancer and the fact that the thiol-disulfide interchange reaction is important to a number of subjects in biochemistry, thermodynamic data regarding the relative energetics of the thiol and disulfide functional groups is essential for the understanding of the driving force and mechanism of biochemical processes. Temperatureinduced changes in crystalline amino acids are of interest for their properties and because they reveal the intrinsic motions of these structural fragments and their contribution to the dynamic properties of proteins.

So, a thermophysical study of the sulfur containing amino acids *L*-cysteine and *L*-cystine by DSC has been reported [52]. Heat capacities of both compounds were measured in the temperature interval from T = 268 K to near their respective melting temperatures. Furthermore, a solid-solid phase transition close to the melting point is only observed in the *L*-cysteine. Additionally, several polymorphic forms have been reported for both compounds. *L*-cysteine crystallizes in the monoclinic and orthorhombic forms and has been structurally characterized [53, 54]. Phase transitions have been detected when lowering the temperatures [55] and also when decreasing pressures up to 4.2 GPa and decreasing to 1-7 GPa [56]. *L*-cystine crystallizes in the tetragonal and hexagonal forms and has also been studied at ambient [57, 58] and at low temperature [59] and at high pressures although no solid-solid phase transition has been detected.

### **3.2. Metal complexes of sulfur compounds**

Applications of Calorimetry in a Wide Context –

**with anticancer activity** 

dynamic properties of proteins.

**3.1. Sulfur amino acids and cysteine cathepsins.** 

anticancer activity.

370 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Oligothiophenes and polythiophenes are another sulfur compounds that have attracted much attention due to their unusual electric and nonlinear optical properties as interesting materials for organic electronics and optoelectronics, LEDs, field-effect transistors, thin-film transistors… So, the relative stabilities of 2,2´- and 3,3´-bithiophenes (the main building blocks of these conducting organic materials) have been evaluated by experimental thermochemistry [51].

**3. Application of thermal analysis to sulfur and selenium compounds** 

In the last decade, among the wide range of compounds tested as potential anticancer agents, several structurally diverse derivatives that contain a sulfur or selenium template have been reported and have generated growing interest. For that reason, in this chapter we have focused on some relevant thermal studies in sulfur and selenium compounds with

The human family of cysteine cathepsins are a family of lysosomal proteases and has 11 members (cysteine cathepsin B, C, F, H, K, L, O, S, V, W and X), which share a conserved active site that is formed by cysteine, histidine and asparagine residues. Cysteine cathepsins are often upregulated in various human cancers, and have been implicated in distinct tumorigenic processes such as angiogenesis, proliferation, apoptosis and invasion. During cancer progression, cathepsins are often translocated to the cell surface of tumor cells or are secreted into the extracellular milieu, where they can promote tumor invasion through several possible mechanisms. Causal roles for cysteine cathepsins in cancer have been demonstrated by pharmacological and genetic techniques. This includes functional downregulation of cysteine cathepsin activity by increasing expression of endogenous inhibitors and administration of small-molecule cysteine protease inhibitors. Besides, causal roles for specific cysteine cathepsins in cancer have been demonstrated by downregulating their expression or crossing mouse models of cancer with mice in which the cysteine cathepsin has been genetically ablated. These studies have identified roles for cysteine cathepsins in both tumor

Taking into account the causal roles for cysteine cathepsins, which present a cysteine residue in the active site, in cancer and the fact that the thiol-disulfide interchange reaction is important to a number of subjects in biochemistry, thermodynamic data regarding the relative energetics of the thiol and disulfide functional groups is essential for the understanding of the driving force and mechanism of biochemical processes. Temperatureinduced changes in crystalline amino acids are of interest for their properties and because they reveal the intrinsic motions of these structural fragments and their contribution to the

So, a thermophysical study of the sulfur containing amino acids *L*-cysteine and *L*-cystine by DSC has been reported [52]. Heat capacities of both compounds were measured in the temperature interval from T = 268 K to near their respective melting temperatures.

cells and tumor-associated cells such as endothelial cells and macrophages.

During the past decade the study of mixed sulfur donor ligand complexes with main group metals has made a progressive development due to the development of new analytical and structural techniques [60-62]. These complexes present potential applications in areas such as fast ion conductivity, photocatalysis and electro-optics, among others as well as several biochemical applications [63-65].

One of these promising complexes is antimony(III) bis(pyrrolidinedithiocarbamato) alkyldithiocarbonates. The link of two active ligands was the rational design used for the design of these complexes. So, pyrrolidine dithiocarbamates which represent a class of antioxidants mediate a wide variety of effects in biological systems[66]. It is a multipotent synthetic compound well known for its metal chelation property and one of the most potent and specific NF-kB inhibitor [67]. Besides, antimony metal containing compounds are commonly used to treat parasitic infections and exhibit a broad spectrum of chemotherapeutic applications and cytotoxic activities. So, a study has reported the synthesis, spectroscopic, thermal and structural behavior of antimony(III) bis(pyrrolidinedithiocarbamato)alkyldithiocarbonates [12]. Thermogravimetric studies not only allows to determine purity and thermal stability of the complex but also composition of the complex as well which it is observed during different steps of weight losses as a fragment formed in different temperature ranges [12].

Another type of complexes with a potent anticancer activity which were designed using the link of two active ligands, are the palladium (II) and platinum (IV) complexes with active sulfur ligands. The use of antitumor drugs based on platinum(II) metal complexes, cisplatin and its analogues carboplatin and oxaliplatin is limited by two factors: installation of tumor drug resistance and severe adverse effects [68, 69]. Therapeutic strategies are oriented towards the development of new platinum- and non-platinum-based antitumor drugs with higher efficiency, reduced general toxicity and broader spectrum of activity [70]. Sulfurcontaining molecules are studied as chemoprotectors in platinum-based chemotherapy. Dithiocarbamates have attracted particular attention for the use of chemical modulation of cisplatin nephrotoxicity [71-73].

The thermal behaviour of Pd(II) complexes with some dithiocarbamate derivatives was studied in order to establish the coordination mode of the ligand, to test the thermal stability [11] or to understand the effect of the alkyl chain attached to the nitrogen atom over the

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

thermochemical parameters of the complexes [74, 75]. A series of Pd(II) complexes with *tert*butylsarcosinedithiocarbamate [76], ethylsarcosinedithiocarbamate and 2-/3-picoline [77], dithiocarbamates and various amines [78] were developed as antitumor agents with low nephrotoxicity. Thermogravimetric analysis was used for the characterization of these compounds. Taking into accounts the kinetic inertness, high activity, low toxicity and suitability for oral administration of Pt(IV) complexes, some Pt(IV) complexes with dithiocarbamates have been synthesized. Morpholine dithiocarbamate, aniline dithiocarbamate and N-(methyl, cyclohexyl) dithiocarbamate alone [79] or with triphenyl phosphine as second ligand [80] were used in order to obtain Pt(IV) complexes with antitumour activity.

Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs 373

EI201, inhibits the PI3K/AKT/mTOR pathway, which is persistently activated and contributes to malignant progression in various cancers, and contributes to the loss of maintenance of the selfrenewal and tumorigenic capacity of cancer stem cells. This compound (EI201) suppressed almost 80% prostate tumor growth *in vivo* (*p* < 0.01) compared to controls at a relatively low dose (10 mg/kg) in a mouse xenograft model [90].

Degradation and fusion temperatures for 20 of these anticancer derivatives were determined using TG and DSC [91]. Analysis of the thermal data indicated that: (a) in general, sulfur compounds are more stable than selenium compounds; (b) the pyridine ring diminished stability of sulfur and selenium compounds much more than the carbocyclic aromatic rings did; (c) selenomethyl derivatives are more stable than selenoethyl and selenoisopropyl compounds; (d) a chlorine atom on selenocompounds has surprising effects. So, the presence of intermolecular bonds was pointed out between chlorine atom and selenium atom [91]. With regard some substituents present on aromating ring and the ramification and length of chain, it can be concluded that the presence of electron-withdrawing groups in selenocompound structures improves their stability. Besides, selenomethyl derivatives are

The determination of the polymorphism of a substance is of great importance due to the strong influence of the crystalline form on the physicochemical properties, bioavailability and stability of drugs [92], and, in some compounds with biological activity, can even become metastable forms, being twice as active as the stable form [93]. So, our research group has carried out the study of the physicochemical properties of polymorphic forms of a serie of alkylimidothio- and alkylimidoselenocarbamate derivatives with a combination of DSC, thermomicroscopy and X-ray diffractometry [94]. In this study we observed that polymorphs could be formed when the compounds are heated above their melting points. The results showed that there are four types of thermal behavior for alkylimidothio- and alkylmidoselenocarbamate derivatives: (a) compounds which do not evidence any polymorphic forms (behavior I); (b) compounds which solidify into an amorphous solid form (behavior II); (c) compounds which present a new polymorphic form at a Tonset lower than the original one (behavior III); (d) finally, compounds which have three polymorphic forms with three different Tonset values (behavior IV). Calorimetric studies demonstrated that sulfur and selenium analogs have the same thermal behavior. So, the different thermal behaviors observed for these alkylimidothio- and alkylimidoselenocarbamates are caused by the substituent groups in the aromatic ring, although there is no relationship between

more stable than selenoethyl and selenoisopropyl compounds [91].

electron-withdrawing and electron-donating groups and the thermal behavior.

In 2009, our research group reported the cytotoxic and antiproliferative activities *in vitro* of selenyl acetic derivatives against several cancer cell lines [95]. Considering the structure of these derivatives and their inefficacy to induce apoptosis and to affect to cell cycle, we decided to perform a thermal analysis for these derivatives. So, we carried out a thermal stability and calorimetric studies for some of these anticancer selenyl acetic acids (**Figure 1**).

**3.4. Case study: Thermal analysis of selenyl acetic derivatives.** 

In 2012, Uivarosi *et al*. have reported the thermal and spectral studies of palladium(II) and platinum(IV) complexes with bis(dimethylthiocarbamoyl)sulphide and bis(diethylthiocarbamoyl)disulphide [81]. TG experiments revealed the nature of complex species as hydrated or anhydrous. Thermal decomposition of coordinated organic ligands occurs in one or two exothermic stages, the final residue being in all cases the free metal (Pd or Pt).

Other complexes with anticancer activity are de ruthenium (III) complexes with sulfur ligands. Ruthenium complexes with dimethyl sulfoxide (dmso) showed selective antitumor properties in preclinical testing [82]. Biological studies in *cis*- and *trans*-RuX2(dmso)4 complexes (X = Cl and Br) refer to different tumor toxicity and anti-metastasis properties of the isomers [83]. Dmso can be coordinated to ruthenium as a metal center either through the sulfur (dmso-S) or through the oxygen atom (dmso-O). Dmso provides a moderate acceptor site for π-electron donors and bound through sulfur stabilizes ruthenium in lower Ru(II) oxidation state, more reactive toward tumor cells [84]. The biological activity of complexes can be modified by addition or change of the ligands. Phenothiazines and their *N*-alkyl derivatives are themselves biological active compounds, suitable to take part in complex formation. Moreover, they exhibit a strong in vitro antitumor activity in numerous and various tumor cell lines [85].

Recently, thermal decomposition of chlorpromazine hydrochloride (CP·HCl), trifluoperazine dihydrochloride (TF·2HCl) and thioridazine hydrochloride (TR·HCl), and the ruthenium complexes with dimethyl sulfoxide (dmso) of composition [RuCl2(dmso)4] and L[RuCl3(dmso)3]·*x*EtOH, L = CP·HCl, TF·2HCl or TR·HCl is described [86]. The phenothiazines are stable to temperature range of 200–280 ºC with an increasing stability order of TF·2HCl < CP·HCl < TR·HCl. The decomposition of all the compounds takes place in superposing steps.

### **3.3. Alkylimidothio- and alkylimidoselenocarbamates**

During the last five years, our research group reported the promising and potent anticancer effects for several alkylimidothio- and alkylimidoselenocarbamate derivatives [87-89]. These compounds showed a remarkable cytotoxic activity *in vitro* against prostate cancer cells and other several cancer cell lines. One of these derivatives, the quinoline imidoselenocarbamate EI201, inhibits the PI3K/AKT/mTOR pathway, which is persistently activated and contributes to malignant progression in various cancers, and contributes to the loss of maintenance of the selfrenewal and tumorigenic capacity of cancer stem cells. This compound (EI201) suppressed almost 80% prostate tumor growth *in vivo* (*p* < 0.01) compared to controls at a relatively low dose (10 mg/kg) in a mouse xenograft model [90].

Applications of Calorimetry in a Wide Context –

antitumour activity.

various tumor cell lines [85].

in superposing steps.

(Pd or Pt).

372 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

thermochemical parameters of the complexes [74, 75]. A series of Pd(II) complexes with *tert*butylsarcosinedithiocarbamate [76], ethylsarcosinedithiocarbamate and 2-/3-picoline [77], dithiocarbamates and various amines [78] were developed as antitumor agents with low nephrotoxicity. Thermogravimetric analysis was used for the characterization of these compounds. Taking into accounts the kinetic inertness, high activity, low toxicity and suitability for oral administration of Pt(IV) complexes, some Pt(IV) complexes with dithiocarbamates have been synthesized. Morpholine dithiocarbamate, aniline dithiocarbamate and N-(methyl, cyclohexyl) dithiocarbamate alone [79] or with triphenyl phosphine as second ligand [80] were used in order to obtain Pt(IV) complexes with

In 2012, Uivarosi *et al*. have reported the thermal and spectral studies of palladium(II) and platinum(IV) complexes with bis(dimethylthiocarbamoyl)sulphide and bis(diethylthiocarbamoyl)disulphide [81]. TG experiments revealed the nature of complex species as hydrated or anhydrous. Thermal decomposition of coordinated organic ligands occurs in one or two exothermic stages, the final residue being in all cases the free metal

Other complexes with anticancer activity are de ruthenium (III) complexes with sulfur ligands. Ruthenium complexes with dimethyl sulfoxide (dmso) showed selective antitumor properties in preclinical testing [82]. Biological studies in *cis*- and *trans*-RuX2(dmso)4 complexes (X = Cl and Br) refer to different tumor toxicity and anti-metastasis properties of the isomers [83]. Dmso can be coordinated to ruthenium as a metal center either through the sulfur (dmso-S) or through the oxygen atom (dmso-O). Dmso provides a moderate acceptor site for π-electron donors and bound through sulfur stabilizes ruthenium in lower Ru(II) oxidation state, more reactive toward tumor cells [84]. The biological activity of complexes can be modified by addition or change of the ligands. Phenothiazines and their *N*-alkyl derivatives are themselves biological active compounds, suitable to take part in complex formation. Moreover, they exhibit a strong in vitro antitumor activity in numerous and

Recently, thermal decomposition of chlorpromazine hydrochloride (CP·HCl), trifluoperazine dihydrochloride (TF·2HCl) and thioridazine hydrochloride (TR·HCl), and the ruthenium complexes with dimethyl sulfoxide (dmso) of composition [RuCl2(dmso)4] and L[RuCl3(dmso)3]·*x*EtOH, L = CP·HCl, TF·2HCl or TR·HCl is described [86]. The phenothiazines are stable to temperature range of 200–280 ºC with an increasing stability order of TF·2HCl < CP·HCl < TR·HCl. The decomposition of all the compounds takes place

During the last five years, our research group reported the promising and potent anticancer effects for several alkylimidothio- and alkylimidoselenocarbamate derivatives [87-89]. These compounds showed a remarkable cytotoxic activity *in vitro* against prostate cancer cells and other several cancer cell lines. One of these derivatives, the quinoline imidoselenocarbamate

**3.3. Alkylimidothio- and alkylimidoselenocarbamates** 

Degradation and fusion temperatures for 20 of these anticancer derivatives were determined using TG and DSC [91]. Analysis of the thermal data indicated that: (a) in general, sulfur compounds are more stable than selenium compounds; (b) the pyridine ring diminished stability of sulfur and selenium compounds much more than the carbocyclic aromatic rings did; (c) selenomethyl derivatives are more stable than selenoethyl and selenoisopropyl compounds; (d) a chlorine atom on selenocompounds has surprising effects. So, the presence of intermolecular bonds was pointed out between chlorine atom and selenium atom [91]. With regard some substituents present on aromating ring and the ramification and length of chain, it can be concluded that the presence of electron-withdrawing groups in selenocompound structures improves their stability. Besides, selenomethyl derivatives are more stable than selenoethyl and selenoisopropyl compounds [91].

The determination of the polymorphism of a substance is of great importance due to the strong influence of the crystalline form on the physicochemical properties, bioavailability and stability of drugs [92], and, in some compounds with biological activity, can even become metastable forms, being twice as active as the stable form [93]. So, our research group has carried out the study of the physicochemical properties of polymorphic forms of a serie of alkylimidothio- and alkylimidoselenocarbamate derivatives with a combination of DSC, thermomicroscopy and X-ray diffractometry [94]. In this study we observed that polymorphs could be formed when the compounds are heated above their melting points. The results showed that there are four types of thermal behavior for alkylimidothio- and alkylmidoselenocarbamate derivatives: (a) compounds which do not evidence any polymorphic forms (behavior I); (b) compounds which solidify into an amorphous solid form (behavior II); (c) compounds which present a new polymorphic form at a Tonset lower than the original one (behavior III); (d) finally, compounds which have three polymorphic forms with three different Tonset values (behavior IV). Calorimetric studies demonstrated that sulfur and selenium analogs have the same thermal behavior. So, the different thermal behaviors observed for these alkylimidothio- and alkylimidoselenocarbamates are caused by the substituent groups in the aromatic ring, although there is no relationship between electron-withdrawing and electron-donating groups and the thermal behavior.

#### **3.4. Case study: Thermal analysis of selenyl acetic derivatives.**

In 2009, our research group reported the cytotoxic and antiproliferative activities *in vitro* of selenyl acetic derivatives against several cancer cell lines [95]. Considering the structure of these derivatives and their inefficacy to induce apoptosis and to affect to cell cycle, we decided to perform a thermal analysis for these derivatives. So, we carried out a thermal stability and calorimetric studies for some of these anticancer selenyl acetic acids (**Figure 1**).

374 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs 375

a. Compounds with phenyl ring (2 and 7) possess values for enthalpy of fusion higher than Tonset ones. It could be caused by the presence of strong π-π stacking interactions

b. Compounds with groups that can establish hydrogen interactions, such as CN and Cl, substituted over the ring present the highest enthalpy values, owing to these hydrogen

c. The substitution on the *para* position of the phenyl ring with groups that cannot establish hydrogen interactions significantly diminished the enthalpy values. It seems that these substituents alter the electronic distribution over the ring, affecting to the π-π

> **Reference Tonset (ºC ± SD) Δ***Hf* **(Jg-1)** *Compound 1* 157.2 ± 0.2 126.8 ± 4.8 *Compound 2* 83.3 ± 0.6 92.3 ± 2.2 *Compound 3* 117.4 ± 0.3 108.3 ± 5.5 *Compound 4* 107.7 ± 1.1 73.7 ± 1.0 *Compound 5* 146.5 ± 0.1 112.3 ± 1.7 *Compound 6* 92.2 ± 0.2 78.7 ± 0.8 *Compound 7* 73.8 ± 0.3 74.9 ± 7.2 *Compound 8* 130.1 ± 0.4 105.9 ± 4.6

**Table 1.** Tonset and enthalpy of fusion values for selenyl acetic acid derivatives studied.

should be stronger than the interactions established in the rest of the compounds.

**Figure 2.** Possible interactions in the crystal packaging for compounds 1 and 5.

The calorimetric data (**Table 1**) demonstrated that compounds 1 and 5 present a very significant higher Tonset value for the fusion process than the other selenyl acetic derivatives. Both compounds present two groups substituted in the *para* position of the aromatic ring that can act as hydrogen bonding donors. So, these groups could form a different hydrogen bond interaction with the proton of carboxylic acid group (**Figure 2**) and this interaction

If we compare the calorimetric data for selenyl acetic derivatives with other organoselenium compounds (alkylimidoselenocarbamates) synthesized and published by our research group [91], we observed that the Tonset values for the first ones were significantly lower that their imidoselenocarbamate analogs (**Table 2**). The selenyl acetic derivatives are smaller molecules than imidoselenocarbamates and hence they possess lower Tonset values. Nevertheless, the enthalpy of fusion values for selenyl acetic acids are significantly higher

between two molecules in the crystal packaging.

interactions.

stacking interactions strength.

**Figure 1.** General structure for studied selenyl acetic acids.

### *3.4.1. Thermal stability studies*

The thermogravimetric studies were carried out with a Perkin-Elmer TGA-7. The thermobalance was calibrated with alumel and nickel at 10 ºC min-1. The calibration of the oven temperatures was carried out automatically. Mass calibration was carried out with a certified mass of 10 mg (ASTM E617).

The calorimeter was calibrated with indium and zinc (provided by Perkin-Elmer and fabricated according to guideline ISO35) at 10 ºC min-1 and a nitrogen flow of 20 mL min-1. The gases connected to the equipment were nitrogen and air with a purity of 99.999%.

Thermogravimetric analyses were carried out under nitrogen atmosphere with a gas flow of 40 mL min-1 at 10 ºC min-1, using a sample of approximately 3 mg.

All the compounds sublimated before the degradation process start. So, it is not possible to study the thermal stability of these compounds using thermogravimetric techniques.

### *3.4.2. Calorimetric studies*

The calorimetric studies were carried out with a Perkin-Elmer DSC Diamond. Calorimetric analyses were carried out in aluminium capsules for volatiles of 10 µL, at a heating rate of 10 ºC min-1, using a sample of approximately 3 mg, in order to establish the Tonset and the enthalpy of fusion Δ*Hf*. All of the experiments were performed at least three times and the values were expressed as mean ± standard deviation.

The obtained data (**Table 1**) allow us to point out the following calorimetric behaviors:


a. Compounds with phenyl ring (2 and 7) possess values for enthalpy of fusion higher than Tonset ones. It could be caused by the presence of strong π-π stacking interactions between two molecules in the crystal packaging.

Applications of Calorimetry in a Wide Context –

**Figure 1.** General structure for studied selenyl acetic acids.

*3.4.1. Thermal stability studies* 

*3.4.2. Calorimetric studies* 

1. Regarding to the Tonset values:

these compounds.

certified mass of 10 mg (ASTM E617).

374 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The thermogravimetric studies were carried out with a Perkin-Elmer TGA-7. The thermobalance was calibrated with alumel and nickel at 10 ºC min-1. The calibration of the oven temperatures was carried out automatically. Mass calibration was carried out with a

The calorimeter was calibrated with indium and zinc (provided by Perkin-Elmer and fabricated according to guideline ISO35) at 10 ºC min-1 and a nitrogen flow of 20 mL min-1. The gases connected to the equipment were nitrogen and air with a purity of 99.999%.

Thermogravimetric analyses were carried out under nitrogen atmosphere with a gas flow of

All the compounds sublimated before the degradation process start. So, it is not possible to

The calorimetric studies were carried out with a Perkin-Elmer DSC Diamond. Calorimetric analyses were carried out in aluminium capsules for volatiles of 10 µL, at a heating rate of 10 ºC min-1, using a sample of approximately 3 mg, in order to establish the Tonset and the enthalpy of fusion Δ*Hf*. All of the experiments were performed at least three times and the

The obtained data (**Table 1**) allow us to point out the following calorimetric behaviors:

a. The substitution on the aromatic ring causes an increase in the fusion temperatures of

b. The inclusion of a methylene group between aromatic ring and carbonyl group seem to

c. The presence of groups such as cyano and chloro on the ring, which can form hydrogen

bonds, significantly increase the fusion temperatures of these derivatives.

study the thermal stability of these compounds using thermogravimetric techniques.

40 mL min-1 at 10 ºC min-1, using a sample of approximately 3 mg.

values were expressed as mean ± standard deviation.

lead to a diminution in the Tonset values.

2. Regarding to the enthalpy of fusion values:



**Table 1.** Tonset and enthalpy of fusion values for selenyl acetic acid derivatives studied.

The calorimetric data (**Table 1**) demonstrated that compounds 1 and 5 present a very significant higher Tonset value for the fusion process than the other selenyl acetic derivatives. Both compounds present two groups substituted in the *para* position of the aromatic ring that can act as hydrogen bonding donors. So, these groups could form a different hydrogen bond interaction with the proton of carboxylic acid group (**Figure 2**) and this interaction should be stronger than the interactions established in the rest of the compounds.

**Figure 2.** Possible interactions in the crystal packaging for compounds 1 and 5.

If we compare the calorimetric data for selenyl acetic derivatives with other organoselenium compounds (alkylimidoselenocarbamates) synthesized and published by our research group [91], we observed that the Tonset values for the first ones were significantly lower that their imidoselenocarbamate analogs (**Table 2**). The selenyl acetic derivatives are smaller molecules than imidoselenocarbamates and hence they possess lower Tonset values. Nevertheless, the enthalpy of fusion values for selenyl acetic acids are significantly higher 376 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

compared with the imidoselenocarbamates in all cases (**Table 2**). These data seem to point to the existence of intramolecular hydrogen bonds for selenyl acetic derivatives (**Figure 3**).

Thermal Analysis of Sulfur and Selenium Compounds with Multiple Applications, Including Anticancer Drugs 377

in these compounds since they can point out future issues in its pharmaceutical development. The determination of the polymorphism of a substance is of great importance due to the strong influence of the crystalline form on the physicochemical properties, bioavailability and stability of drug, and, in some compounds with biological activity, can

Finally, we report the unpublished thermal analysis data for eight selenyl acetic acid derivatives, which possess cytotoxic activity *in vitro* against several cancer cell lines. All the compounds sublimated before the degradation process start. So, it is not possible to study the thermal stability of these compounds using thermogravimetric techniques. Nevertheless, the obtained results for calorimetric studies allow to point out some calorimetric behaviors concerning to their stability in the fusion process: (a) the substitution on the aromatic ring causes an increase in the fusion temperatures of these compounds; (b) the inclusion of a methylene group between aromatic ring and carbonyl group seem to lead to a diminution in the Tonset values; (c) the presence of groups such as cyano and chloro on the ring, which can form hydrogen bonds, significantly increase the fusion temperatures of these derivatives.

*Synthesis Section, Department of Organic and Pharmaceutical Chemistry, University of Navarra,* 

*Synthesis Section, Department of Organic and Pharmaceutical Chemistry, University of Navarra,* 

[1] Zhou Y Z, Larson J D, Bottoms C A, Arturo E C, Henzl M T, Jenkins J L, Nix J C, Becker D F, Tanner J J (2008) Structural Basis of the Transcriptional Regulation of the Proline Utilization Regulon by Multifunctional PutA. Journal of Molecular Biology. 381: 174-

[2] Verly R M, Rodrigues M A, Daghastanli K R P, Denadai A M L, Cuccovia I M, Bloch C, Frezard F, Santoro M M, Pilo-Veloso D, Bemquerer M P (2008) Effect of Cholesterol on the Interaction of the Amphibian Antimicrobial Peptide DD K with Liposomes.

[3] Andrushchenko V V, Aarabi M H, Nguyen L T, Prenner E J, Vogel H J (2008) Thermodynamics of the Interactions of Tryptophan-Rich Cathelicidin Antimicrobial Peptides with Model and Natural Membranes. Biochimica Et Biophysica Acta-

*Department of Pharmacology, Penn State Hershey College of Medicine, Hershey, PA, USA* 

even become metastable forms, being twice as active as the stable form.

**Author details** 

Daniel Plano\*

*Pamplona, Spain* 

*Pamplona, Spain* 

**5. References** 

188.

 \*

Peptides. 29: 15-24.

Corresponding Author

Biomembranes. 1778: 1004-1014.

Juan Antonio Palop and Carmen Sanmartín


**Table 2.** Tonset and enthalpy of fusion values for selenyl acetic acids and imidoselenocarbamates.

**Figure 3.** Intramolecular hydrogen bonds for selenyl acetic derivatives.

### **4. Conclusions**

Sulfur (S) and selenium (Se) compounds present several applications in a great variety of fields and the study of their thermal behavior is important for their usefulness in these applications. So, the thermal data are necessary to understand the properties and functions for most of these derivatives. The application of the thermal techniques to these S and Se compounds allows, among others: (a) the study of degradation process, as well as the quantification of the purity and composition for coordination compounds; (b) the characterization of thermal behavior for semiconducting glasses; (c) the determination of solubility isotherms and the field of crystallization of inorganic metal-selenite mixtures.

In the last decade, among the wide range of compounds tested as potential anticancer agents, several structurally diverse derivatives that contain a sulfur or selenium template have been reported and have generated growing interest. For that reason, in this chapter we have focused on some relevant thermal studies in sulfur and selenium compounds with anticancer activity. The thermal techniques, and particularly the DSC, are especially useful in these compounds since they can point out future issues in its pharmaceutical development. The determination of the polymorphism of a substance is of great importance due to the strong influence of the crystalline form on the physicochemical properties, bioavailability and stability of drug, and, in some compounds with biological activity, can even become metastable forms, being twice as active as the stable form.

Finally, we report the unpublished thermal analysis data for eight selenyl acetic acid derivatives, which possess cytotoxic activity *in vitro* against several cancer cell lines. All the compounds sublimated before the degradation process start. So, it is not possible to study the thermal stability of these compounds using thermogravimetric techniques. Nevertheless, the obtained results for calorimetric studies allow to point out some calorimetric behaviors concerning to their stability in the fusion process: (a) the substitution on the aromatic ring causes an increase in the fusion temperatures of these compounds; (b) the inclusion of a methylene group between aromatic ring and carbonyl group seem to lead to a diminution in the Tonset values; (c) the presence of groups such as cyano and chloro on the ring, which can form hydrogen bonds, significantly increase the fusion temperatures of these derivatives.

### **Author details**

Daniel Plano\*

Applications of Calorimetry in a Wide Context –

**Ref. R X n Tonset**

376 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 3.** Intramolecular hydrogen bonds for selenyl acetic derivatives.

**4. Conclusions** 

compared with the imidoselenocarbamates in all cases (**Table 2**). These data seem to point to the existence of intramolecular hydrogen bonds for selenyl acetic derivatives (**Figure 3**).

2-Cl N 0 157.2 ± 0.2 126.8 ± 4.8 186.8 ± 0.2 42.4 ± 1.3 H C 0 83.3 ± 0.6 92.3 ± 2.2 139.5 ± 0.2 30.6 ± 0.6 3,5-diOCH3 C 0 117.4 ± 0.3 108.3 ± 5.5 163.6 ± 0.3 39.6 ± 0.3 4-CF3 C 0 107.7 ± 1.1 73.7 ± 1.0 172.9 ± 0.3 30.7 ± 0.8 4-CN C 0 146.5 ± 0.1 112.3 ± 1.7 219.5 ± 2.8 44.4 ± 14.3 4-CH3 C 0 92.2 ± 0.2 78.7 ± 0.8 148.5 ± 0.3 32.7 ± 4.9 H C 1 73.8 ± 0.3 74.9 ± 7.2 --- --- Phenyl C 0 130.1 ± 0.4 105.9 ± 4.6 --- --- **Table 2.** Tonset and enthalpy of fusion values for selenyl acetic acids and imidoselenocarbamates.

Sulfur (S) and selenium (Se) compounds present several applications in a great variety of fields and the study of their thermal behavior is important for their usefulness in these applications. So, the thermal data are necessary to understand the properties and functions for most of these derivatives. The application of the thermal techniques to these S and Se compounds allows, among others: (a) the study of degradation process, as well as the quantification of the purity and composition for coordination compounds; (b) the characterization of thermal behavior for semiconducting glasses; (c) the determination of solubility isotherms and the field of crystallization of inorganic metal-selenite mixtures.

In the last decade, among the wide range of compounds tested as potential anticancer agents, several structurally diverse derivatives that contain a sulfur or selenium template have been reported and have generated growing interest. For that reason, in this chapter we have focused on some relevant thermal studies in sulfur and selenium compounds with anticancer activity. The thermal techniques, and particularly the DSC, are especially useful

**Selenyl acetic acids Imidoselenocarbamates** 

**(ºC ± SD) Δ***Hf* **(Jg-1)** 

**(ºC ± SD) Δ***Hf* **(Jg-1) Tonset**

*Synthesis Section, Department of Organic and Pharmaceutical Chemistry, University of Navarra, Pamplona, Spain Department of Pharmacology, Penn State Hershey College of Medicine, Hershey, PA, USA* 

Juan Antonio Palop and Carmen Sanmartín

*Synthesis Section, Department of Organic and Pharmaceutical Chemistry, University of Navarra, Pamplona, Spain* 

### **5. References**


<sup>\*</sup> Corresponding Author

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[88] Plano D, Baquedano Y, Ibáñez E, Jiménez I, Palop J A, Spallholz J E, Sanmartín C (2010) Antioxidant-Prooxidant Properties of a New Organoselenium Compound Library. Molecules. 15: 7292-7312.

**Chapter 17** 

© 2013 Leitner 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,

**Calorimetric Determination of Heat Capacity,** 

**Entropy and Enthalpy of Mixed Oxides in the** 

Jindřich Leitner, David Sedmidubský, Květoslav Růžička and Pavel Svoboda

Mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5 possess many extraordinary electric, magnetic and optical properties for which they are used in fabrication of various electronic components. For example Sr2(Nb,Ta)2O7 and (Sr,Ca)Bi2(Nb,Ta)2O9 are used for ferroelectric memory devices, CaNb2O6, Sr5(Nb1–xTax)4O15 and Bi(Nb,Ta)O4 for microwave dielectric resonators and Ca2Nb2O7 as non-linear optical materials and hosts for rare-earth ions in solid-state lasers. Ternary strontium bismuth oxides SrBi2O4, Sr2Bi2O5, and Sr6Bi2O9

To assess the thermodynamic stability and reactivity of these oxides under various conditions during their preparation, processing and operation, a complete set of consistent thermodynamic data, including heat capacity, entropy and enthalpy of formation, is necessary. Some of these data are available in literature. Akishige et al. [1] have been measured the heat capacities of Sr2Nb2O7 and Sr2Ta2O7 single crystals in the temperature range 2-600 K. The results have been only plotted and the values of *S*°m(298) have not been calculated. A commensurate transformation of Sr2Nb2O7 at *T*INC = 495 K has been observed accompanied by changes in enthalpy and entropy of Δ*H* = 291 J mol-1 and Δ*S* = 0.587 J K-1 mol-1. The heat capacity of Sr2Nb2O7 has been also measured by Shabbir at al. [2] in the temperature range 375-575 K. They have observed a phase transition at *T*INC = 487 ± 2 K connected with Δ*H* = 147 ± 14 J mol-1 and Δ*S* = 0.71 ± 0.10 J K-1 mol-1. The heat capacities of polycrystalline and monocrystalline SrBi2Ta2O9 and Sr0,85Bi2,1Ta2O9 have been measured by Onodera at al. [3–5] at 80-800 K. Morimoto at al. [6] have reported the results of the heat capacity measurements of SrBi2(Nb*x*Ta1-*x*)2O9 (*x* = 0, 1/3, 2/3 a 1). The temperature dependences of heat capacities show lambda-transitions with maxima at the Currie temperature *T*C = 570 ± 1 K, 585 ± 2 K, 625 ± 3 K a 690 ± 2 K for *x* = 0, 1/3, 2/3 and 1,

are of considerable interest due to a visible light driven fotocatalytic activity.

**System CaO–SrO–Bi2O3–Nb2O5–Ta2O5**

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54064

**1. Introduction** 


## **Calorimetric Determination of Heat Capacity, Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5**

Jindřich Leitner, David Sedmidubský, Květoslav Růžička and Pavel Svoboda

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54064

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

Molecules. 15: 7292-7312.

Calorimetry. 98: 559-566.

Thermochimica Acta. 234: 31-39.

Calorimetry. 105: 1007-1013.

134.

3313-3338.

384 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[88] Plano D, Baquedano Y, Ibáñez E, Jiménez I, Palop J A, Spallholz J E, Sanmartín C (2010) Antioxidant-Prooxidant Properties of a New Organoselenium Compound Library.

[89] Ibáñez E, Plano D, Font M, Calvo A, Prior C, Palop J A, Sanmartín C (2011) Synthesis and Antiproliferative Activity of Novel Symmetrical Alkylthio- and Alkylseleno-

[90] Ibáñez E, Agliano A, Prior C, Nguewa P, Redrado M, González-Zubeldia I, Plano D, Palop J A, Sanmartin C, Calvo A (2012) The Quinoline Imidoselenocarbamate EI201 Blocks the Akt/Mtor Pathway and Targets Cancer Stem Cells Leading to a Strong

[91] Plano D, Lizarraga E, Font M, Palop J A, Sanmartin C (2009) Thermal Stability and Decomposition of Sulphur and Selenium Compounds. Journal of Thermal Analysis and

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Imidocarbamates. European Journal of Medicinal Chemistry. 46: 265-274.

Antitumor Activity. Current Medicinal Chemistry. 19: 3031-3043.

Mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5 possess many extraordinary electric, magnetic and optical properties for which they are used in fabrication of various electronic components. For example Sr2(Nb,Ta)2O7 and (Sr,Ca)Bi2(Nb,Ta)2O9 are used for ferroelectric memory devices, CaNb2O6, Sr5(Nb1–xTax)4O15 and Bi(Nb,Ta)O4 for microwave dielectric resonators and Ca2Nb2O7 as non-linear optical materials and hosts for rare-earth ions in solid-state lasers. Ternary strontium bismuth oxides SrBi2O4, Sr2Bi2O5, and Sr6Bi2O9 are of considerable interest due to a visible light driven fotocatalytic activity.

To assess the thermodynamic stability and reactivity of these oxides under various conditions during their preparation, processing and operation, a complete set of consistent thermodynamic data, including heat capacity, entropy and enthalpy of formation, is necessary. Some of these data are available in literature. Akishige et al. [1] have been measured the heat capacities of Sr2Nb2O7 and Sr2Ta2O7 single crystals in the temperature range 2-600 K. The results have been only plotted and the values of *S*°m(298) have not been calculated. A commensurate transformation of Sr2Nb2O7 at *T*INC = 495 K has been observed accompanied by changes in enthalpy and entropy of Δ*H* = 291 J mol-1 and Δ*S* = 0.587 J K-1 mol-1. The heat capacity of Sr2Nb2O7 has been also measured by Shabbir at al. [2] in the temperature range 375-575 K. They have observed a phase transition at *T*INC = 487 ± 2 K connected with Δ*H* = 147 ± 14 J mol-1 and Δ*S* = 0.71 ± 0.10 J K-1 mol-1. The heat capacities of polycrystalline and monocrystalline SrBi2Ta2O9 and Sr0,85Bi2,1Ta2O9 have been measured by Onodera at al. [3–5] at 80-800 K. Morimoto at al. [6] have reported the results of the heat capacity measurements of SrBi2(Nb*x*Ta1-*x*)2O9 (*x* = 0, 1/3, 2/3 a 1). The temperature dependences of heat capacities show lambda-transitions with maxima at the Currie temperature *T*C = 570 ± 1 K, 585 ± 2 K, 625 ± 3 K a 690 ± 2 K for *x* = 0, 1/3, 2/3 and 1,

© 2013 Leitner 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.

