**Meet the editor**

Dr. Eram Sharmin is an assistant professor in the Department of Pharmaceutical Chemistry, College of Pharmacy, Umm Al-Qura University, Makkah, Saudi Arabia. She obtained her PhD degree in Chemistry from Jamia Millia Islamia (JMI)—A Central University, New Delhi, India, in 2007. She received her MSc degree in Organic Chemistry, in 2000, and BSc degree in Chemistry,

in 1998, from Aligarh Muslim University (AMU), India. She has previously worked as a senior research associate (under Scientists' Pool Scheme, Council of Scientific and Industrial Research [CSIR], New Delhi, India), research associate (CSIR, New Delhi), and senior Research fellow (CSIR, New Delhi) at Materials Research Laboratory, Department of Chemistry, JMI. Dr. Sharmin has more than 50 publications in peer-reviewed journals and books and has presented more than 30 research papers in national and international conferences. Her research interests include the development of "green" materials with applications as antimicrobial and corrosion-resistant films, coatings, and packaging materials.

Dr. Fahmina Zafar is a senior researcher working at the Department of Chemistry, JMI, New Delhi, India, under the Women Scientists Scheme for Research in Basic/ Applied Sciences, DST, India. Dr. Zafar has received her PhD degree in Chemistry from JMI in 2006. She has worked as a postdoctoral fellow under UGC Kothari Postdoctoral Fellowship, as a scientist pool, research

associate, and senior research fellow (CSIR) at the same Department. She has more than 50 publications in peer-reviewed journals and books, and has presented more than 40 research papers in national and international conferences. Her research work involves the development of bio-based materials for green environment in different fields including adsorption, antimicrobial, and corrosion-protective applications.

## Contents

**Preface XI**




## Preface

Chapter 8 **Quantum Dots for Pharmaceutical and Biomedical**

Hayriye Eda Şatana Kara and Nusret Ertaş

**and Biomedical Analyses 171**

Marinela Florea and Mihaela Ilie

**Pharmaceutical Analysis 213**

Marwa S. Elazazy

**Section 2 Applications of Spectrophotometric Methods in Pharmaceutical**

Chapter 9 **Ion-Pair Spectrophotometry in Pharmaceutical and Biomedical**

**Analysis: Challenges and Perspectives 173**

**Pharmaceutical and Biomedical Analyses 193**

Chapter 11 **Factorial Design and Machine Learning Strategies: Impacts on**

Bruno E.S. Costa, Henrique P. Rezende, Liliam Q. Tavares, Luciana M. Coelho, Nívia M.M. Coelho, Priscila A.R. Sousa and Thais S. Néri

Chapter 10 **Application of Flow-Injection Spectrophotometry to**

**Analysis 143**

**VI** Contents

Spectroscopic methods hold ubiquitous importance in analyses of materials, both qualitative and quantitative. They are being actively used as characterization and diagnostic tools in plethora of analyses as they are simple, sensitive, accurate, cost-efficient, reproducible, and quick. Spectro‐ scopic and spectrophotometric methods have gained considerable importance in pharmaceutical and biomedical applications, as diagnostic tools, in drug quality control, for analyses and estima‐ tion of major/active constituents in drugs and natural products, and many other applications.

The book presents developments and applications of these methods, such as NMR, mass, and oth‐ ers, including their applications in pharmaceutical and biomedical analyses. The book is divided into two sections. The first section covers spectroscopic methods, their applications, and their sig‐ nificance as characterization tools; the second section is dedicated to the applications of spectro‐ photometric methods in pharmaceutical and biomedical analyses. The first four chapters in the first section deal with the recent advancements and applications of NMR spectroscopy, followed by a couple of chapters on the applications of NMR and Mass spectroscopy in profiling of natural products, and other pharmaceutical applications, while the last two chapters highlight the use of these methods as characterization tools. The second section focuses particularly on the pharma‐ ceutical and biomedical applications of spectrophotometric methods such as ion-pair spectropho‐ tometry and flow-injection spectrophotometry.