386 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

respectively. Using EMF (electromotive force) measurements, Raghavan has obtained the values of the Gibbs energy of formation from binary oxides, Δox*G*, for some niobates [7,8] and tantalates [9,10] of calcium. His results are summarized in Table 1. The same technique has been employed by Dneprova et al. [11] for Δox*G* measurement for CaNb2O6 and Ca2Nb2O7. Their results presented in Table 1 are not significantly different from the results of Raghavan. Using the CALPHAD approach [13], Yang et al. [14] have assessed thermodynamic data for various mixed oxides in the SrO–Nb2O5 system. The same approach has been used by Hallstedt et al. for the assessment of thermodynamic data of mixed oxides in the systems CaO–Bi2O3 [14] and SrO–Bi2O3 [15]. Besides equilibrium data, values of the enthalpy of formation [16] of mixed oxide have been considered. Later on, these systems have been studied by EMF method by Jacob and Jayadevan [17,18] and temperature dependences of Δox*G* for various mixed oxides have been derived. These data have been included into the thermodynamic re-assessment of the CaO-SrO-Bi2O3 system [19].

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 387

This review brings a summary of our results [20–30] focused on calorimetric determination of heat capacity, entropy end enthalpy of mixed oxides in the system CaO–SrO–Bi2O3– Nb2O5–Ta2O5. Temperature dependences of molar heat capacity in a broad temperature range were evaluated from the experimental heat capacity and relative enthalpy data. Molar entropies at *T* = 298.15 K were calculated from low temperature heat capacity measurements. Furthermore, the results of calorimetric measurements of the enthalpies of drop-solution in a sodium oxide-molybdenum oxide melt for several stoichiometric mixed oxides in the above mentioned system are reported from which the values of enthalpy of formation from constituent binary oxides were derived. Finally, some empirical estimation and correlation methods (the Neumann-Kopp's rule, entropy-volume correlation and electronegativity-differences method) for evaluation of thermodynamic data of mixed

Nineteen mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5 with stoichiometry CaBi2O4, Ca4Bi6O13, Ca2Bi2O5, SrBi2O4, Sr2Bi2O5, CaNb2O6, Ca2Nb2O7, SrNb2O6, Sr2Nb2O7, Sr2Nb10O27, Sr5Nb4O15, BiNbO4, BiNb5O14, BiTaO4, Bi4Ta2O11, Bi7Ta3O18, Bi3TaO7, SrBi2Nb2O9, and SrBi2Ta2O9 were prepared, characterized and examined. The samples were prepared by conventional solid state reactions from high purity precursors (CaCO3, SrCO3 Bi2O3, Nb2O5 and Ta2O5). A three step procedure was used consisting of an initial calcination run of mixed powder precursors and subsequent double firing of prereacted mixtures pressed into pellets. The phase composition of the prepared samples was checked by X-ray powder diffraction (XRD). XRD data were collected at room temperature with an X'Pert PRO (PANalytical, the Netherlands) *θ*-*θ* powder diffractometer with parafocusing Bragg-Brentano geometry using CuKα radiation (*λ* = 1.5418 nm). Data were scanned over the angular range 5–60° (2*θ*) with an increment of 0.02° (2*θ*) and a counting time of 0.3 s step–1.

The PPMS equipment 14 T-type (Quantum Design, USA) was used for the heat capacity measurements in the low temperature region [31-35]. The measurements were performed by the relaxation method [36] with fully automatic procedure under high vacuum (pressure ~10–2 Pa) to avoid heat loss through the exchange gas. The samples were compressed

The samples were mounted to the calorimeter platform with cryogenic grease Apiezon N (supplied by Quantum Design). The procedure was as follows: First, a blank sample holder with the Apiezon only was measured in the temperature range approx. 2–280 K to obtain background data, then the sample plate was attached to the calorimeter platform and the measurement was repeated in the same temperature range with the same temperature steps. The sample heat capacity was then obtained as a difference between the two data sets. This procedure was applied, because the heat capacity of Apiezon is not negligible in comparison with the sample heat capacity (~8 % at room temperature) and exhibits a peak-shaped transition below room temperature [37]. The manufacturer claims the precision of this

powder pellets. The densities of the samples were about 65 % of the theoretical ones.

Data evaluation was performed by means of the HighScore Plus software.

oxides are tested and assessed.

**2. Experimental** 


**Table 1.** Published values of Δox*G*, Δox*H* a Δox*S* for some mixed oxides in the system CaO-SrO-Bi2O3- Nb2O5-Ta2O5

This review brings a summary of our results [20–30] focused on calorimetric determination of heat capacity, entropy end enthalpy of mixed oxides in the system CaO–SrO–Bi2O3– Nb2O5–Ta2O5. Temperature dependences of molar heat capacity in a broad temperature range were evaluated from the experimental heat capacity and relative enthalpy data. Molar entropies at *T* = 298.15 K were calculated from low temperature heat capacity measurements. Furthermore, the results of calorimetric measurements of the enthalpies of drop-solution in a sodium oxide-molybdenum oxide melt for several stoichiometric mixed oxides in the above mentioned system are reported from which the values of enthalpy of formation from constituent binary oxides were derived. Finally, some empirical estimation and correlation methods (the Neumann-Kopp's rule, entropy-volume correlation and electronegativity-differences method) for evaluation of thermodynamic data of mixed oxides are tested and assessed.

### **2. Experimental**

Applications of Calorimetry in a Wide Context –

Oxide Δox*<sup>G</sup>*

Nb2O5-Ta2O5

(kJ mol–1)

386 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

respectively. Using EMF (electromotive force) measurements, Raghavan has obtained the values of the Gibbs energy of formation from binary oxides, Δox*G*, for some niobates [7,8] and tantalates [9,10] of calcium. His results are summarized in Table 1. The same technique has been employed by Dneprova et al. [11] for Δox*G* measurement for CaNb2O6 and Ca2Nb2O7. Their results presented in Table 1 are not significantly different from the results of Raghavan. Using the CALPHAD approach [13], Yang et al. [14] have assessed thermodynamic data for various mixed oxides in the SrO–Nb2O5 system. The same approach has been used by Hallstedt et al. for the assessment of thermodynamic data of mixed oxides in the systems CaO–Bi2O3 [14] and SrO–Bi2O3 [15]. Besides equilibrium data, values of the enthalpy of formation [16] of mixed oxide have been considered. Later on, these systems have been studied by EMF method by Jacob and Jayadevan [17,18] and temperature dependences of Δox*G* for various mixed oxides have been derived. These data have been

included into the thermodynamic re-assessment of the CaO-SrO-Bi2O3 system [19].

*T* (K)

CaNb2O6 –75.82 – 0.03345*T* 1245-1300 –75.82 33.45 [7] Ca2Nb2O7 –178.44 1256 [8] Ca3Nb2O8 –209.94 1256 [8] CaTa4O11 –36.982 – 0.029*T* 1250-1300 –36.98 29.0 [9] CaTa2O6 –65.14 1250 [10] Ca2Ta2O7 –102.82 1250 [10] Ca4Ta2O9 –165.05 1250 [10] CaNb2O6 –175.73 + 0.02259*T* 1100-1276 –175.73 –22.59 [11] Ca2Nb2O7 –212.54 – 0.02218*T* 1100-1350 –212.54 22.18 [11] Sr2Nb10O27 –1125.69 + 0.35069*T* 298-5000 –1125.69 –350.69 [12] SrNb2O6 *–*325.04 + 0.05865*T* 298-5000 –325.04 –58.65 [12] Sr2Nb2O7 –367.43 + 0.03993*T* 298-5000 –367.43 –39.93 [12] Sr5Nb4O14 –746.72 + 0.05101*T* 298-5000 –746.72 –51.01 [12] Ca5Bi14O26 –125.90 – 0.055*T* 298-1300 –125.9 55.0 [19] CaBi2O4 –27.60 – 0.003*T* 298-1300 –27.6 3.0 [19] Ca4Bi6O13 –97.60 – 0.008*T* 298-1300 –97.6 8.0 [19] Ca2Bi2O5 –42.20 – 0.003*T* 298-1300 –42.2 3.0 [19] SrBi2O4 –63.86 – 0.0018*T* 298-1300 –63.86 1.8 [19] Sr2Bi2O5 –118.75 + 0.024*T* 298-1300 –118.75 –24.0 [19] Sr3Bi2O6 –109.60 + 0.0024*T* 298-1300 –109.60 –2.4 [19]

**Table 1.** Published values of Δox*G*, Δox*H* a Δox*S* for some mixed oxides in the system CaO-SrO-Bi2O3-

Δox*H* (kJ mol–1) Δox*S*

(J K-1 mol–1) Ref.

Nineteen mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5 with stoichiometry CaBi2O4, Ca4Bi6O13, Ca2Bi2O5, SrBi2O4, Sr2Bi2O5, CaNb2O6, Ca2Nb2O7, SrNb2O6, Sr2Nb2O7, Sr2Nb10O27, Sr5Nb4O15, BiNbO4, BiNb5O14, BiTaO4, Bi4Ta2O11, Bi7Ta3O18, Bi3TaO7, SrBi2Nb2O9, and SrBi2Ta2O9 were prepared, characterized and examined. The samples were prepared by conventional solid state reactions from high purity precursors (CaCO3, SrCO3 Bi2O3, Nb2O5 and Ta2O5). A three step procedure was used consisting of an initial calcination run of mixed powder precursors and subsequent double firing of prereacted mixtures pressed into pellets. The phase composition of the prepared samples was checked by X-ray powder diffraction (XRD). XRD data were collected at room temperature with an X'Pert PRO (PANalytical, the Netherlands) *θ*-*θ* powder diffractometer with parafocusing Bragg-Brentano geometry using CuKα radiation (*λ* = 1.5418 nm). Data were scanned over the angular range 5–60° (2*θ*) with an increment of 0.02° (2*θ*) and a counting time of 0.3 s step–1. Data evaluation was performed by means of the HighScore Plus software.

The PPMS equipment 14 T-type (Quantum Design, USA) was used for the heat capacity measurements in the low temperature region [31-35]. The measurements were performed by the relaxation method [36] with fully automatic procedure under high vacuum (pressure ~10–2 Pa) to avoid heat loss through the exchange gas. The samples were compressed powder pellets. The densities of the samples were about 65 % of the theoretical ones.

The samples were mounted to the calorimeter platform with cryogenic grease Apiezon N (supplied by Quantum Design). The procedure was as follows: First, a blank sample holder with the Apiezon only was measured in the temperature range approx. 2–280 K to obtain background data, then the sample plate was attached to the calorimeter platform and the measurement was repeated in the same temperature range with the same temperature steps. The sample heat capacity was then obtained as a difference between the two data sets. This procedure was applied, because the heat capacity of Apiezon is not negligible in comparison with the sample heat capacity (~8 % at room temperature) and exhibits a peak-shaped transition below room temperature [37]. The manufacturer claims the precision of this measurement better then 2 % [38]; the control measurement of the copper sample (99.999 % purity) confirmed this precision in the temperature range 50–250 K. However, the precision of the measurement strongly depends on the thermal coupling between the sample and the calorimeter platform. Due to unavoidable porosity of the sample plate this coupling is rapidly getting worse as the temperature raises above 270 K and Apiezon diffuses into the porous sample. Consequently, the uncertainty of the obtained data tends to be larger.

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 389

The XRD analysis revealed that the prepared samples were without any observable diffraction lines from unreacted precursors or other phases. The lattice parameters of the oxides were evaluated by Rietveld refinement [40] and are summarized in Table 2 together

**2.2. Evaluation of temperature dependence of heat capacity at low temperatures** 

The fit of the low-temperature heat capacity data (LT fit) consists of two steps. Assuming the validity of the phenomenological formula *Cp*m = *βT* 3 *+ γ*el*T*, at *T* → 0 where *β* is proportional to the inverse cube root of the Debye temperature *Θ*D and *γ*el*T* is the Sommerfeld term, we plotted the *Cp*m/*T vs*. *T* 2 dependence for *T* < 8 K to estimate the *Θ*D and *γ*el values. Since all compounds under study are semiconductors with a sufficiently large band gap, the non-zero *γ*el values are supposed to be either due to some metallic impurities or to a series of Schottkylike transitions resulting from structure defects. Nevertheless, they are negligible in most cases (typically < 0.5 mJ K–2 mol–1) and can be ignored in further analysis. As an example, the results

of heat capacity measurements on CaNb2O6 and LT fit for *T* < 10 K is shown in Fig. 1.

Oxide *a* (nm) *b* (nm) *c* (nm) *α* (°) *β* (°) *γ* (°) *d* (g cm–3) Ref. CaBi2O4 1.66143 1.15781 1.39915 90 134.03 90 6.631 [20] Ca4Bi6O13 0.59308 1.73512 0.72192 90 90 90 6.540 [20] Ca2Bi2O5 1.01074 1.01249 1.04618 116.88 107.16 92.98 6.468 [20] SrBi2O4 1.92635 0.43437 0.61444 90 95.50 90 7.392 [29] Sr2Bi2O5 1.42935 0.61715 0.76478 90 90 90 6.628 [29] CaNb2O6 1.49698 0.57472 0.52202 90 90 90 4.760 [26] Ca2Nb2O7 0.76853 1.33587 0.54959 90 90 98.29 4.496 [26] SrNb2O6 0.77209 0.55930 1.09821 90 90.37 90 5.174 [24] Sr2Nb2O7 0.39544 2.67735 0.57004 90 90 90 5.206 [26] Sr2Nb10O27 3.715 3.697 0.3943 90 90 90 5.653 a) Sr5Nb4O15 0.56576 0.56576 1.14536 90 90 120 5.490 [27] BiNbO4 0.56893 1.1728 0.49915 90 90 90 7.297 [21] BiNb5O14 1.76762 1.72072 0.39610 90 90 90 4.948 b) BiTaO4 0.56394 1.1776 0.49626 90 90 90 9.149 [21] Bi4Ta2O11 0.66159 0.76528 0.98781 101.39 90.10 89.99 9.306 [28] Bi7Ta3O18 3.40162 0.76054 0.66354 90 109.16 90 9.395 [28] Bi3TaO7 0.54711 0.54711 0.54711 90 90 90 9.327 [28] SrBi2Nb2O9 0.55160 0.55087 2.51020 90 90 90 7.275 [22] SrBi2Ta2O9 0.55224 0.55266 2.50124 90 90 90 8.801 [22]

with the values of theoretical density calculated from the lattice parameters.

**2.1. Characterization of prepared samples** 

a) Quoted according to JCPDS 035-1220. b) Quoted according to JCPDS 048-0986

**Table 2.** Structural characterization of prepared samples

A Micro DSC III calorimeter (Setaram, France) was used for the heat capacity determination in the temperature range of 253–352 K. First, the samples were preheated in a continuous mode from room temperature up to 352 K (heating rate 0.5 K min–1). Then the heat capacity was measured in the incremental temperature scanning mode consisting of a number of 5– 10 K steps (heating rate 0.2 K min–1) followed by isothermal delays of 9000 s. Two subsequent step-by-step heating were recorded for each sample. Synthetic sapphire, NIST Standard reference material No. 720, was used as the reference. The uncertainty of heat capacity measurements is estimated to be better than ±1 %.

Enthalpy increment determinations were carried out by drop method using hightemperature calorimeter, Multi HTC 96 (Setaram, France). All measurements were performed in air by alternating dropping of the reference material (small pieces of synthetic sapphire, NIST Standard reference material No. 720) and of the sample (pressed pellets 5 mm in diameter) being initially held at room temperature, through a lock into the working cell of the preheated calorimeter. Endothermic effects are detected and the relevant peak area is proportional to the heat content of the dropped specimen. The delays between two subsequent drops were 25–30 min. To check the accuracy of measurement, the enthalpy increments of platinum in the temperature range 770–1370 K were measured first and compared with published reference values [39]. The standard deviation of 22 runs was 0.47 kJ mol–1, the average relative error was 2.0 %. Estimated overall accuracy of the drop measurements is ±3 %.

The heats of drop-solution were determined using a Multi HTC 96 high-temperature calorimeter (Setaram, France). A sodium oxide-molybdenum oxide melt of the stoichiometry 3Na2O + 4MoO3 was used as the solvent. The ratio of solute/solvent varied from 1/250 up to 1/500. The measurements were performed at temperatures of 973 and 1073 K in argon or air atmosphere. The method consists in alternating dropping of the reference material (small spherules of pure platinum) and of the sample (small pieces of pressed tablets 10–40 mg), being initially held near room temperature (*T*0), through a lock into the working cell (a platinum crucible with the solvent) of the preheated calorimeter at temperature *T*. Two or three samples were examined during one experimental run. The delays between two subsequent drops were 30–60 min. The total heat effect (Δds*H*) includes the heat of solution (Δsol*H*), the heat content of the sample (Δ*TH*), and, for the carbonates, the heat of decomposition (Δdecomp*H*) to form solid CaO or SrO and gaseous CO2. Using appropriate thermochemical cycles, the values of the enthalpy of formation of mixed oxides from the binary oxides and from the elements at 298 K were evaluated. The temperature dependence of the heat capacity of platinum [39] was used for the calculation of the sensitivity of the calorimeters.

### **2.1. Characterization of prepared samples**

Applications of Calorimetry in a Wide Context –

388 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

capacity measurements is estimated to be better than ±1 %.

measurements is ±3 %.

calorimeters.

measurement better then 2 % [38]; the control measurement of the copper sample (99.999 % purity) confirmed this precision in the temperature range 50–250 K. However, the precision of the measurement strongly depends on the thermal coupling between the sample and the calorimeter platform. Due to unavoidable porosity of the sample plate this coupling is rapidly getting worse as the temperature raises above 270 K and Apiezon diffuses into the

A Micro DSC III calorimeter (Setaram, France) was used for the heat capacity determination in the temperature range of 253–352 K. First, the samples were preheated in a continuous mode from room temperature up to 352 K (heating rate 0.5 K min–1). Then the heat capacity was measured in the incremental temperature scanning mode consisting of a number of 5– 10 K steps (heating rate 0.2 K min–1) followed by isothermal delays of 9000 s. Two subsequent step-by-step heating were recorded for each sample. Synthetic sapphire, NIST Standard reference material No. 720, was used as the reference. The uncertainty of heat

Enthalpy increment determinations were carried out by drop method using hightemperature calorimeter, Multi HTC 96 (Setaram, France). All measurements were performed in air by alternating dropping of the reference material (small pieces of synthetic sapphire, NIST Standard reference material No. 720) and of the sample (pressed pellets 5 mm in diameter) being initially held at room temperature, through a lock into the working cell of the preheated calorimeter. Endothermic effects are detected and the relevant peak area is proportional to the heat content of the dropped specimen. The delays between two subsequent drops were 25–30 min. To check the accuracy of measurement, the enthalpy increments of platinum in the temperature range 770–1370 K were measured first and compared with published reference values [39]. The standard deviation of 22 runs was 0.47 kJ mol–1, the average relative error was 2.0 %. Estimated overall accuracy of the drop

The heats of drop-solution were determined using a Multi HTC 96 high-temperature calorimeter (Setaram, France). A sodium oxide-molybdenum oxide melt of the stoichiometry 3Na2O + 4MoO3 was used as the solvent. The ratio of solute/solvent varied from 1/250 up to 1/500. The measurements were performed at temperatures of 973 and 1073 K in argon or air atmosphere. The method consists in alternating dropping of the reference material (small spherules of pure platinum) and of the sample (small pieces of pressed tablets 10–40 mg), being initially held near room temperature (*T*0), through a lock into the working cell (a platinum crucible with the solvent) of the preheated calorimeter at temperature *T*. Two or three samples were examined during one experimental run. The delays between two subsequent drops were 30–60 min. The total heat effect (Δds*H*) includes the heat of solution (Δsol*H*), the heat content of the sample (Δ*TH*), and, for the carbonates, the heat of decomposition (Δdecomp*H*) to form solid CaO or SrO and gaseous CO2. Using appropriate thermochemical cycles, the values of the enthalpy of formation of mixed oxides from the binary oxides and from the elements at 298 K were evaluated. The temperature dependence of the heat capacity of platinum [39] was used for the calculation of the sensitivity of the

porous sample. Consequently, the uncertainty of the obtained data tends to be larger.

The XRD analysis revealed that the prepared samples were without any observable diffraction lines from unreacted precursors or other phases. The lattice parameters of the oxides were evaluated by Rietveld refinement [40] and are summarized in Table 2 together with the values of theoretical density calculated from the lattice parameters.

### **2.2. Evaluation of temperature dependence of heat capacity at low temperatures**

The fit of the low-temperature heat capacity data (LT fit) consists of two steps. Assuming the validity of the phenomenological formula *Cp*m = *βT* 3 *+ γ*el*T*, at *T* → 0 where *β* is proportional to the inverse cube root of the Debye temperature *Θ*D and *γ*el*T* is the Sommerfeld term, we plotted the *Cp*m/*T vs*. *T* 2 dependence for *T* < 8 K to estimate the *Θ*D and *γ*el values. Since all compounds under study are semiconductors with a sufficiently large band gap, the non-zero *γ*el values are supposed to be either due to some metallic impurities or to a series of Schottkylike transitions resulting from structure defects. Nevertheless, they are negligible in most cases (typically < 0.5 mJ K–2 mol–1) and can be ignored in further analysis. As an example, the results of heat capacity measurements on CaNb2O6 and LT fit for *T* < 10 K is shown in Fig. 1.


a) Quoted according to JCPDS 035-1220.

b) Quoted according to JCPDS 048-0986

**Table 2.** Structural characterization of prepared samples

In the second step of the LT fit, both sets of the *Cp*m data (relaxation time + DSC) were considered. Analysis of the phonon heat capacity was performed as an additive combination of Debye and Einstein models. Both models include corrections for anharmonicity, which is responsible for a small, but not negligible, additive term at higher temperatures and which accounts for the difference between isobaric and isochoric heat capacity. According to literature [41], the term 1/(1 – *T* ) is considered as a correction factor.

The acoustic part of the phonon heat capacity is described using the Debye model

$$C\_{\rm phD} = \frac{9R}{1 - \alpha\_{\rm D}T} \left(\frac{T}{\Theta\_{\rm D}}\right)^3 \int\_0^{x\_0} \frac{\mathbf{x}^4 \exp(\mathbf{x})}{\left[\exp(\mathbf{x}) - 1\right]^2} d\mathbf{x} \tag{1}$$

Calorimetric Determination of Heat Capacity,

Δox*S*

(J K-1 mol–1) Ref.

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 391

(3)

*i*

*S*m(298) (J K–1 mol–1)

3 3 ph phD phE

*n*

*i*

All the estimated values were further treated by a simplex routine and a full non-linear fit

The values of relative enthalpies at 298.15 K, *H*m(298.15) – *H*m(0), were evaluated from the low-temperature *Cp*m data (LT fit) by numerical integration of the *Cp*m(*T*) dependences from zero to 298.15 K. Standard deviations (2σ) were calculated using the error propagation law. The values of standard molar entropies at 298.15 K, *S*m(298.15), were derived from the lowtemperature *Cp*m data (LT fit) by numerical integration of the *Cp*m(*T*)/*T* dependences from zero to 298.15 K. A numerical integration was used with the boundary conditions *S*m = 0 and *Cp*m = 0 at *T* = 0 K. Standard deviations (2σ) were calculated using the error propagation law.

CaBi2O4 151.3 26470 158 188.5 3.3 1.9 [20] Ca4Bi6O13 504.1 85079 507 574.1 8.8 –23.8 [20] Ca2Bi2O5 197.4 33735 201 231.3 2.9 6.6 [20] SrBi2O4 155.6 29601 169 206.1 1.1 4.0 [29] Sr2Bi2O5 201.9 38199 219 261.2 1.4 5.5 [29] CaNb2O6 171.8 28159 170 167.3 0.9 –8.1 [26] Ca2Nb2O7 218.1 35631 215 212.4 1.2 –1.1 [26] SrNb2O6 170.2 28722 174 173.9 0.9 –17.0 [24] Sr2Nb2O7 216.6 37977 266 238.5 1.3 –5.9 [26] Sr2Nb10O27 746.8 124150 740 759.7 4.1 –33.9 [27] Sr5Nb4O15 477.2 83340 490 524.5 2.8 –18.4 [27] BiNbO4 121.3 22120 134 147.9 0.8 5.0 [21] BiNb5O14 386.8 62639 362 397.2 2.1 –25.8 [23] BiTaO4 119.3 22021 132 149.1 0.8 3.3 [21] Bi4Ta2O11 363.2 66566 384 449.6 2.3 9.5 [28] Bi7Ta3O18 602.7 109760 634 743.0 3.8 8.6 [28] Bi3TaO7 235.2 44265 254 304.3 1.6 10.0 [28] SrBi2Nb2O9 286.4 49230 292 327.2 1.7 –12.2 [22] SrBi2Ta2O9 286.6 49060 289 339.2 1.8 –5.9 [22]

**Table 3.** Heat capacity, relative enthalpy, entropy and entropy of formation from binary oxides at temperature 298.15 K of various mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5

*H*m(298)–*H*m(0) (J mol–1)

*CC C*

was performed on all adjustable parameters.

All calculated values are summarized in Table 3.

(J K–1 mol–1)

Oxide *Cp*m(298)

1

where *R* is the gas constant, *Θ*D is the Debye characteristic temperature, D is the coefficient of anharmonicity of acoustic branches and *x*D = *Θ*D/*T*. Here the three acoustic branches are taken as one triply degenerate branch. Similarly, the individual optical branches are described by the Einstein model

**Figure 1.** Temperature dependence of *Cp*m/*T* function for CaNb2O7 at low temperatures

$$C\_{\rm phE\ell} = \frac{R}{1 - \alpha\_{\rm E\ell}T} \frac{\mathbf{x}\_{\rm E\ell}^2 \exp(\mathbf{x}\_{\rm E\ell})}{\left[\exp(\mathbf{x}\_{\rm E\ell}) - 1\right]^2} \tag{2}$$

where <sup>E</sup>*<sup>i</sup>* and *x*E*<sup>i</sup>* = *Θ*E*<sup>i</sup>*/*T* have analogous meanings as in the previous case. Several optical branches are again grouped into one degenerate multiple branch with the same Einstein characteristic temperature and anharmonicity coefficient. The phonon heat capacity then reads

Calorimetric Determination of Heat Capacity, Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 391

$$\mathbf{C\_{ph}} = \mathbf{C\_{phD}} + \sum\_{i=1}^{3n-3} \mathbf{C\_{phEi}} \tag{3}$$

All the estimated values were further treated by a simplex routine and a full non-linear fit was performed on all adjustable parameters.

Applications of Calorimetry in a Wide Context –

literature [41], the term 1/(1 –

described by the Einstein model

0

2

4

*C*

where 

reads

**pm/***T* **(mJ K-2 mol-1**

**)**

6

8

10

12

14

16

390 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

In the second step of the LT fit, both sets of the *Cp*m data (relaxation time + DSC) were considered. Analysis of the phonon heat capacity was performed as an additive combination of Debye and Einstein models. Both models include corrections for anharmonicity, which is responsible for a small, but not negligible, additive term at higher temperatures and which accounts for the difference between isobaric and isochoric heat capacity. According to

The acoustic part of the phonon heat capacity is described using the Debye model

where *R* is the gas constant, *Θ*D is the Debye characteristic temperature,

 RT-Exp 

el = 0.167 mJ K-2

D = 233.8 K

el + 1943.7

*T* ) is considered as a correction factor.

 *Θ* <sup>D</sup>

phD <sup>0</sup> <sup>2</sup> D D

of anharmonicity of acoustic branches and *x*D = *Θ*D/*T*. Here the three acoustic branches are taken as one triply degenerate branch. Similarly, the individual optical branches are

> x103 *T* 2 /<sup>D</sup> 3

mol-1

0 20 40 60 80 100

exp( )

*<sup>T</sup> <sup>x</sup>* (2)

*i i*

2 E E

*i i*

<sup>E</sup>*<sup>i</sup>* and *x*E*<sup>i</sup>* = *Θ*E*<sup>i</sup>*/*T* have analogous meanings as in the previous case. Several optical

phE 2 E E

branches are again grouped into one degenerate multiple branch with the same Einstein characteristic temperature and anharmonicity coefficient. The phonon heat capacity then

*<sup>R</sup> x x <sup>C</sup>*

exp( ) 1

*T* **2 (K 2 )**

**Figure 1.** Temperature dependence of *Cp*m/*T* function for CaNb2O7 at low temperatures

1 

*i*

3 4

(1)

D is the coefficient

<sup>9</sup> exp( ) <sup>d</sup> 1 exp( ) 1 *RT x x <sup>x</sup> C x T x*

The values of relative enthalpies at 298.15 K, *H*m(298.15) – *H*m(0), were evaluated from the low-temperature *Cp*m data (LT fit) by numerical integration of the *Cp*m(*T*) dependences from zero to 298.15 K. Standard deviations (2σ) were calculated using the error propagation law. The values of standard molar entropies at 298.15 K, *S*m(298.15), were derived from the lowtemperature *Cp*m data (LT fit) by numerical integration of the *Cp*m(*T*)/*T* dependences from zero to 298.15 K. A numerical integration was used with the boundary conditions *S*m = 0 and *Cp*m = 0 at *T* = 0 K. Standard deviations (2σ) were calculated using the error propagation law. All calculated values are summarized in Table 3.


**Table 3.** Heat capacity, relative enthalpy, entropy and entropy of formation from binary oxides at temperature 298.15 K of various mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5

392 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

A comparison is given in Table 4 of the values of entropy of formation from binary oxides Δox*S* at 298 K calculated from our results and those from literature. The values of Δox*S* are calculated using the relation

$$
\Delta\_{\text{ox}}S = S\_{\text{m}} \text{(MO)} - \sum\_{i} b\_{i} S\_{\text{m}} \text{(BO}\_{i}\text{i)}\tag{4}
$$

Calorimetric Determination of Heat Capacity,

(7)

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 393

<sup>2</sup> *C A BT C T <sup>p</sup>*<sup>m</sup> (5)

2

(8)

m m (MO) (BO, ) *<sup>p</sup> i p <sup>i</sup> <sup>C</sup> bC i* (9)

 <sup>0</sup> 2 2

**2.3. Evaluation of heat capacity at temperatures above 298 K** 

The sum of squares which is minimized has the following form

from LT fit were used as constraints and so Eq. (7) is modified

*C* of Eq. (4) for mixed oxides are presented in Table 5.

Neumann-Kopp's rule (NKR) is also plotted for comparison.

*N Cp*

dependence of *Cp*m was considered in the form

 

*N H*

For the assessment of temperature dependences of *Cp*m above room temperature, the heat capacity data from DSC and the enthalpy increment data from drop calorimetry were treated simultaneously by the linear least-squares method (HT fit). The temperature

thus the related temperature dependence of Δ*H*m(*T*) = *H*m(*T*) – *H*m(*T*0) is given by equation

m m m0 m <sup>0</sup> <sup>0</sup> <sup>0</sup> () () ( ) d 2 11 *<sup>T</sup> H T H T H T C T AT T BT T C T T <sup>T</sup> <sup>p</sup>* (6)

*i pi i i i*

where the first sum runs over the *Cp*m experimental points while the second sum runs over the Δ*H*m experimental points. Different weights *wi* (*wj*) were assigned to individual points calculated as *wi* = 1/δ*i* (*wj* = 1/δ*j*) where δ*i* (δ*j*) is the absolute deviation of the measurement estimated from overall accuracies of measurements (1 % for DSC and 3 % for drop calorimetry). Both types of experimental data thus gain comparable significance during the regression analysis. To smoothly connect the LT fit and HT fit data the values of *Cp*m(298.15)

constr <sup>m</sup>(298.15) 298.15 298.15 min *<sup>p</sup> F F C A BC*

The numerical values of parameters *A*, *B* and *C* are now obtained by solving a set of equations deduced as derivatives of *F*constr with respect of these parameters and a multiplier λ which are equal to zero at the minimum of *F*constr. Assessed values of parameters *A*, *B* and

As an example, the results of heat capacity measurements and relative enthalpy measurements on Bi7Ta3O18 [28] are shown in Fig. 2. Empirical estimation according to the

The empirical Neumann-Kopp's rule (NKR) is frequently used for estimation of unknown values of the heat capacity of mixed oxides [46–48]. According to NKR, heat capacity of a

mixed oxide is calculated as a sum of heat capacities of the constituent binary ones

<sup>2</sup> ( ) 2 2 m, <sup>1</sup>

<sup>2</sup> ( ) <sup>2</sup> 2 2 m, 0, 0, 0, <sup>1</sup> 2 1 1 min

*w H AT T BT T C T T*

*F w C A BT C T*

*j j jj j j j j j*

where *S*m(MO) and *S*m(BO,*i*) stand for the molar entropies of a mixed oxide and a binary oxide *i*, respectively, and *bi* is a constitution coefficient representing the number of formula units of a binary oxide *i* per formula unit of the mixed oxide. The following values were used for calculation: *S*m(CaO,298.15 K) = 38.1 J K–1 mol–1 [42], *S*m(SrO,298.15 K) = 53.58 J K–1 mol–1 [43], *S*m(Bi2O3,298.15 K) = 148.5 J K–1 mol–1 [44], *S*m(Nb2O5, 298.15) = 137.30 J K–1 mol–1 [45] *S*m(Ta2O5, 298.15) = 143.09 J K–1 mol–1 [45]. Furthermore, *S*m(Sr2Nb2O7, 298.15) = 238.5 J K–1 mol–1 from this work can be directly compared with the value 232.37 J K–1 mol–1 obtained by numeric integration of the *Cp*m(*T*)/*T* dependences from zero to 298.15 K given in Ref. [1]. It should be noted that the values of entropy assessed by thermodynamic optimization of phase equilibrium data are generally considered as less reliable as the values derived from low temperature heat capacity measurements. It is due to possible strong correlation between the enthalpy and entropy contributions to the Gibbs energy. So the obvious discrepancies between our values and data from assessments [12,19] could be explain in this way.


a) This work

**Table 4.** The values of entropy of formation from binary oxides at 298.15 K: a comparison of our results and data from literature

It should be noted that the thorough analysis of the Debye and Einstein contributions to the heat capacities reveals that the different vibrational modes contribute to the total values of Δox*S* to a different extent and partial compensation is possible in some cases.

#### **2.3. Evaluation of heat capacity at temperatures above 298 K**

Applications of Calorimetry in a Wide Context –

calculated using the relation

a) This work

and data from literature

392 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

our values and data from assessments [12,19] could be explain in this way.

(J K-1 mol–1)

CaNb2O6 –8.1 33.45 [7]

Ca2Nb2O7 –1.1 22.18 [11] Sr2Nb10O27 –34.0 –350.69 [12] SrNb2O6 –17.0 –58.65 [12] Sr2Nb2O7 –6.0 –39.93 [12] Sr5Nb4O14 –18.0 –51.01 [12] CaBi2O4 1.9 3.0 [19] Ca4Bi6O13 –23.8 8.0 [19] Ca2Bi2O5 6.6 3.0 [19] SrBi2O4 4.0 1.8 [19] Sr2Bi2O5 5.5 –24.0 [19]

**Table 4.** The values of entropy of formation from binary oxides at 298.15 K: a comparison of our results

It should be noted that the thorough analysis of the Debye and Einstein contributions to the heat capacities reveals that the different vibrational modes contribute to the total values of

Δox*S* to a different extent and partial compensation is possible in some cases.

Oxide Δox*S* a)

A comparison is given in Table 4 of the values of entropy of formation from binary oxides Δox*S* at 298 K calculated from our results and those from literature. The values of Δox*S* are

ox m *S S* (MO) (BO, ) *<sup>i</sup>*

where *S*m(MO) and *S*m(BO,*i*) stand for the molar entropies of a mixed oxide and a binary oxide *i*, respectively, and *bi* is a constitution coefficient representing the number of formula units of a binary oxide *i* per formula unit of the mixed oxide. The following values were used for calculation: *S*m(CaO,298.15 K) = 38.1 J K–1 mol–1 [42], *S*m(SrO,298.15 K) = 53.58 J K–1 mol–1 [43], *S*m(Bi2O3,298.15 K) = 148.5 J K–1 mol–1 [44], *S*m(Nb2O5, 298.15) = 137.30 J K–1 mol–1 [45] *S*m(Ta2O5, 298.15) = 143.09 J K–1 mol–1 [45]. Furthermore, *S*m(Sr2Nb2O7, 298.15) = 238.5 J K–1 mol–1 from this work can be directly compared with the value 232.37 J K–1 mol–1 obtained by numeric integration of the *Cp*m(*T*)/*T* dependences from zero to 298.15 K given in Ref. [1]. It should be noted that the values of entropy assessed by thermodynamic optimization of phase equilibrium data are generally considered as less reliable as the values derived from low temperature heat capacity measurements. It is due to possible strong correlation between the enthalpy and entropy contributions to the Gibbs energy. So the obvious discrepancies between

*bS i <sup>i</sup>* <sup>m</sup> (4)

Δox*S*

(J K-1 mol–1) Ref.

–22.59 [11]

For the assessment of temperature dependences of *Cp*m above room temperature, the heat capacity data from DSC and the enthalpy increment data from drop calorimetry were treated simultaneously by the linear least-squares method (HT fit). The temperature dependence of *Cp*m was considered in the form

$$\mathbf{C}\_{\text{pm}} = \mathbf{A} + \mathbf{B}\mathbf{T} + \mathbf{C}\mathbf{f}^{\prime}\mathbf{T}^{2} \tag{5}$$

thus the related temperature dependence of Δ*H*m(*T*) = *H*m(*T*) – *H*m(*T*0) is given by equation

$$
\Delta H\_{\rm m}(T) = H\_{\rm m}(T) - H\_{\rm m}(T\_0) = \int\_{T\_0}^{T} \mathbb{C}\_{\rm pm} \, \text{d}T = A \left( T - T\_0 \right) + B \left( T^2 - T\_0^2 \right) \Big/ 2 - \mathcal{C} \left( 1/T - 1/T\_0 \right) \tag{6}
$$

The sum of squares which is minimized has the following form

$$F = \sum\_{i=1}^{N(\mathcal{C}\_{\boldsymbol{\gamma}})} w\_i^2 \left[ \mathcal{C}\_{\text{pm},i} - A - B T\_i - \mathcal{C} \right/T\_i^2 \right]^2 + \tag{7}$$

$$+ \sum\_{j=1}^{N(\Delta H)} w\_j^2 \left[ \Delta H\_{\text{m},j} - A \left( T\_j - T\_{0,j} \right) - B \left( T\_j^2 - T\_{0,j}^2 \right) \right] \cdot 2 + \mathcal{C} \left( 1 \left| T\_j - 1 / T\_{0,j} \right| \right)^2 \to \min$$

where the first sum runs over the *Cp*m experimental points while the second sum runs over the Δ*H*m experimental points. Different weights *wi* (*wj*) were assigned to individual points calculated as *wi* = 1/δ*i* (*wj* = 1/δ*j*) where δ*i* (δ*j*) is the absolute deviation of the measurement estimated from overall accuracies of measurements (1 % for DSC and 3 % for drop calorimetry). Both types of experimental data thus gain comparable significance during the regression analysis. To smoothly connect the LT fit and HT fit data the values of *Cp*m(298.15) from LT fit were used as constraints and so Eq. (7) is modified

$$F\_{\text{constr}} = F - \lambda \left[ C\_{p\text{m}} \text{(298.15)} - A - 298.15B - C \Big/ 298.15^2 \right] \to \min \tag{8}$$

The numerical values of parameters *A*, *B* and *C* are now obtained by solving a set of equations deduced as derivatives of *F*constr with respect of these parameters and a multiplier λ which are equal to zero at the minimum of *F*constr. Assessed values of parameters *A*, *B* and *C* of Eq. (4) for mixed oxides are presented in Table 5.

As an example, the results of heat capacity measurements and relative enthalpy measurements on Bi7Ta3O18 [28] are shown in Fig. 2. Empirical estimation according to the Neumann-Kopp's rule (NKR) is also plotted for comparison.

The empirical Neumann-Kopp's rule (NKR) is frequently used for estimation of unknown values of the heat capacity of mixed oxides [46–48]. According to NKR, heat capacity of a mixed oxide is calculated as a sum of heat capacities of the constituent binary ones

$$\mathcal{C}\_{\rm pm} \text{(MO)} = \sum\_{i} b\_{i} \mathcal{C}\_{\rm pm} \text{(BO} \, i \text{)}\tag{9}$$

It was concluded [47,48] that NKR predicts the heat capacities of mixed oxides remarkably well around room temperature but the deviations (mostly positive) from NKR become substantial at higher temperatures. Mean relative error of the estimated values of *Cp*m(298.15 K) is 1.4 %. Calculated temperature dependences of Δox*Cp*m = *Cp*m(MO) – *biCp*m(BO,*i*) for various mixed oxides in the systems CaO–Nb2O5, SrO–Nb2O5 and Bi2O3– Ta2O5 are shown in Fig. 3.

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 395

 RT-Exp DSC-Exp #1 DSC-Exp #2 LT Fit HT Fit NKR

> Drop-Exp HT Fit NKR

0 200 400 600 800 1000 1200 1400

*T* **(K)**

600 800 1000 1200 1400

*T* **(K)**

**Figure 2.** Temperature dependence of heat capacity (a) and relative enthalpy (b) of Bi7Ta3O18 (3*NR*

0

200

means the Dulong-Petit limit).

300

400

*H***m(***T* **)-**

*H***m(298) (kJ mol-1**

**)**

500

600

700

200

*C*

**pm (J.mol-1.K-1**

**)**

400

600

3*NR*

<sup>800</sup> (a)

<sup>800</sup> (b)


a) An extra term 1.363108/*T*3 was added.

b) An extra term 2.360108/*T*3 was added.

**Table 5.** Parameters of temperature dependence of molar heat capacities of various mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5

Ta2O5 are shown in Fig. 3.

a) An extra term 1.363108/*T*3 was added. b) An extra term 2.360108/*T*3 was added.

system CaO–SrO–Bi2O3–Nb2O5–Ta2O5

Oxide

394 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*Cp*m = *A* + *B*

A 103 B 10–6 C

CaBi2O4 157.161 38.750 –1.546 298-1000 [20] Ca4Bi6O13 550.808 114.890 –7.201 298-1200 [20] Ca2Bi2O5 226.096 33.374 –3.432 298-1100 [20] SrBi2O4 161.97 45.936 –1.7832 298–1100 [29] Sr2Bi2O5 197.48 87.463 –1.9282 298–1200 [29] CaNb2O6 200.40 34.32 –3.45 298-1500 [26] Ca2Nb2O7 257.20 36.21 –4.435 298-1400 [26] SrNb2O6 200.47 29.37 –3.473 298-1500 [24] Sr2Nb2O7 248.00 43.50 –3.948 298-1400 [26] Sr2Nb10O27 835.351 227.648 –13.904 298-1400 [27] Sr5Nb4O15 504.796 147.981 –6.376 298-1400 [27] BiNbO4 a) 128.628 33.400 –1.991 150-1200 [21] BiNb5O14 455.840 60.160 –7.734 298-1400 [23] BiTaO4 b) 133.594 25.390 –2.734 150-1200 [21] Bi4Ta2O11 445.8 5.451 –7.489 298–1400 [28] Bi7Ta3O18 699.0 52.762 –9.956 298–1400 [28] Bi3TaO7 251.6 67.05 –3.237 298–1400 [28] SrBi2Nb2O9 324.470 63.710 –5.076 298-1400 [22] SrBi2Ta2O9 320.220 64.510 –4.700 298-1400 [22]

**Table 5.** Parameters of temperature dependence of molar heat capacities of various mixed oxides in the

It was concluded [47,48] that NKR predicts the heat capacities of mixed oxides remarkably well around room temperature but the deviations (mostly positive) from NKR become substantial at higher temperatures. Mean relative error of the estimated values of *Cp*m(298.15 K) is 1.4 %. Calculated temperature dependences of Δox*Cp*m = *Cp*m(MO) – *biCp*m(BO,*i*) for various mixed oxides in the systems CaO–Nb2O5, SrO–Nb2O5 and Bi2O3–

*T* + *C*/*T* 2 (J K–1 mol–1) Temperature

range (K) Ref.

**Figure 2.** Temperature dependence of heat capacity (a) and relative enthalpy (b) of Bi7Ta3O18 (3*NR* means the Dulong-Petit limit).

396 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

#### **2.4. Evaluation of enthalpy of formation**

The heats of drop-solution for the calcium and strontium carbonates and for the bismuth and niobium oxides were measured first. These data are necessary for the evaluation of the Δox*H* values for the mixed oxides, and furthermore, these data could be compared with the literature data [49–52]. For the AECO3 carbonates, the measured heat effect consists of three contributions:

$$
\Delta\_{\text{ds}}H\text{(AECO}\_3, T) = \Delta\_T H\text{(AECO}\_3, T\_0 \to T) + \Delta\_{\text{decomp}}H\text{(AECO}\_3, T) + \Delta\_{\text{sol}}H\text{(AECO}, T) \tag{10}
$$

The measurements were performed at 973 K. The values of Δds*H*(AECO3, 973 K) are given in Table 6 along with the values of Δds*H*(AEO, 973 K), which were derived based on the following thermochemical cycle (*T*<sup>0</sup> 298 K):

$$\text{AECO}\_3(\text{s}\_7\text{I}\_0) \quad \rightarrow \quad \text{AECO}(\text{melt}, T) + \text{CO}\_2(\text{g}\_7T), \qquad \Delta\_{\text{ds}}H(\text{AECO}\_3) \tag{11}$$

$$\text{AECO}\_3(\text{s}\_7T\_0) \quad \rightarrow \quad \text{AFeO}(\text{s}\_7T\_0) + \text{CO}\_2(\text{g}\,T\_0), \qquad \Delta\_{\text{decomp}}H(\text{AECO}\_3) \tag{12}$$

$$\text{CO}\_2(\text{g}\_7\text{T}\_0) \quad \rightarrow \quad \text{CO}\_2(\text{g}\_7\text{T}), \qquad \Delta\_T H(\text{CO}\_2) \tag{13}$$

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 397

300 500 700 900 1100 1300

*T* **(K)**

(b)

300 500 700 900 1100 1300

*T* **(K)**

**Figure 3.** Temperature dependences of Δox*Cp*m for various mixed oxides in the systems CaO–Nb2O5, and



SrO–Nb2O5 (a) and Bi2O3–Ta2O5 (b)



0

*Cp* **(%)**

**ox**

2

4

6

8

10


0

2

*Cp* **(%)**

**ox**

4

6

8

10

<sup>12</sup> (a)

 CaNb2 O6

 SrNb2 O6

 Ca2 Nb2 O7

 Sr2 Nb2 O7

 Sr2 Nb10O27

 Sr5 Nb4 O15

 BiTaO4 Bi4 Ta2 O11

 Bi7 Ta3 O18

 Bi3 TaO7

$$\text{AEO(s/}T\_0\text{)} \rightarrow \text{ AEO(melt/}T\text{)}\prime \qquad \Delta\_{\text{ds}}H\text{(AEO)}\tag{14}$$

$$
\Delta\_{\rm ds}H(\rm AFeO) = \Delta\_{\rm ds}H(\rm AECO\_3) - \Delta\_{\rm decomposition}H(\rm AECO\_3) - \Delta\_{\rm T}H(\rm CO\_2) \tag{15}
$$

The values Δdecomp*H*(CaCO3, 298 K) = 178.8 kJ mol–1, Δdecomp*H*(SrCO3, 298 K) = 233.9 kJ mol–1 and Δ*TH*(CO2, 298 → 973 K) = 32.0 kJ mol–1 [53] were used for the calculations.

Next, the Δds*H* values of the binary oxides Bi2O3 and Nb2O5 were measured. Because the dissolution of Nb2O5 and of the mixed oxides at 973 K proceeds rather slowly, the higher temperature of 1073 K was used. The measured values Δds*H* are also given in Table 6.

The experimental values of Δds*H* for SrCO3 and CaCO3 are in quite good agreement with the literature data [49–51]. On the other hand, our results and the published [52] values of Δds*H*(Nb2O5) are quite different. It should be noted that a more endothermic value Δdecomp*H*(SrCO3, 298 K) = 249.4 kJ mol–1 is presented in the literature [45], which results in more exothermic value for Δds*H*(SrO) by 15.5 kJ mol–1.

Δds*H* for the mixed oxides was measured at 1073 K. The following thermochemical cycle was used for the calculation of Δox*H* for calcium and strontium niobates (*T*<sup>0</sup> 298 K):

$$\text{AE}\_{\text{x}}\text{Nb}\_{2}\text{O}\_{5\text{+x}}(\text{s}/T\_{0}) \quad \rightarrow \quad \text{x} \\ \text{AEO(melt},T) + \text{Nb}\_{2}\text{O}\_{5}(\text{melt},T), \qquad \Lambda\_{\text{ds}}H(\text{AEO}) \tag{16}$$

$$\text{AEO(s/}T\_0) \quad \rightarrow \quad \text{AEO(melt/}T) \quad \quad \quad \Lambda\_{\text{ds}}H \text{(AEO)} \tag{17}$$

$$\text{Nb}\_2\text{O}\_5(\text{s}\_\prime T\_0) \quad \rightarrow \quad \text{Nb}\_2\text{O}\_5(\text{melt}, T)\_\prime \qquad \Lambda\_{\text{ds}}H(\text{Nb}\_2\text{O}\_5) \tag{18}$$

$$\text{xAEO(s}\_{\prime}T\_{0}) + \text{Nb}\_{2}\text{O}\_{5}(\text{s}\_{\prime}T\_{0}) \quad \rightarrow \text{ AE}\_{\text{x}}\text{Nb}\_{2}\text{O}\_{5\text{+x}}(\text{s}\_{\prime}T\_{0}) \quad \quad \Delta\_{\text{ox}}H \text{(AE}\_{\text{x}}\text{Nb}\_{2}\text{O}\_{5\text{+x}}\text{)}\tag{19}$$

contributions:

**2.4. Evaluation of enthalpy of formation** 

following thermochemical cycle (*T*<sup>0</sup> 298 K):

396 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The heats of drop-solution for the calcium and strontium carbonates and for the bismuth and niobium oxides were measured first. These data are necessary for the evaluation of the Δox*H* values for the mixed oxides, and furthermore, these data could be compared with the literature data [49–52]. For the AECO3 carbonates, the measured heat effect consists of three

ds AECO , AECO , <sup>3</sup> 3 0 decomp AECO , 3 sol AEO, *H T H TT H T H T <sup>T</sup>* (10)

AECO (s, ) AEO(melt, ) + CO ( 3 0 <sup>2</sup> g ds <sup>3</sup> *T T TH* , ), (AECO ) (11)

AECO (s, ) AEO(s, ) + CO ( 3 0 0 2 0 decomp g <sup>3</sup> *T TT H* , ), (AECO ) (12)

ds ds 3 decomp <sup>3</sup> <sup>2</sup> (AEO) (AECO ) (AECO ) (CO ) *HH H HT* (15)

CO ( 20 2 g <sup>2</sup> , ) CO (g, ), (CO ) *T THT* (13)

AEO(s, ) AEO(melt, ), (AEO) *T TH* <sup>0</sup> ds (14)

The measurements were performed at 973 K. The values of Δds*H*(AECO3, 973 K) are given in Table 6 along with the values of Δds*H*(AEO, 973 K), which were derived based on the

The values Δdecomp*H*(CaCO3, 298 K) = 178.8 kJ mol–1, Δdecomp*H*(SrCO3, 298 K) = 233.9 kJ mol–1

Next, the Δds*H* values of the binary oxides Bi2O3 and Nb2O5 were measured. Because the dissolution of Nb2O5 and of the mixed oxides at 973 K proceeds rather slowly, the higher

The experimental values of Δds*H* for SrCO3 and CaCO3 are in quite good agreement with the literature data [49–51]. On the other hand, our results and the published [52] values of Δds*H*(Nb2O5) are quite different. It should be noted that a more endothermic value Δdecomp*H*(SrCO3, 298 K) = 249.4 kJ mol–1 is presented in the literature [45], which results in

Δds*H* for the mixed oxides was measured at 1073 K. The following thermochemical cycle was

AE Nb O (s, ) AEO(melt, ) + Nb O (melt, ), (AEO) *x x* 25 0 *Tx T T H* 2 5 ds (16)

AEO(s, ) + Nb O (s, ) AE Nb O (s, ), (AE Nb O ) 0 25 0 *x x* 2 5 0 ox 2 5 *x x xT T T H* (19)

AEO(s, ) AEO(melt, ), (AEO) *T TH* <sup>0</sup> ds (17)

Nb O (s, ) Nb O (melt, ), (Nb O ) 25 0 *T* 2 5 *T H*ds 2 5 (18)

used for the calculation of Δox*H* for calcium and strontium niobates (*T*<sup>0</sup> 298 K):

temperature of 1073 K was used. The measured values Δds*H* are also given in Table 6.

and Δ*TH*(CO2, 298 → 973 K) = 32.0 kJ mol–1 [53] were used for the calculations.

more exothermic value for Δds*H*(SrO) by 15.5 kJ mol–1.

**Figure 3.** Temperature dependences of Δox*Cp*m for various mixed oxides in the systems CaO–Nb2O5, and SrO–Nb2O5 (a) and Bi2O3–Ta2O5 (b)

398 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

$$
\Delta\_{\text{ox}}H(\text{AE}\_{\text{x}}\text{Nb}\_{2}\text{O}\_{5+x}) = \text{x}\Delta\_{\text{ds}}H(\text{AEO}) + \Delta\_{\text{ds}}H(\text{Nb}\_{2}\text{O}\_{5}) - \Delta\_{\text{ds}}H(\text{AE}\_{\text{x}}\text{Nb}\_{2}\text{O}\_{5+x}) \tag{20}
$$

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 399

1 1 3 1 <sup>m</sup> f.u. *S V* (JK mol ) 1680.5 (nm f.u. ) (21)

(22)

Nb Me Nb Me

Our values for the calcium niobates are in good agreement with Raghavan's data [7,8], while the data from Dneprova et al. [11] are quite different. Moreover, a relation, Δox*H*(CaNb2O6) > Δox*H*(Ca2Nb2O7), that holds for the values from the work of Dneprova et al. is rather unexpected. The Δox*H* values for strontium niobates obtained based on the binary SrO-Nb2O5 phase diagram evaluation [12] are substantially more exothermic than our calorimetric data. These large differences in the Δox*H* values are not surprising in view of simultaneous differences in the Δox*S* values from the assessment [12] and those derived from low temperature dependences of the molar heat capacity of SrNb2O6 and Sr2Nb2O7 [24,26].

A linear correlation between the standard molar entropy at 298.15 K and the formula unit volume *V*f.u has been proposed by Jenkins and Glaser [54–56]. This approach was used in this work for mixed oxides in the CaO–SrO–Bi2O3–Nb2O5–Ta2O5 system. The linear relation

The average relative error in entropy is 8.2 %, the binary oxides CaO and Nb2O5 show the deviations around 20 %. It should be noted that, in this set of values, the simple analogy of NKR (Eq.(9)) provides a better prediction with an average relative error in entropy of

Eq. (21) can be used for estimation of missing data. So, the estimated value *S*m(Sr2Ta2O7) = 256.06 J K–1 mol–1 can be compared with the value 245.41 J K–1 mol–1 obtained by numeric integration of the *Cp*m(*T*)/*T* dependences from zero to 298.15 K given in Ref. [1] (relative deviation of –4.3 %). Simple calculation *S*m(Sr2Ta2O5) = 2*S*m(SrO) + *S*m(Ta2O5) = 250.25 J K–1

There are other mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5 for which the values of enthalpy of formation Δf*H* or enthalpy of formation from binary oxides Δox*H* have not yet been determined. As a rough estimate, the values of Δox*H* calculated according to an empirical method proposed by the authors [56] can be used. In the case of Ca, Sr and Bi

2 96.5 *<sup>H</sup> yx x X X*

where *X*Nb and *X*Me (Me = Ca, Sr or Bi) are Pauling's electronegativities of the relevant elements, *x*Nb and *x*Me are the molar fractions of the oxide-forming elements (*x*Nb = *n*Nb/(*n*Nb + *n*Me) etc.), *y* is the number of oxygen atoms per one atom of oxide-forming elements and

 ox 2

mol–1 gives more reliable value (relative deviation 2.0 %).

niobates the following relation holds for Δox*H*:

**4. Empirical estimation of enthalpy of formation** 

Nb Me

*n n*

is obvious (see Fig. 4) and the straight line almost naturally passes through the origin:

**3. Empirical correlation** *S***–***V*

4.2 %.

An analogous scheme was applied to calculate Δox*H*(BiNbO4). All of the experimental and calculated values are summarized in Table 7. The Δox*H*(298 K) values derived from hightemperature EMN measurements [7,8,11] for the CaO-Nb2O5 oxides and the assessed values from the phase diagram for the SrO-Nb2O5 oxides [12] are also presented in Table 7.


a) Data from the present work. The uncertainty is two standard deviations of the mean (95% confidence level), the number in parentheses is the number of experiments performed, b) From ref. [49], *T* = 976 K, c) The value Δ*TH*(CaO, 973 → 1073 K) = 5.35 kJ mol–1 [26] was used for the calculation, d) From ref. [50], *T* = 975 K, e) From ref. [51], *T* = 974 K, f) The value Δ*TH*(SrO, 973 → 1073 K) = 5.35 kJ mol–1 [27] was used for the calculation, g) The value Δ*TH*(Bi2O3, 973 → 1073 K) = 13.61 kJ mol–1 [28] was used for the calculation, h) From ref. [52], *T* = 973 K.

**Table 6.** Enthalpy of drop-solution in 3Na2O + 4MoO3 melts [30]


a) Data from the present work. The uncertainty is two standard deviations of the mean (95% confidence level), the number in parentheses is the number of experiments performed, b) The experimental data from the present work. The uncertainty was calculated according to the error propagation law, c) From ref. [11], d) From ref. [7], e) From ref. [8], f) From ref. [12].

**Table 7.** Enthalpies of drop-solution in 3Na2O + 4MoO3 melt (Δds*H*) and enthalpy of formation from constituent binary oxides (Δox*H*) [30]

Our values for the calcium niobates are in good agreement with Raghavan's data [7,8], while the data from Dneprova et al. [11] are quite different. Moreover, a relation, Δox*H*(CaNb2O6) > Δox*H*(Ca2Nb2O7), that holds for the values from the work of Dneprova et al. is rather unexpected. The Δox*H* values for strontium niobates obtained based on the binary SrO-Nb2O5 phase diagram evaluation [12] are substantially more exothermic than our calorimetric data. These large differences in the Δox*H* values are not surprising in view of simultaneous differences in the Δox*S* values from the assessment [12] and those derived from low temperature dependences of the molar heat capacity of SrNb2O6 and Sr2Nb2O7 [24,26].

### **3. Empirical correlation** *S***–***V*

Applications of Calorimetry in a Wide Context –

398 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

CaO 1073 –77.04 c)

SrO 1073 –129.25 f) Bi2O3 973 26.0 ± 2.9 (12) Bi2O3 1073 39.6 g)

**Table 6.** Enthalpy of drop-solution in 3Na2O + 4MoO3 melts [30]

Substance *T* (K) Δds*H* (kJ mol–1) a) Δox*H*(298 K)

BiNbO4 1073 132.61 ± 8.9 (7) –41.9 ± 11.1

f) From ref. [12].

constituent binary oxides (Δox*H*) [30]

ox 2 5 ds ds 2 5 ds 2 5 (AE Nb O ) (AEO) + (Nb O ) (AE Nb O ) *H x x x x xH H H* (20)

An analogous scheme was applied to calculate Δox*H*(BiNbO4). All of the experimental and calculated values are summarized in Table 7. The Δox*H*(298 K) values derived from hightemperature EMN measurements [7,8,11] for the CaO-Nb2O5 oxides and the assessed values

from the phase diagram for the SrO-Nb2O5 oxides [12] are also presented in Table 7.

Substance *T* (K) Δds*H* (kJ mol–1) a) Δds*H* (kJ mol–1) CaCO3 973 128.4 ± 10.1 (10) 119.70 ± 1.02 b) CaO 973 –82.39 –90.70 ± 1.69 b)

SrCO3 973 131.4 ± 9.1 (7) 130.16 ± 1.66 d)

SrO 973 –134.47 –135.82 ± 2.48 d)

Nb2O5 1073 141.8 ± 6.0 (11) 91.97 ± 0.78 h) a) Data from the present work. The uncertainty is two standard deviations of the mean (95% confidence level), the number in parentheses is the number of experiments performed, b) From ref. [49], *T* = 976 K, c) The value

Δ*TH*(CaO, 973 → 1073 K) = 5.35 kJ mol–1 [26] was used for the calculation, d) From ref. [50], *T* = 975 K, e) From ref. [51], *T*

CaNb2O6 1073 196.8 ± 20.7 (8) –132.0 ± 23.8 –159.8 c)

Ca2Nb2O7 1073 195.7 ± 27.8 (8) –208.0 ± 31.9 –147.3 c)

SrNb2O6 1073 180.50 ± 15.7 (4) –167.9 ± 19.1 –325.0 f) Sr2Nb2O7 1073 167.54 ± 34.7 (4) –289.2 ± 37.5 –367.4 f)

a) Data from the present work. The uncertainty is two standard deviations of the mean (95% confidence level), the number in parentheses is the number of experiments performed, b) The experimental data from the present work. The uncertainty was calculated according to the error propagation law, c) From ref. [11], d) From ref. [7], e) From ref. [8],

**Table 7.** Enthalpies of drop-solution in 3Na2O + 4MoO3 melt (Δds*H*) and enthalpy of formation from

(kJ mol–1) b)

= 974 K, f) The value Δ*TH*(SrO, 973 → 1073 K) = 5.35 kJ mol–1 [27] was used for the calculation, g) The value Δ*TH*(Bi2O3, 973 → 1073 K) = 13.61 kJ mol–1 [28] was used for the calculation, h) From ref. [52], *T* = 973 K.

134.48 ± 1.89 e)

–131.42 ± 1.89 e)

Δox*H* (298 K) (kJ mol–1)

–130.1 d)

–177.5 e)

A linear correlation between the standard molar entropy at 298.15 K and the formula unit volume *V*f.u has been proposed by Jenkins and Glaser [54–56]. This approach was used in this work for mixed oxides in the CaO–SrO–Bi2O3–Nb2O5–Ta2O5 system. The linear relation is obvious (see Fig. 4) and the straight line almost naturally passes through the origin:

$$\text{S}\_{\text{m}} \text{(J K}^{-1} \text{mol}^{-1}) = 1680.5 \,\text{V}\_{\text{f.u.}} \text{(nm}^3 \text{f.u.}^{-1}) \tag{21}$$

The average relative error in entropy is 8.2 %, the binary oxides CaO and Nb2O5 show the deviations around 20 %. It should be noted that, in this set of values, the simple analogy of NKR (Eq.(9)) provides a better prediction with an average relative error in entropy of 4.2 %.

Eq. (21) can be used for estimation of missing data. So, the estimated value *S*m(Sr2Ta2O7) = 256.06 J K–1 mol–1 can be compared with the value 245.41 J K–1 mol–1 obtained by numeric integration of the *Cp*m(*T*)/*T* dependences from zero to 298.15 K given in Ref. [1] (relative deviation of –4.3 %). Simple calculation *S*m(Sr2Ta2O5) = 2*S*m(SrO) + *S*m(Ta2O5) = 250.25 J K–1 mol–1 gives more reliable value (relative deviation 2.0 %).

### **4. Empirical estimation of enthalpy of formation**

There are other mixed oxides in the system CaO–SrO–Bi2O3–Nb2O5–Ta2O5 for which the values of enthalpy of formation Δf*H* or enthalpy of formation from binary oxides Δox*H* have not yet been determined. As a rough estimate, the values of Δox*H* calculated according to an empirical method proposed by the authors [56] can be used. In the case of Ca, Sr and Bi niobates the following relation holds for Δox*H*:

$$\frac{\Delta\_{\rm ox}H}{n\_{\rm Nb} + n\_{\rm Me}} = -2 \cdot 96.5 \alpha y \,\text{x}\_{\rm Nb} \,\text{x}\_{\rm Me}^{\delta} \left(X\_{\rm Nb} - X\_{\rm Me}\right)^2\tag{22}$$

where *X*Nb and *X*Me (Me = Ca, Sr or Bi) are Pauling's electronegativities of the relevant elements, *x*Nb and *x*Me are the molar fractions of the oxide-forming elements (*x*Nb = *n*Nb/(*n*Nb + *n*Me) etc.), *y* is the number of oxygen atoms per one atom of oxide-forming elements and 

#### Applications of Calorimetry in a Wide Context – 400 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and *δ* are the model parameters. Using Pauling's electronegativities, *X*Nb = 1.60, *X*Ca = 1.00, *X*Sr = 0.95, and *X*Bi = 2.02, and the calorimetric values of Δox*H* obtained in this work, the values of = 2.576 and *δ* = 1.50 were derived from the least-squares fit. The estimated Δox*H* values for calcium and strontium niobates are shown in Fig. 5. The values of Δox*H* that were calculated according to an empirical method proposed by Zhuang et al. [57] are displayed for comparison.

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 401

0.0 0.2 0.4 0.6 0.8 1.0

 [30] (exp) [30] (estim)

 Zhuang et al. [57] (estim) Dneprova et al. [11] (EMF) Raghavan [7,8] (EMF)

*x*(Nb)

0.0 0.2 0.4 0.6 0.8 1.0

*x*(Nb)

**Figure 5.** Values of enthalpy of formation of the mixed oxides from constituent binary oxides in the




*H* (kJ/mol(Sr+Nb))

ox






*H* (kJ/mol(Ca+Nb))

ox





<sup>0</sup> (a)

<sup>0</sup> (b)

 [30] (exp) [30] (estim)

 Zhuang et al. [57] (estim) Yang et al. [12] (assessed)

CaO–Nb2O5 (a) and SrO–Nb2O5 (b) systems (lines serve only as a guide for the eyes)

**Figure 4.** Correlation between the standard molar entropy at 298.15 K and the formula unit volume *V*f.u. for various mixed oxides in the system CaO–SrO– Bi2O3–Nb2O5–Ta2O5 (data from table Table 3)

### **5. Conclusion**

The above presented data derived from calorimetric measurements became the basis for thermodynamic database FS-FEROX [58] compatible with the FactSage software [59,60]. Missing data for other stoichiometric mixed oxides were estimated by the empirical methods described before: the Neumann-Kopp's rule for heat capacities, the entropyvolume correlation for molar entropies and electronegativity-differences method for enthalpies of formation. At the same time, thermodynamic description of a multicomponent oxide melt was obtained analyzing relevant binary phase diagrams published in literature. The database and the FactSage software were subsequently used for various equilibrium calculations including binary *T-x* phase diagrams and ternary phase diagrams in subsolidus region. Thermodynamic modeling of SrBi2Ta2O9 and SrBi2Nb2O9 thin layers deposition from the gaseous phase were also performed to optimize the deposition conditions.

0

100

200

*S*

**5. Conclusion** 

**m (J mol-1 K-1**

**)**

300

400

500

600

700

800

values of

for comparison.

400 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and *δ* are the model parameters. Using Pauling's electronegativities, *X*Nb = 1.60, *X*Ca = 1.00, *X*Sr = 0.95, and *X*Bi = 2.02, and the calorimetric values of Δox*H* obtained in this work, the

values for calcium and strontium niobates are shown in Fig. 5. The values of Δox*H* that were calculated according to an empirical method proposed by Zhuang et al. [57] are displayed

> Binary oxides - reference data Mixed oxides - calorimetric values

Calculated

0.0 0.1 0.2 0.3 0.4 0.5

 **f.u.-1 )**

*<sup>V</sup>***f.u. (nm3**

**Figure 4.** Correlation between the standard molar entropy at 298.15 K and the formula unit volume *V*f.u. for various mixed oxides in the system CaO–SrO– Bi2O3–Nb2O5–Ta2O5 (data from table Table 3)

The above presented data derived from calorimetric measurements became the basis for thermodynamic database FS-FEROX [58] compatible with the FactSage software [59,60]. Missing data for other stoichiometric mixed oxides were estimated by the empirical methods described before: the Neumann-Kopp's rule for heat capacities, the entropyvolume correlation for molar entropies and electronegativity-differences method for enthalpies of formation. At the same time, thermodynamic description of a multicomponent oxide melt was obtained analyzing relevant binary phase diagrams published in literature. The database and the FactSage software were subsequently used for various equilibrium calculations including binary *T-x* phase diagrams and ternary phase diagrams in subsolidus region. Thermodynamic modeling of SrBi2Ta2O9 and SrBi2Nb2O9 thin layers deposition from

the gaseous phase were also performed to optimize the deposition conditions.

*S*m = 1680.5 *V*f.u.

= 0.985

*R*2

= 2.576 and *δ* = 1.50 were derived from the least-squares fit. The estimated Δox*H*

**Figure 5.** Values of enthalpy of formation of the mixed oxides from constituent binary oxides in the CaO–Nb2O5 (a) and SrO–Nb2O5 (b) systems (lines serve only as a guide for the eyes)

Applications of Calorimetry in a Wide Context – 402 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

### **Author details**

Jindřich Leitner, David Sedmidubský and Květoslav Růžička *Institute of Chemical Technology, Prague, Czech Republic* 

Pavel Svoboda

*Charles University in Prague, Faculty of Mathematics and Physics, Prague, Czech Republic* 

### **Acknowledgment**

This work was supported by the Ministry of Education of the Czech Republic (research projects N° MSM6046137302 and N° MSM6046137307). Part of this work was also supported from the Grant Agency of the Czech Republic, grant No P108/10/1006. Low temperature experiments were performed in MLTL (http://mltl.eu/), which is supported within the program of Czech Research Infrastructures (project no. LM2011025).

Calorimetric Determination of Heat Capacity,

Entropy and Enthalpy of Mixed Oxides in the System CaO–SrO–Bi2O3–Nb2O5–Ta2O5 403

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SiO2 system. CALPHAD 14: 71–88.

samples. Eur. J. Mineral. 17: 251–259.

404 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

entropy of SrBi2O4 and Sr2Bi2O5. Thermochim. Acta. 531: 60–65.

relaxation calorimetry. Rev. Sci. Instrum. 77: 096108 (3 pp).

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measurement system. Cryogenics 47: 107–112.

neutron powder diffraction. Physica B 192: 55–69.

[28] Leitner J, Jakeš V, Sofer Z, Sedmidubský D, Růžička K, Svoboda P (2011) Heat capacity, enthalpy and entropy of ternary bismuth tantalum oxides. J. Solid State Chem. 184: 241–

[29] Leitner J, Sedmidubský D, Růžička K, Svoboda P (2012) Heat capacity, enthalpy and

[30] Leitner J, Nevřiva M, Sedmidubský D, Voňka P (2011) Enthalpy of formation of selected mixed oxides in a CaO–SrO–Bi2O3–Nb2O5 system. J. Alloys Compd. 509: 4940–

[31] Lashley J.C., Hundley MF, Migliori A, Sarrao JL, Pagliuso PG, Darling TW, Jaime M, Cooley JC, Hults WL, Morales L, Thoma DJ, Smith JL, Boerio-Goates J, Woodward BF, Stewart GR, Fisher RA, Phillips NE (2003) Critical examination of heat capacity measurements made on a Quantum Design physical property measurement system.

[32] Dachs E, Bertoldi C (2005) Precision and accuracy of the heat-pulse calorimetric technique: low-temperature heat capacities of milligram-sized synthetic mineral

[33] Marriott RA, Stancescu M, Kennedy CA, White MA (2006) Technique for determination of accurate heat capacities of volatile, powdered, or air-sensitive samples using

[34] Kennedy CA, Stancescu M, Marriott RA, White MA (2007) Recommendations for accurate heat capacity measurements using a Quantum Design physical property

[35] Shi Q, Snow CL, Boerio-Goates J, Woodfield BF (2010) Accurate heat capacity measurements on powdered samples using a Quantum Design physical property

[36] Hwang JS, Lin KJ, Tien C (1997) Measurement of heat capacity by fitting the whole temperature response of a heat-pulse calorimeter. Rev. Sci. Instrum. 68: 94–101. [37] Schnelle W, Engelhardt J, Gmelin E (1999) Specific heat capacity of Apiezon N high

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[42] Taylor JR, Dinsdale AT (1990) Thermodynamic and phase diagram data for the CaO-

vacuum grease and of Duran borosilicate glass. Cryogenics 39: 271–275.


406 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

[59] Bale CW, Chartrand P, Degterov SA, Eriksson G, Hack K, Ben Mahfoud R, Melançon J, Pelton AD, Petersen S (2002) FactSage thermochemical software and databases. Calphad 26: 189-228.

**Chapter 18** 

© 2013 Smith and Dea, 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,

**Differential Scanning Calorimetry** 

**The Interdigitated Gel Phase** 

Additional information is available at the end of the chapter

chemicals that can induce or inhibit lipid interdigitation.

Eric A. Smith and Phoebe K. Dea

http://dx.doi.org/10.5772/51882

**1. Introduction** 

**Studies of Phospholipid Membranes:** 

DSC is a versatile technique and has been used for decades to study hydrated phospholipid membranes [1-4]. It can even be used to analyze whole cell samples [5]. For pure lipids, DSC can accurately determine the phase transition temperatures and the associated enthalpies. As a consequence, how the chemical structure of lipids translates into thermodynamic properties can be systematically studied. In addition to determining the physical properties of pure lipids, the miscibility and phase behavior of lipid mixtures can be determined.

The detailed review of the interdigitated phase written by Slater and Huang in 1988 provides an excellent outline of the properties of the interdigitated phase and the relevant analytical techniques [6]. Furthermore, the meticulous studies of Koynova and Caffrey describe how systematic changes in lipid chemistry can affect their phase behavior [7-9]. Lipids with asymmetrical acyl chains that form either mixed- or partially-interdigitated phases have also been thoroughly investigated [7,10-12]. This review focuses on the interdigitated phase of fully hydrated phospholipids with hydrocarbon chain lengths of equal size. We pay special attention to recently discovered interdigitated systems and the

For simplicity, we have centered our review around the extensively studied lipid, 1,2 dipalmitoyl-*sn*-glycero-3-phosphocholine (DPPC). DPPC is naturally occurring and has thermodynamic phase behavior that is typical for saturated phosphatidylcholines (PCs) [7]. Although DPPC does not spontaneously interdigitate when hydrated, it can be reliably transformed into the fully interdigitated gel phase (Tables 1 and 2). Alterations in the lipid hydrocarbon chains (Figure 1) and the lipid head group (Figure 2) substantially affect spontaneous interdigitation (Figure 3). The predisposition for interdigitation is a finely

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

[60] Bale CW, Bélisle E, Chartrand P, Decterov SA, Eriksson G, Hack K, Jung IH, Kang YB, Melançon J, Pelton AD, Robelin C, Petersen S (2009) FactSage thermochemical software and databases — recent developments. Calphad 33: 295-311.

## **Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase**

Eric A. Smith and Phoebe K. Dea

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/51882

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

Calphad 26: 189-228.

406 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

and databases — recent developments. Calphad 33: 295-311.

[59] Bale CW, Chartrand P, Degterov SA, Eriksson G, Hack K, Ben Mahfoud R, Melançon J, Pelton AD, Petersen S (2002) FactSage thermochemical software and databases.

[60] Bale CW, Bélisle E, Chartrand P, Decterov SA, Eriksson G, Hack K, Jung IH, Kang YB, Melançon J, Pelton AD, Robelin C, Petersen S (2009) FactSage thermochemical software

> DSC is a versatile technique and has been used for decades to study hydrated phospholipid membranes [1-4]. It can even be used to analyze whole cell samples [5]. For pure lipids, DSC can accurately determine the phase transition temperatures and the associated enthalpies. As a consequence, how the chemical structure of lipids translates into thermodynamic properties can be systematically studied. In addition to determining the physical properties of pure lipids, the miscibility and phase behavior of lipid mixtures can be determined.

> The detailed review of the interdigitated phase written by Slater and Huang in 1988 provides an excellent outline of the properties of the interdigitated phase and the relevant analytical techniques [6]. Furthermore, the meticulous studies of Koynova and Caffrey describe how systematic changes in lipid chemistry can affect their phase behavior [7-9]. Lipids with asymmetrical acyl chains that form either mixed- or partially-interdigitated phases have also been thoroughly investigated [7,10-12]. This review focuses on the interdigitated phase of fully hydrated phospholipids with hydrocarbon chain lengths of equal size. We pay special attention to recently discovered interdigitated systems and the chemicals that can induce or inhibit lipid interdigitation.

> For simplicity, we have centered our review around the extensively studied lipid, 1,2 dipalmitoyl-*sn*-glycero-3-phosphocholine (DPPC). DPPC is naturally occurring and has thermodynamic phase behavior that is typical for saturated phosphatidylcholines (PCs) [7]. Although DPPC does not spontaneously interdigitate when hydrated, it can be reliably transformed into the fully interdigitated gel phase (Tables 1 and 2). Alterations in the lipid hydrocarbon chains (Figure 1) and the lipid head group (Figure 2) substantially affect spontaneous interdigitation (Figure 3). The predisposition for interdigitation is a finely

tuned balance of interactions among hydrocarbon chains, between polar head groups, and at the interfacial area with the aqueous phase.

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 409

**Figure 3.** Phase transitions of representative lipids. Solid arrows indicate heating transitions and dotted

arrows indicate cooling transitions. Note: subgel phase transitions are not shown.

**Figure 1.** Representative examples of fatty acid modifications of DPPC. The segments in red identify modifications to the structure of DPPC.

**Figure 2.** Representative examples of head group modifications of DPPC. The segments in red identify modifications to the structure of DPPC. The segments in blue demonstrate the resulting change in charge.

modifications to the structure of DPPC.

at the interfacial area with the aqueous phase.

408 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

tuned balance of interactions among hydrocarbon chains, between polar head groups, and

**Figure 1.** Representative examples of fatty acid modifications of DPPC. The segments in red identify

**Figure 2.** Representative examples of head group modifications of DPPC. The segments in red identify modifications to the structure of DPPC. The segments in blue demonstrate the resulting change in charge.

**Figure 3.** Phase transitions of representative lipids. Solid arrows indicate heating transitions and dotted arrows indicate cooling transitions. Note: subgel phase transitions are not shown.