This book would be useful for students, scholars, and scientists engaged in synthesis, analyses, and applications of materials/polymers.

Due to great efforts of the authors, contributors, and technical staff of InTech Open Access Pub‐ lisher, the book project is finally accomplished. We appreciate Ms. Romina Rovan, Publishing Process Manager, InTechOpen for her patience and prompt responses, during the whole process. Dr. Fahmina Zafar is thankful to the Department of Science and Technology, New Delhi, India, for the award of fellowship under the Women Scientists Scheme (WOS) for Research in Basic/ Applied Sciences (Ref. No. SR/WOS-A/CS-97/2016).

We would like to give special thanks to our family members for their great support during the entire process of compilation of the book project *Spectroscopic Analyses - Developments and Applications*.

> **Dr. Eram Sharmin** Department of Pharmaceutical Chemistry, College of Pharmacy, Umm Al-Qura University, Makkah Al-Mukarramah, Saudi Arabia

**Dr. Fahmina Zafar** Inorganic Materials Research Laboratory, Department of Chemistry, Jamia Millia Islamia, New Delhi, India

## **Spectroscopic Techniques Such as Proton and Carbon NMR and Mass and Their Applications**

**Provisional chapter**

## **Solid State NMR**

**Solid State NMR**

#### Maria Ines Bruno Tavares Maria Ines Bruno Tavares Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.71004

#### **Abstract**

The nuclear magnetic resonance (NMR) spectroscopy is a very powerful tool in the chemical characterization, both in solution and in solid state. With the development of NMR spectrometers more potent field, employing radio frequency pulse, provided the development of studies on materials, especially amorphous materials. Thus, there was a need to develop techniques to obtain spectra in solid state with high resolution in comparison to those obtained in solution. Therefore, the study of polymers and polymeric materials could be developed quickly as a result a lot of information about the structure-property could be obtained with more details. The use of NMR in the solid state has become particularly important in the study of amorphous materials, as well as in the study of crystal structures, and permits us to detect different constituents present in material. This chapter covers the basic solid-state NMR techniques that provide important information on sample molecular behavior because they are powerful and versatile tools to evaluate polymer and complex materials like nanomaterials.

DOI: 10.5772/intechopen.71004

**Keywords:** NMR, solid-state, polymer, nanomaterials, relaxation times

#### **1. Introduction**

Solid-state nuclear magnetic resonance (NMR) consists of several techniques, which are distinguished by different pulse sequences and generate different responses on the sample, allowing obtaining data on different time scales. This makes the development of new analytical methods for the study of polymer materials interesting. The solid-state analyses differentiate the solution by two main factors; the first is signal width. In the solid state, the signals are broader than solution, concerning to polymers due to the high-molecular weight and monomer ordination; among other factors, the signals are wider. The second point concerns the type of response obtained; in the solid state, the number of information obtained is greater than solution. When the material is insoluble or has soluble difficulties, the study of

© 2016 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. © 2017 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.

structure-property relation is of great interest because the search for responses with respect to homogeneity, phase dispersion, and intermolecular interaction between components is of great importance.

#### **1.1. Nuclear magnetic resonance experiment**

In the NMR experiment, a sample is placed in probe in a strong magnetic field, denominated Bo; if this sample presents magnetic moment (μ), its nuclear spins magnetize and at the excess of spin population, called magnetization (Mo), is applied for a radio frequency (RF) pulse by a radio frequency emission (B<sup>1</sup> ) field, the magnetization is excited by transfer to the *xy* plane. When the RF emission is turned off, nuclear spins tend to return to the steady state since this state has less energy, occurring in a process called relaxation. In this process, two types of relaxation occur simultaneously: one denominated transverse or spin-spin relaxation, which occurs in the *xy* plane and has a time constant—T2 , and the other called longitudinal or spinlattice relaxation that occurs along the axis *z* and is characterized by the time constant—T1 . The NMR signal is detected after the withdrawal of radio frequency, with a process of free induction decay (FID) of the radio frequency, which results from the free precession of the nuclear spins, upon its return to steady state.