410 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry


Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 411

gel phase when fully hydrated under typical preparation procedures and at ambient pressure. Some notable recent examples are highlighted, such as cationic lipids and lipids with monofluorinated acyl chains. Whether or not a particular lipid spontaneously interdigitates is determined by the balance of properties that favor and disfavor interdigitation. Lipids often have conflicting characteristics regarding the ability to form the interdigitated phase. Consequently, there is no simple formula for determining which lipids

**Figure 4.** Schematic representation of the different types of membrane interdigitation: A) symmetrical lipid, non-interdigitated; B) symmetrical lipid, fully interdigitated; C) asymmetrical lipid, partially interdigitated; D) highly asymmetrical lipid, mixed-interdigitated; E) lysolipid, fully interdigitated. For

As can be seen in Figure 4, the structural difference between the interdigitated and noninterdigitated phases can be substantial. In the non-interdigitated membrane, both ends of the hydrocarbon chains meet in the membrane midplane (Figure 4A). Two well-defined leaflets are formed and there is a thick hydrophobic core. In the fully-interdigitated membrane, the thickness of the interdigitated phase is greatly reduced and there is the loss of the membrane midplane. There is an increase in the spacing between the polar lipid head groups and the ends of the lipid hydrocarbon chains become more exposed to the aqueous interface [6]. The difference is most dramatic in the fully interdigitated phase compared to the non-interdigitated membrane (Figure 4A and 4B). In the partially-interdigitated system, the longer chain extends to the other side of the membrane and aligns with the apposing shorter chain (Figure 4C). In the mixed-interdigitated membrane, the short hydrocarbon chains line up with each other and the full-length chain extends to the other side of the membrane (Figure 4D). Lyso lipids also form a fully interdigitated structure (Figure 4E) [35].

clarity, the terminal ends of the hydrocarbon chains are labeled in red.

will spontaneously interdigitate without relying on experimental data.

**Table 1.** Threshold concentrations for some alcohol-induced interdigitation.


**Table 2.** Induced interdigitation of PC membranes.

There are multiple types of interdigitation (Figure 4). The type of interdigitation that forms is heavily dependent on the structure and symmetry of the hydrocarbon chains [6]. Interdigitated lipid systems can further be separated into two classes: spontaneous and induced. We use "spontaneous" to describe lipids that self-assemble into the interdigitated gel phase when fully hydrated under typical preparation procedures and at ambient pressure. Some notable recent examples are highlighted, such as cationic lipids and lipids with monofluorinated acyl chains. Whether or not a particular lipid spontaneously interdigitates is determined by the balance of properties that favor and disfavor interdigitation. Lipids often have conflicting characteristics regarding the ability to form the interdigitated phase. Consequently, there is no simple formula for determining which lipids will spontaneously interdigitate without relying on experimental data.

Applications of Calorimetry in a Wide Context –

Anesthetics

Drugs

Organic solvents

**Table 2.** Induced interdigitation of PC membranes.

410 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Table 1.** Threshold concentrations for some alcohol-induced interdigitation.

Chemicals References

[17] [17] [17] [17] [17-19]

> [20] [19] [21]

[22-24] [25] [26,27] [27,28] [27] [27]

bupivacaine dibucaine lidocaine procaine tetracaine

labdanes chlorpromazine valsartan

glycerol ethylene glycol acetone acetonitrile propionaldehyde petrahydrofuran

Salts KSCN [29,30] Pressure N/A [31-34]

There are multiple types of interdigitation (Figure 4). The type of interdigitation that forms is heavily dependent on the structure and symmetry of the hydrocarbon chains [6]. Interdigitated lipid systems can further be separated into two classes: spontaneous and induced. We use "spontaneous" to describe lipids that self-assemble into the interdigitated

DPPC/alcohol Threshold concentration (M) References

Methanol 2.75 ± 0.35 [13] Ethanol 1.10 ± 0.10 [13] 1-propanol 0.39 ± 0.03 [14] 2-propanol 0.52 ± 0.03 [14] 1-butanol 0.16 ± 0.02 [15] Isobutanol 0.17 ± 0.02 [15] *sec*-butanol 0.22 ± 0.02 [15] *tert*-butanol 0.27 ± 0.02 [15] 1-pentanol 0.07 ± 0.01 [16] 2-pentanol 0.10 ± 0.01 [16] 3-pentanol 0.11 ± 0.01 [16] 3-methyl-2-butanol 0.10 ± 0.01 [16] 2-methyl-1-butanol 0.08 ± 0.01 [16] 3-methyl-1-butanol 0.08 ± 0.01 [16] 2-methyl-2-butanol 0.13 ± 0.01 [16] neopentanol 0.08 ± 0.01 [16]

**Figure 4.** Schematic representation of the different types of membrane interdigitation: A) symmetrical lipid, non-interdigitated; B) symmetrical lipid, fully interdigitated; C) asymmetrical lipid, partially interdigitated; D) highly asymmetrical lipid, mixed-interdigitated; E) lysolipid, fully interdigitated. For clarity, the terminal ends of the hydrocarbon chains are labeled in red.

As can be seen in Figure 4, the structural difference between the interdigitated and noninterdigitated phases can be substantial. In the non-interdigitated membrane, both ends of the hydrocarbon chains meet in the membrane midplane (Figure 4A). Two well-defined leaflets are formed and there is a thick hydrophobic core. In the fully-interdigitated membrane, the thickness of the interdigitated phase is greatly reduced and there is the loss of the membrane midplane. There is an increase in the spacing between the polar lipid head groups and the ends of the lipid hydrocarbon chains become more exposed to the aqueous interface [6]. The difference is most dramatic in the fully interdigitated phase compared to the non-interdigitated membrane (Figure 4A and 4B). In the partially-interdigitated system, the longer chain extends to the other side of the membrane and aligns with the apposing shorter chain (Figure 4C). In the mixed-interdigitated membrane, the short hydrocarbon chains line up with each other and the full-length chain extends to the other side of the membrane (Figure 4D). Lyso lipids also form a fully interdigitated structure (Figure 4E) [35].

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

### **2.**

### **2.1. Thermodynamics of phosphatidylcholine membranes**

PCs are common in mammalian membranes and have well known phase transitions [7]. The most ubiquitous of these is the gel-to-liquid crystalline transition, often referred to as the melting or main transition. This transition is relatively rapid and is highly reversible [36]. It is characterized by the co-operative melting of the hydrocarbon chains and a high enthalpy DSC peak [2]. The liquid crystalline (*L*α) phase has an increased number of gauche conformers and a large increase in membrane fluidity and disorder [2,37]. The pre-transition from the planar gel (*L*β′) to the rippled gel phase (*P*β′) has a low enthalpy and is sensitive to sample preparation and the presence of impurities [7,36]. It is also more sensitive to the scan rate, with lower scan rates resulting in lower *T*p temperatures [3]. Some PCs also have subgel phases. The subgel transition is slow and is dependent on sample preparation, especially incubation temperature and time [36]. All of the above phases are strongly affected by changes in lipid structure. This review will show that such alterations also have a profound effect on the interdigitated phase.

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 413

The shape and magnitude of the *T*m biphasic effect is also dependent on the alcohol isomer used as shown in Figure 5 [15,16]. For example, *tert*-butanol is an effective inducer of interdigitation and has a pronounced biphasic effect [15]. Other alcohols, such as the pentanol isomers have more "stunted" biphasic behavior [16]. While a difference in trend can still be observed above and below the threshold concentration, the distinction is less

**Figure 5.** Effects of *n*-butanol, isobutanol, *sec*-butanol, and *tert*-butanol on DPPC phase transition temperatures. (■ , heating scan main peak; □, heating scan shoulder peak; , cooling scan main peak; ▲ Δ, cooling scan shoulder peak; ●, pre-transition peak). Reprinted from Biophys. Chem., 128, Reeves MD, Schawel AK, Wang W, Dea PK, Effects of butanol isomers on dipalmitoylphosphatidylcholine bilayer

Increasing the alcohol content well above the threshold concentration lowers the *T*m [15,16]. At these concentrations, additional alcohol destabilizes the *L*βI phase relative to the *L*α phase. The membrane bilayer structure can also break down for alcohols that are highly soluble in water [15]. For example, above 2.00 M *tert*-butanol in DPPC, the main transition hysteresis is absent (Figure 5). Additionally, the heating main transition DSC peaks above 2.00 M *tert*butanol become increasingly broad. Changes in the 31P-NMR spectra at high concentrations

The biphasic behavior is also reflected in the increase in the main transition enthalpy as the alcohol concentration increases [15,16]. Often, the rate of change in the transition enthalpy above and below the threshold concentration is different (Figure 6). This effect also depends on the alcohol chain length and isomer used. For instance, this difference is clear with *n*-

membranes, Pages No. 13-18, Copyright (2007), with permission from Elsevier [15].

confirm the loss of lamellar structure [15].

butanol but not *tert*-butanol [15].

pronounced.

### **2.2. Chemically-induced interdigitation of phosphatidylcholines**

The most widely studied chemical inducer of interdigitation is ethanol. In non-interdigitated phospholipid membranes, ethanol tends to adsorb to the head groups, especially the region near the hydrocarbon chains [38,39]. In particular, the carbonyl groups of the glycerol backbone of phospholipids are thought to be the favored hydrogen bonding sites for ethanol [40]. Ethanol displaces water when it adsorbs to the head group, which increases the head group volume and decreases the order of the hydrocarbon chains [13,41,42]. The increase in head group volume leads to increased chain tilting and creates energetically unfavorable voids in the hydrocarbon region of non-interdigitated membranes, encouraging the creation of the *L*βI phase at high concentrations [13,39,42-44]. Once the *L*βI phase is formed, ethanol can bind to the exposed hydrocarbon chains, replacing the unfavorable interaction of the acyl chains with water [45]. Also, it is typical for alcohols to increase the main transition enthalpy above the threshold concentration for interdigitation [15,16].

There are three main characteristics of the chemically-induced interdigitated phase in the DSC thermograms of saturated PCs: the presence of biphasic phase behavior, an increase in *T*m hysteresis, and the suppression of the pre-transition. The combination of these can be used to determine the threshold concentration for interdigitation.

The "biphasic effect" indicates two independent interactions within different concentration ranges [46,47]. The biphasic effect is most strongly characterized by an initial decrease in the *T*m, but an increase in or stabilization of the *T*m once the *L*βI phase is formed. The first interaction lies below the threshold concentration. Here, ethanol preferentially partitions into the liquid crystalline phase, lowering the phase transition temperature [47]. The secondary interaction above the threshold concentration stabilizes the interdigitated gel phase. The main transition co-operativity (sharpness of transition peak) can also be enhanced above the threshold concentration [47].

The shape and magnitude of the *T*m biphasic effect is also dependent on the alcohol isomer used as shown in Figure 5 [15,16]. For example, *tert*-butanol is an effective inducer of interdigitation and has a pronounced biphasic effect [15]. Other alcohols, such as the pentanol isomers have more "stunted" biphasic behavior [16]. While a difference in trend can still be observed above and below the threshold concentration, the distinction is less pronounced.

Applications of Calorimetry in a Wide Context –

a profound effect on the interdigitated phase.

**2.** 

412 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**2.1. Thermodynamics of phosphatidylcholine membranes** 

**2.2. Chemically-induced interdigitation of phosphatidylcholines** 

enthalpy above the threshold concentration for interdigitation [15,16].

used to determine the threshold concentration for interdigitation.

enhanced above the threshold concentration [47].

PCs are common in mammalian membranes and have well known phase transitions [7]. The most ubiquitous of these is the gel-to-liquid crystalline transition, often referred to as the melting or main transition. This transition is relatively rapid and is highly reversible [36]. It is characterized by the co-operative melting of the hydrocarbon chains and a high enthalpy DSC peak [2]. The liquid crystalline (*L*α) phase has an increased number of gauche conformers and a large increase in membrane fluidity and disorder [2,37]. The pre-transition from the planar gel (*L*β′) to the rippled gel phase (*P*β′) has a low enthalpy and is sensitive to sample preparation and the presence of impurities [7,36]. It is also more sensitive to the scan rate, with lower scan rates resulting in lower *T*p temperatures [3]. Some PCs also have subgel phases. The subgel transition is slow and is dependent on sample preparation, especially incubation temperature and time [36]. All of the above phases are strongly affected by changes in lipid structure. This review will show that such alterations also have

The most widely studied chemical inducer of interdigitation is ethanol. In non-interdigitated phospholipid membranes, ethanol tends to adsorb to the head groups, especially the region near the hydrocarbon chains [38,39]. In particular, the carbonyl groups of the glycerol backbone of phospholipids are thought to be the favored hydrogen bonding sites for ethanol [40]. Ethanol displaces water when it adsorbs to the head group, which increases the head group volume and decreases the order of the hydrocarbon chains [13,41,42]. The increase in head group volume leads to increased chain tilting and creates energetically unfavorable voids in the hydrocarbon region of non-interdigitated membranes, encouraging the creation of the *L*βI phase at high concentrations [13,39,42-44]. Once the *L*βI phase is formed, ethanol can bind to the exposed hydrocarbon chains, replacing the unfavorable interaction of the acyl chains with water [45]. Also, it is typical for alcohols to increase the main transition

There are three main characteristics of the chemically-induced interdigitated phase in the DSC thermograms of saturated PCs: the presence of biphasic phase behavior, an increase in *T*m hysteresis, and the suppression of the pre-transition. The combination of these can be

The "biphasic effect" indicates two independent interactions within different concentration ranges [46,47]. The biphasic effect is most strongly characterized by an initial decrease in the *T*m, but an increase in or stabilization of the *T*m once the *L*βI phase is formed. The first interaction lies below the threshold concentration. Here, ethanol preferentially partitions into the liquid crystalline phase, lowering the phase transition temperature [47]. The secondary interaction above the threshold concentration stabilizes the interdigitated gel phase. The main transition co-operativity (sharpness of transition peak) can also be

**Figure 5.** Effects of *n*-butanol, isobutanol, *sec*-butanol, and *tert*-butanol on DPPC phase transition temperatures. (■ , heating scan main peak; □, heating scan shoulder peak; , cooling scan main peak; ▲ Δ, cooling scan shoulder peak; ●, pre-transition peak). Reprinted from Biophys. Chem., 128, Reeves MD, Schawel AK, Wang W, Dea PK, Effects of butanol isomers on dipalmitoylphosphatidylcholine bilayer membranes, Pages No. 13-18, Copyright (2007), with permission from Elsevier [15].

Increasing the alcohol content well above the threshold concentration lowers the *T*m [15,16]. At these concentrations, additional alcohol destabilizes the *L*βI phase relative to the *L*α phase. The membrane bilayer structure can also break down for alcohols that are highly soluble in water [15]. For example, above 2.00 M *tert*-butanol in DPPC, the main transition hysteresis is absent (Figure 5). Additionally, the heating main transition DSC peaks above 2.00 M *tert*butanol become increasingly broad. Changes in the 31P-NMR spectra at high concentrations confirm the loss of lamellar structure [15].

The biphasic behavior is also reflected in the increase in the main transition enthalpy as the alcohol concentration increases [15,16]. Often, the rate of change in the transition enthalpy above and below the threshold concentration is different (Figure 6). This effect also depends on the alcohol chain length and isomer used. For instance, this difference is clear with *n*butanol but not *tert*-butanol [15].

414 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 415

it depresses both the temperature of the pre-transition and the main transition prior to the

The ether-linked analogue of DPPC, 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphocholine (DHPC), is also a useful model membrane for studying interdigitation. DHPC goes through a low temperature pre-transition from the *L*βI phase to the non-interdigitated rippled gel phase *P*β′ (Figure 3) [52,53]. Therefore, chemicals that stabilize the *L*βI phase increase the *T*<sup>p</sup> until it merges with the main transition into the *L*α phase [49]. This process occurs at lower

It is well established that the application of hydrostatic pressure favors interdigitation in a multitude of lipid systems (Tables 2 and 3). As hydrostatic pressure is applied, the intermolecular distance between adjacent lipids is reduced and molecular packing becomes denser [34]. By changing the packing structure of the membrane, interdigitation can relieve

Pressure-induced interdigitation is dependent on lipid hydrocarbon chain length and the chemical structure, much like chemically-induced interdigitation. Ether- and ester-linked lipids with longer chains require less pressure to interdigitate [51,54]. Under high temperature and pressure conditions, ester-linked lipids behave similarly to the equivalent ether-linked lipids at normal pressure [51]. Pressure-induced interdigitation is not universal, however. As with chemically-induced interdigitation, certain lipids do not interdigitate even

The type of bond that connects the hydrocarbon chain to the lipid head group also affects the thermodynamic properties. Switching either or both of the ester bonds of DPPC with ether linkages results in a small increase in the *T*m (<4 °C) and enthalpy (<1 kcal/mol) [57]. A single ether linkage can be sufficient to allow the formation of the interdigitated gel phase [57,58]. Furthermore, in ether lipids that spontaneously interdigitate, the interdigitated phase is stable up to higher temperatures as the chain length increases (Figure 7) [51]. There is an increased amount of head group repulsion in DHPC, which favors the interdigitated phase [51,59,60]. Conversely, the stronger interactions in the head groups of ester lipids hinder interdigitation [34,51]. DHPC is an especially useful lipid for studying the interdigitated phase because its transition from the interdigitated gel to non-interdigitated

The similarity of DHPC to DPPC also allows for the comparison between ether- and esterlinked lipids. It is consistently easier to interdigitate ether-linked lipids whether through chemical means [17,48,49] or by the application of pressure [51,61]. Furthermore, the etherlinked 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphoethanolamine (DHPE) demonstrates the result of competing influences on the interdigitated gel phase. In DHPE, the ether linkages

**2.4. Spontaneous interdigitation in ether-linked lipids and 1,3-DPPC** 

concentrations for more effective inducers of interdigitation.

**2.3. Pressure-induced interdigitation** 

under high pressure [34,55,56].

the stress caused by the increased steric hindrance.

ripple gel phase is highly sensitive to its environment.

threshold concentration [15].

**Figure 6.** Effects of (a) *n*-butanol, (b) isobutanol, (c) *sec*-butanol and (d) *tert*-butanol on DPPC main transition enthalpies (■ , heating scan main transition enthalpy; Δ, cooling scan main transition enthalpy). Reprinted from Biophys. Chem., 128, Reeves MD, Schawel AK, Wang W, Dea PK, Effects of butanol isomers on dipalmitoylphosphatidylcholine bilayer membranes, Pages No. 13-18, Copyright (2007), with permission from Elsevier [15].

A property that accompanies the biphasic effect is the emergence of hysteresis in the main transition [15,16,48,49]. The hysteresis as it relates to DSC is defined as the difference in the transition temperature between heating and cooling scans. This corresponds to the reversibility and kinetics of the transition. The return to the interdigitated phase with a decrease in temperature is a slow process and is therefore less reversible [48,51]. For systems that do not interdigitate, such as phosphatidylethanolamine (PE) lipids, the addition of alcohol does not affect the transition hysteresis [48].

The disappearance of the pre-transition is another consistent property of alcohol-induced interdigitation of saturated PCs. The decrease in the *T*p follows a well defined trend below the threshold concentration until it is finally abolished (Figure 5). The rate at which the *T*p is depressed depends on the efficacy of the chemical inducer.

By comparing the threshold concentrations of different chemicals, they can be ranked on their effectiveness at inducing the interdigitated phase. For instance, the threshold concentrations for alcohol-induced interdigitation systematically decreases as the lipid hydrocarbon chain length increases (Table 1). The isomers with the most solubility in water are the least effective at inducing interdigitation, as shown by the increase in threshold concentrations [15]. Additionally, the more soluble an isomer is in water, the less effectively it depresses both the temperature of the pre-transition and the main transition prior to the threshold concentration [15].

The ether-linked analogue of DPPC, 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphocholine (DHPC), is also a useful model membrane for studying interdigitation. DHPC goes through a low temperature pre-transition from the *L*βI phase to the non-interdigitated rippled gel phase *P*β′ (Figure 3) [52,53]. Therefore, chemicals that stabilize the *L*βI phase increase the *T*<sup>p</sup> until it merges with the main transition into the *L*α phase [49]. This process occurs at lower concentrations for more effective inducers of interdigitation.

### **2.3. Pressure-induced interdigitation**

Applications of Calorimetry in a Wide Context –

(2007), with permission from Elsevier [15].

alcohol does not affect the transition hysteresis [48].

depressed depends on the efficacy of the chemical inducer.

414 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 6.** Effects of (a) *n*-butanol, (b) isobutanol, (c) *sec*-butanol and (d) *tert*-butanol on DPPC main transition enthalpies (■ , heating scan main transition enthalpy; Δ, cooling scan main transition enthalpy). Reprinted from Biophys. Chem., 128, Reeves MD, Schawel AK, Wang W, Dea PK, Effects of butanol isomers on dipalmitoylphosphatidylcholine bilayer membranes, Pages No. 13-18, Copyright

A property that accompanies the biphasic effect is the emergence of hysteresis in the main transition [15,16,48,49]. The hysteresis as it relates to DSC is defined as the difference in the transition temperature between heating and cooling scans. This corresponds to the reversibility and kinetics of the transition. The return to the interdigitated phase with a decrease in temperature is a slow process and is therefore less reversible [48,51]. For systems that do not interdigitate, such as phosphatidylethanolamine (PE) lipids, the addition of

The disappearance of the pre-transition is another consistent property of alcohol-induced interdigitation of saturated PCs. The decrease in the *T*p follows a well defined trend below the threshold concentration until it is finally abolished (Figure 5). The rate at which the *T*p is

By comparing the threshold concentrations of different chemicals, they can be ranked on their effectiveness at inducing the interdigitated phase. For instance, the threshold concentrations for alcohol-induced interdigitation systematically decreases as the lipid hydrocarbon chain length increases (Table 1). The isomers with the most solubility in water are the least effective at inducing interdigitation, as shown by the increase in threshold concentrations [15]. Additionally, the more soluble an isomer is in water, the less effectively It is well established that the application of hydrostatic pressure favors interdigitation in a multitude of lipid systems (Tables 2 and 3). As hydrostatic pressure is applied, the intermolecular distance between adjacent lipids is reduced and molecular packing becomes denser [34]. By changing the packing structure of the membrane, interdigitation can relieve the stress caused by the increased steric hindrance.

Pressure-induced interdigitation is dependent on lipid hydrocarbon chain length and the chemical structure, much like chemically-induced interdigitation. Ether- and ester-linked lipids with longer chains require less pressure to interdigitate [51,54]. Under high temperature and pressure conditions, ester-linked lipids behave similarly to the equivalent ether-linked lipids at normal pressure [51]. Pressure-induced interdigitation is not universal, however. As with chemically-induced interdigitation, certain lipids do not interdigitate even under high pressure [34,55,56].

### **2.4. Spontaneous interdigitation in ether-linked lipids and 1,3-DPPC**

The type of bond that connects the hydrocarbon chain to the lipid head group also affects the thermodynamic properties. Switching either or both of the ester bonds of DPPC with ether linkages results in a small increase in the *T*m (<4 °C) and enthalpy (<1 kcal/mol) [57]. A single ether linkage can be sufficient to allow the formation of the interdigitated gel phase [57,58]. Furthermore, in ether lipids that spontaneously interdigitate, the interdigitated phase is stable up to higher temperatures as the chain length increases (Figure 7) [51]. There is an increased amount of head group repulsion in DHPC, which favors the interdigitated phase [51,59,60]. Conversely, the stronger interactions in the head groups of ester lipids hinder interdigitation [34,51]. DHPC is an especially useful lipid for studying the interdigitated phase because its transition from the interdigitated gel to non-interdigitated ripple gel phase is highly sensitive to its environment.

The similarity of DHPC to DPPC also allows for the comparison between ether- and esterlinked lipids. It is consistently easier to interdigitate ether-linked lipids whether through chemical means [17,48,49] or by the application of pressure [51,61]. Furthermore, the etherlinked 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphoethanolamine (DHPE) demonstrates the result of competing influences on the interdigitated gel phase. In DHPE, the ether linkages

Applications of Calorimetry in a Wide Context – 416 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

favor interdigitation, but the PE head group is more strongly opposed to interdigitation [62]. Therefore, while DHPC spontaneously interdigitates, the PE head group of DHPE prevents interdigitation.

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 417

DPPC : F-DPPC

0 : 100

10 : 90

20 : 80

30 : 70

40 : 60

70 : 30

80 : 20

90 : 10

100 : 0

The monofluorinated analogue of DPPC, 1-palmitoyl-2-(16-fluoropalmitoyl)*sn*-glycero-3 phosphocholine (F-DPPC), spontaneously forms the *L*βI phase below the main transition temperature (*T*m) [67-69]. The main transition temperature of F-DPPC also occurs at a higher temperature (~50 °C) and with a higher transition enthalpy (9.8 kcal/mol) compared to DPPC [67]. The endothermic peak of F-DPPC is also broader than DPPC. The transition can be split into two overlapping peaks, with the peak centered at 50.6 °C accounting for 36% of the area and the peak at 52.0 °C accounting for 64% of the area [67]. The lower transition peak component does not correspond to a change in the hydrocarbon chains as detected by

**Figure 8.** Heating (red lines) and cooling (dashed blue lines) DSC thermograms of the *T*m of the DPPC/F-DPPC system are shown. The cooling scans have been inverted to allow comparison with the heating thermograms. For clarity, the thermograms are also offset vertically. Reprinted from Biophys. Chem., 147, Smith E.A., van Gorkum C.M., Dea P.K., Properties of phosphatidylcholine in the presence of its monofluorinated analogue, Pages No. 20-27, Copyright (2010), with permission from Elsevier [69].

39 41 43 45 47 49 51

**Temperature (°C)**

**2.5. The monofluorinated analogue of DPPC: F-DPPC** 

**Excess Heat Capacity**

**Figure 7.** DSC heating thermograms of ether-linked PC bilayer membranes: (1) *O*-14:0-PC, (2) *O*-16:0- PC, (3) *O*-18:0-PC Reprinted from Biochim. Biophys. Acta, 1768, Matsuki H, Miyazaki E, Sakano F, Tamai N, Kaneshina S, Thermotropic and barotropic phase transitions in bilayer membranes of etherlinked phospholipids with varying alkyl chain lengths, Pages No. 479-489, Copyright (2007), with permission from Elsevier [51].

While the majority of PC lipid studies use lipids with the hydrocarbon chains on the *sn*-1 and *sn*-2 positions, there are some examples of experiments using synthetic lipids with the chains located at *sn*-1 and *sn*-3. One intriguing example is the positional isomer of DPPC, 1,3-dipalmitoyl-*sn*-glycero-2-phosphocholine (1,3-DPPC or *β*-DPPC), which has unique properties including the ability to spontaneously interdigitate [63-65]. However, the phase diagram is different from the ether-linked lipids that spontaneously interdigitate [51,66]. At lower temperatures, 1,3-DPPC exists in a non-interdigitated "crystalline" bilayer phase termed (*L*c). At higher temperatures, but below the *T*m, 1,3- DPPC can form a fully interdigitated structure [63]. The ability to interdigitate may be due to greater head group repulsion resulting from a different phosphocholine tilt or conformation relative to the glycerol backbone [63-65]. As with most interdigitated systems, 1,3-DPPC converts into a non-interdigitated structure during the heating transition into the *L*α phase. The cooling transition from the *L*α phase into the interdigitated phase has considerable hysteresis [63].

#### **2.5. The monofluorinated analogue of DPPC: F-DPPC**

Applications of Calorimetry in a Wide Context –

interdigitation.

permission from Elsevier [51].

interdigitated phase has considerable hysteresis [63].

416 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

favor interdigitation, but the PE head group is more strongly opposed to interdigitation [62]. Therefore, while DHPC spontaneously interdigitates, the PE head group of DHPE prevents

**Figure 7.** DSC heating thermograms of ether-linked PC bilayer membranes: (1) *O*-14:0-PC, (2) *O*-16:0- PC, (3) *O*-18:0-PC Reprinted from Biochim. Biophys. Acta, 1768, Matsuki H, Miyazaki E, Sakano F, Tamai N, Kaneshina S, Thermotropic and barotropic phase transitions in bilayer membranes of etherlinked phospholipids with varying alkyl chain lengths, Pages No. 479-489, Copyright (2007), with

While the majority of PC lipid studies use lipids with the hydrocarbon chains on the *sn*-1 and *sn*-2 positions, there are some examples of experiments using synthetic lipids with the chains located at *sn*-1 and *sn*-3. One intriguing example is the positional isomer of DPPC, 1,3-dipalmitoyl-*sn*-glycero-2-phosphocholine (1,3-DPPC or *β*-DPPC), which has unique properties including the ability to spontaneously interdigitate [63-65]. However, the phase diagram is different from the ether-linked lipids that spontaneously interdigitate [51,66]. At lower temperatures, 1,3-DPPC exists in a non-interdigitated "crystalline" bilayer phase termed (*L*c). At higher temperatures, but below the *T*m, 1,3- DPPC can form a fully interdigitated structure [63]. The ability to interdigitate may be due to greater head group repulsion resulting from a different phosphocholine tilt or conformation relative to the glycerol backbone [63-65]. As with most interdigitated systems, 1,3-DPPC converts into a non-interdigitated structure during the heating transition into the *L*α phase. The cooling transition from the *L*α phase into the The monofluorinated analogue of DPPC, 1-palmitoyl-2-(16-fluoropalmitoyl)*sn*-glycero-3 phosphocholine (F-DPPC), spontaneously forms the *L*βI phase below the main transition temperature (*T*m) [67-69]. The main transition temperature of F-DPPC also occurs at a higher temperature (~50 °C) and with a higher transition enthalpy (9.8 kcal/mol) compared to DPPC [67]. The endothermic peak of F-DPPC is also broader than DPPC. The transition can be split into two overlapping peaks, with the peak centered at 50.6 °C accounting for 36% of the area and the peak at 52.0 °C accounting for 64% of the area [67]. The lower transition peak component does not correspond to a change in the hydrocarbon chains as detected by

**Figure 8.** Heating (red lines) and cooling (dashed blue lines) DSC thermograms of the *T*m of the DPPC/F-DPPC system are shown. The cooling scans have been inverted to allow comparison with the heating thermograms. For clarity, the thermograms are also offset vertically. Reprinted from Biophys. Chem., 147, Smith E.A., van Gorkum C.M., Dea P.K., Properties of phosphatidylcholine in the presence of its monofluorinated analogue, Pages No. 20-27, Copyright (2010), with permission from Elsevier [69].

FTIR spectroscopy. It is possible that this relates to a conversion from interdigitated to noninterdigitated gel right before the transition into the liquid crystalline phase [67]. The main transition is also characterized by a large main transition hysteresis (Figures 8 and 9) [67,69]. Additionally, the *L*βI phase has high conformational order and tight lipid packing [68].

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 419

microbial membranes [90]. The interaction of some peptides with lipids is heavily dependent on the composition of the membrane [82]. This contributes to the ability of antimicrobial peptides to selectively target microbial membranes [91]. Recently, it was found that DPPG has the ability to form a quasi-interdigitated gel phase with the addition of the human multifunctional peptide LL-37 [81,82]. The antimicrobial peptide peptidylglycylleucine-carboxyamide (PGLa) has a similar effect below the main transition temperature of saturated PGs [83]. In these instances, the peptide shields the acyl chains of the interdigitated lipid from the aqueous layer by orienting in the interfacial region below

Furthermore, other chemicals such as Tris-HCl induce interdigitation in DPPG by binding between lipids, resulting in the increased area per head group that favors interdigitation [85]. As in zwitterionic lipids, interdigitation relieves head group repulsion in charged lipids by allowing for a larger area per head group [84]. Charge repulsion in DPPG leads to tilted acyl chains in the non-interdigitated bilayer [85]. This is similar to the ethanol-induced interdigitation of DPPC, where the increased head group size increases the tilt in the gel phase and which ultimately results in the interdigitated gel phase [43]. Ethanol further enhances interdigitation in DPPG, most likely by partitioning into the interfacial region and

**Figure 10.** Schematic representation of the peptide PGLa-associated structural changes in PG bilayers. Below the main phase transition (*T* < *T*m), the lipids of different hydrocarbon chain lengths exhibit a quasi-interdigitated phase in the presence of PGLa. Reprinted from Biophys. J. 95, Pabst G, Grage SL, Danner-Pongratz S, Jing W, Ulrich AS, Watts A, Lohner K, Hickel A, Membrane thickening by the antimicrobial peptide PGLa, Pages No. 5779-5788, Copyright (2008), with permission from Elsevier [83].

reducing the exposure of the terminal methyl groups to water [84].

the *T*m (Figure 10).

It appears that the fluorine must be located on the terminal hydrocarbon chain to have a dramatic effect on interdigitation. When the fluorine substitution is not located on the terminal carbon, DSC data reveal that the physical properties are only modestly changed and they are largely miscible with the non-fluorinated parent lipid [70]. Lipids with more fluorine, such as when the 13-16 carbons are perfluorinated, do not spontaneously interdigitate either [71,72]. Therefore, it is the interaction of the polar terminal C-F bond with the aqueous interface that encourages interdigitation [67]. The large dipole moment is the most likely culprit for stabilizing the interdigitated phase by reducing the unfavorable exposure of the hydrophobic acyl chains to water. However, the slightly larger van der Waals radius and the possibility of weak hydrogen bonding may also play a role [73-77].

**Figure 9.** The main transition temperature (*T*m) of DPPC/F-DPPC mixtures determined by DSC. Heating scans shown by filled red triangles (▲ ). Cooling scans shown by filled blue circles (●). Shoulder peaks indicated by unfilled triangles for heating scans (Δ) and unfilled circles for cooling scans (○ ). Reprinted from Biophys. Chem., 147, Smith EA, van Gorkum CM, Dea PK, Properties of phosphatidylcholine in the presence of its monofluorinated analogue, Pages No. 20-27, Copyright (2010), with permission from Elsevier [69].

### **2.6. The interdigitated gel phase in anionic lipids**

As with PCs, di-saturated long chain phosphatidylglycerols (PGs) have a strong propensity towards interdigitation (Table 3) [78]. The negatively charged PGs are commonly found in microbial membranes [90]. The interaction of some peptides with lipids is heavily dependent on the composition of the membrane [82]. This contributes to the ability of antimicrobial peptides to selectively target microbial membranes [91]. Recently, it was found that DPPG has the ability to form a quasi-interdigitated gel phase with the addition of the human multifunctional peptide LL-37 [81,82]. The antimicrobial peptide peptidylglycylleucine-carboxyamide (PGLa) has a similar effect below the main transition temperature of saturated PGs [83]. In these instances, the peptide shields the acyl chains of the interdigitated lipid from the aqueous layer by orienting in the interfacial region below the *T*m (Figure 10).

Applications of Calorimetry in a Wide Context –

a role [73-77].

(2010), with permission from Elsevier [69].

**2.6. The interdigitated gel phase in anionic lipids** 

418 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

FTIR spectroscopy. It is possible that this relates to a conversion from interdigitated to noninterdigitated gel right before the transition into the liquid crystalline phase [67]. The main transition is also characterized by a large main transition hysteresis (Figures 8 and 9) [67,69]. Additionally, the *L*βI phase has high conformational order and tight lipid packing [68].

It appears that the fluorine must be located on the terminal hydrocarbon chain to have a dramatic effect on interdigitation. When the fluorine substitution is not located on the terminal carbon, DSC data reveal that the physical properties are only modestly changed and they are largely miscible with the non-fluorinated parent lipid [70]. Lipids with more fluorine, such as when the 13-16 carbons are perfluorinated, do not spontaneously interdigitate either [71,72]. Therefore, it is the interaction of the polar terminal C-F bond with the aqueous interface that encourages interdigitation [67]. The large dipole moment is the most likely culprit for stabilizing the interdigitated phase by reducing the unfavorable exposure of the hydrophobic acyl chains to water. However, the slightly larger van der Waals radius and the possibility of weak hydrogen bonding may also play

**Figure 9.** The main transition temperature (*T*m) of DPPC/F-DPPC mixtures determined by DSC. Heating scans shown by filled red triangles (▲ ). Cooling scans shown by filled blue circles (●). Shoulder peaks indicated by unfilled triangles for heating scans (Δ) and unfilled circles for cooling scans (○ ). Reprinted from Biophys. Chem., 147, Smith EA, van Gorkum CM, Dea PK, Properties of phosphatidylcholine in the presence of its monofluorinated analogue, Pages No. 20-27, Copyright

As with PCs, di-saturated long chain phosphatidylglycerols (PGs) have a strong propensity towards interdigitation (Table 3) [78]. The negatively charged PGs are commonly found in Furthermore, other chemicals such as Tris-HCl induce interdigitation in DPPG by binding between lipids, resulting in the increased area per head group that favors interdigitation [85]. As in zwitterionic lipids, interdigitation relieves head group repulsion in charged lipids by allowing for a larger area per head group [84]. Charge repulsion in DPPG leads to tilted acyl chains in the non-interdigitated bilayer [85]. This is similar to the ethanol-induced interdigitation of DPPC, where the increased head group size increases the tilt in the gel phase and which ultimately results in the interdigitated gel phase [43]. Ethanol further enhances interdigitation in DPPG, most likely by partitioning into the interfacial region and reducing the exposure of the terminal methyl groups to water [84].

**Figure 10.** Schematic representation of the peptide PGLa-associated structural changes in PG bilayers. Below the main phase transition (*T* < *T*m), the lipids of different hydrocarbon chain lengths exhibit a quasi-interdigitated phase in the presence of PGLa. Reprinted from Biophys. J. 95, Pabst G, Grage SL, Danner-Pongratz S, Jing W, Ulrich AS, Watts A, Lohner K, Hickel A, Membrane thickening by the antimicrobial peptide PGLa, Pages No. 5779-5788, Copyright (2008), with permission from Elsevier [83].

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


Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 421

data lend some support to this conclusion, since the polar/apolar interfaces of cationic PCs are less polar than the parent PC lipids [96]. These lipids have complex phase diagrams that are dependent on temperature, mechanical agitation, and kinetics (Figure

**Figure 11.** Diagram of the morphological changes in EDPPC dispersions. The equilibrium low temperature arrangement appears to be lamellar sheets, with chain interdigitation. Upon heating, liposomes and lamellar sheets (both non-interdigitated) coexist, whose mixture fully converts into liposomes (apparently the equilibrium liquid crystalline phase arrangement) only after mechanical treatment. Cooling back to the gel phase produces gel-phase liposomes which convert back into lamellar sheets only after prolonged low-temperature exposure. Reprinted from Biochim. Biophys. Acta., 1613, Koynova R, MacDonald RC, Cationic *O*-ethylphosphatidylcholines and their lipoplexes: phase behavior aspects, structural organization and morphology, Pages No. 39-48, Copyright (2003),

with permission from Elsevier [97].

11) [97].

**Table 3.** Induced interdigitation of PG membranes

When ethanol substitutes for water in the transphosphatidylation reaction catalyzed by phospholipase D, phosphatidylethanols (Peth) are formed [84,92]. Peth lipids are unique because they have a small anionic lipid headgroup (Figure 2). These lipids are biologically relevant since Peths accumulate in membranes of animal models of alcoholism [93]. Like DPPG, DPPeth can be chemically induced to interdigitate with Tris-HCl and the interdigitated phase is stabilized with the addition of ethanol [84].

### **2.7. The interdigitated gel phase in cationic lipids**

Cationic lipids with modified head groups can spontaneously form interdigitated gel phases below the main transition. One recent example is the positively charged lysyl-DPPG, which is DPPG with a lysine moiety attached. Lysyl-DPPC forms an interdigitated phase primarily due to the large repulsion between head groups [94].