The NMR relaxation processes with time constants T1 and T2 are governed by fluctuating magnetic fields associated with molecular motion. The relaxation process that determines the T1 values involving energy absorption, since this process is enthalpic. The temporal evolution of the transverse relaxation is fundamentally different from longitudinal, and it corresponds to a loss of phase coherence between the individual magnetic moment process in it, and, thus an increase of entropy. In many cases, solid sample loss phase coherence initially created by B1 is due to direct interactions between the spin moments of individual [1–10].

#### **1.2. High-field NMR**

#### *1.2.1. Solid-state NMR analyses*

The solid-state NMR is constituted by several distinct pulse sequences, which generate different responses on the sample, allowing obtaining data on different time scales. This makes possible to develop new analytical methods for the study of complex solid materials [1–5], as polymer nanocomposites.

The analysis of the complex materials in the solid state differentiates the analysis in solution by two main factors: the first is the signal width. In the solid state, the signals are broader than in solution and especially for polymers due to their high molecular weight and mere ordination, among other factors, the signals become even wider. The second point concerns the type of response to be obtained in the solid state the number of information to be obtained is greater than in solution [11–14]. However, when the material is insoluble or has soluble difficulties, the study of the structure-property relation is of great interest because the search for responses with respect to homogeneity, phase dispersion, and interaction between the components is of great importance.

**a.** Nuclear magnetic resonance signal line width

structure-property relation is of great interest because the search for responses with respect to homogeneity, phase dispersion, and intermolecular interaction between components is of

In the NMR experiment, a sample is placed in probe in a strong magnetic field, denominated Bo; if this sample presents magnetic moment (μ), its nuclear spins magnetize and at the excess of spin population, called magnetization (Mo), is applied for a radio frequency (RF) pulse by

When the RF emission is turned off, nuclear spins tend to return to the steady state since this state has less energy, occurring in a process called relaxation. In this process, two types of relaxation occur simultaneously: one denominated transverse or spin-spin relaxation, which

lattice relaxation that occurs along the axis *z* and is characterized by the time constant—T1

The NMR signal is detected after the withdrawal of radio frequency, with a process of free induction decay (FID) of the radio frequency, which results from the free precession of the

magnetic fields associated with molecular motion. The relaxation process that determines

The solid-state NMR is constituted by several distinct pulse sequences, which generate different responses on the sample, allowing obtaining data on different time scales. This makes possible to develop new analytical methods for the study of complex solid materials [1–5], as

The analysis of the complex materials in the solid state differentiates the analysis in solution by two main factors: the first is the signal width. In the solid state, the signals are broader than in solution and especially for polymers due to their high molecular weight and mere ordination, among other factors, the signals become even wider. The second point concerns the type of response to be obtained in the solid state the number of information to be obtained is greater than in solution [11–14]. However, when the material is insoluble or has soluble difficulties, the study of the structure-property relation is of great interest because the search for responses with respect to homogeneity, phase dispersion, and interaction between the

 values involving energy absorption, since this process is enthalpic. The temporal evolution of the transverse relaxation is fundamentally different from longitudinal, and it corresponds to a loss of phase coherence between the individual magnetic moment process in it, and, thus an increase of entropy. In many cases, solid sample loss phase coherence

) field, the magnetization is excited by transfer to the *xy* plane.

and T2

is due to direct interactions between the spin moments of individual

, and the other called longitudinal or spin-

are governed by fluctuating

.

great importance.

the T1

[1–10].

initially created by B1

**1.2. High-field NMR**

*1.2.1. Solid-state NMR analyses*

polymer nanocomposites.

components is of great importance.

**1.1. Nuclear magnetic resonance experiment**

4 Spectroscopic Analyses - Developments and Applications

occurs in the *xy* plane and has a time constant—T2

The NMR relaxation processes with time constants T1

nuclear spins, upon its return to steady state.

a radio frequency emission (B<sup>1</sup>

Generally, the spectra obtained in solution generate narrow signals best resolved comparing to solid-state signals, due to the isotropy of the chemical shift, since all interactions as shielding, dipolar coupling, and indirect coupling depend on the orientation of the local environment in nuclear magnetic field B<sup>o</sup> and when the samples are in solution, these effects are compensated. However, they are dependent on the nature of the sample and the external magnetic field strength applied [7–10].