Another modification is the esterification of the phosphate head group, which increases the steric bulk and changes the molecule from zwitterionic to positively charged, allowing interdigitation [95,96]. For example, the P-O-ethyl ester analogue of DPPC, 1,2 dipalmitoyl-*sn*-glycero-3-ethylphosphocholine (EDPPC or Et-DPPC), is fully interdigitated in the gel phase and has a main transition at 42.5 °C with an enthalpy of 9.6 kcal/mol [95-97]. These values are slightly higher than those for DPPC, which has a *T*m around 41.3 °C and a corresponding enthalpy of 8.2 kcal/mol ([7] and references therein). The thermodynamic behavior of these cationic triesters of phosphatidylcholine can be attributed to the net positive charge and the absence of intermolecular hydrogen bonding [98]. Furthermore, the overall polarity of the lipid is decreased, which may decrease the interfacial polarity. This would reduce the energetic cost when the ends of the hydrocarbon chains are exposed to the polar head group and the aqueous phase in the interdigitated phase [96]. The additional ethyl group in the head group may also mitigate the unfavorable exposure of the acyl chains [96]. Infrared spectroscopic data lend some support to this conclusion, since the polar/apolar interfaces of cationic PCs are less polar than the parent PC lipids [96]. These lipids have complex phase diagrams that are dependent on temperature, mechanical agitation, and kinetics (Figure 11) [97].

Applications of Calorimetry in a Wide Context –

**Table 3.** Induced interdigitation of PG membranes

interdigitated phase is stabilized with the addition of ethanol [84].

**2.7. The interdigitated gel phase in cationic lipids** 

due to the large repulsion between head groups [94].

420 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Inducer References polymyxin B [24,79,80] peptide LL-37 [81,82] peptide PGLa [83] myelin basic protein [80]

Tris HCl [79,84,85]

atropine [87,88] anisodamine [89] Pressure [50]

choline and acetylcholine [86]

When ethanol substitutes for water in the transphosphatidylation reaction catalyzed by phospholipase D, phosphatidylethanols (Peth) are formed [84,92]. Peth lipids are unique because they have a small anionic lipid headgroup (Figure 2). These lipids are biologically relevant since Peths accumulate in membranes of animal models of alcoholism [93]. Like DPPG, DPPeth can be chemically induced to interdigitate with Tris-HCl and the

Cationic lipids with modified head groups can spontaneously form interdigitated gel phases below the main transition. One recent example is the positively charged lysyl-DPPG, which is DPPG with a lysine moiety attached. Lysyl-DPPC forms an interdigitated phase primarily

Another modification is the esterification of the phosphate head group, which increases the steric bulk and changes the molecule from zwitterionic to positively charged, allowing interdigitation [95,96]. For example, the P-O-ethyl ester analogue of DPPC, 1,2 dipalmitoyl-*sn*-glycero-3-ethylphosphocholine (EDPPC or Et-DPPC), is fully interdigitated in the gel phase and has a main transition at 42.5 °C with an enthalpy of 9.6 kcal/mol [95-97]. These values are slightly higher than those for DPPC, which has a *T*m around 41.3 °C and a corresponding enthalpy of 8.2 kcal/mol ([7] and references therein). The thermodynamic behavior of these cationic triesters of phosphatidylcholine can be attributed to the net positive charge and the absence of intermolecular hydrogen bonding [98]. Furthermore, the overall polarity of the lipid is decreased, which may decrease the interfacial polarity. This would reduce the energetic cost when the ends of the hydrocarbon chains are exposed to the polar head group and the aqueous phase in the interdigitated phase [96]. The additional ethyl group in the head group may also mitigate the unfavorable exposure of the acyl chains [96]. Infrared spectroscopic

**Figure 11.** Diagram of the morphological changes in EDPPC dispersions. The equilibrium low temperature arrangement appears to be lamellar sheets, with chain interdigitation. Upon heating, liposomes and lamellar sheets (both non-interdigitated) coexist, whose mixture fully converts into liposomes (apparently the equilibrium liquid crystalline phase arrangement) only after mechanical treatment. Cooling back to the gel phase produces gel-phase liposomes which convert back into lamellar sheets only after prolonged low-temperature exposure. Reprinted from Biochim. Biophys. Acta., 1613, Koynova R, MacDonald RC, Cationic *O*-ethylphosphatidylcholines and their lipoplexes: phase behavior aspects, structural organization and morphology, Pages No. 39-48, Copyright (2003), with permission from Elsevier [97].

Vesicles formed from cationic triester lipids readily fuse with anionic lipids [98]. This may help explain why lipoplexes made from cationic *o*-ethylphosphatidylcholines with disaturated hydrocarbon chains are effective transfection agents [98,99]. The structure and transfection capability of cationic phospholipid-DNA complexes are dependent on preparation conditions and ionic strength [98,100]. These lipids confer multiple advantages: they are non-viral, metabolized by cells, have low toxicity, and closely resemble naturally occurring phospholipids [101].

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 423

The inhibition of interdigitation also applies to lipid mixtures involving unsaturated lipids. In a model membrane of DPPC/DOPC/ergosterol, increasing the unsaturated lipid or sterol component co-operatively hinders the formation of the interdigitated phase [107]. DOPC is known to result in a more disordered and less tilted gel phase and can lead to phase separation at higher concentrations [108]. As a consequence, it was hypothesized that changes in the plasma membrane composition may play a role in the ethanol tolerance of

There are some exceptions, however. While lipids with double bonds on both chains are particularly unlikely to interdigitate, there are a few examples of interdigitation where only one chain has a double bond. For example, McIntosh et al. tested the ethanol-induced interdigitation of five positional isomers of 1-eicosanoyl-2-eicosenoyl-*sn*-glycero-3 phosphocholine (C(20):C(20:1Δ*n*)PC) with a single *cis* bond on the *sn*-2 chain at position *n* = 5, 8, 11, 13 and 17 [109]. Ethanol-induced interdigitation can be induced when the position of the *cis* bond is at *n*= 5 or 8, but not at *n*= 11, 13, or 17 [109]. In contrast, the fully saturated lipid with

Additionally the *cis* mono-unsaturated 1-stearoyl,2-oleoyl-phosphatidylcholine (SOPC) can be interdigitated with glycerol [24]. The PG lipid, 1-palmitoyl,2-oleoyl-phosphatidylglycerol (POPG), can also be interdigitated with the addition of polymyxin B [24]. Certain mixtures of unsaturated zwitterionic and charged lipids, such as 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) and POPG, can form the interdigitated phase at high

Therefore, it can be concluded that while it is possible to induce the interdigitated gel phase in unsaturated lipids, they are more resistant to interdigitation compared to the equivalent saturated lipid. Additionally, when the interdigitated phase does occur in unsaturated lipids, the phase appears to be less stable and less ordered than in saturated lipids [24].

The curvature of the membrane due to the macromolecular size and shape affects the thermodynamic properties [36]. For instance, on DSC scans, small unilamellar vesicles (SUVs) have lower enthalpic peaks and greater widths compared to multilamellar vesicles (MLVs) [2,3]. SUVs also have more mobility and less order in the hydrocarbon chains [2].

The degree of membrane curvature also affects the ability to interdigitate. Bending in the membrane causes increased steric interference in opposing lipid monolayers [44]. As a consequence, ethanol-induced interdigitation is dependent on curvature, with the more highly curved vesicles requiring more ethanol to interdigitate [111,112]. Sonicated DPPC SUVs are not stable in the presence of ethanol above the threshold concentration for interdigitation [112]. Furthermore, SUVs have a tendency to fuse into large unilamellar vesicles (LUVs), which have properties more similar to MLVs [36,113]. The more planar MLVs allow interdigitated lipids to slide by each other with low steric interference and

the same chain length can easily be interdigitated with a small amount of ethanol [47].

yeast cells during fermentation ([107] and references therein).

concentrations of ethanol and at low hydration [110].

**2.10. Membrane curvature and interdigitation** 

therefore have the lowest threshold concentrations [44,112].

In some instances, DNA can be sandwiched between interdigitated gel phase lipid sheets into a rectangular columnar two-dimensional superlattice [97,99]. The gel-to-liquid crystalline phase transition results in the contraction of the DNA strand arrays so that the mean charge density is balanced with the increased positive charge of the non-interdigitated lipid. Additionally, in the non-interdigitated liquid crystalline phase, the interlamellar correlation in DNA ordering is no longer observed [99].

### **2.8. Phosphatidylethanolamines**

Phosphatidylethanolamines (PEs) are distinct due to their strong reluctance to interdigitate. PEs are not susceptible to alcohol-induced interdigitation [48] or pressure-induced interdigitation [55]. Even the ether-linked DHPE does not interdigitate with pressure [34,56]. A major reason for this is that the PE headgroup can form hydrogen bonds [34]. PC headgroups interact through a weaker electrostatic attraction between the positively charged quaternary nitrogen and the negatively charged oxygen of a neighboring lipid headgroup [34]. Additionally, the smaller size of the PE headgroup also allows for closer interaction (less repulsion) [2,8,102].

### **2.9. Unsaturated phospholipids**

Unsaturated lipids with common head groups and acyl chains of nearly equal length are strongly disfavored to interdigitate spontaneously. In general, unsaturated lipids are also resistant to both pressure- and chemically-induced interdigitation [44,103,104]. Even under high pressure, unsaturated lipids typically retain the transition from the non-interdigitated lamellar gel phase (*L*β) into the liquid crystalline phase (*L*α) [104,105]. Pressure does stabilize the *L*β phase to the detriment of the *L*α phase, but it is not sufficient to induce interdigitation [105].

Furthermore, unsaturated lipids have substantially lower main transition temperatures [7,10]. As interdigitation is highly unfavorable in the liquid crystalline phase, the relevant temperature range of the gel phase where interdigitation is likely to occur is much smaller. The main transition tends to be lowered the most when the double bond is located near the middle of the fatty acid chain [2,10,36]. Although double bonds that are *trans* usually have less influence than *cis* bonds [7,36], no ethanol-induced interdigitation was found in the *trans* lipid 1,2-dielaidoyl-*sn*-glycero-3-phosphocholine (DEPC) [106]. It was postulated that the increased cross-sectional area due to the double bond and the restriction in sliding motions contributes to the lack of interdigitation [106].

The inhibition of interdigitation also applies to lipid mixtures involving unsaturated lipids. In a model membrane of DPPC/DOPC/ergosterol, increasing the unsaturated lipid or sterol component co-operatively hinders the formation of the interdigitated phase [107]. DOPC is known to result in a more disordered and less tilted gel phase and can lead to phase separation at higher concentrations [108]. As a consequence, it was hypothesized that changes in the plasma membrane composition may play a role in the ethanol tolerance of yeast cells during fermentation ([107] and references therein).

There are some exceptions, however. While lipids with double bonds on both chains are particularly unlikely to interdigitate, there are a few examples of interdigitation where only one chain has a double bond. For example, McIntosh et al. tested the ethanol-induced interdigitation of five positional isomers of 1-eicosanoyl-2-eicosenoyl-*sn*-glycero-3 phosphocholine (C(20):C(20:1Δ*n*)PC) with a single *cis* bond on the *sn*-2 chain at position *n* = 5, 8, 11, 13 and 17 [109]. Ethanol-induced interdigitation can be induced when the position of the *cis* bond is at *n*= 5 or 8, but not at *n*= 11, 13, or 17 [109]. In contrast, the fully saturated lipid with the same chain length can easily be interdigitated with a small amount of ethanol [47].

Additionally the *cis* mono-unsaturated 1-stearoyl,2-oleoyl-phosphatidylcholine (SOPC) can be interdigitated with glycerol [24]. The PG lipid, 1-palmitoyl,2-oleoyl-phosphatidylglycerol (POPG), can also be interdigitated with the addition of polymyxin B [24]. Certain mixtures of unsaturated zwitterionic and charged lipids, such as 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) and POPG, can form the interdigitated phase at high concentrations of ethanol and at low hydration [110].

Therefore, it can be concluded that while it is possible to induce the interdigitated gel phase in unsaturated lipids, they are more resistant to interdigitation compared to the equivalent saturated lipid. Additionally, when the interdigitated phase does occur in unsaturated lipids, the phase appears to be less stable and less ordered than in saturated lipids [24].

### **2.10. Membrane curvature and interdigitation**

Applications of Calorimetry in a Wide Context –

occurring phospholipids [101].

**2.8. Phosphatidylethanolamines** 

interaction (less repulsion) [2,8,102].

**2.9. Unsaturated phospholipids** 

422 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

correlation in DNA ordering is no longer observed [99].

motions contributes to the lack of interdigitation [106].

Vesicles formed from cationic triester lipids readily fuse with anionic lipids [98]. This may help explain why lipoplexes made from cationic *o*-ethylphosphatidylcholines with disaturated hydrocarbon chains are effective transfection agents [98,99]. The structure and transfection capability of cationic phospholipid-DNA complexes are dependent on preparation conditions and ionic strength [98,100]. These lipids confer multiple advantages: they are non-viral, metabolized by cells, have low toxicity, and closely resemble naturally

In some instances, DNA can be sandwiched between interdigitated gel phase lipid sheets into a rectangular columnar two-dimensional superlattice [97,99]. The gel-to-liquid crystalline phase transition results in the contraction of the DNA strand arrays so that the mean charge density is balanced with the increased positive charge of the non-interdigitated lipid. Additionally, in the non-interdigitated liquid crystalline phase, the interlamellar

Phosphatidylethanolamines (PEs) are distinct due to their strong reluctance to interdigitate. PEs are not susceptible to alcohol-induced interdigitation [48] or pressure-induced interdigitation [55]. Even the ether-linked DHPE does not interdigitate with pressure [34,56]. A major reason for this is that the PE headgroup can form hydrogen bonds [34]. PC headgroups interact through a weaker electrostatic attraction between the positively charged quaternary nitrogen and the negatively charged oxygen of a neighboring lipid headgroup [34]. Additionally, the smaller size of the PE headgroup also allows for closer

Unsaturated lipids with common head groups and acyl chains of nearly equal length are strongly disfavored to interdigitate spontaneously. In general, unsaturated lipids are also resistant to both pressure- and chemically-induced interdigitation [44,103,104]. Even under high pressure, unsaturated lipids typically retain the transition from the non-interdigitated lamellar gel phase (*L*β) into the liquid crystalline phase (*L*α) [104,105]. Pressure does stabilize the *L*β phase

Furthermore, unsaturated lipids have substantially lower main transition temperatures [7,10]. As interdigitation is highly unfavorable in the liquid crystalline phase, the relevant temperature range of the gel phase where interdigitation is likely to occur is much smaller. The main transition tends to be lowered the most when the double bond is located near the middle of the fatty acid chain [2,10,36]. Although double bonds that are *trans* usually have less influence than *cis* bonds [7,36], no ethanol-induced interdigitation was found in the *trans* lipid 1,2-dielaidoyl-*sn*-glycero-3-phosphocholine (DEPC) [106]. It was postulated that the increased cross-sectional area due to the double bond and the restriction in sliding

to the detriment of the *L*α phase, but it is not sufficient to induce interdigitation [105].

The curvature of the membrane due to the macromolecular size and shape affects the thermodynamic properties [36]. For instance, on DSC scans, small unilamellar vesicles (SUVs) have lower enthalpic peaks and greater widths compared to multilamellar vesicles (MLVs) [2,3]. SUVs also have more mobility and less order in the hydrocarbon chains [2].

The degree of membrane curvature also affects the ability to interdigitate. Bending in the membrane causes increased steric interference in opposing lipid monolayers [44]. As a consequence, ethanol-induced interdigitation is dependent on curvature, with the more highly curved vesicles requiring more ethanol to interdigitate [111,112]. Sonicated DPPC SUVs are not stable in the presence of ethanol above the threshold concentration for interdigitation [112]. Furthermore, SUVs have a tendency to fuse into large unilamellar vesicles (LUVs), which have properties more similar to MLVs [36,113]. The more planar MLVs allow interdigitated lipids to slide by each other with low steric interference and therefore have the lowest threshold concentrations [44,112].

### **2.11. Inhibition of the interdigitated gel phase by cholesterol**

Just as there are chemicals that induce interdigitation, there are chemicals that inhibit the formation of the *L*βI phase. Cholesterol is a chemical inhibitor of interdigitation in a wide variety of lipid systems (Table 4).

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 425

**Figure 12.** Heating (solid red lines) and cooling (dashed blue lines) DSC thermograms of: (A) F-DPPC and (B) 1:1 F-DPPC/DPPC with various concentrations of cholesterol. The cooling scans have been inverted to allow comparison with the heating peaks. For clarity, the thermograms are also offset vertically. Reprinted from Chem. Phys. Lipids, 165, Smith EA, Wang W, Dea PK, Effects of cholesterol on phospholipid membranes: Inhibition of the interdigitated gel phase of F-DPPC and F-DPPC/DPPC,

In a general sense, solvent inhibitors of interdigitation work in the opposite fashion as chemical inducers. Some researchers have focused on the difference of how kosmotropic and chaotropic solutes interact with lipid membranes [122-124]. Kosmotropes deplete the solution at the interface and increase the interfacial tension whereas chaotropes accumulate in the interface and decrease surface tension [125]. The changes in the structure of water due to these types of chemicals can be attributed to alterations in the hydrogen bonding network of water [126,127]. Kosmotropic substances are classified as water-structure makers, meaning that they stabilize the structure of bulk water. When kosmotropes interact with hydrated lipids, they tend to reduce the interfacial area and inhibit interdigitation [122]. Chaotropic chemicals are classified as water-structure breakers and increase the surface area

Pages No. 151-159, Copyright (2012), with permission from Elsevier [117].

**2.12. Chemical inhibition of the interdigitated gel phase** 

per lipid, favoring interdigitation [122,124].


**Table 4.** The inhibition of interdigitation by cholesterol

In non-interdigitated membranes, cholesterol increases the fluidity of the gel phase, broadens the main transition, and decreases the main transition enthalpy [119]. Figure 12 demonstrates that these effects are also seen in membranes where cholesterol eliminates the interdigitated phase [115-117]. The amount of cholesterol required to prevent interdigitation is related to the stability of the *L*βI phase. For DHPC, only ~5 mol% cholesterol is required to eliminate interdigitation [66,116]. However, the amount of cholesterol required to prevent interdigitation is approximately quadrupled for F-DPPC, which exists in the *L*βI phase around 15 °C higher than DHPC [117]. At high cholesterol concentrations the *L*βI phase of F-DPPC is replaced by a non-interdigitated liquid-ordered (*l*o) phase with properties similar to DPPC/cholesterol [117]. On DSC scans, this effect can be observed by the broadening of the main transition peak and a reduction in the *T*m hysteresis (Figure 12). The interdigitated phase of cationic EDPPC is especially resilient in the presence of cholesterol, with interdigitated domains still present at 30 mol% cholesterol [95].

There are multiple reasons why cholesterol-rich membranes disfavor interdigitation. For example, lipid head group crowding is mitigated by cholesterol serving as a spacer between lipids [115]. If cholesterol is placed within an interdigitated membrane, the increased spacing also increases the likelihood that the terminal lipid methyl groups will be exposed at the aqueous interface. Since the interdigitated phase lacks the thick membrane midplane region of non-interdigitated membranes, hydrophobic cholesterol located within the interdigitated phase is more likely to come in contact with water [115]. Furthermore, cholesterol significantly disrupts the lattice structure of gel phase lipids [108,117,120]. Lastly, in the interdigitated phase of highly asymmetrical lyso-lipids, cholesterol can take the place of the missing acyl chain thereby compensating for the size mismatch between the head group and the hydrocarbon chains [118,121].

**Figure 12.** Heating (solid red lines) and cooling (dashed blue lines) DSC thermograms of: (A) F-DPPC and (B) 1:1 F-DPPC/DPPC with various concentrations of cholesterol. The cooling scans have been inverted to allow comparison with the heating peaks. For clarity, the thermograms are also offset vertically. Reprinted from Chem. Phys. Lipids, 165, Smith EA, Wang W, Dea PK, Effects of cholesterol on phospholipid membranes: Inhibition of the interdigitated gel phase of F-DPPC and F-DPPC/DPPC, Pages No. 151-159, Copyright (2012), with permission from Elsevier [117].

#### **2.12. Chemical inhibition of the interdigitated gel phase**

Applications of Calorimetry in a Wide Context –

variety of lipid systems (Table 4).

**Table 4.** The inhibition of interdigitation by cholesterol

interdigitated domains still present at 30 mol% cholesterol [95].

group and the hydrocarbon chains [118,121].

424 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**2.11. Inhibition of the interdigitated gel phase by cholesterol** 

Just as there are chemicals that induce interdigitation, there are chemicals that inhibit the formation of the *L*βI phase. Cholesterol is a chemical inhibitor of interdigitation in a wide

> Interdigitated Lipid System References DPPC/EtOH [114] DPPC/Pressure [31] DPPeth/Tris-HCl [115] DPPG/Tris-HCl [115] DHPC [66,116] EDPPC [95] F-DPPC [117]

3:7 ratio of 16:0 LPC:DPPC [118]

In non-interdigitated membranes, cholesterol increases the fluidity of the gel phase, broadens the main transition, and decreases the main transition enthalpy [119]. Figure 12 demonstrates that these effects are also seen in membranes where cholesterol eliminates the interdigitated phase [115-117]. The amount of cholesterol required to prevent interdigitation is related to the stability of the *L*βI phase. For DHPC, only ~5 mol% cholesterol is required to eliminate interdigitation [66,116]. However, the amount of cholesterol required to prevent interdigitation is approximately quadrupled for F-DPPC, which exists in the *L*βI phase around 15 °C higher than DHPC [117]. At high cholesterol concentrations the *L*βI phase of F-DPPC is replaced by a non-interdigitated liquid-ordered (*l*o) phase with properties similar to DPPC/cholesterol [117]. On DSC scans, this effect can be observed by the broadening of the main transition peak and a reduction in the *T*m hysteresis (Figure 12). The interdigitated phase of cationic EDPPC is especially resilient in the presence of cholesterol, with

There are multiple reasons why cholesterol-rich membranes disfavor interdigitation. For example, lipid head group crowding is mitigated by cholesterol serving as a spacer between lipids [115]. If cholesterol is placed within an interdigitated membrane, the increased spacing also increases the likelihood that the terminal lipid methyl groups will be exposed at the aqueous interface. Since the interdigitated phase lacks the thick membrane midplane region of non-interdigitated membranes, hydrophobic cholesterol located within the interdigitated phase is more likely to come in contact with water [115]. Furthermore, cholesterol significantly disrupts the lattice structure of gel phase lipids [108,117,120]. Lastly, in the interdigitated phase of highly asymmetrical lyso-lipids, cholesterol can take the place of the missing acyl chain thereby compensating for the size mismatch between the head

In a general sense, solvent inhibitors of interdigitation work in the opposite fashion as chemical inducers. Some researchers have focused on the difference of how kosmotropic and chaotropic solutes interact with lipid membranes [122-124]. Kosmotropes deplete the solution at the interface and increase the interfacial tension whereas chaotropes accumulate in the interface and decrease surface tension [125]. The changes in the structure of water due to these types of chemicals can be attributed to alterations in the hydrogen bonding network of water [126,127]. Kosmotropic substances are classified as water-structure makers, meaning that they stabilize the structure of bulk water. When kosmotropes interact with hydrated lipids, they tend to reduce the interfacial area and inhibit interdigitation [122]. Chaotropic chemicals are classified as water-structure breakers and increase the surface area per lipid, favoring interdigitation [122,124].

The differences between chemicals that induce or inhibit interdigitation have also been illustrated according to the interaction free energy of the lipid membrane interface with solvents ([128] and references therein). The solvent free energy relationship can be further split into interactions with the polar head groups and interactions with the hydrophobic lipid chains. In this model, when "good" solvents are added, the interfacial area swells to increase the total contract with the solvent. For organic solvents that are water-miscible and have a high solubility for alkanes, such as acetone and ethanol, the interaction increases the interfacial area by reducing the interaction free energy between the solvent and the interfacial alkyl chains [128]. On the other hand, the interaction of "poor" solvents with lipids is unfavorable and has larger free energy penalty. As a result, the interfacial segments shrink in size to prevent contact with the solvent. Consequently, "good" solvents will favor interdigitation while "poor" solvents will destabilize the *L*βI phase.

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 427

**Figure 13.** Phase transition temperatures of DHPC-MLV at various concentrations of DMSO (mole fraction) determined by DSC. (●) shows gel to liquid-crystalline phase transition temperatures and (○ )

shows *L*βI to *P*β′ phase transition temperatures. Reprinted from Biochim. Biophys. Acta., 1467, Yamashita Y, Kinoshita K, Yamazaki M, Low concentration of DMSO stabilizes the bilayer gel phase rather than the interdigitated gel phase in dihexadecylphosphatidylcholine membrane, Pages No. 395-

**2.13. The interdigitated gel phase versus the inverted hexagonal phase** 

A clear inverse relationship exists between the interdigitated phase gel phase and the inverted hexagonal phase (HII) [56,128]. The major structural factor is the relative size of the lipid headgroup and the attraction/repulsion between headgroups. A lipid that forms the inverted hexagonal phase is unlikely to interdigitate and vice versa. The temperature dependence of these phases is also opposite. For example, with DHPC, the interdigitated phase is present only below the pre-transition. The interdigitated phase requires predominately *trans* confirmations in the hydrocarbon chains, so it is unlikely to form in the liquid crystalline phase where there are abundant *gauche* confirmations and a high degree of disorder [2,37]. In contrast, the inverted hexagonal phase typically forms well above the

This relationship also extends to environmental factors that encourage or discourage interdigitation (Table 5). Chemicals that favor the interdigitated phase such as ethanol tend to destabilize the HII phase [128,124 and references therein]. Interdigitation is favored because the surface area per lipid head group in the *L*βI phase is substantially larger versus non-interdigitated membranes [124]. The HII is the opposite because it requires a small head group area. Solvents that stabilize the HII phase like dimethyl sulfoxide therefore also inhibit interdigitation [56,122,128]. This relationship appears to apply to hydrostatic pressure as well. While increased pressure favors interdigitation (Tables 2 and 3), pressure destabilizes

405, Copyright (2000), with permission from Elsevier [131].

main transition into the liquid crystalline phase [8].

the inverted hexagonal phase in PE lipids [56].

The inhibition of interdigitation has also been described in terms of osmotic stress. Chemicals that apply osmotic stress, such as poly(ethylene glycol) tend to inhibit interdigitation [60]. As in the other models described above, this has been proposed to occur because of a decrease in the repulsive interaction between the lipid head groups.

Dimethyl sulfoxide (DMSO) is an example of a solvent inhibitor of interdigitation. The interaction of DMSO with membranes is of great interest because it can be used as a cryoprotectant for biological material, such as stem cells [129]. DMSO can also enhance the permeability of membranes [130]. The mechanism by which DMSO inhibits interdigitation is by decreasing the repulsion between head groups [131]. The ability of DMSO to form unusually strong hydrogen bonds may explain this effect [132]. This phenomenon can be clearly seen in the phase behavior of DHPC. Just as chemicals that favor interdigitation shift the pre-transition of DHPC to a higher temperature; factors that disfavor interdigitation shift the pre-transition to a lower temperature. The suppression of the pre-transition clearly demonstrates that DMSO destabilizes the *L*βI phase (Figure 13) [131].

A major caveat with these solvent models is that the interactions with lipids are often concentration-dependent. For instance, in the DPPC/DMSO/water system, three distinct effects are found within different DMSO concentration ranges [133]. Perhaps the most remarkable is at above mol fractions of ~0.9 DMSO, the *T*m temperature is greatly elevated and an interdigitated gel phase is formed [133].

The disaccharide trehalose is another example of a chemical inhibitor of interdigitation [124]. Like DMSO, the interactions of trehalose with membranes show promise in the cryopreservation of biological material [129]. In the yeast *Saccharomyces cerevisiae*, trehalose appears to increase viability during ethanol fermentation and provide protection against oxidative stress [134-137]. Similar to DMSO, trehalose disfavors interdigitation by increasing the packing density of the lipid head groups [124,138,139]. However, there is disagreement over the exact molecular interaction with lipids. The main dispute is over whether or not sugars are directly bound to or excluded from the membrane surface [140,141]. Recently, Andersen et al. have tried to explain this discrepancy by proposing that there are two concentration-dependent interactions. In this explanation, trehalose binds strongly to the bilayer at low concentrations, but is gradually expelled above ~0.2 M [141].

426 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

interdigitation while "poor" solvents will destabilize the *L*βI phase.

demonstrates that DMSO destabilizes the *L*βI phase (Figure 13) [131].

bilayer at low concentrations, but is gradually expelled above ~0.2 M [141].

and an interdigitated gel phase is formed [133].

The differences between chemicals that induce or inhibit interdigitation have also been illustrated according to the interaction free energy of the lipid membrane interface with solvents ([128] and references therein). The solvent free energy relationship can be further split into interactions with the polar head groups and interactions with the hydrophobic lipid chains. In this model, when "good" solvents are added, the interfacial area swells to increase the total contract with the solvent. For organic solvents that are water-miscible and have a high solubility for alkanes, such as acetone and ethanol, the interaction increases the interfacial area by reducing the interaction free energy between the solvent and the interfacial alkyl chains [128]. On the other hand, the interaction of "poor" solvents with lipids is unfavorable and has larger free energy penalty. As a result, the interfacial segments shrink in size to prevent contact with the solvent. Consequently, "good" solvents will favor

The inhibition of interdigitation has also been described in terms of osmotic stress. Chemicals that apply osmotic stress, such as poly(ethylene glycol) tend to inhibit interdigitation [60]. As in the other models described above, this has been proposed to occur

Dimethyl sulfoxide (DMSO) is an example of a solvent inhibitor of interdigitation. The interaction of DMSO with membranes is of great interest because it can be used as a cryoprotectant for biological material, such as stem cells [129]. DMSO can also enhance the permeability of membranes [130]. The mechanism by which DMSO inhibits interdigitation is by decreasing the repulsion between head groups [131]. The ability of DMSO to form unusually strong hydrogen bonds may explain this effect [132]. This phenomenon can be clearly seen in the phase behavior of DHPC. Just as chemicals that favor interdigitation shift the pre-transition of DHPC to a higher temperature; factors that disfavor interdigitation shift the pre-transition to a lower temperature. The suppression of the pre-transition clearly

A major caveat with these solvent models is that the interactions with lipids are often concentration-dependent. For instance, in the DPPC/DMSO/water system, three distinct effects are found within different DMSO concentration ranges [133]. Perhaps the most remarkable is at above mol fractions of ~0.9 DMSO, the *T*m temperature is greatly elevated

The disaccharide trehalose is another example of a chemical inhibitor of interdigitation [124]. Like DMSO, the interactions of trehalose with membranes show promise in the cryopreservation of biological material [129]. In the yeast *Saccharomyces cerevisiae*, trehalose appears to increase viability during ethanol fermentation and provide protection against oxidative stress [134-137]. Similar to DMSO, trehalose disfavors interdigitation by increasing the packing density of the lipid head groups [124,138,139]. However, there is disagreement over the exact molecular interaction with lipids. The main dispute is over whether or not sugars are directly bound to or excluded from the membrane surface [140,141]. Recently, Andersen et al. have tried to explain this discrepancy by proposing that there are two concentration-dependent interactions. In this explanation, trehalose binds strongly to the

because of a decrease in the repulsive interaction between the lipid head groups.

**Figure 13.** Phase transition temperatures of DHPC-MLV at various concentrations of DMSO (mole fraction) determined by DSC. (●) shows gel to liquid-crystalline phase transition temperatures and (○ ) shows *L*βI to *P*β′ phase transition temperatures. Reprinted from Biochim. Biophys. Acta., 1467, Yamashita Y, Kinoshita K, Yamazaki M, Low concentration of DMSO stabilizes the bilayer gel phase rather than the interdigitated gel phase in dihexadecylphosphatidylcholine membrane, Pages No. 395- 405, Copyright (2000), with permission from Elsevier [131].

### **2.13. The interdigitated gel phase versus the inverted hexagonal phase**

A clear inverse relationship exists between the interdigitated phase gel phase and the inverted hexagonal phase (HII) [56,128]. The major structural factor is the relative size of the lipid headgroup and the attraction/repulsion between headgroups. A lipid that forms the inverted hexagonal phase is unlikely to interdigitate and vice versa. The temperature dependence of these phases is also opposite. For example, with DHPC, the interdigitated phase is present only below the pre-transition. The interdigitated phase requires predominately *trans* confirmations in the hydrocarbon chains, so it is unlikely to form in the liquid crystalline phase where there are abundant *gauche* confirmations and a high degree of disorder [2,37]. In contrast, the inverted hexagonal phase typically forms well above the main transition into the liquid crystalline phase [8].

This relationship also extends to environmental factors that encourage or discourage interdigitation (Table 5). Chemicals that favor the interdigitated phase such as ethanol tend to destabilize the HII phase [128,124 and references therein]. Interdigitation is favored because the surface area per lipid head group in the *L*βI phase is substantially larger versus non-interdigitated membranes [124]. The HII is the opposite because it requires a small head group area. Solvents that stabilize the HII phase like dimethyl sulfoxide therefore also inhibit interdigitation [56,122,128]. This relationship appears to apply to hydrostatic pressure as well. While increased pressure favors interdigitation (Tables 2 and 3), pressure destabilizes the inverted hexagonal phase in PE lipids [56].

428 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry


Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 429

However, this is not true of all such binary mixtures. Outside of the phase transition regions

Mixing an interdigitated lipid with cholesterol can also produce gel phase coexistence. Cholesterol-poor interdigitated domains and cholesterol-rich non-interdigitated domains have been found in DHPC/cholesterol [116], F-DPPC/cholesterol [117], and EDPPC/cholesterol [95]. For these mixtures, the lipids with the most stable interdigitated

Alternatively, a lipid such as DPPC that can be chemically induced to interdigitate can be mixed with lipids that cannot, such as PE lipids [147]. The DPPC-rich domains will interdigitate with ethanol, but domains composed of mostly PE lipid will not. A similar result can be achieved in mixtures of DPPC/cholesterol/ethanol, where the cholesterol-rich

It is also possible to have coexistence in membranes with only one lipid. For instance, coexisting interdigitated and non-interdigitated phases form in supported F-DPPC membranes where the lateral expansion of the lipid film is restricted [68]. This results in a "frustrated" state, where the energetically favorable interdigitated phase cannot fully form due to constraints in topology and the available surface area [68]. Additionally, while the 16 carbon chain length DPPG does not spontaneously interdigitate, the 18-carbon chain DSPG spontaneously forms an interdigitated gel phase that coexists with a non-interdigitated gel phase [78]. This two-phase coexistence was attributed to a kinetically trapped system that is

One of the most promising applications for the interdigitated gel phase is the creation of large unilamellar vesicles termed interdigitation-fusion (IF) vesicles [44,148]. Figure 14 demonstrates the process for the creation of IF liposomes using ethanol [148]. Below the main transition, the ethanol causes the formation rigid and flat interdigitated sheets [149]. These sheets are surprisingly stable under the *T*m, even when ethanol is removed [149]. When the temperature is raised above the main transition, the sheets fuse into large vesicles. This fusion encapsulates particles from the surrounding solution [149,150]. These materials include other small vesicles, biological macromolecules, colloids, and nanoparticles [149,150]. The amphiphilic nature of lipids allows for the capture of hydrophobic materials [151]. Transmembrane insertion of protein into IF vesicles has also been achieved using

The IF procedure can also be used to create multicompartment vesicle-in-vesicle structures called "vesosomes" [150]. These multicompartment vesicles should be closer replicas of eukaryotic cells than regular vesicles [150,153]. Therefore, vesosomes have the potential to more closely mimic biological conditions and reactions in artificial cells [150,154,155]. Furthermore, the retention of encapsulated material can be substantially increased in vesosomes [151,156,157]. These vesicles are highly customizable because the composition of

phase tend to have a larger region of phase coexistence within the phase diagram.

in DPPC/EDPPC, for instance, there is no gel phase segregation [95].

domains remain non-interdigitated in the presence of ethanol [39,146].

not at thermal equilibrium [78].

electropulsation [152].

**2.16. Applications of the interdigitated gel phase** 

**Table 5.** Factors that stabilize the interdigitated gel (*L*βI) phase and the inverted hexagonal (HII) phase.

### **2.14. Influence of hydration and pH on the** *L***βI phase**

While most interdigitated systems are studied in excess water, interdigitation can be affected at less than full hydration. For instance, interdigitation of DHPC is reliant on hydration, as coexisting interdigitated and non-interdigitated phases are found at low hydration [142,143]. However, the cationic EDPPC may be interdigitated in the dry state [97].

Furthermore, substituting deuterium oxide (D2O) for water slightly disfavors the spontaneous interdigitated phase of DHPC [144]. Using D2O also increases the threshold concentration for the chemically-induced interdigitation of DPPC [27] and increases threshold pressure for interdigitation [145]. These phenomena are explained by the different hydrophobic interactions and interfacial energies in H2O versus D2O [27,144,145].

Changing the pH of the aqueous solution can also affect interdigitation. In DHPC membranes a low pH will inhibit interdigitation [59]. As the pH is lowered the phosphate groups are protonated and ultimately the total repulsive force between head groups is decreased, disfavoring interdigitation [59]. The pH is also highly relevant to the interdigitated phase in charged lipids, such as PGs. At a high pH, the electrostatic repulsion between head groups that encourages interdigitation in PGs is increased [78].

### **2.15. Lipid mixtures and interdigitated/non-interdigitated gel phase coexistence**

Under certain circumstances, interdigitated and non-interdigitated phases can coexist within a membrane even though the boundaries between these domains are considered to be energetically unfavorable [115,116]. The uneven structure between these domains can significantly increase the membrane permeability [146,147]. With the variety of lipids now known to interdigitate, there are many possible lipid systems that will have complex phase diagrams involving the *L*βI phase.

Gel phase coexistence can often be found in binary mixtures of a lipid that can spontaneously interdigitate (e.g. F-DPPC or EDPPC) and one that cannot (e.g. DPPC or PE lipids). For example, at equimolar amounts of F-DPPC and DPPC, interdigitated F-DPPCrich domains create a phase-segregated system [69,117]. On DSC scans this manifests itself as multiple peaks (Figure 8). The peaks with the greatest transition hysteresis likely correspond to interdigitated domains rich in F-DPPC. When the F-DPPC molar fraction is large, the hysteresis is also increased [69]. Additionally, gel phase coexistence occurs in the mixture of 1,2-dielaidoyl-sn-glycero-3-phosphoethanolamine (DEPE) and EDPPC [95]. However, this is not true of all such binary mixtures. Outside of the phase transition regions in DPPC/EDPPC, for instance, there is no gel phase segregation [95].

Mixing an interdigitated lipid with cholesterol can also produce gel phase coexistence. Cholesterol-poor interdigitated domains and cholesterol-rich non-interdigitated domains have been found in DHPC/cholesterol [116], F-DPPC/cholesterol [117], and EDPPC/cholesterol [95]. For these mixtures, the lipids with the most stable interdigitated phase tend to have a larger region of phase coexistence within the phase diagram.

Alternatively, a lipid such as DPPC that can be chemically induced to interdigitate can be mixed with lipids that cannot, such as PE lipids [147]. The DPPC-rich domains will interdigitate with ethanol, but domains composed of mostly PE lipid will not. A similar result can be achieved in mixtures of DPPC/cholesterol/ethanol, where the cholesterol-rich domains remain non-interdigitated in the presence of ethanol [39,146].

It is also possible to have coexistence in membranes with only one lipid. For instance, coexisting interdigitated and non-interdigitated phases form in supported F-DPPC membranes where the lateral expansion of the lipid film is restricted [68]. This results in a "frustrated" state, where the energetically favorable interdigitated phase cannot fully form due to constraints in topology and the available surface area [68]. Additionally, while the 16 carbon chain length DPPG does not spontaneously interdigitate, the 18-carbon chain DSPG spontaneously forms an interdigitated gel phase that coexists with a non-interdigitated gel phase [78]. This two-phase coexistence was attributed to a kinetically trapped system that is not at thermal equilibrium [78].

### **2.16. Applications of the interdigitated gel phase**

Applications of Calorimetry in a Wide Context –

diagrams involving the *L*βI phase.

[97].

428 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**2.14. Influence of hydration and pH on the** *L***βI phase** 

*L*βI HII Large head group repulsion Small head group repulsion Chaotropic chemicals Kosmotropic chemicals High hydrostatic pressure Low hydrostatic pressure Low Temperatures High Temperatures **Table 5.** Factors that stabilize the interdigitated gel (*L*βI) phase and the inverted hexagonal (HII) phase.

While most interdigitated systems are studied in excess water, interdigitation can be affected at less than full hydration. For instance, interdigitation of DHPC is reliant on hydration, as coexisting interdigitated and non-interdigitated phases are found at low hydration [142,143]. However, the cationic EDPPC may be interdigitated in the dry state

Furthermore, substituting deuterium oxide (D2O) for water slightly disfavors the spontaneous interdigitated phase of DHPC [144]. Using D2O also increases the threshold concentration for the chemically-induced interdigitation of DPPC [27] and increases threshold pressure for interdigitation [145]. These phenomena are explained by the different

Changing the pH of the aqueous solution can also affect interdigitation. In DHPC membranes a low pH will inhibit interdigitation [59]. As the pH is lowered the phosphate groups are protonated and ultimately the total repulsive force between head groups is decreased, disfavoring interdigitation [59]. The pH is also highly relevant to the interdigitated phase in charged lipids, such as PGs. At a high pH, the electrostatic repulsion

**2.15. Lipid mixtures and interdigitated/non-interdigitated gel phase coexistence** 

Under certain circumstances, interdigitated and non-interdigitated phases can coexist within a membrane even though the boundaries between these domains are considered to be energetically unfavorable [115,116]. The uneven structure between these domains can significantly increase the membrane permeability [146,147]. With the variety of lipids now known to interdigitate, there are many possible lipid systems that will have complex phase

Gel phase coexistence can often be found in binary mixtures of a lipid that can spontaneously interdigitate (e.g. F-DPPC or EDPPC) and one that cannot (e.g. DPPC or PE lipids). For example, at equimolar amounts of F-DPPC and DPPC, interdigitated F-DPPCrich domains create a phase-segregated system [69,117]. On DSC scans this manifests itself as multiple peaks (Figure 8). The peaks with the greatest transition hysteresis likely correspond to interdigitated domains rich in F-DPPC. When the F-DPPC molar fraction is large, the hysteresis is also increased [69]. Additionally, gel phase coexistence occurs in the mixture of 1,2-dielaidoyl-sn-glycero-3-phosphoethanolamine (DEPE) and EDPPC [95].

hydrophobic interactions and interfacial energies in H2O versus D2O [27,144,145].

between head groups that encourages interdigitation in PGs is increased [78].

One of the most promising applications for the interdigitated gel phase is the creation of large unilamellar vesicles termed interdigitation-fusion (IF) vesicles [44,148]. Figure 14 demonstrates the process for the creation of IF liposomes using ethanol [148]. Below the main transition, the ethanol causes the formation rigid and flat interdigitated sheets [149]. These sheets are surprisingly stable under the *T*m, even when ethanol is removed [149]. When the temperature is raised above the main transition, the sheets fuse into large vesicles. This fusion encapsulates particles from the surrounding solution [149,150]. These materials include other small vesicles, biological macromolecules, colloids, and nanoparticles [149,150]. The amphiphilic nature of lipids allows for the capture of hydrophobic materials [151]. Transmembrane insertion of protein into IF vesicles has also been achieved using electropulsation [152].

The IF procedure can also be used to create multicompartment vesicle-in-vesicle structures called "vesosomes" [150]. These multicompartment vesicles should be closer replicas of eukaryotic cells than regular vesicles [150,153]. Therefore, vesosomes have the potential to more closely mimic biological conditions and reactions in artificial cells [150,154,155]. Furthermore, the retention of encapsulated material can be substantially increased in vesosomes [151,156,157]. These vesicles are highly customizable because the composition of the inner and outer components can be varied [149,150,154]. As a result, it is theoretically possible to use vesosomes as controlled nanoreactors [153,155]. For complex and expensive chemistry such as enzyme reactions, vesosomes should be able to optimize reaction conditions and drastically reduce the amount of reagents needed [155].

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 431

be maintained. The importance of this can be seen in alcohol-induced interdigitation, where the low enthalpy pre-transition is an important aspect of the analysis (Figure 5) [15]. Moreover, the effects of pressure can be measured concomitantly with calorimetry data with the appropriate equipment. This greatly expands the range of the phase diagram that can be

We have shown that DSC can accurately measure changes in the thermodynamic properties of phospholipid membranes with the addition of chemicals that either encourage or discourage interdigitation. DSC is particularly well-suited for the study of chemicallyinduced interdigitation because it is sensitive enough to detect small, incremental changes in phase transition temperatures (Figure 5). With the capability to perform heating and cooling scans at a constant rate, the transition hysteresis can also be easily determined. In addition, the transition enthalpy can highlight the "biphasic" behavior above and below the threshold

Moreover, DSC can reveal how changes in either the hydrocarbon chains (Figure 1) or in the polar head group (Figure 2) will affect the thermodynamics. Modifications that either encourage or discourage interdigitation are summarized in Figure 15. Understanding the importance of structural differences reveals the importance of lipid diversity in biological membranes. Lipid composition can help explain why, for example, a peptide might interact differently with human versus microbial membranes [81]. With the increasing popularity of liposomes for pharmaceutical applications and research, it also is essential to find suitable lipid candidates. For instance, calorimetry can be applied to screen potential IF vesicles by determining whether interdigitation is present and by determining the *T*m temperature.

In addition, more information can be inferred from DSC data than the phase transition temperature. With careful analysis, the nature of the lipid/solvent interaction and the properties of the chemicals themselves can be derived. For example, the characteristics of kosmotropic and chaotropic chemicals are clearly reflected in their effects on lipid membranes (see section 3.12.). This analysis can also increase the understanding of how chemicals interact with biological membranes, such as why chemicals like DMSO and

However, DSC also has limitations when analyzing phospholipid samples. Perhaps the greatest weakness is the lack of direct structural information. As a consequence, relying solely on DSC data can be misleading. For instance, the pre-transition peaks of DPPC and DHPC look similar on DSC thermograms. However, the actual nature of the transition is substantially different (Figure 3). While the structure can often be reasonably inferred from thermodynamic properties, it is not as robust as other experimental techniques [6]. Additionally, while alterations in the macromolecular structure can be reflected in DSC data (see section 3.10.), the changes are not specific enough to be able to infer the true structure.

Overlapping or multiple transitions can also present a problem. In F-DPPC/DPPC, the multiple peaks reflect the presence of phase segregation (Figure 8), but this is not always the case. Multiple DSC peaks can also indicate separate phase transitions that involve the entire

experimented with.

concentration for interdigitation (Figure 6).

trehalose can protect cells during cryopreservation [129].

**Figure 14.** Liposome formation by interdigitation fusion (IF) using ethanol. Reprinted from Biochim. Biophys. Acta., 1195, Ahl PL, Chen L, Perkins WR, Minchey SR, Boni LT, Taraschi TF, Janoff AS, Interdigitation-fusion: a new method for producing lipid vesicles of high internal volume, Pages No. 237-244, Copyright (1994), with permission from Elsevier [148].

As described by Ahl et al. [44], there are four general guidelines for IF liposomes: (1) the lipids must be able to form the interdigitated phase; (2) the precursor liposomes should be small, preferably sonicated SUVs; (3) the temperature of the precursor SUV suspension after the addition of the alcohol must be below the *T*m of the phospholipids; and (4) the temperature should be raised above the *T*m of the phospholipids after the formation of the interdigitated sheets. Therefore, the creation of these liposomes is dependent on the lipid composition. Adding cholesterol and lipids containing *cis* double bonds can compromise the formation of IF liposomes [103,148]. PE lipids are also unsuitable because of their reluctance to interdigitate [44].

A similar result can be achieved using pressure to create pressure-induced fusion (PIF) liposomes [103]. An advantage of this technique is that no organic solvent is required and it is an effective sterilization method [103]. The captured volume of the IF or PIF vesicles is larger than other techniques for liposome preparation ([44] and references therein).

### **3. Conclusions**

As an analytical instrument, DSC offers many advantages. One advantage is the simplicity of the sample preparation procedure. Samples do not have to be supported or spatially oriented and do not require the insertion of a membrane probe. For sensitive low enthalpy phase transitions, it is a great benefit not to need a probe so that the purity of the sample can be maintained. The importance of this can be seen in alcohol-induced interdigitation, where the low enthalpy pre-transition is an important aspect of the analysis (Figure 5) [15]. Moreover, the effects of pressure can be measured concomitantly with calorimetry data with the appropriate equipment. This greatly expands the range of the phase diagram that can be experimented with.

Applications of Calorimetry in a Wide Context –

430 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

conditions and drastically reduce the amount of reagents needed [155].

237-244, Copyright (1994), with permission from Elsevier [148].

to interdigitate [44].

**3. Conclusions** 

the inner and outer components can be varied [149,150,154]. As a result, it is theoretically possible to use vesosomes as controlled nanoreactors [153,155]. For complex and expensive chemistry such as enzyme reactions, vesosomes should be able to optimize reaction

**Figure 14.** Liposome formation by interdigitation fusion (IF) using ethanol. Reprinted from Biochim. Biophys. Acta., 1195, Ahl PL, Chen L, Perkins WR, Minchey SR, Boni LT, Taraschi TF, Janoff AS, Interdigitation-fusion: a new method for producing lipid vesicles of high internal volume, Pages No.

As described by Ahl et al. [44], there are four general guidelines for IF liposomes: (1) the lipids must be able to form the interdigitated phase; (2) the precursor liposomes should be small, preferably sonicated SUVs; (3) the temperature of the precursor SUV suspension after the addition of the alcohol must be below the *T*m of the phospholipids; and (4) the temperature should be raised above the *T*m of the phospholipids after the formation of the interdigitated sheets. Therefore, the creation of these liposomes is dependent on the lipid composition. Adding cholesterol and lipids containing *cis* double bonds can compromise the formation of IF liposomes [103,148]. PE lipids are also unsuitable because of their reluctance

A similar result can be achieved using pressure to create pressure-induced fusion (PIF) liposomes [103]. An advantage of this technique is that no organic solvent is required and it is an effective sterilization method [103]. The captured volume of the IF or PIF vesicles is

As an analytical instrument, DSC offers many advantages. One advantage is the simplicity of the sample preparation procedure. Samples do not have to be supported or spatially oriented and do not require the insertion of a membrane probe. For sensitive low enthalpy phase transitions, it is a great benefit not to need a probe so that the purity of the sample can

larger than other techniques for liposome preparation ([44] and references therein).

We have shown that DSC can accurately measure changes in the thermodynamic properties of phospholipid membranes with the addition of chemicals that either encourage or discourage interdigitation. DSC is particularly well-suited for the study of chemicallyinduced interdigitation because it is sensitive enough to detect small, incremental changes in phase transition temperatures (Figure 5). With the capability to perform heating and cooling scans at a constant rate, the transition hysteresis can also be easily determined. In addition, the transition enthalpy can highlight the "biphasic" behavior above and below the threshold concentration for interdigitation (Figure 6).

Moreover, DSC can reveal how changes in either the hydrocarbon chains (Figure 1) or in the polar head group (Figure 2) will affect the thermodynamics. Modifications that either encourage or discourage interdigitation are summarized in Figure 15. Understanding the importance of structural differences reveals the importance of lipid diversity in biological membranes. Lipid composition can help explain why, for example, a peptide might interact differently with human versus microbial membranes [81]. With the increasing popularity of liposomes for pharmaceutical applications and research, it also is essential to find suitable lipid candidates. For instance, calorimetry can be applied to screen potential IF vesicles by determining whether interdigitation is present and by determining the *T*m temperature.

In addition, more information can be inferred from DSC data than the phase transition temperature. With careful analysis, the nature of the lipid/solvent interaction and the properties of the chemicals themselves can be derived. For example, the characteristics of kosmotropic and chaotropic chemicals are clearly reflected in their effects on lipid membranes (see section 3.12.). This analysis can also increase the understanding of how chemicals interact with biological membranes, such as why chemicals like DMSO and trehalose can protect cells during cryopreservation [129].

However, DSC also has limitations when analyzing phospholipid samples. Perhaps the greatest weakness is the lack of direct structural information. As a consequence, relying solely on DSC data can be misleading. For instance, the pre-transition peaks of DPPC and DHPC look similar on DSC thermograms. However, the actual nature of the transition is substantially different (Figure 3). While the structure can often be reasonably inferred from thermodynamic properties, it is not as robust as other experimental techniques [6]. Additionally, while alterations in the macromolecular structure can be reflected in DSC data (see section 3.10.), the changes are not specific enough to be able to infer the true structure.

Overlapping or multiple transitions can also present a problem. In F-DPPC/DPPC, the multiple peaks reflect the presence of phase segregation (Figure 8), but this is not always the case. Multiple DSC peaks can also indicate separate phase transitions that involve the entire

Applications of Calorimetry in a Wide Context – 432 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

membrane. In the case of EDPPC, different morphologies result in separate DSC peaks (Figure 11) [97]. Overlapping peaks can also obscure individual transitions, especially when there are multiple components in the membrane and the transition peaks are broad.

Differential Scanning Calorimetry Studies of Phospholipid Membranes: The Interdigitated Gel Phase 433

nuclear magnetic resonance, and fluorescence techniques can fill in the gaps ([6] and references therein). Additionally, DSC is highly valuable in determining the relevant

The stability of the interdigitated phase plainly demonstrates the balance of forces within the membrane. Factors as varied as electrostatic and steric interactions, van der Waals forces, solvent binding at the interface, and the presence of double bonds all contribute to the properties of hydrated phospholipid membranes. DSC provides a way to judge the resulting balance of these forces by measuring the stability of different thermodynamic phases. Consequently, the wealth of information calorimetric analysis provides ensures that

temperature range to use for the other experimental techniques.

*Department of Chemistry, Occidental College, Los Angeles, USA* 

**Author details** 

**Abbreviations** 

planar gel phase (*L*β′) ripple gel phase (*P*β′) liquid crystalline phase (*L*α) inverted hexagonal phase (HII) crystalline bilayer phase (*L*c)

liquid-ordered (*l*o)

Corresponding Author

 \*

phosphatidylcholine (PC) phosphatidylglycerol (PG) phosphatidylethanolamine (PE) phosphatidylethanol (Peth)

1,2-dipalmitoyl-*sn*-glycero-3-phosphocholine (DPPC)

1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphocholine (DHPC)

1,2-dipalmitoyl-*sn*-glycero-3-phosphoethanol (DPPeth)

1,3-dipalmitoyl-*sn*-glycero-2-phosphocholine (1,3-DPPC or *β*-DPPC)

1-palmitoyl-2-(16-fluoropalmitoyl)*sn*-glycero-3-phosphocholine (F-DPPC)

Eric A. Smith and Phoebe K. Dea\*

differential scanning calorimetry (DSC) main transition temperature (*T*m) pre-transition temperature (*T*p) small unilamellar vesicle (SUV) large unilamellar vesicle (LUV) multilamellar vesicle (MLV) interdigitation-fusion vesicle (IFV) interdigitated gel phase (*L*βI)

DSC will remain an invaluable tool for the study of membrane biophysics.

**Figure 15.** Schematic representation of factors that favor or disfavor interdigitation.

Fortunately, one of the greatest strengths of DSC data is that it is highly compatible with other analytical techniques. In the case of the *L*βI phase, methods such as x-ray diffraction, nuclear magnetic resonance, and fluorescence techniques can fill in the gaps ([6] and references therein). Additionally, DSC is highly valuable in determining the relevant temperature range to use for the other experimental techniques.

The stability of the interdigitated phase plainly demonstrates the balance of forces within the membrane. Factors as varied as electrostatic and steric interactions, van der Waals forces, solvent binding at the interface, and the presence of double bonds all contribute to the properties of hydrated phospholipid membranes. DSC provides a way to judge the resulting balance of these forces by measuring the stability of different thermodynamic phases. Consequently, the wealth of information calorimetric analysis provides ensures that DSC will remain an invaluable tool for the study of membrane biophysics.

### **Author details**

Applications of Calorimetry in a Wide Context –

432 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

membrane. In the case of EDPPC, different morphologies result in separate DSC peaks (Figure 11) [97]. Overlapping peaks can also obscure individual transitions, especially when

there are multiple components in the membrane and the transition peaks are broad.

**Figure 15.** Schematic representation of factors that favor or disfavor interdigitation.

Fortunately, one of the greatest strengths of DSC data is that it is highly compatible with other analytical techniques. In the case of the *L*βI phase, methods such as x-ray diffraction, Eric A. Smith and Phoebe K. Dea\* *Department of Chemistry, Occidental College, Los Angeles, USA* 

### **Abbreviations**

differential scanning calorimetry (DSC) main transition temperature (*T*m) pre-transition temperature (*T*p) small unilamellar vesicle (SUV) large unilamellar vesicle (LUV) multilamellar vesicle (MLV) interdigitation-fusion vesicle (IFV) interdigitated gel phase (*L*βI) planar gel phase (*L*β′) ripple gel phase (*P*β′) liquid crystalline phase (*L*α) inverted hexagonal phase (HII) crystalline bilayer phase (*L*c) liquid-ordered (*l*o) phosphatidylcholine (PC) phosphatidylglycerol (PG) phosphatidylethanolamine (PE) phosphatidylethanol (Peth) 1,2-dipalmitoyl-*sn*-glycero-3-phosphocholine (DPPC) 1,3-dipalmitoyl-*sn*-glycero-2-phosphocholine (1,3-DPPC or *β*-DPPC) 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphocholine (DHPC) 1-palmitoyl-2-(16-fluoropalmitoyl)*sn*-glycero-3-phosphocholine (F-DPPC) 1,2-dipalmitoyl-*sn*-glycero-3-phosphoethanol (DPPeth)

<sup>\*</sup> Corresponding Author

Applications of Calorimetry in a Wide Context – 434 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

1,2-dipalmitoyl-*sn*-glycero-3-phospho-(1'-*rac*-glycerol) (DPPG) 1-palmitoyl-2-hydroxy-*sn*-glycero-3-phosphocholine (16:0 LPC) 1,2-dipalmitoyl-*sn*-glycero-3-ethylphosphocholine (EDPPC or Et-DPPC) 1,2-dipalmitoyl-*sn*-glycero-3-phosphoethanolamine (DPPE) 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphoethanolamine (DHPE) 1,2-dielaidoyl-*sn*-glycero-3-phosphoethanolamine (DEPE) 1,2-dioleoyl-*sn*-glycero-3-phosphocholine (DOPC) 1,2-dielaidoyl-*sn*-glycero-3-phosphocholine (DEPC) 1-stearoyl-2-oleoyl-phosphatidylcholine (SOPC) 1-palmitoyl-2-oleoyl-phosphatidylcholine (POPC) 1-palmitoyl-2-oleoyl-phosphatidylglycerol (POPG)

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1,2-dipalmitoyl-*sn*-glycero-3-phosphoethanolamine (DPPE) 1,2-di-*O*-hexadecyl-*sn*-glycero-3-phosphoethanolamine (DHPE) 1,2-dielaidoyl-*sn*-glycero-3-phosphoethanolamine (DEPE)

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**Chapter 19** 

© 2013 Saldaña and Martínez-Monteagudo, 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,

**Oxidative Stability of Fats and Oils Measured by** 

Fats and oils are important ingredients in the human diet for nutritional and sensory contributions. The terms fats and oils commonly refer to their phase being solid and liquid, respectively. In addition, lipids are the main ingredients to manufacture various products, such as soups, butter, ready to eat food, among others for the food industry and other products, such as lipstick, creams, etc, for the cosmetic and pharmaceutical industries. Most of these products use vegetable oils from seeds, beans, and nuts, which are important due to their high content in polyunsaturated fatty acids compared to animal fats. However, oxidation of unsaturated fatty acids is the main reaction responsible for the lipid degradation, which is related to the final quality of the product. Furthermore, lipids undergo oxidation, developing unpleasant taste, off flavour and undesirable changes in quality, decreasing the nutritional value of the product and compromising safety of the

In general, oxygen reacts with the double bonds present in lipids, following a free radical mechanism, known as autooxidation. This reaction is quite complex and depends on the lipid type used and the processing conditions. The use of thermal processes, such as frying, sterilization, hydrolysis, etc, accelerate the oxidation of lipids. Various different reactions during lipid oxidation occur simultaneously at different rates. These reactions release heat

Oxidation temperatures and kinetic parameters obtained from DSC can be used to rank and classify lipids in terms of their oxidative stability. Therefore, the reproducibility of oxidation experiments is crucial to evaluate the oxidative stability of lipids using DSC since variables, such as pre-treatment and amount of sample, the heating protocol, among others, strongly

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

**Differential Scanning Calorimetry for Food and** 

**Industrial Applications** 

http://dx.doi.org/10.5772/54486

**1. Introduction** 

M.D.A. Saldaña and S.I. Martínez-Monteagudo

Additional information is available at the end of the chapter

properly cited.

product that might even affect health and well-being.

that can be measured using differential scanning calorimetry (DSC).


## **Oxidative Stability of Fats and Oils Measured by Differential Scanning Calorimetry for Food and Industrial Applications**

M.D.A. Saldaña and S.I. Martínez-Monteagudo

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54486

### **1. Introduction**

Applications of Calorimetry in a Wide Context –

colloid interface sci. 16: 203-214.

Lipases and Serum. ACS nano. 1: 176-182.

Enhanced Drug Retention. Adv. Mater. 23: 2320-2325.

2649.

444 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Giant Unilamellar Lipid Vesicles. J. biol. chem. 272: 25524-25530.

based Systems Based on Vesicle Interactions. Langmuir. 28: 2337-2346.

[150] Kisak ET, Coldren B, Evans CA, Boyer C, Zasadzinski JA (2004) The Vesosome- A

[151] Zasadzinski JA, Wong B, Forbes N, Braun G, Wu G (2011) Novel Methods of Enhanced Retention in and Rapid, Targeted Release from Liposomes, Curr. opin.

[152] Raffy S, Teissié J (1997) Electroinsertion of Glycophorin A in Interdigitation-fusion

[153] Paleos CM, Tsiourvas D, Sideratou Z (2012) Preparation of Multicompartment Lipid-

[154] Chandrawati R, van Koeverden MP, Lomas H, Caruso F (2011) Multicompartment Particle Assemblies for Bioinspired Encapsulated Reactions. J. phys. chem. lett. 2: 2639-

[155] Bolinger P-Y, Stamou D, Vogel H (2008) An Integrated Self-assembled Nanofluidic System for Controlled Biological Chemistries. Angew. chem. int. ed. 47: 5544-5549. [156] Boyer C, Zasadzinski JA (2007) Multiple Lipid Compartments Slow Content Release in

[157] Wong B, Boyer C, Steinbeck C, Peters D, Schmidt J, van Zanten R, Chmelka B, Zasadzinski JA (2011) Design and In Situ Characterization of Lipid Containers with

Multicompartment Drug Delivery Vehicle. Curr. med. chem. 11: 199-219.

Fats and oils are important ingredients in the human diet for nutritional and sensory contributions. The terms fats and oils commonly refer to their phase being solid and liquid, respectively. In addition, lipids are the main ingredients to manufacture various products, such as soups, butter, ready to eat food, among others for the food industry and other products, such as lipstick, creams, etc, for the cosmetic and pharmaceutical industries. Most of these products use vegetable oils from seeds, beans, and nuts, which are important due to their high content in polyunsaturated fatty acids compared to animal fats. However, oxidation of unsaturated fatty acids is the main reaction responsible for the lipid degradation, which is related to the final quality of the product. Furthermore, lipids undergo oxidation, developing unpleasant taste, off flavour and undesirable changes in quality, decreasing the nutritional value of the product and compromising safety of the product that might even affect health and well-being.

In general, oxygen reacts with the double bonds present in lipids, following a free radical mechanism, known as autooxidation. This reaction is quite complex and depends on the lipid type used and the processing conditions. The use of thermal processes, such as frying, sterilization, hydrolysis, etc, accelerate the oxidation of lipids. Various different reactions during lipid oxidation occur simultaneously at different rates. These reactions release heat that can be measured using differential scanning calorimetry (DSC).

Oxidation temperatures and kinetic parameters obtained from DSC can be used to rank and classify lipids in terms of their oxidative stability. Therefore, the reproducibility of oxidation experiments is crucial to evaluate the oxidative stability of lipids using DSC since variables, such as pre-treatment and amount of sample, the heating protocol, among others, strongly

Applications of Calorimetry in a Wide Context – 446 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

influence the results. Other methods that assess the extent of oxidative deterioration are peroxide value (PV) that measures volumetrically the concentration of hydroperoxides, anisidine value (AV), spectrophotometric measurements in the UV region and gas chromatography (GC) analysis for volatile compounds [1-3]. Over the years, thousands of studies have focused on monitoring and evaluating the oxidation of lipids using the Rancimat method, PV, AV, spectrophotometric and GC analysis of fats and oils from various sources. However, it is beyond the scope of this chapter to provide a comprehensive listing of all research using those methods. Comprehensive reviews on the oxidative lipid deterioration using those methods are well discussed somewhere else [4-6].

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 447

which further reacts with triplet oxygen to form peroxyl radicals. Among the starters, hydroxyl radicals are mainly responsible for the initiation of lipid oxidation due to its strong tendency to acquire electrons [10]. These radical products that have high energy, bond to a hydrogen molecule from the lipid structure, forming hydroperoxides (primary oxidation products). The formation of hydroperoxides can be repeated several times, propagating the oxidation reactions. Conjugated fatty acids have more than one type of primary oxidation products and more than one oxidation pathway, as previously reported [11, 12]. A kinetic analysis on autoxidation of methyl-conjugated linoleate showed that monomeric and cyclic peroxides are the major primary oxidation products rather than hydroperoxides [12]. Consequently, addition by Diels Alder-type reaction was earlier suggested as a reaction

The next oxidation stage is the propagation, which consists in the further degradation of hydroperoxides or any other primary oxidation product [1]. There are mainly two types of degradation products from hydroperoxides. First, hydroperoxides interact with double bonds to form monomeric degradation products, such as ketones. The reaction occurs through the reduction of the hydroperoxyl group to hydroxyl derivative. Second, low molecular weight products, that results from the cleavage of the hydroperoxide chain, form aldehydes, ketones, alcohols and hydrocarbons. These low molecular weight compounds are responsible for the rancid and off-flavour produced by oxidized fats [1-4]. Finally, hydroperoxides and primary oxidation products homolyze to form peroxyl or alkoxy radicals that further reacts to form stable dimer-like products. In addition, alcohols, and unsaturated fatty acids (secondary oxidation products) also lead to termination products. The resulting compounds form viscous materials through polymerization as the oxidation proceeds. These polymers are oil insoluble and represent the termination stage of oxidation

mechanism.

[2, 15].

**Figure 1.** Main lipid oxidation reactions.

Among all these methods that measure the extent of lipid oxidation, DSC is widely used as an analytical, diagnostic and research tool from which relevant information, such as onset temperature of oxidation (Ton), height, shape and position of peaks are obtained and used for subsequent kinetic calculations. Kinetic information of lipid oxidation has been reported for a number of lipid systems, such as soybean/anhydrous milk fat blends, unsaturated fatty acids (oleic, linoleic, and linolenic acids), saturated fatty acids (lauric, myristic, palmitic, and stearic acids), "natural" vegetable oils (canola, corn, cottonseed, and soybean oils) and genetically modified vegetable oils.

This chapter focuses on the principles of lipid oxidation, the use of DSC technique to evaluate lipid oxidation, and recent studies on oxidative stability of fats and oils for food and industrial applications, addressing the generation and analysis of DSC thermograms for kinetic studies, where a method to analyse DSC data is described in detail, as well as the interpretation of kinetic parameters obtained at isothermal and non-isothermal conditions. In addition, some results on oxidation kinetics of milk fat after the use of traditional and emerging technologies, such as enzymatic hydrolysis and pressure assisted thermal processing are discussed in detail. Finally, conclusions on lipid oxidation analysis by DSC are provided.

### **2. Fundamentals of lipid oxidation**

Lipid oxidation is a free radical chain reaction that leads to the development of unpleasant flavour and taste, loss of nutrients and formation of toxic compounds [7, 8]. Consequently, the shelf life and the final use of any lipid depend on its resistance to oxidation or oxidative stability [9]. The term lipid oxidation usually refers to a three consecutive reactions or stages, known as initiation, propagation and termination (Figure 1). In the initiation stage, free radicals are formed through thermolysis, where the break of covalent bonds is induced by heat. In addition, free radicals can also be formed due to the presence of enzymes, light, metal ions (Ca2+ and Fe3+) and reactive oxygen species. A list of initiators of lipid oxidation and their standard reduction potentials are provided somewhere else [10]. Compounds that homolyze at relative low temperature (<100C) are important initiators of radical-based chain reactions. Unsaturated fatty acids are compounds that homolyze at lower temperatures compare to saturated fatty acids. The homolytic products of unsaturated fatty acids are hydroxyl radical (HO•), alkyl radical (RO•) and hydroperoxyl radical (HOO•), which further reacts with triplet oxygen to form peroxyl radicals. Among the starters, hydroxyl radicals are mainly responsible for the initiation of lipid oxidation due to its strong tendency to acquire electrons [10]. These radical products that have high energy, bond to a hydrogen molecule from the lipid structure, forming hydroperoxides (primary oxidation products). The formation of hydroperoxides can be repeated several times, propagating the oxidation reactions. Conjugated fatty acids have more than one type of primary oxidation products and more than one oxidation pathway, as previously reported [11, 12]. A kinetic analysis on autoxidation of methyl-conjugated linoleate showed that monomeric and cyclic peroxides are the major primary oxidation products rather than hydroperoxides [12]. Consequently, addition by Diels Alder-type reaction was earlier suggested as a reaction mechanism.

The next oxidation stage is the propagation, which consists in the further degradation of hydroperoxides or any other primary oxidation product [1]. There are mainly two types of degradation products from hydroperoxides. First, hydroperoxides interact with double bonds to form monomeric degradation products, such as ketones. The reaction occurs through the reduction of the hydroperoxyl group to hydroxyl derivative. Second, low molecular weight products, that results from the cleavage of the hydroperoxide chain, form aldehydes, ketones, alcohols and hydrocarbons. These low molecular weight compounds are responsible for the rancid and off-flavour produced by oxidized fats [1-4]. Finally, hydroperoxides and primary oxidation products homolyze to form peroxyl or alkoxy radicals that further reacts to form stable dimer-like products. In addition, alcohols, and unsaturated fatty acids (secondary oxidation products) also lead to termination products. The resulting compounds form viscous materials through polymerization as the oxidation proceeds. These polymers are oil insoluble and represent the termination stage of oxidation [2, 15].

**Figure 1.** Main lipid oxidation reactions.

Applications of Calorimetry in a Wide Context –

genetically modified vegetable oils.

**2. Fundamentals of lipid oxidation** 

are provided.

446 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

deterioration using those methods are well discussed somewhere else [4-6].

influence the results. Other methods that assess the extent of oxidative deterioration are peroxide value (PV) that measures volumetrically the concentration of hydroperoxides, anisidine value (AV), spectrophotometric measurements in the UV region and gas chromatography (GC) analysis for volatile compounds [1-3]. Over the years, thousands of studies have focused on monitoring and evaluating the oxidation of lipids using the Rancimat method, PV, AV, spectrophotometric and GC analysis of fats and oils from various sources. However, it is beyond the scope of this chapter to provide a comprehensive listing of all research using those methods. Comprehensive reviews on the oxidative lipid

Among all these methods that measure the extent of lipid oxidation, DSC is widely used as an analytical, diagnostic and research tool from which relevant information, such as onset temperature of oxidation (Ton), height, shape and position of peaks are obtained and used for subsequent kinetic calculations. Kinetic information of lipid oxidation has been reported for a number of lipid systems, such as soybean/anhydrous milk fat blends, unsaturated fatty acids (oleic, linoleic, and linolenic acids), saturated fatty acids (lauric, myristic, palmitic, and stearic acids), "natural" vegetable oils (canola, corn, cottonseed, and soybean oils) and

This chapter focuses on the principles of lipid oxidation, the use of DSC technique to evaluate lipid oxidation, and recent studies on oxidative stability of fats and oils for food and industrial applications, addressing the generation and analysis of DSC thermograms for kinetic studies, where a method to analyse DSC data is described in detail, as well as the interpretation of kinetic parameters obtained at isothermal and non-isothermal conditions. In addition, some results on oxidation kinetics of milk fat after the use of traditional and emerging technologies, such as enzymatic hydrolysis and pressure assisted thermal processing are discussed in detail. Finally, conclusions on lipid oxidation analysis by DSC

Lipid oxidation is a free radical chain reaction that leads to the development of unpleasant flavour and taste, loss of nutrients and formation of toxic compounds [7, 8]. Consequently, the shelf life and the final use of any lipid depend on its resistance to oxidation or oxidative stability [9]. The term lipid oxidation usually refers to a three consecutive reactions or stages, known as initiation, propagation and termination (Figure 1). In the initiation stage, free radicals are formed through thermolysis, where the break of covalent bonds is induced by heat. In addition, free radicals can also be formed due to the presence of enzymes, light, metal ions (Ca2+ and Fe3+) and reactive oxygen species. A list of initiators of lipid oxidation and their standard reduction potentials are provided somewhere else [10]. Compounds that homolyze at relative low temperature (<100C) are important initiators of radical-based chain reactions. Unsaturated fatty acids are compounds that homolyze at lower temperatures compare to saturated fatty acids. The homolytic products of unsaturated fatty acids are hydroxyl radical (HO•), alkyl radical (RO•) and hydroperoxyl radical (HOO•),

Applications of Calorimetry in a Wide Context – 448 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

### **3. Fundamentals on the use of DSC to study lipid oxidation**

The oxidation mechanisms presented in Figure 1 is an oversimplification because lipids consist of a non-homogeneous mixture of fatty acids. For example, anhydrous milk fat (AMF) is composed of more than 400 fatty acids with extremely diverse chain lengths, position and number of unsaturations of their fatty acids [13, 14]. Consequently, several reactions occur simultaneously at different rates as the oxidation proceeds. Although several methods have been used to analyze and monitor lipid oxidation [1], the oxidation reactions cannot be measured by a single method due to their complexity. Some of the available methods allow quantifying one or more reaction products of the different oxidation stages. Methods, such as oxidative stability index (OSI) and peroxide value (PV) are officially accepted by the American of Analytical Communities (AOAC) [1-6], while other methods are routinely used, such as the Racimat, chemilominescent, and volumetric methods [16].

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 449

which the heat flow signal separates from the baseline (straight line) is considered to be the end of the induction time (arrow (1)). Arrow (1) also indicates the start of oxidation or initiation stage. This stage is short and can be theoretically interpreted as the reaction between the radical, formed during the induction time, and the unsaturated fatty acid. The products of this reaction are unstable hydroperoxides that further react propagating the oxidation. A sudden increase in the heat flow signal is related to the propagation stage. The blue dashed lines illustrate oxidation reactions that occur and cannot be detected by the DSC because they are less exothermal. Finally, arrow (2) illustrates the termination stage, where stable products are formed. The red line is the actual heat flow recorded by the DSC. In the next section, a set of recommended guidelines and laboratory practices are reviewed

**4. Important considerations for measurement of lipid oxidation using** 

used, heating protocol, gas flow rate, and interpretation of DSC thermograms.

Although DSC is a simple, convenient and fast technique to measure lipid oxidation, some recommended guidelines should be considered to obtain reliable and reproducible results. Among those guidelines are the pre-treatment and sample preparation, amount of sample

*Sample pre-treatment* – a representative amount of lipid sample should be used for DSC oxidation measurements. The lipid should be melted at a temperature that ensures that its thermal memory is erased. The melting temperature for lipids is quite diverse, ranging from -25 to 80C. Melting temperatures of some vegetable oils are provided elsewhere [18]. In some lipid-based products, the pre-treatment of sample involves the fat extraction from the food matrix. For example, fat from commercial baby formulas was first extracted with chloroform [19], and then the fat was further dried under vacuum. Therefore, the behavior of these extracted fats might be different from the fat in the original matrix. In addition, a proper chemical description of any pre-treatment must be provided together with the

*Sample preparation* – a liquid sample should be loaded into the DSC pan using a syringe or a Pasteur pipette. The lipid oxidation measured by DSC can be conducted in an open aluminum pan or in a hermetic sealed pan with a pinhole (Figure 3). The main difference between an open pan and a sealed pan with a pinhole is the diffusion of oxygen and the amount of oxygen that is in contact with the sample. This is because the thermal conductivity of the air is smaller than that of the metal of the pan. Indeed, numerical simulations showed that the energy transmitted to the sample comes from the plate, which

A comparison of glycerol oxidation obtained in an open pan and a hermetic sealed pan with a pinhole was earlier reported [21]. For experiments conducted in an open pan, the maximum heat flow temperature of oxidation of glycerol was around 40C lower than those obtained with sealed pans. In an open pan, the vapor produced during lipid oxidation

for the good use and analysis of data using DSC.

**DSC** 

thermal history.

transmits the heat to the pan [20].

An important overlooked characteristic of the oxidation reactions of lipids is the exothermal effect as the oxidation occurs. The released heat from a particular reaction can be measured using DSC in either isothermal or non-isothermal mode. For DSC oxidation measurements, the heat released from the oxidized oil is compared to the heat flowing from an inert reference (empty pan) both heated at the same rate. When the oxidation of the sample occurs, the recorded heat shows a peak which area is proportional to the amount of heat released by the sample. Figure 2 shows an ideal thermogram for the non-isothermal oil oxidation with the three consecutive reaction stages of initiation, propagation and termination.

The heat released by the oxidized oil is recorded as the heat flow signal (*y*-axis) as a function of temperature (*x*-axis). The period of time where no change in the heat flow signal occurs is known as the induction time (Figure 2) that is exemplified at the beginning of the thermogram. An excellent review on the theory and application of induction time is provided elsewhere [17]. The length of the induction time is often considered as a measurement of oil stability. During this period, no chemical reaction occurs. At the point in

**Figure 2.** Ideal thermogram of non-isothermal oil oxidation.

which the heat flow signal separates from the baseline (straight line) is considered to be the end of the induction time (arrow (1)). Arrow (1) also indicates the start of oxidation or initiation stage. This stage is short and can be theoretically interpreted as the reaction between the radical, formed during the induction time, and the unsaturated fatty acid. The products of this reaction are unstable hydroperoxides that further react propagating the oxidation. A sudden increase in the heat flow signal is related to the propagation stage. The blue dashed lines illustrate oxidation reactions that occur and cannot be detected by the DSC because they are less exothermal. Finally, arrow (2) illustrates the termination stage, where stable products are formed. The red line is the actual heat flow recorded by the DSC.