In solids, there is usually little movement relative to the liquid. However, most samples (except single crystals) have a substantial molecular orientation range of line width. This fact comes from the anisotropy of the chemical shift as well as the strong dipolar interaction between the hydrogen nuclei and carbon-13. The nature of the sample and the type of nucleus to be observed are also two points of fundamental importance to the spectral resolution in solid state.

**b.** Solid-state nuclear magnetic resonance response

The type of answer you want to get on a specific material or on a polymeric system may be a reason why those must be analyzed by solid-state NMR. Information on the molecular dynamics is of great interest for answers about the correlation structure-molecular-dynamic property.

The problem of signal line width in NMR solid-state spectra led to the development of techniques that allow them to obtain signals in the solid state the narrowest possible, like liquids. Along with the information to be obtained on the material, different techniques are performed to analyze more different polymer systems.

#### *1.2.1.1. High-resolution solid-state NMR basic theory*

The Hamiltonian that governs the analysis involves a solid sum of different Hamiltonians, according to expression 1.

$$\mathbf{H}\_{\text{NMR}} = \mathbf{H}\_{\text{Z}} + \mathbf{H}\_{\text{RF}} + \mathbf{H}\_{\text{CSA}} + \mathbf{H}\_{\text{D}} + \mathbf{H}\_{\text{j}} + \mathbf{H}\_{\text{Q}} \tag{1}$$

where **H**<sup>Z</sup> is the Zeeman effect; **H**RF is the radio frequency effect; **H**CSA is the chemical shift anisotropy; **H**<sup>D</sup> is the dipolar interaction between hydrogen nucleus and the carbon-13 nucleus; **H**<sup>J</sup> is the coupling constant; and **H**<sup>Q</sup> is the quadrupolar moment.

When one observes spin nuclei ½, as carbon-13 (13C), for example, the Hamiltonian that promotes more interference in the signal enlargement are HCSA e HD. Improving the resolution of the signals in the NMR spectra obtained in the solid state requires techniques to eliminate factors that cause this signal enlargement [10–14]. Thus, techniques were developed using methods that mathematically eliminate these effects.

#### *1.2.1.1.1. Magic angle spinning (MAS)*

The strong dipolar interactions between hydrogen nuclei and carbon-13, facilitated by the internuclear distance between them and the restricted mobility of the chains and the anisotropy of the chemical shift generate signals in very wide solid, with line width of 20 kHz order. The elimination of the dipole-dipole interaction generates a decrease in the signal line width of 5 kHz, and the elimination of the anisotropy of chemical shift width of the signals decreases to 100 Hz, making possible the detection of signals. Both the dipolar interaction and the anisotropy of the chemical shift dependence have with the term 3cos2 *θ*−1. The elimination of these two effects occurs when the solid analyzes are performed by rotating the sample at high rotational speeds (each nucleus suitable for a given magnetic field) in a sample introduction probe angle corresponding to the amount of 54.74°, able to eliminate the term 3cos2 *θ*−1, aligned with a strong decoupling of the hydrogen nucleus generating a significant narrowing of the line width in spectrum.

The employed pulse sequence is simple:

$$\begin{array}{ccccc}\circ & \circ & \circ & \circ\\\text{The employed pulse sequence is simple:}\\ & \text{hydrogen} & \text{decoupled} \\ & \text{nucleus observed} & [90^\circ x \rightarrow \text{FID} \text{ } t]n \end{array} \tag{2}$$

where *t* is the time interval between 90° pulses (delay) and n is the number of scans.

The time *t* is variable and it is directly related to the relaxation time of different types of nuclei that are analyzed. Thus, variations in this parameter allow studies that provide information about the molecular mobility of the sample and the time of spin-lattice relaxation.