Applications of Calorimetry in a Wide Context –

termination.

448 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**3. Fundamentals on the use of DSC to study lipid oxidation** 

The oxidation mechanisms presented in Figure 1 is an oversimplification because lipids consist of a non-homogeneous mixture of fatty acids. For example, anhydrous milk fat (AMF) is composed of more than 400 fatty acids with extremely diverse chain lengths, position and number of unsaturations of their fatty acids [13, 14]. Consequently, several reactions occur simultaneously at different rates as the oxidation proceeds. Although several methods have been used to analyze and monitor lipid oxidation [1], the oxidation reactions cannot be measured by a single method due to their complexity. Some of the available methods allow quantifying one or more reaction products of the different oxidation stages. Methods, such as oxidative stability index (OSI) and peroxide value (PV) are officially accepted by the American of Analytical Communities (AOAC) [1-6], while other methods are routinely used, such as the Racimat, chemilominescent, and volumetric methods [16].

An important overlooked characteristic of the oxidation reactions of lipids is the exothermal effect as the oxidation occurs. The released heat from a particular reaction can be measured using DSC in either isothermal or non-isothermal mode. For DSC oxidation measurements, the heat released from the oxidized oil is compared to the heat flowing from an inert reference (empty pan) both heated at the same rate. When the oxidation of the sample occurs, the recorded heat shows a peak which area is proportional to the amount of heat released by the sample. Figure 2 shows an ideal thermogram for the non-isothermal oil oxidation with the three consecutive reaction stages of initiation, propagation and

The heat released by the oxidized oil is recorded as the heat flow signal (*y*-axis) as a function of temperature (*x*-axis). The period of time where no change in the heat flow signal occurs is known as the induction time (Figure 2) that is exemplified at the beginning of the thermogram. An excellent review on the theory and application of induction time is provided elsewhere [17]. The length of the induction time is often considered as a measurement of oil stability. During this period, no chemical reaction occurs. At the point in

**Figure 2.** Ideal thermogram of non-isothermal oil oxidation.

In the next section, a set of recommended guidelines and laboratory practices are reviewed for the good use and analysis of data using DSC.

### **4. Important considerations for measurement of lipid oxidation using DSC**

Although DSC is a simple, convenient and fast technique to measure lipid oxidation, some recommended guidelines should be considered to obtain reliable and reproducible results. Among those guidelines are the pre-treatment and sample preparation, amount of sample used, heating protocol, gas flow rate, and interpretation of DSC thermograms.

*Sample pre-treatment* – a representative amount of lipid sample should be used for DSC oxidation measurements. The lipid should be melted at a temperature that ensures that its thermal memory is erased. The melting temperature for lipids is quite diverse, ranging from -25 to 80C. Melting temperatures of some vegetable oils are provided elsewhere [18]. In some lipid-based products, the pre-treatment of sample involves the fat extraction from the food matrix. For example, fat from commercial baby formulas was first extracted with chloroform [19], and then the fat was further dried under vacuum. Therefore, the behavior of these extracted fats might be different from the fat in the original matrix. In addition, a proper chemical description of any pre-treatment must be provided together with the thermal history.

*Sample preparation* – a liquid sample should be loaded into the DSC pan using a syringe or a Pasteur pipette. The lipid oxidation measured by DSC can be conducted in an open aluminum pan or in a hermetic sealed pan with a pinhole (Figure 3). The main difference between an open pan and a sealed pan with a pinhole is the diffusion of oxygen and the amount of oxygen that is in contact with the sample. This is because the thermal conductivity of the air is smaller than that of the metal of the pan. Indeed, numerical simulations showed that the energy transmitted to the sample comes from the plate, which transmits the heat to the pan [20].

A comparison of glycerol oxidation obtained in an open pan and a hermetic sealed pan with a pinhole was earlier reported [21]. For experiments conducted in an open pan, the maximum heat flow temperature of oxidation of glycerol was around 40C lower than those obtained with sealed pans. In an open pan, the vapor produced during lipid oxidation

450 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 451

oxidize a larger sample and the development of a temperature gradient within the sample. Another reason is that the probability of vapor molecules to escape from the pan through the pinhole is considerable reduced. Consequently, the peak maximum temperature shifts to a lower temperature because some of the vapor molecules react, accelerating the termination

**Figure 4.** Illustration of (a) optimum sample size, and (b) excess sample size, in hermetic sealed pans

*Heating rate* – this is one of the most important parameters to determine the oxidative stability and oxidation kinetics of lipids. Before the start of the heating rate, an equilibrium period between 3 and 5 min is recommended to enhance the baseline. At slow heating rates, primary oxidation products, such as hydroperoxides generated during the initial oxidation stage, react with excess of oxygen to form low molecular weight compounds (intermediate oxidation products), accelerating the degradation process. At fast heating rates, these intermediate products are lost through evaporation before they react with the lipid, shifting to a high value the threshold DSC signal [6, 9]. This phenomenon is the basis to calculate the kinetic parameters from a DSC thermogram [28]. However, it is important to highlight that the heating rate should not exceed 25C/min since the temperature of the sample is different from the furnace temperature, creating a temperature gradient which affects the oxidation kinetics [29]. An important overlooked consideration is the temperature range at which the oxidation study should be conducted. In general, the temperature range should start and end as far as possible from the Ton and Tp (approximately a difference of at least 50C).

**Figure 5.** Effect of sample size on non-isothermal oxidation of anhydrous milk fat at 12C/min.

Ton – onset temperature of oxidation; Tp – maximum heat flow temperature.

stage of oxidation.

with a pinhole.

**Figure 3.** Illustrations of common DSC pans: (a) hermetically sealed pan with a pinhole, and (b) an open aluminium pan.

leaves the pan as it is formed. This is because the purge of oxygen acts as a carrier of the vapor. Consequently, part of the mass is lost before reaching the temperature at which the oxidation starts. On the other hand, in a sealed pan with a pinhole, the vapor produced cannot escape from the pan, remaining in the oil. This vapor increases the pressure inside the pan and elevates the oxidation temperature. Contradictory results were reported for the melting temperature of benzoic acid and vanillin obtained in an open pan and a sealed pan with a pinhole [22]. No significant differences were observed in the onset temperature (Ton) and the peak maximum temperature (Tp). Unfortunately, studies with a direct comparison between the types of pans (open and sealed with a pinhole) for oxidation of are scarce in the literature. Indeed, the international organization for standardization does not specify the types of pans for the determination of oxidation induction time [23]. Although hermetic sealed pans with a pinhole have an additional cost to each experimental run, their use avoids contamination of the DSC chamber.

*Sample size* – the amount of sample has significant effect on the shape of the thermogram and reproducibility of the DSC oxidation experiments as it is related to heat transfer within the pan. Figure 4 illustrates the effect of the amount of sample in hermetic sealed pans with a pinhole. For the sample with an optimum sample thickness (Figure 4a), the oil is in contact with excess of oxygen, facilitating oxygen diffusion within the oil sample. An earlier study [7] recommended 1 mm of sample thickness (approximately 1.5 mg of oil) to yield consistent results in non-isothermal oil oxidation. Similarly, no changes on the DSC thermograms using samples between 1 to 4 mg were reported [24]. A ratio of 1:3 (oil:oxygen) not only avoids diffusional limitations [6, 7, 25] but also allows the vapor molecules formed during the oxidation reaction to rapidly escape from the pan [26]. This enhances the baseline and the resolution of the oxidation thermogram [27].

On the other hand, an excess of sample (Figure 4b) creates a temperature gradient within the sample, especially at high heating rates [27]. Also, the diffusion of oxygen is limited, which broader the DSC oxidation curves. This is illustrated in Figure 5 where samples of 3 and 13 mg of anhydrous milk fat (AMF) were oxidized at 12C/min from 100 to 250C. Interestingly, the Ton of oxidation is quite similar between samples (181.12 and 179.33C, respectively). But, the use of 13 mg of AMF leads to a broader and less resolved curve. The deviation of the heat flow signal from the vertical edge (broadening) is attributed to a longer time needed to oxidize a larger sample and the development of a temperature gradient within the sample. Another reason is that the probability of vapor molecules to escape from the pan through the pinhole is considerable reduced. Consequently, the peak maximum temperature shifts to a lower temperature because some of the vapor molecules react, accelerating the termination stage of oxidation.

Applications of Calorimetry in a Wide Context –

avoids contamination of the DSC chamber.

the resolution of the oxidation thermogram [27].

open aluminium pan.

450 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 3.** Illustrations of common DSC pans: (a) hermetically sealed pan with a pinhole, and (b) an

leaves the pan as it is formed. This is because the purge of oxygen acts as a carrier of the vapor. Consequently, part of the mass is lost before reaching the temperature at which the oxidation starts. On the other hand, in a sealed pan with a pinhole, the vapor produced cannot escape from the pan, remaining in the oil. This vapor increases the pressure inside the pan and elevates the oxidation temperature. Contradictory results were reported for the melting temperature of benzoic acid and vanillin obtained in an open pan and a sealed pan with a pinhole [22]. No significant differences were observed in the onset temperature (Ton) and the peak maximum temperature (Tp). Unfortunately, studies with a direct comparison between the types of pans (open and sealed with a pinhole) for oxidation of are scarce in the literature. Indeed, the international organization for standardization does not specify the types of pans for the determination of oxidation induction time [23]. Although hermetic sealed pans with a pinhole have an additional cost to each experimental run, their use

*Sample size* – the amount of sample has significant effect on the shape of the thermogram and reproducibility of the DSC oxidation experiments as it is related to heat transfer within the pan. Figure 4 illustrates the effect of the amount of sample in hermetic sealed pans with a pinhole. For the sample with an optimum sample thickness (Figure 4a), the oil is in contact with excess of oxygen, facilitating oxygen diffusion within the oil sample. An earlier study [7] recommended 1 mm of sample thickness (approximately 1.5 mg of oil) to yield consistent results in non-isothermal oil oxidation. Similarly, no changes on the DSC thermograms using samples between 1 to 4 mg were reported [24]. A ratio of 1:3 (oil:oxygen) not only avoids diffusional limitations [6, 7, 25] but also allows the vapor molecules formed during the oxidation reaction to rapidly escape from the pan [26]. This enhances the baseline and

On the other hand, an excess of sample (Figure 4b) creates a temperature gradient within the sample, especially at high heating rates [27]. Also, the diffusion of oxygen is limited, which broader the DSC oxidation curves. This is illustrated in Figure 5 where samples of 3 and 13 mg of anhydrous milk fat (AMF) were oxidized at 12C/min from 100 to 250C. Interestingly, the Ton of oxidation is quite similar between samples (181.12 and 179.33C, respectively). But, the use of 13 mg of AMF leads to a broader and less resolved curve. The deviation of the heat flow signal from the vertical edge (broadening) is attributed to a longer time needed to

**Figure 4.** Illustration of (a) optimum sample size, and (b) excess sample size, in hermetic sealed pans with a pinhole.

*Heating rate* – this is one of the most important parameters to determine the oxidative stability and oxidation kinetics of lipids. Before the start of the heating rate, an equilibrium period between 3 and 5 min is recommended to enhance the baseline. At slow heating rates, primary oxidation products, such as hydroperoxides generated during the initial oxidation stage, react with excess of oxygen to form low molecular weight compounds (intermediate oxidation products), accelerating the degradation process. At fast heating rates, these intermediate products are lost through evaporation before they react with the lipid, shifting to a high value the threshold DSC signal [6, 9]. This phenomenon is the basis to calculate the kinetic parameters from a DSC thermogram [28]. However, it is important to highlight that the heating rate should not exceed 25C/min since the temperature of the sample is different from the furnace temperature, creating a temperature gradient which affects the oxidation kinetics [29]. An important overlooked consideration is the temperature range at which the oxidation study should be conducted. In general, the temperature range should start and end as far as possible from the Ton and Tp (approximately a difference of at least 50C).

**Figure 5.** Effect of sample size on non-isothermal oxidation of anhydrous milk fat at 12C/min. Ton – onset temperature of oxidation; Tp – maximum heat flow temperature.

*DSC mode* – oxidation experiments can be conducted in either isothermal or non-isothermal mode. Both methods provide analytical information, such as the oxidation induction time in the case of isothermal measurements and the oxidation onset temperature in the case of nonisothermal measurements [28, 29]. Further comparisons on the kinetic studies conducted in either isothermal or non-isothermal mode are discussed in the following sections.

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 453

manually by the DSC operator, relying in the equipment software. Inherently, there is certain degree of uncertainty associated with this procedure. A method that accurately and unambiguously determines those key parameters from the DSC spectra was early proposed for lipid crystallization [30]. This method was first developed to calculate onset, offset, and peak maximum temperatures in crystallization of binary mixtures of different triacylglycerols. More recently, the same methodology was adapted to calculate the start, onset and peak maximum temperatures in non-isothermal oxidation of anhydrous milk fat [9]. Figure 6 exemplifies the location of the start, onset and peak maximum temperatures for anhydrous milk fat rich in conjugated linoleic acid oxidized at 15C/min in a hermetic sealed

Once the DSC curves are generated, the error associated with the raw data is calculated through standard deviation. Then, the first and second derivatives are calculated. The error is obtained from the baseline, which in Figure 6 corresponds to the segment of 140 to 178C. This is essential since the signal variability can be misinterpreted as a thermal event. In this method, a true thermal event was considered when the heat flow signal is twice greater than the standard deviation of the baseline. This criterion is known as the departure value (inlet Figure 6a). To locate the start temperature of oxidation, three criteria were considered. Firstly, the first derivative of the signal shows an inflexion point between a maximum and a minimum point of the signal (arrow (1)). Secondly, the second derivative reaches a maximum point on the heat flow signal (arrow (2)). Finally, the heat flow signal should be greater than the departure value (inlet). Tp was obtained when the first derivative of the signal intersects with the *x*-axis (arrow (3)) and the second derivative reached a maximum point on the signal (arrow (4)). Ton was obtained extrapolating the tangent drawn on the

In chemical reactions, the degree of conversion (0 ≤ α ≤ 1) or extent of reaction of a particular compound is defined by moles at a given time divided by the initial moles [29]. Similarly, α in thermal analysis is defined by the heat flow at a given time or temperature divided by the heat flow at time or temperature at which the maximum heat flow signal is reached. The heat flow from the DSC spectra is converted to α based on the initial (signalo) and final

*o*

At a given degree of conversion, the reaction kinetics is described by a single-step reaction that follows an Arrhenius type equation within a narrow range of temperature. Then, the

*<sup>d</sup> RT Aexp f dt*

overall kinetics [31-34] is the result of multiple single-step reactions in the form:

*signal signal signal signal*

*o f*

*a E*

()

(1)

(2)

pan with a pinhole.

steepest slope of Tp.

**5.2. Iso-conversional method** 

(signalf) heat flow signals, as shown in equation (1).

### **5. Analysis of DSC thermograms**

### **5.1. Location of key parameters**

The analysis and interpretation of the generated DSC spectra consist in identifying key parameters, such as the induction time, onset and peak maximum temperatures. These key parameters are manually obtained from the DSC spectra. The *Ton* is obtained extrapolating the tangent drawn on the steepest slope of *Tp*. This procedure is usually performed

**Figure 6.** Anhydrous milk fat rich in conjugated linoleic acid oxidized at 15°C min-1. (a) Determination of the start temperature (Ts) (inlet), onset temperature (Ton) and maximum heat flow temperature (Tp), and (b) zoom on the first and second derivatives that precisely locates the Ts, Ton, and Tp

manually by the DSC operator, relying in the equipment software. Inherently, there is certain degree of uncertainty associated with this procedure. A method that accurately and unambiguously determines those key parameters from the DSC spectra was early proposed for lipid crystallization [30]. This method was first developed to calculate onset, offset, and peak maximum temperatures in crystallization of binary mixtures of different triacylglycerols. More recently, the same methodology was adapted to calculate the start, onset and peak maximum temperatures in non-isothermal oxidation of anhydrous milk fat [9]. Figure 6 exemplifies the location of the start, onset and peak maximum temperatures for anhydrous milk fat rich in conjugated linoleic acid oxidized at 15C/min in a hermetic sealed pan with a pinhole.

Once the DSC curves are generated, the error associated with the raw data is calculated through standard deviation. Then, the first and second derivatives are calculated. The error is obtained from the baseline, which in Figure 6 corresponds to the segment of 140 to 178C. This is essential since the signal variability can be misinterpreted as a thermal event. In this method, a true thermal event was considered when the heat flow signal is twice greater than the standard deviation of the baseline. This criterion is known as the departure value (inlet Figure 6a). To locate the start temperature of oxidation, three criteria were considered. Firstly, the first derivative of the signal shows an inflexion point between a maximum and a minimum point of the signal (arrow (1)). Secondly, the second derivative reaches a maximum point on the heat flow signal (arrow (2)). Finally, the heat flow signal should be greater than the departure value (inlet). Tp was obtained when the first derivative of the signal intersects with the *x*-axis (arrow (3)) and the second derivative reached a maximum point on the signal (arrow (4)). Ton was obtained extrapolating the tangent drawn on the steepest slope of Tp.

### **5.2. Iso-conversional method**

Applications of Calorimetry in a Wide Context –

**5. Analysis of DSC thermograms** 

**5.1. Location of key parameters** 

452 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

*DSC mode* – oxidation experiments can be conducted in either isothermal or non-isothermal mode. Both methods provide analytical information, such as the oxidation induction time in the case of isothermal measurements and the oxidation onset temperature in the case of nonisothermal measurements [28, 29]. Further comparisons on the kinetic studies conducted in

The analysis and interpretation of the generated DSC spectra consist in identifying key parameters, such as the induction time, onset and peak maximum temperatures. These key parameters are manually obtained from the DSC spectra. The *Ton* is obtained extrapolating the tangent drawn on the steepest slope of *Tp*. This procedure is usually performed

**Figure 6.** Anhydrous milk fat rich in conjugated linoleic acid oxidized at 15°C min-1. (a) Determination of the start temperature (Ts) (inlet), onset temperature (Ton) and maximum heat flow temperature (Tp),

and (b) zoom on the first and second derivatives that precisely locates the Ts, Ton, and Tp

either isothermal or non-isothermal mode are discussed in the following sections.

In chemical reactions, the degree of conversion (0 ≤ α ≤ 1) or extent of reaction of a particular compound is defined by moles at a given time divided by the initial moles [29]. Similarly, α in thermal analysis is defined by the heat flow at a given time or temperature divided by the heat flow at time or temperature at which the maximum heat flow signal is reached. The heat flow from the DSC spectra is converted to α based on the initial (signalo) and final (signalf) heat flow signals, as shown in equation (1).

$$\alpha = \frac{\text{signal}\_o - \text{signal}}{\text{signal}\_o - \text{signal}\_f} \tag{1}$$

At a given degree of conversion, the reaction kinetics is described by a single-step reaction that follows an Arrhenius type equation within a narrow range of temperature. Then, the overall kinetics [31-34] is the result of multiple single-step reactions in the form:

$$\frac{d\alpha}{dt} = A \exp^{\left(\frac{-E\_x}{RT}\right)} f(\alpha) \tag{2}$$

where *t* is the time, *A* is the pre-exponential factor, *Ea* is the effective activation energy, *T* is the temperature, and *f* (*α*) is the reaction model. This procedure, known as iso-conversional or model-free method, is used to calculate kinetic triplet parameters (effective activation energy, *Ea*, pre-exponential factor, *A* and constant rate, *k*) in thermally stimulated reactions [29-34]. As known, reactions are the sequence of physical changes that can be measured by thermal techniques.

In non-isothermal oxidation of lipids, the consumption of oxygen can be neglected due to the large excess of oxygen generated by a constant flow rate (>25 mL/min). Such condition allows the formation of peroxides, being independently of the oxygen concentration, which also means that the autoxidation is a first order reaction [7, 9]. This is an essential assumption for the calculation of the kinetic triplet parameters (*Ea*, *A*, and *k*). A commonly used iso-conversional method is the Ozawa-Flynn-Wall method. Using this method, a set of data (*Ts, Ton*, and *Tp*) was obtained for constant heating rates (*β= dT/dt*) from which the kinetic parameters were calculated using the following equations:

$$a \log \beta = a \frac{1}{T} + b$$

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 455

standard protocol for the determination of the oxidation induction time has been developed

Figure 7a illustrates the standard protocol for determination of oxidation induction time (OIT). The polymer sample (15 mg) is rapidly heated under nitrogen atmosphere (≤ 20C/min) until it reaches the temperature that corresponds to time, t1, which is the starting point for OIT determination. At *t1*, the atmosphere is switched to oxygen and the sample is held at the same temperature until t2 is reached. The difference between t2 and t1 is the OIT. A disadvantage of this protocol is to find an adequate temperature for the isothermal stage. For example, the use of a low temperature might considerably increase the OIT while the use of a high temperature might oxidize the sample immediately, making difficult to obtain a reliable baseline. In tests conducted in 16 different laboratories, it was demonstrated that OIT is associated with a high degree of uncertainty. On the other hand, Figure 7b illustrates the experimental protocol for the determination of oxidation induction temperature (OIT\*). In this case, the sample is continuously heated at a constant heat rate (for example,

**Figure 7.** Determination of oxidation induction time, OIT (a), and oxidation induction temperature, OIT\* (b). Tm – melting temperature, t1 – start of the oxidation induction time, t2 – end of the oxidation

Tables 1 and 2 summarize oxidation studies of fats and oils using DSC. Most of the isothermal studies were conducted between 80 and 180C with different flow rates varying from 10 to 100 mL/min. The amount of sample used also varied from 3 to 30 mg and most of these studies used open pans. The oxidation onset times were quite diverse (23-108 min) and therefore the *Ea* values ranged from 50 to 130 kJ/mol, depending mainly on the oil composition, temperature, and amount of sample. For the non-isothermal studies, the temperature ranged from 50 to 350C and the heating rate used ranged from 1 to 25C/min. The onset oxidation temperatures depended on the heating rate and oil

for lipids.

12C/min) under oxygen atmosphere.

induction time. Adapted from reference [35].

composition.

**6. Kinetic studies of oxidation of fats and oils** 

where *β* is the heating rate (K/min) and *T* is the temperature *Ts, Ton*, or *Tp* (K). By plotting log β against *1/T*, the effective activation energy (*Ea*) and the pre-exponential factor (*A*) were determined directly from the slope and intercept according to:

$$a = -0.4567 \frac{E\_a}{R} \tag{4}$$

$$b = -2.315 + \log\left(A\frac{E\_a}{T}\right) \tag{5}$$

where *a* and *b* are the slope and intercept from equation (3), respectively, and *R* is the universal gas constant (8.31 J/mol K). Therefore, the effective activation energy (*Ea*) and the constant rate (*k*) are calculated from:

$$E\_a = -2.19 \, R \frac{d \log \beta}{dT^{-1}} \tag{6}$$

$$k = A \exp^{\left(\frac{E\_a}{RT}\right)}\tag{7}$$

#### **5.3. Induction time**

As mentioned earlier, the period of time where no change in the heat flow signal occurs is known as the induction time and its length is considered as a measurement of lipid stability [17]. The determination of the induction period is routinely conducted to evaluate stability of oils, lubricants, biodiesel, and pharmaceutical products [34-38]. Unfortunately, no standard protocol for the determination of the oxidation induction time has been developed for lipids.

Applications of Calorimetry in a Wide Context –

thermal techniques.

454 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

kinetic parameters were calculated using the following equations:

determined directly from the slope and intercept according to:

constant rate (*k*) are calculated from:

**5.3. Induction time** 

where *t* is the time, *A* is the pre-exponential factor, *Ea* is the effective activation energy, *T* is the temperature, and *f* (*α*) is the reaction model. This procedure, known as iso-conversional or model-free method, is used to calculate kinetic triplet parameters (effective activation energy, *Ea*, pre-exponential factor, *A* and constant rate, *k*) in thermally stimulated reactions [29-34]. As known, reactions are the sequence of physical changes that can be measured by

In non-isothermal oxidation of lipids, the consumption of oxygen can be neglected due to the large excess of oxygen generated by a constant flow rate (>25 mL/min). Such condition allows the formation of peroxides, being independently of the oxygen concentration, which also means that the autoxidation is a first order reaction [7, 9]. This is an essential assumption for the calculation of the kinetic triplet parameters (*Ea*, *A*, and *k*). A commonly used iso-conversional method is the Ozawa-Flynn-Wall method. Using this method, a set of data (*Ts, Ton*, and *Tp*) was obtained for constant heating rates (*β= dT/dt*) from which the

> <sup>1</sup> log *a b T*

where *β* is the heating rate (K/min) and *T* is the temperature *Ts, Ton*, or *Tp* (K). By plotting log β against *1/T*, the effective activation energy (*Ea*) and the pre-exponential factor (*A*) were

0.4567 *<sup>a</sup> <sup>E</sup>*

1

*dT*

*a E*

 

2.315 *<sup>a</sup> <sup>E</sup> b log A <sup>T</sup>*

where *a* and *b* are the slope and intercept from equation (3), respectively, and *R* is the universal gas constant (8.31 J/mol K). Therefore, the effective activation energy (*Ea*) and the

> log 2.19 *<sup>a</sup> <sup>d</sup> E R*

> > *RT k A exp*

As mentioned earlier, the period of time where no change in the heat flow signal occurs is known as the induction time and its length is considered as a measurement of lipid stability [17]. The determination of the induction period is routinely conducted to evaluate stability of oils, lubricants, biodiesel, and pharmaceutical products [34-38]. Unfortunately, no

(3)

*<sup>R</sup>* (4)

(6)

(7)

(5)

*a*

Figure 7a illustrates the standard protocol for determination of oxidation induction time (OIT). The polymer sample (15 mg) is rapidly heated under nitrogen atmosphere (≤ 20C/min) until it reaches the temperature that corresponds to time, t1, which is the starting point for OIT determination. At *t1*, the atmosphere is switched to oxygen and the sample is held at the same temperature until t2 is reached. The difference between t2 and t1 is the OIT. A disadvantage of this protocol is to find an adequate temperature for the isothermal stage. For example, the use of a low temperature might considerably increase the OIT while the use of a high temperature might oxidize the sample immediately, making difficult to obtain a reliable baseline. In tests conducted in 16 different laboratories, it was demonstrated that OIT is associated with a high degree of uncertainty. On the other hand, Figure 7b illustrates the experimental protocol for the determination of oxidation induction temperature (OIT\*). In this case, the sample is continuously heated at a constant heat rate (for example, 12C/min) under oxygen atmosphere.

**Figure 7.** Determination of oxidation induction time, OIT (a), and oxidation induction temperature, OIT\* (b). Tm – melting temperature, t1 – start of the oxidation induction time, t2 – end of the oxidation induction time. Adapted from reference [35].

### **6. Kinetic studies of oxidation of fats and oils**

Tables 1 and 2 summarize oxidation studies of fats and oils using DSC. Most of the isothermal studies were conducted between 80 and 180C with different flow rates varying from 10 to 100 mL/min. The amount of sample used also varied from 3 to 30 mg and most of these studies used open pans. The oxidation onset times were quite diverse (23-108 min) and therefore the *Ea* values ranged from 50 to 130 kJ/mol, depending mainly on the oil composition, temperature, and amount of sample. For the non-isothermal studies, the temperature ranged from 50 to 350C and the heating rate used ranged from 1 to 25C/min. The onset oxidation temperatures depended on the heating rate and oil composition.

### **6.1. Isothermal studies**

For isothermal oxidation, the heat flow signal generated at constant temperature is plotted against time (Fig 7a). From these curves, the start of the oxidation (t1) and the end of the oxidation induction time (t2) are first located and then used for analysis [39].

Oxidative Stability of Fats and Oils Measured by

At 130C


At 140C - *B. purpurea* = 48 - Rice = 18 - Cotton = 20

140C - Buriti = 3.3 - Rubber = 3.3 - Passion = 30.3

; k150C = 0.073

; k150C = 0.084

; k150C = 0.201

[42]

[43]

[44]

[45]

[49]

[47, 48]

[50]

[51, 52]

[53]

[54]

[55]

Differential Scanning Calorimetry for Food and Industrial Applications 457

**Oxidation induction times (OIT, min) Ref.**

At 130C - *B. purpurea* = 99 - Rice = 36 - Cotton = 42

130C - Buriti = 7.8 - Rubber = 7.5 - Passion = 66.5

At 120C

110C - Buriti = 42 - Rubber = 51 - Passion = 369

At 110C - *B. purpurea* = 483 - Rice = 132 - Cotton = 172

100C - Buriti = 116 - Rubber = 106 - Passion = 778 - Olive = 108 - Blackcurrant = 95 - Corn = 78 - Peanut = 68 - Sunflower = 69 - Linseed = 50 - Safflower = 43

At 120C - *B. purpurea* = 269 - Rice = 72 - Cotton = 92

120C - Buriti = 23 - Rubber = 25 - Passion = 163



**Lipid Experimental protocol Kinetic parameters (***Ea***, kJ/mol;** *A* **min-1;** *k***, min) Ref.**










Cocoa butter/cocoa butter fat like


**Table 1.** Summary of isothermal oxidation studies of lipids using differential scanning calorimetry

A comparative study of sunflower seed oil and rapeseed oil oxidation using DSC and volatile analysis showed that the ratio of hexanal/2-trans-nonenal linearly correlates with



; k160C = 0.013

**Lipid Experimental** 


Linoleic, linolenic, peanut, oleic, stearic, safflower and blackcurrant seed

Rice, cotton seed and *B. purpurea*

Buriti, rubber seed and passion fruit oil

Rapeseed and sunflower

Rapeseed, soybean, corn and sunflower

Soybean, rapeseed, and sunflower oil

Soybean, rapeseed, corn and peanut oil

Lauric, myristic, palmitic, stearic acids and their ester

Blends of cocoa butter/cocoa butter fat like

Canola, coconut, corn, grapeseed, peanut, palm kernel, palm olein, safflower, sesame and soybean

Linseed - 130C

**protocol**












140C


Table 1 summarizes the isothermal oxidation studies of fats and oils, such as peanut, safflower seed, blackcurrant seed, rice bran, cotton seed, Buriti seed, passion fruit seed, sunflower seed, soybean, linseed, canola seed, coconut, grape seed, palm seed, and sesame seed. Earlier studies on isothermal oxidation were imprecise because the baselines obtained were highly unstable, making it difficult to obtain oxidation onset times [40, 41]. However, stable baselines were currently obtained in the isothermal oxidation of linoleic, linolenic, oleic, stearic, peanut, safflower and blackcurrant seed oils [42]. These oils were heated under argon flow. After thermal equilibrium was reached, the gas flow was switched to oxygen, allowing the oxidation to start. The temperature used to conduct the oxidation test should be far below the self-ignition temperature for fats and oils (~ 350C). Thus, the recorded thermal events are due to lipid oxidation rather than combustion. Using this approach, the obtained induction times were reproducible and highly influenced by the test temperature and sample composition. Attempting to validate the isothermal DSC oxidation, an earlier study [43] isothermally oxidized purpurea seed, rice bran and cotton seed oils using the DSC and the Rancimat methods. At each tested temperature, the DSC oxidation times were shorter than those obtained using the Rancimat method for the same oil. Despite these differences, the oxidation times were satisfactorily correlated with the Rancimat induction times. Similarly, longer induction times were obtained with the use of the Rancimat method for Buriti pulp seed oil, rubber seed oil and passion fruit seed oil [44]. In these studies, DSC rapidly reaches the threshold of the heat flow signal. This difference is attributed to the small sample used in DSC experiments, allowing a higher oil-oxygen ratio compared to the Rancimat method. Moreover, to oxidize the oil, DSC employs pure oxygen (99% purity) while the Rancimat method uses air (~21% of oxygen).

#### Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 457


Applications of Calorimetry in a Wide Context –

**6.1. Isothermal studies** 

456 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

while the Rancimat method uses air (~21% of oxygen).

oxidation induction time (t2) are first located and then used for analysis [39].

For isothermal oxidation, the heat flow signal generated at constant temperature is plotted against time (Fig 7a). From these curves, the start of the oxidation (t1) and the end of the

Table 1 summarizes the isothermal oxidation studies of fats and oils, such as peanut, safflower seed, blackcurrant seed, rice bran, cotton seed, Buriti seed, passion fruit seed, sunflower seed, soybean, linseed, canola seed, coconut, grape seed, palm seed, and sesame seed. Earlier studies on isothermal oxidation were imprecise because the baselines obtained were highly unstable, making it difficult to obtain oxidation onset times [40, 41]. However, stable baselines were currently obtained in the isothermal oxidation of linoleic, linolenic, oleic, stearic, peanut, safflower and blackcurrant seed oils [42]. These oils were heated under argon flow. After thermal equilibrium was reached, the gas flow was switched to oxygen, allowing the oxidation to start. The temperature used to conduct the oxidation test should be far below the self-ignition temperature for fats and oils (~ 350C). Thus, the recorded thermal events are due to lipid oxidation rather than combustion. Using this approach, the obtained induction times were reproducible and highly influenced by the test temperature and sample composition. Attempting to validate the isothermal DSC oxidation, an earlier study [43] isothermally oxidized purpurea seed, rice bran and cotton seed oils using the DSC and the Rancimat methods. At each tested temperature, the DSC oxidation times were shorter than those obtained using the Rancimat method for the same oil. Despite these differences, the oxidation times were satisfactorily correlated with the Rancimat induction times. Similarly, longer induction times were obtained with the use of the Rancimat method for Buriti pulp seed oil, rubber seed oil and passion fruit seed oil [44]. In these studies, DSC rapidly reaches the threshold of the heat flow signal. This difference is attributed to the small sample used in DSC experiments, allowing a higher oil-oxygen ratio compared to the Rancimat method. Moreover, to oxidize the oil, DSC employs pure oxygen (99% purity)

**Table 1.** Summary of isothermal oxidation studies of lipids using differential scanning calorimetry

A comparative study of sunflower seed oil and rapeseed oil oxidation using DSC and volatile analysis showed that the ratio of hexanal/2-trans-nonenal linearly correlates with

Applications of Calorimetry in a Wide Context – 458 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

the onset heat flow signal of the DSC spectra [44]. In addition, a correlation between the peroxide values with the oxidation onset time was developed to monitor rapeseed oil oxidation [44]. Unfortunately, the correlation was valid only for oils with peroxide values lower than 30 mmol O2/kg oil. In other study, the experimental oxidation data obtained from electron spin spectroscopy was compared with the data obtained from DSC oxidation [46]. The onset oxidation times were highly correlated for different fat and oil blends. However, the obtained correlations were valid only at moderate temperatures of 60C, which considerably limits the applicability of electron spin spectroscopy for oxidation analysis.

An investigation of isothermal oxidation of oils (e.g. rapeseed, soybean, corn and sunflower oils) used onset time (ton) to rank the oxidized oils in terms of their oxidative stability [47]. The high maximum heat flow time (tp) value indicates that the oil is more stable. Although these relationships were statistically validated, a single parameter to evaluate the oxidative stability can lead to overestimation of the oxidative stability. In the same study, the authors considered *tp* to be proportional to the rate of oxidation, which might not be valid. Indeed, peroxide value determinations showed that *tp* represents the oxidation termination stage while *ton* is associated with the rate of initiation [48]. Furthermore, the addition of antioxidants prolongs only *ton* while *tp* values were minimally affected [48]. The same behavior was also observed in the isothermal oxidation of linseed oil with the use of antioxidants [49]. The addition of BHA (butylated hydroxyl anisole) and a mixture of antioxidants (tocopherol, ascorbyl palmitate, citric acid and ascorbic acid) prolonged the onset time at 130C. All these approaches provided information of great value for validation of the DSC isothermal oxidation. However, these equations are limited for a set of temperatures and specific oils (Table 1). Additional factors, such as degree of saturation, amount of free fatty acids, chain length and the presence of natural antioxidants were not considered.

Using the isothermal method, the sample is heated at a constant temperature and the released heat is recorded as a function of temperature. Such situation allows the identification of the maximum heat flow time (*tm*), which linearly correlates with the temperature [39,48, 49].

$$
\log t\_m = A \cdot T^{-1} + B \tag{8}
$$

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 459

kinetic parameters of isothermally heated rapeseed, soybean and sunflower seed oils at different temperatures was proposed [50]. The authors correlated the oxidation induction times with the tested temperature using Arrhenius-like equations. The obtained kinetic parameters were comparable to those obtained by the Rancimat method. The onset time values of 12 different oils obtained by DSC were reduced by half of their previous values for every increase of 10C in the oxidation temperature [51]. These relationships were further used to obtain kinetic parameters of DSC oxidation [52]. The *Ea* values of rapeseed, soybean, corn and peanut oils were strongly influenced by the amount of saturated fatty acids [53]. The oxidation of saturated fatty acids (C12-C18) and their esters revealed that the Ea values (100-125 kJ/mol) were within the same range for all the tested oils [54]. This suggests that the isothermal oxidation is not influenced by the carbon chain length. Another important conclusion from this investigation [54] is that the start of oxidation is similar for fatty acids, their esters and triglycerides. The kinetic oxidation parameters of cocoa butter blends were obtained using the oxidation onset time [55]. The blends were oxidized from 130 to 160C in an open pan. Interestingly, the *Ea* and *A* values were slightly affected by the addition of saturated fatty acids. But, *k* values considerably changed with the amount of saturated fatty acids. Thus, *k* values can be used to rank the oxidative stability of cocoa butter blends. However, the use of *k* values to evaluate oxidative stability might be valid only at the temperature tested since changes in the reaction mechanisms can occur as a function of

For non-isothermal oxidation studies, two maximum heat flow peaks are commonly observed in the DSC spectra [56-59]. But, only the first peak is related to lipid oxidation. This was demonstrated in non-isothermal oxidation studies of corn and linseed oils with different peroxide values [57]. A decrease in the onset temperature was observed as the peroxide value increased. Contrary, the first and second peak temperatures were not affected by increasing the peroxide value. Consequently, the first peak can be related to hydroperoxides formation while the second peak can be due to further oxidation of peroxides. In an earlier study [58], the weight loss of lecithin during non-isothermal heating under nitrogen flow rate was analyzed. The thermogravimetric analysis showed that in the temperature range of the first peak only 4% of weight was lost but above that temperature, the weight loss considerably increased. Therefore, changes in the DSC signal within the range of the first peak temperature were attributed to oxidation and those changes above that temperature corresponded to thermal degradation rather than

**Figure 8.** Reaction mechanism proposed for lipid oxidation under non-isothermal conditions.

temperature.

**6.2. Non-isothermal studies** 

oxidation (Figure 8).

where A and B are regression parameters. Due to the excess of oxygen generated by a constant flow rate, the formation of peroxides is considered to be independent of the oxygen concentration, which also means that the autoxidation is a first order reaction [48, 49]. This is an essential assumption for the calculation of kinetic parameters, such as effective activation energy (*Ea*), pre-exponential factor (*A*), and reaction rate (*k*).

$$E\_a = 2.19 \cdot R \cdot \frac{d\log(t\_m)}{dT^{-1}}\tag{9}$$

Equations 8 and 9 have been applied not only to obtain the maximum heat flow signal [47- 49] but also to obtain the oxidation onset time. An attempt to correlate induction times and kinetic parameters of isothermally heated rapeseed, soybean and sunflower seed oils at different temperatures was proposed [50]. The authors correlated the oxidation induction times with the tested temperature using Arrhenius-like equations. The obtained kinetic parameters were comparable to those obtained by the Rancimat method. The onset time values of 12 different oils obtained by DSC were reduced by half of their previous values for every increase of 10C in the oxidation temperature [51]. These relationships were further used to obtain kinetic parameters of DSC oxidation [52]. The *Ea* values of rapeseed, soybean, corn and peanut oils were strongly influenced by the amount of saturated fatty acids [53]. The oxidation of saturated fatty acids (C12-C18) and their esters revealed that the Ea values (100-125 kJ/mol) were within the same range for all the tested oils [54]. This suggests that the isothermal oxidation is not influenced by the carbon chain length. Another important conclusion from this investigation [54] is that the start of oxidation is similar for fatty acids, their esters and triglycerides. The kinetic oxidation parameters of cocoa butter blends were obtained using the oxidation onset time [55]. The blends were oxidized from 130 to 160C in an open pan. Interestingly, the *Ea* and *A* values were slightly affected by the addition of saturated fatty acids. But, *k* values considerably changed with the amount of saturated fatty acids. Thus, *k* values can be used to rank the oxidative stability of cocoa butter blends. However, the use of *k* values to evaluate oxidative stability might be valid only at the temperature tested since changes in the reaction mechanisms can occur as a function of temperature.

### **6.2. Non-isothermal studies**

Applications of Calorimetry in a Wide Context –

natural antioxidants were not considered.

temperature [39,48, 49].

analysis.

458 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

the onset heat flow signal of the DSC spectra [44]. In addition, a correlation between the peroxide values with the oxidation onset time was developed to monitor rapeseed oil oxidation [44]. Unfortunately, the correlation was valid only for oils with peroxide values lower than 30 mmol O2/kg oil. In other study, the experimental oxidation data obtained from electron spin spectroscopy was compared with the data obtained from DSC oxidation [46]. The onset oxidation times were highly correlated for different fat and oil blends. However, the obtained correlations were valid only at moderate temperatures of 60C, which considerably limits the applicability of electron spin spectroscopy for oxidation

An investigation of isothermal oxidation of oils (e.g. rapeseed, soybean, corn and sunflower oils) used onset time (ton) to rank the oxidized oils in terms of their oxidative stability [47]. The high maximum heat flow time (tp) value indicates that the oil is more stable. Although these relationships were statistically validated, a single parameter to evaluate the oxidative stability can lead to overestimation of the oxidative stability. In the same study, the authors considered *tp* to be proportional to the rate of oxidation, which might not be valid. Indeed, peroxide value determinations showed that *tp* represents the oxidation termination stage while *ton* is associated with the rate of initiation [48]. Furthermore, the addition of antioxidants prolongs only *ton* while *tp* values were minimally affected [48]. The same behavior was also observed in the isothermal oxidation of linseed oil with the use of antioxidants [49]. The addition of BHA (butylated hydroxyl anisole) and a mixture of antioxidants (tocopherol, ascorbyl palmitate, citric acid and ascorbic acid) prolonged the onset time at 130C. All these approaches provided information of great value for validation of the DSC isothermal oxidation. However, these equations are limited for a set of temperatures and specific oils (Table 1). Additional factors, such as degree of saturation, amount of free fatty acids, chain length and the presence of

Using the isothermal method, the sample is heated at a constant temperature and the released heat is recorded as a function of temperature. Such situation allows the identification of the maximum heat flow time (*tm*), which linearly correlates with the

where A and B are regression parameters. Due to the excess of oxygen generated by a constant flow rate, the formation of peroxides is considered to be independent of the oxygen concentration, which also means that the autoxidation is a first order reaction [48, 49]. This is an essential assumption for the calculation of kinetic parameters, such as effective

> ( ) 2.19 *<sup>m</sup> <sup>a</sup> dlog t E R*

Equations 8 and 9 have been applied not only to obtain the maximum heat flow signal [47- 49] but also to obtain the oxidation onset time. An attempt to correlate induction times and

1

activation energy (*Ea*), pre-exponential factor (*A*), and reaction rate (*k*).

<sup>1</sup> log *mt AT B* (8)

*dT* (9)

For non-isothermal oxidation studies, two maximum heat flow peaks are commonly observed in the DSC spectra [56-59]. But, only the first peak is related to lipid oxidation. This was demonstrated in non-isothermal oxidation studies of corn and linseed oils with different peroxide values [57]. A decrease in the onset temperature was observed as the peroxide value increased. Contrary, the first and second peak temperatures were not affected by increasing the peroxide value. Consequently, the first peak can be related to hydroperoxides formation while the second peak can be due to further oxidation of peroxides. In an earlier study [58], the weight loss of lecithin during non-isothermal heating under nitrogen flow rate was analyzed. The thermogravimetric analysis showed that in the temperature range of the first peak only 4% of weight was lost but above that temperature, the weight loss considerably increased. Therefore, changes in the DSC signal within the range of the first peak temperature were attributed to oxidation and those changes above that temperature corresponded to thermal degradation rather than oxidation (Figure 8).

$$\text{LLH} + \text{O}\_2 \xrightarrow[\text{First peak}]{\text{Autocoridation}} \text{LCOOH} + \text{O}\_2 \xrightarrow[\text{Hydroperoxidase}]{\text{Decomposition and}} \text{Products}$$

**Figure 8.** Reaction mechanism proposed for lipid oxidation under non-isothermal conditions.

460 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The proposed reactions in Figure 8 resemble to an autocatalytic reaction scheme. Indeed, computer simulated DSC oxidation curves using autocatalytic scheme fitted well the experimental data [56]. Similarly, the non-isothermal oxidation of mustard oil was best described by an autocatalytic reaction scheme [58]. Therefore, it was proposed that *Ton* is the most representative reference point of lipid oxidation under non-isothermal conditions. In addition, kinetic parameters calculated from *Ton* were comparable to those obtained at isothermal DSC conditions (Tables 1 and 2) [56-59]. Similarly, non-isothermal kinetics was used to evaluate the oxidative stability of commercial olive oil samples [59-62]. The obtained kinetic parameters were comparable to those obtained with the Rancimat method.

Oxidative Stability of Fats and Oils Measured by

; k = 0.51

; k = 0.44

; k = 0.44



; k = 0.38



min-1; k90C = 0.792


; k = 0.48

; k = 0.47


; k90C = 0.541

k = 0.42

[65]

[66]

[67]

[68]

Differential Scanning Calorimetry for Food and Industrial Applications 461

**Lipid Experimental protocol Kinetics parameters (***Ea***, kJ/mol;** *A* **min-1;** *k***, min) Ref.**











AA – ascorbic acid; TOC – tocopherol; MBP – methylenebis (2,6 ditert-butylphenol); PG – propyl gallate; BHT- Butylated hydroxytoluene, DHZdehydrozingerone, AMF-anhydrous milk fat, CLA-conjugated linoleic acid, OOT – oxidation onset temperature. **Table 2.** Summary of non-isothermal oxidation studies of lipids using differential scanning calorimetry

According to the Arrhenius principle, oil with a high *Ea* value oxidizes faster at high temperatures, while oil with a low *Ea* value oxidizes faster at low temperatures. Unfortunately, calculated values of *Ea* should not be used as a single parameter to rank the oxidative stability of lipid systems. This was exemplified in blends of soybean/anhydrous milk fat [63] that were non-isothermally oxidized. Interestingly, as the percentage of unsaturated fatty acids increased, the onset temperature of oxidation decreased and the only kinetic parameter that exhibited the same pattern was the constant rate of oxidation. The calculated *Ea* value is the cumulative effect of all the *Ea* values available in the system during oxidation, including intermediate compounds that have their own kinetic values. An equation representing the overall activation energy for autoxidation of lipids was earlier proposed [54, 56]. The overall effect included activation energies of initiation (*Ei*), propagation (*Ep*) and termination (*Et*) based on the classical rate equation for autoxidation of

Unfortunately, equation (10) has been applied to limited fatty acids (C12-C18) [56, 57] and correlations between other kinetic parameters and the initiation and termination activation









linoleic safflower, high oleic sunflower, soybean and sunflower

Rapeseed, soybean, sunflower, lard and highly rancid oils

High oleic sunflower (HOS) and castor oil with blends of antioxidants

Linolenic acid (LNA) with different phenols

LNA with BHT, olivetol and

hydrocarbons.

energies are needed.

DHZ

Fat extracted from baby

formulas

Base oil lubricants - 0.5 mg in a sealed pan







AA and MBP




#### Oxidative Stability of Fats and Oils Measured by Differential Scanning Calorimetry for Food and Industrial Applications 461


Applications of Calorimetry in a Wide Context –

Corn and linseed oil - 50-300C

Linolenic acid and soy lecithin - 50-300C

Mustartd oil - 140-350C

Blends of soybean/AMF - 100 to 350C

Oleic, erucic, linoleic, linolenic and their ethyl esters and glycerol trioleate and trilinoleate

AMF with low, medium and high CLA content

Cotton, corn, canola, safflower, high oleic safflower, high

Olive oil - 2-3 mg in an open pan









460 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

The proposed reactions in Figure 8 resemble to an autocatalytic reaction scheme. Indeed, computer simulated DSC oxidation curves using autocatalytic scheme fitted well the experimental data [56]. Similarly, the non-isothermal oxidation of mustard oil was best described by an autocatalytic reaction scheme [58]. Therefore, it was proposed that *Ton* is the most representative reference point of lipid oxidation under non-isothermal conditions. In addition, kinetic parameters calculated from *Ton* were comparable to those obtained at isothermal DSC conditions (Tables 1 and 2) [56-59]. Similarly, non-isothermal kinetics was used to evaluate the oxidative stability of commercial olive oil samples [59-62]. The obtained

**Lipid Experimental protocol Kinetics parameters (***Ea***, kJ/mol;** *A* **min-1;** *k***, min) Ref.**




















k120C = 0.09-0.015

*Soybean/AMF* 









; k100C = 0.016


; k225C = 0.97

; k200C = 0.68

; k200C = 0.71

; k200C = 0.80

; k200C = 0.88

; k200C = 0.95

; k200C = 1.09

; k90C = 0.071

; k90C = 0.024

; k200C = 0.013

; k = 0.37

; k = 0.43

; k90C = 0.020

; k90C = 0.027

; k90C = 0.082

; k225C = 0.90

; k225C = 1.12

[56]

[57]

[58]

[59]

[62]

[63, 64]

[9]

[7]

*Onset temperature* 

kinetic parameters were comparable to those obtained with the Rancimat method.

**Table 2.** Summary of non-isothermal oxidation studies of lipids using differential scanning calorimetry

According to the Arrhenius principle, oil with a high *Ea* value oxidizes faster at high temperatures, while oil with a low *Ea* value oxidizes faster at low temperatures. Unfortunately, calculated values of *Ea* should not be used as a single parameter to rank the oxidative stability of lipid systems. This was exemplified in blends of soybean/anhydrous milk fat [63] that were non-isothermally oxidized. Interestingly, as the percentage of unsaturated fatty acids increased, the onset temperature of oxidation decreased and the only kinetic parameter that exhibited the same pattern was the constant rate of oxidation. The calculated *Ea* value is the cumulative effect of all the *Ea* values available in the system during oxidation, including intermediate compounds that have their own kinetic values. An equation representing the overall activation energy for autoxidation of lipids was earlier proposed [54, 56]. The overall effect included activation energies of initiation (*Ei*), propagation (*Ep*) and termination (*Et*) based on the classical rate equation for autoxidation of hydrocarbons.

Unfortunately, equation (10) has been applied to limited fatty acids (C12-C18) [56, 57] and correlations between other kinetic parameters and the initiation and termination activation energies are needed.

462 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

$$E = E\_p + \bigvee\_2 E\_i - \bigvee\_2 E\_t \tag{10}$$

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 463

A proper kinetic interpretation should include the compensation effect, which is usually used to explain whether the variations on effective activation energy values have physical meaning or they are caused by either variations of process conditions or complexity of the reaction systems. In previous investigations [69, 70], the compensation effect is illustrated for various thermal degraded materials, such as polymers, cellulosic materials and CaCO3. The compensation effect can be evaluated by plotting ln *k*, obtained by equation (7), against *1/T*. Figure 9 shows that an increase in the effective activation energy causes an increase in *ln k* (equation 7). Similarly, a decrease in the effective activation energy results in a lower value of *ln k*. The point of concurrence, where the different lines intercept, corresponds to *ln kiso* and *1/Tiso* (*kiso* is the isokinetic rate constant and *Tiso* is the isokinetic temperature), which

**Figure 9.** Arrhenius plot (*ln k vs 1/T*) for the non-isothermal oxidation: (a) compensation effect theory

In studies of non-isothermal oxidation of anhydrous milk fat (AMF) [9], there is no concurrence at a single point. Therefore, the non-isothermal oxidation of AMF does not exhibit a compensation effect and thus the variations in kinetic parameters have no physical background. In fact, AMF is a very complex fat mainly composed of triacylglycerols that have a glycerol backbone to which three fatty acid moieties are esterified. These triacylglycerols are extremely diverse in chain lengths, position and number of unsaturations of their fatty acids [72]. Moreover, more than 400 fatty acids in milk fat were found [73]. Therefore, several reactions with different constant rates simultaneously occur and DSC only detects those reactions that have the greatest exothermal effect. This could explain why the variations in effective activation energy values have no physical meaning or

The isokinetic temperature can also be defined as the temperature at which two rate constants of two different reactions are equal. For a set of kinetic parameters of two different

**6.3. Compensation theory** 

indicates the existence of the compensation effect.

adapted from reference [69], and (b) anhydrous milk fat [9].

reactions, the isokinetic temperature can be expressed as:

there is no compensation effect.

The non-isothermal oxidation of different fatty acids and their esters [56, 57] showed that the calculated *Ea* values are similar among the different tested samples, indicating that the oxidation does not occur on free or esterified carboxyl groups of fatty acids. The nonisothermal oxidation of anhydrous milk fat with different ratios of unsaturated/saturated fatty acids showed that the start temperature of oxidation shifted to lower values as the ratio increased [9]. More importantly, the kinetics parameters (*Ea, A* and *k*) calculated also decreased. The onset temperature of oxidation not only is affected by the amount of saturated fatty acids but also by the presence and abundance of aromatic compounds and their alkyl substitutions [7, 25]. Kinetic parameters obtained from different oils were compared with structural parameters obtained with NMR spectroscopy. Moreover, an increase in the methylene carbons of the fatty acid chains increased the oxidative stability while conjugated structures were rapidly oxidized.

The addition of antioxidants to enhance oxidative stability of oils can be evaluated using the DSC in non-isothermal mode. A novel approach based on DSC data, named protective factor (PF) was provided in the literature [65]. In this investigation, the oxidation of methyl esters derived from rapeseed and waste frying oil was monitored at different concentrations of BHT and pyrogallol (PG). The oxidation onset temperature asymptotically increased with the addition of BHT and PG, without finding an optimum antioxidant concentration. In addition, the increase in the heating rate might change the reaction mechanisms in which antioxidants can capture free radicals, making difficult to compare their effectiveness. Therefore, the protective factor concept [65] was developed according to:

$$\text{Productivity factor (PF)} = \frac{\text{onset temperature of oil with antiionization}}{\text{onset temperature of oil without antiionizedant}} \tag{11}$$

Values of PF lower than 1 means that the antioxidant has a pro-oxidant effect. On the other hand, PF values greater than one can be considered as a measurement of antioxidant effectiveness. Another important factor is the physical stability of the antioxidants. In a comparative study [65, 68], the addition of BHT, BHA and PG was evaluated in rapeseed, soybean, sunflower and lard oils. BHA and BHT were not effective antioxidants due to their volatility. These antioxidants escaped from the heated oil before they can react to neutralize free radicals. An optimum antioxidant concentration was found for BHT (8.4 mmol), BHA (2.8 mmol) and olivetol (4.5 mmol) in oxidized linolenic acid [63-65]. After the optimal concentration, a decrease in the antioxidant activity was observed. Interestingly, at high temperatures (<180C), the antioxidants are no longer stable and their effectiveness significantly decreased. Similarly, α-tocopherol and *L*-ascorbic acid 6-palmitate were not effective even at high concentrations (up to 2% wt) during the oxidation of either high oleic sunflower oil or castor oil [66, 69].

#### **6.3. Compensation theory**

Applications of Calorimetry in a Wide Context –

while conjugated structures were rapidly oxidized.

sunflower oil or castor oil [66, 69].

462 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

1 1

The non-isothermal oxidation of different fatty acids and their esters [56, 57] showed that the calculated *Ea* values are similar among the different tested samples, indicating that the oxidation does not occur on free or esterified carboxyl groups of fatty acids. The nonisothermal oxidation of anhydrous milk fat with different ratios of unsaturated/saturated fatty acids showed that the start temperature of oxidation shifted to lower values as the ratio increased [9]. More importantly, the kinetics parameters (*Ea, A* and *k*) calculated also decreased. The onset temperature of oxidation not only is affected by the amount of saturated fatty acids but also by the presence and abundance of aromatic compounds and their alkyl substitutions [7, 25]. Kinetic parameters obtained from different oils were compared with structural parameters obtained with NMR spectroscopy. Moreover, an increase in the methylene carbons of the fatty acid chains increased the oxidative stability

The addition of antioxidants to enhance oxidative stability of oils can be evaluated using the DSC in non-isothermal mode. A novel approach based on DSC data, named protective factor (PF) was provided in the literature [65]. In this investigation, the oxidation of methyl esters derived from rapeseed and waste frying oil was monitored at different concentrations of BHT and pyrogallol (PG). The oxidation onset temperature asymptotically increased with the addition of BHT and PG, without finding an optimum antioxidant concentration. In addition, the increase in the heating rate might change the reaction mechanisms in which antioxidants can capture free radicals, making difficult to compare their effectiveness.

*onsettemperature of oil with antioxidant Protective factor PF onset temperature of oil without antioxidant*

Values of PF lower than 1 means that the antioxidant has a pro-oxidant effect. On the other hand, PF values greater than one can be considered as a measurement of antioxidant effectiveness. Another important factor is the physical stability of the antioxidants. In a comparative study [65, 68], the addition of BHT, BHA and PG was evaluated in rapeseed, soybean, sunflower and lard oils. BHA and BHT were not effective antioxidants due to their volatility. These antioxidants escaped from the heated oil before they can react to neutralize free radicals. An optimum antioxidant concentration was found for BHT (8.4 mmol), BHA (2.8 mmol) and olivetol (4.5 mmol) in oxidized linolenic acid [63-65]. After the optimal concentration, a decrease in the antioxidant activity was observed. Interestingly, at high temperatures (<180C), the antioxidants are no longer stable and their effectiveness significantly decreased. Similarly, α-tocopherol and *L*-ascorbic acid 6-palmitate were not effective even at high concentrations (up to 2% wt) during the oxidation of either high oleic

Therefore, the protective factor concept [65] was developed according to:

( )

2 2 *<sup>p</sup> i t EE E E* (10)

(11)

A proper kinetic interpretation should include the compensation effect, which is usually used to explain whether the variations on effective activation energy values have physical meaning or they are caused by either variations of process conditions or complexity of the reaction systems. In previous investigations [69, 70], the compensation effect is illustrated for various thermal degraded materials, such as polymers, cellulosic materials and CaCO3. The compensation effect can be evaluated by plotting ln *k*, obtained by equation (7), against *1/T*. Figure 9 shows that an increase in the effective activation energy causes an increase in *ln k* (equation 7). Similarly, a decrease in the effective activation energy results in a lower value of *ln k*. The point of concurrence, where the different lines intercept, corresponds to *ln kiso* and *1/Tiso* (*kiso* is the isokinetic rate constant and *Tiso* is the isokinetic temperature), which indicates the existence of the compensation effect.

**Figure 9.** Arrhenius plot (*ln k vs 1/T*) for the non-isothermal oxidation: (a) compensation effect theory adapted from reference [69], and (b) anhydrous milk fat [9].

In studies of non-isothermal oxidation of anhydrous milk fat (AMF) [9], there is no concurrence at a single point. Therefore, the non-isothermal oxidation of AMF does not exhibit a compensation effect and thus the variations in kinetic parameters have no physical background. In fact, AMF is a very complex fat mainly composed of triacylglycerols that have a glycerol backbone to which three fatty acid moieties are esterified. These triacylglycerols are extremely diverse in chain lengths, position and number of unsaturations of their fatty acids [72]. Moreover, more than 400 fatty acids in milk fat were found [73]. Therefore, several reactions with different constant rates simultaneously occur and DSC only detects those reactions that have the greatest exothermal effect. This could explain why the variations in effective activation energy values have no physical meaning or there is no compensation effect.

The isokinetic temperature can also be defined as the temperature at which two rate constants of two different reactions are equal. For a set of kinetic parameters of two different reactions, the isokinetic temperature can be expressed as:

464 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

$$A\_1 \cdot \exp^{\left(\frac{-E\_1}{R \cdot T\_{iss}}\right)} = A\_2 \cdot \exp^{\left(\frac{-E\_2}{R \cdot T\_{iss}}\right)}\tag{12}$$

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 465

**Figure 10.** Non-isothermal oxidation of non-hydrolyzed and hydrolyzed anhydrous milk fat rich in

**Heating rate [C/min] Non-hydrolyzed AMF [°C] Hydrolyzed AMF [°C]**  3 173.47 ± 0.1 125.06 ± 1.4 6 184.71 ± 2.3 132.46 ± 0.3 9 192.13 ± 0.7 133.25 ± 1.2 12 197.85 ± 3.7 132.46 ± 0.3 15 198.66 ± 0.3 136.78 ± 0.1 *Ea* [kJ/mol] 82.42 175.78 *A* [min-1] 8.7 x 107 2.3 x 1020 *k*130C [min] 0.002 0.003 *k*200C [min] 0.075 10.28

rates (*k*) calculated at 130 C were similar for the non-hydrolyzed and hydrolyzed samples. However, the constant rate of hydrolyzed fat was dramatically higher than that of non-

The isokinetic temperatures of these two fats were calculated mathematically and graphically using equation (12) and Arrhenius plot, respectively. Figure 11 shows the compensation effect for the oxidation of non-hydrolyzed and hydrolyzed AMF rich in CLA. From this figure, the *Tiso* and *kiso* were obtained (*Tiso* = 120C and *kiso* = 0.0011 min). Similarly, the *Tiso* and *kiso* calculated mathematically with equation (12) were 118C and 0.0010 min, respectively. However, *Tiso* for non-hydrolyzed AMF is unrealistic since the start temperature of oxidation is around 155C. Therefore, oxidation of either non-hydrolyzed or

CLA. Tp - maximum heat flow temperature.

hydrolyzed fat at 200C.

**Table 3.** Onset temperature of oxidation for anhydrous milk fat (AMF)

hydrolyzed AMF rich in CLA does not exhibit a compensation effect.

The isokinetic temperature of autoxidation of lecithin and linolenic acid calculated using equation (12) was 167C [57]. This observation exemplifies the difficulty in determining the oxidative stability of multicomponent systems. For example, if the oxidation test is conducted at a temperature below Tiso, linolenic acid oxidizes faster than lecithin. But, if the same test is conducted at a temperature equal to Tiso, both lipids have the same oxidative stability. Contrary, lecithin oxidizes faster than linolenic acid above Tiso. Consequently, the estimation of the oxidative stability based only on the onset temperature is misleading. Therefore, interpretation of the shape of non-isothermal oxidation curves in combination with kinetic parameters can provide a better interpretation of the oxidative behavior in multicomponent systems.

### **7. Case studies of lipid oxidation after processing using new technologies**

### **7.1. Kinetics of non-isothermal oxidation of anhydrous milk fat (AMF) rich in conjugated linoleic acid (CLA) after hydrolysis**

AMF is the richest source of CLA composed of geometrical and positional isomers of linoleic acid. CLA has potential benefits, such as cancer prevention, atherosclerosis, weight control, and bone formation [74]. Additionally, CLA concentration in milk can be markedly enhanced through diet manipulation and nutritional management of dairy cattle [75]. In CLA-enriched AMF, CLA is distributed throughout different triacylglycerols together with other fatty acids, limiting its applicability as ingredient in different milk fat-based products. One known approach to produce free fatty acids (FFA) is through enzymatic hydrolysis. The enzymatic hydrolysis of AMF rich in CLA yielded around 88% of free fatty acids (FFA) [76, 77]. Unfortunately, FFAs are more susceptible to oxidation than those fatty acids attached to the triacylglycerol backbone.

Figure 10 shows the DSC curves of non-hydrolyzed and hydrolyzed AMF rich in CLA. Although the DSC curves were quite different between non-hydrolyzed AMF (blue and black lines) and hydrolyzed AMF (green and red lines), the maximum peak temperatures were in the same range. This observation supports the hypothesis that changes in the DSC signal below the temperature of the first peak can be attributed to oxidation and changes in DSC signal above TP correspond to thermal decomposition and advanced oxidation products as shown in Figure 8. Figure 10 also shows that the oxidation of hydrolyzed AMF starts at low temperatures (~108C), making difficult to obtain a consistent baseline. Therefore, the kinetic parameters were calculated using the onset temperature obtained as described in Section 5.1.

Table 3 shows the onset oxidation temperature and kinetic parameters of non-hydrolyzed and enzymatic hydrolyzed AMF rich in CLA. As expected, the *Ea* for the hydrolyzed fat is greater than that obtained for the non-hydrolyzed fat. Interestingly, the constant reaction

multicomponent systems.

the triacylglycerol backbone.

described in Section 5.1.

**conjugated linoleic acid (CLA) after hydrolysis** 

464 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

1 2

(12)

*E E*

1 2 *iso iso*

The isokinetic temperature of autoxidation of lecithin and linolenic acid calculated using equation (12) was 167C [57]. This observation exemplifies the difficulty in determining the oxidative stability of multicomponent systems. For example, if the oxidation test is conducted at a temperature below Tiso, linolenic acid oxidizes faster than lecithin. But, if the same test is conducted at a temperature equal to Tiso, both lipids have the same oxidative stability. Contrary, lecithin oxidizes faster than linolenic acid above Tiso. Consequently, the estimation of the oxidative stability based only on the onset temperature is misleading. Therefore, interpretation of the shape of non-isothermal oxidation curves in combination with kinetic parameters can provide a better interpretation of the oxidative behavior in

**7. Case studies of lipid oxidation after processing using new technologies** 

AMF is the richest source of CLA composed of geometrical and positional isomers of linoleic acid. CLA has potential benefits, such as cancer prevention, atherosclerosis, weight control, and bone formation [74]. Additionally, CLA concentration in milk can be markedly enhanced through diet manipulation and nutritional management of dairy cattle [75]. In CLA-enriched AMF, CLA is distributed throughout different triacylglycerols together with other fatty acids, limiting its applicability as ingredient in different milk fat-based products. One known approach to produce free fatty acids (FFA) is through enzymatic hydrolysis. The enzymatic hydrolysis of AMF rich in CLA yielded around 88% of free fatty acids (FFA) [76, 77]. Unfortunately, FFAs are more susceptible to oxidation than those fatty acids attached to

Figure 10 shows the DSC curves of non-hydrolyzed and hydrolyzed AMF rich in CLA. Although the DSC curves were quite different between non-hydrolyzed AMF (blue and black lines) and hydrolyzed AMF (green and red lines), the maximum peak temperatures were in the same range. This observation supports the hypothesis that changes in the DSC signal below the temperature of the first peak can be attributed to oxidation and changes in DSC signal above TP correspond to thermal decomposition and advanced oxidation products as shown in Figure 8. Figure 10 also shows that the oxidation of hydrolyzed AMF starts at low temperatures (~108C), making difficult to obtain a consistent baseline. Therefore, the kinetic parameters were calculated using the onset temperature obtained as

Table 3 shows the onset oxidation temperature and kinetic parameters of non-hydrolyzed and enzymatic hydrolyzed AMF rich in CLA. As expected, the *Ea* for the hydrolyzed fat is greater than that obtained for the non-hydrolyzed fat. Interestingly, the constant reaction

**7.1. Kinetics of non-isothermal oxidation of anhydrous milk fat (AMF) rich in** 

*R T R T A exp A exp*

**Figure 10.** Non-isothermal oxidation of non-hydrolyzed and hydrolyzed anhydrous milk fat rich in CLA. Tp - maximum heat flow temperature.


**Table 3.** Onset temperature of oxidation for anhydrous milk fat (AMF)

rates (*k*) calculated at 130 C were similar for the non-hydrolyzed and hydrolyzed samples. However, the constant rate of hydrolyzed fat was dramatically higher than that of nonhydrolyzed fat at 200C.

The isokinetic temperatures of these two fats were calculated mathematically and graphically using equation (12) and Arrhenius plot, respectively. Figure 11 shows the compensation effect for the oxidation of non-hydrolyzed and hydrolyzed AMF rich in CLA. From this figure, the *Tiso* and *kiso* were obtained (*Tiso* = 120C and *kiso* = 0.0011 min). Similarly, the *Tiso* and *kiso* calculated mathematically with equation (12) were 118C and 0.0010 min, respectively. However, *Tiso* for non-hydrolyzed AMF is unrealistic since the start temperature of oxidation is around 155C. Therefore, oxidation of either non-hydrolyzed or hydrolyzed AMF rich in CLA does not exhibit a compensation effect.

466 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 467

start temperature of oxidation (~165-155C) were obtained when the CLA retention was between 85 to 100%. On the other hand, the lowest value of the start temperature of

**Figure 12.** Influence of CLA retention on the start temperature (*Ts*) of oxidation in anhydrous milk fat

A possible reason for the CLA-*Ts* relationship is that CLA can act as an antioxidant capturing those free radicals responsible for the lipid oxidation. This antioxidant behavior was clearly demonstrated in an earlier study by inducing lipid oxidation of fish oil by adding tert-butyl hydroperoxide. CLA effectively reduces lipid peroxidation as measured by chemiluminescence [86]. In addition, the antiradical or scavenging ability of CLA isomers measured by DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) technique depended on the

The use of DSC to analyse lipid oxidation is a reliable, simple and convenient technique. It provides qualitative and quantitative information and offers unique advantages, such as the small amount of sample use, short test time, and good reproducibility. Additionally, the effectiveness of a particular antioxidant can be evaluated using DSC, measuring changes in the oxidation onset times or temperatures. The data obtained from DSC lipid oxidation have been extensively studied and correlated with other oxidation methods, such as the Rancimat method, PV, spectrophotometric and GC analysis of fats and oils from various sources.

A proper interpretation of DSC oxidation experiments should include sample composition, kinetic parameters (*Ea, A,* and *k*) in combination with the compensation theory. In

oxidation (141C) was obtained at 40% of CLA retention.

rich in CLA.

CLA concentration [87].

**8. Conclusions** 

**Figure 11.** Arrhenius plot for the non-isothermal oxidation of non-hydrolyzed and hydrolyzed anhydrous milk fat rich in CLA.

### **7.2. Oxidative stability of AMF rich in CLA treated with pressure assisted thermal processing**

CLA is not stable upon thermal processing and significant losses of its biological activity occurred through oxidation [78]. The application of high pressure (100-600 MPa) to a preheated sample can preserve the biological activity of functional compounds [79]. This is because the rise in temperature due to adiabatic heating is used to reach the target temperature, reducing the thermal damage due to the lack of temperature uniformity that occurs in traditional thermal processes [80, 81]. This technology is known as pressureassisted thermal processing (PATP). Pressure alters interatomic distance, acting mainly on those weak interactions which bond energy is distance–dependent, such as van der Waals forces, electrostatic forces, hydrogen bonding and hydrophobic interactions of proteins. Based on the distance dependence, any pressurized sample would have its covalent bonds intact. This has been the central hypothesis in preserving the biological activity of functional compounds, such as ascorbic acid, folates, vitamins and anthocyanins [82-85].

The effects of PATP conditions on the antiradical ability of CLA in AMF were reported [86]. CLA can donate hydrogen to form a CLA-free radical that further reacts to inhibit hydroperoxides formation, depending on the final CLA retention. This suggests that the retained CLA after PATP treatment might enhance the oxidative stability of AMF. After PATP treatments, samples of AMF rich in CLA were oxidized at 6C/min to calculate the start temperature of oxidation using the method described earlier in Section 5.1 of this chapter.

Figure 12 shows the influence of the retained CLA on the start temperature of oxidation (Ts). The stability of AMF is influenced in a non-linear mode by the CLA retention. Values of the start temperature of oxidation (~165-155C) were obtained when the CLA retention was between 85 to 100%. On the other hand, the lowest value of the start temperature of oxidation (141C) was obtained at 40% of CLA retention.

**Figure 12.** Influence of CLA retention on the start temperature (*Ts*) of oxidation in anhydrous milk fat rich in CLA.

A possible reason for the CLA-*Ts* relationship is that CLA can act as an antioxidant capturing those free radicals responsible for the lipid oxidation. This antioxidant behavior was clearly demonstrated in an earlier study by inducing lipid oxidation of fish oil by adding tert-butyl hydroperoxide. CLA effectively reduces lipid peroxidation as measured by chemiluminescence [86]. In addition, the antiradical or scavenging ability of CLA isomers measured by DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) technique depended on the CLA concentration [87].

### **8. Conclusions**

Applications of Calorimetry in a Wide Context –

anhydrous milk fat rich in CLA.

**thermal processing** 

chapter.

466 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

**Figure 11.** Arrhenius plot for the non-isothermal oxidation of non-hydrolyzed and hydrolyzed

**7.2. Oxidative stability of AMF rich in CLA treated with pressure assisted** 

compounds, such as ascorbic acid, folates, vitamins and anthocyanins [82-85].

CLA is not stable upon thermal processing and significant losses of its biological activity occurred through oxidation [78]. The application of high pressure (100-600 MPa) to a preheated sample can preserve the biological activity of functional compounds [79]. This is because the rise in temperature due to adiabatic heating is used to reach the target temperature, reducing the thermal damage due to the lack of temperature uniformity that occurs in traditional thermal processes [80, 81]. This technology is known as pressureassisted thermal processing (PATP). Pressure alters interatomic distance, acting mainly on those weak interactions which bond energy is distance–dependent, such as van der Waals forces, electrostatic forces, hydrogen bonding and hydrophobic interactions of proteins. Based on the distance dependence, any pressurized sample would have its covalent bonds intact. This has been the central hypothesis in preserving the biological activity of functional

The effects of PATP conditions on the antiradical ability of CLA in AMF were reported [86]. CLA can donate hydrogen to form a CLA-free radical that further reacts to inhibit hydroperoxides formation, depending on the final CLA retention. This suggests that the retained CLA after PATP treatment might enhance the oxidative stability of AMF. After PATP treatments, samples of AMF rich in CLA were oxidized at 6C/min to calculate the start temperature of oxidation using the method described earlier in Section 5.1 of this

Figure 12 shows the influence of the retained CLA on the start temperature of oxidation (Ts). The stability of AMF is influenced in a non-linear mode by the CLA retention. Values of the The use of DSC to analyse lipid oxidation is a reliable, simple and convenient technique. It provides qualitative and quantitative information and offers unique advantages, such as the small amount of sample use, short test time, and good reproducibility. Additionally, the effectiveness of a particular antioxidant can be evaluated using DSC, measuring changes in the oxidation onset times or temperatures. The data obtained from DSC lipid oxidation have been extensively studied and correlated with other oxidation methods, such as the Rancimat method, PV, spectrophotometric and GC analysis of fats and oils from various sources.

A proper interpretation of DSC oxidation experiments should include sample composition, kinetic parameters (*Ea, A,* and *k*) in combination with the compensation theory. In

Applications of Calorimetry in a Wide Context – 468 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

multicomponent systems, the fat sometimes needs to be extracted from the matrix. Therefore, the lipid oxidative behaviour might be different from its original matrix. The results obtained from DSC oxidation depend upon the conditions used to prepare the sample and the heating protocol used. Factors, such as degree of saturation, amount of free fatty acids, chain length and the presence of natural antioxidants influence the oxidative stability and kinetic parameters. DSC can be coupled with other analytical techniques, such as GC, NMR, HPLC, etc, to provide a better description of the oxidative stability of fats and oils.

Oxidative Stability of Fats and Oils Measured by

Differential Scanning Calorimetry for Food and Industrial Applications 469

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468.

### **Author details**

M.D.A. Saldaña and S.I. Martínez-Monteagudo *Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada* 

### **Acknowledgement**

The authors thank to Alberta Livestock and Meat Agency Ltd. (ALMA) and to the Natural Sciences and Engineering Research Council of Canada (NSERC) for funding this project. Martinez-Monteagudo expresses his gratitude to Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) and Instituto de Inovacion y Transferencia Tecnologica (I2T2, Mexico) for the financial support (nr 187497).

### **9. References**


[8] Privett,OS, Blank ML (1962) Initial stages of autoxidation. J. Am. Oil Chem. Soc. 39: 465- 468.

Applications of Calorimetry in a Wide Context –

M.D.A. Saldaña and S.I. Martínez-Monteagudo

and oils.

*Canada* 

**Author details** 

**Acknowledgement** 

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for the financial support (nr 187497).

Publishing, eBook ISBN: 978-1-4398-2239-5.

468 Differential Scanning Calorimetry, Isothermal Titration Calorimetry and Microcalorimetry

multicomponent systems, the fat sometimes needs to be extracted from the matrix. Therefore, the lipid oxidative behaviour might be different from its original matrix. The results obtained from DSC oxidation depend upon the conditions used to prepare the sample and the heating protocol used. Factors, such as degree of saturation, amount of free fatty acids, chain length and the presence of natural antioxidants influence the oxidative stability and kinetic parameters. DSC can be coupled with other analytical techniques, such as GC, NMR, HPLC, etc, to provide a better description of the oxidative stability of fats

*Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB,* 

The authors thank to Alberta Livestock and Meat Agency Ltd. (ALMA) and to the Natural Sciences and Engineering Research Council of Canada (NSERC) for funding this project. Martinez-Monteagudo expresses his gratitude to Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) and Instituto de Inovacion y Transferencia Tecnologica (I2T2, Mexico)

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## *Edited by Amal Ali Elkordy*

Calorimetry, as a technique for thermal analysis, has a wide range of applications which are not only limited to studying the thermal characterisation (e.g. melting temperature, denaturation temperature and enthalpy change) of small and large drug molecules, but are also extended to characterisation of fuel, metals and oils. Differential Scanning Calorimetry is used to study the thermal behaviours of drug molecules and excipients by measuring the differential heat flow needed to maintain the temperature difference between the sample and reference cells equal to zero upon heating at a controlled programmed rate. Microcalorimetry is used to study the thermal transition and folding of biological macromolecules in dilute solutions. Microcalorimetry is applied in formulation and stabilisation of therapeutic proteins. This book presents research from all over the world on the applications of calorimetry on both solid and liquid states of materials.

Applications of Calorimetry in a Wide Context - Differential Scanning Calorimetry,

Isothermal Titration Calorimetry and Microcalorimetry

Applications of Calorimetry

in a Wide Context

Differential Scanning Calorimetry, Isothermal

Titration Calorimetry and Microcalorimetry

*Edited by Amal Ali Elkordy*

Photo by tonymax / iStock