All nuclei that undergo the phenomenon of resonance can be analyzed by this technique. However, for the observation of nuclei that have quadrupole moments, line widths are so large that the signals have no resolution. However, for nuclei having dipole moment, this technique generates high-resolution spectra. It should be considered that for highmolecular weight materials such as polymer, for example, the chemical structure can be defined by this technique. However, a fine or detailed microstructure structure cannot be observed as they are well resolved by the NMR solution techniques. Because in the carbon-13 solid state analysis the signals broadened comes from the dipolar interactions and the chemical shift anisotropy, generating large signals that contain all molecular information's.

Note that using the MAS technique can obtain quantitative spectra solid. However, the long analysis time, comes from the high values of the spin-lattice relaxation times of the different nuclei, mainly rare spin. It makes this type of spectrum replaced by spectra expressing or representing only a portion of the sample. Therefore, variation in spectral parameters of this pulse sequence provides information about the increased mobility of a sample region, for example, a mixture of polymers, polymers, composites, amorphous, and nanocomposite materials. Thus, a greater number of applications of this technique can be obtained, when seeking information about the homogeneity, compatibility, and purity of polymers or any material samples.

The analysis of materials by the MAS technique using a small interval between pulses (ms) can detect only one region or the region that has the highest mobility. This variation in the MAS technique enables, in the case of amorphous polymers, that is, ethylene-*co*-vinyl acetate (EVA), identifies the region of increased molecular mobility, or distinguishes the mobility of different areas, which cause changes in the properties of the material [6–10].

Poly(ethylene-*co*-vinyl acetate) (EVA) is a random copolymer that has a distinct percentage of vinyl acetate, which promotes changes in their mechanical and thermal properties and consequently changes the processing conditions and materials. The monomer sequence of the random copolymer is shown in **Figure 1**.

Analyzing EVA containing 28% of acetate by carbon-13 (C-13) solid-state NMR basic techniques will be shown as an example of how useful is the application of solid-state techniques.

**Figure 2** exhibits the powder EVA C-13 MAS NMR spectrum. Showing the highest signal located at 30.2 ppm referred to CH2 (the methylene group) long chains and a small signal detected at 14.3 ppm attributed to the methyl group of the acetate part. Two small signals were detected at about 21 and 25 ppm, which were assigned as CH2 from the ethylene branching [11, 12].

#### *1.2.1.1.2. Cross-polarization and magic angle spinning angle (CPMAS)*

anisotropy of the chemical shift generate signals in very wide solid, with line width of 20 kHz order. The elimination of the dipole-dipole interaction generates a decrease in the signal line width of 5 kHz, and the elimination of the anisotropy of chemical shift width of the signals decreases to 100 Hz, making possible the detection of signals. Both the dipolar interaction and the anisotropy of the chemical shift dependence have with

performed by rotating the sample at high rotational speeds (each nucleus suitable for a given magnetic field) in a sample introduction probe angle corresponding to the amount of

gen nucleus generating a significant narrowing of the line width in spectrum.

where *t* is the time interval between 90° pulses (delay) and n is the number of scans.

about the molecular mobility of the sample and the time of spin-lattice relaxation.

The time *t* is variable and it is directly related to the relaxation time of different types of nuclei that are analyzed. Thus, variations in this parameter allow studies that provide information

All nuclei that undergo the phenomenon of resonance can be analyzed by this technique. However, for the observation of nuclei that have quadrupole moments, line widths are so large that the signals have no resolution. However, for nuclei having dipole moment, this technique generates high-resolution spectra. It should be considered that for highmolecular weight materials such as polymer, for example, the chemical structure can be defined by this technique. However, a fine or detailed microstructure structure cannot be observed as they are well resolved by the NMR solution techniques. Because in the carbon-13 solid state analysis the signals broadened comes from the dipolar interactions and the chemical shift anisotropy, generating large signals that contain all molecular

Note that using the MAS technique can obtain quantitative spectra solid. However, the long analysis time, comes from the high values of the spin-lattice relaxation times of the different nuclei, mainly rare spin. It makes this type of spectrum replaced by spectra expressing or representing only a portion of the sample. Therefore, variation in spectral parameters of this pulse sequence provides information about the increased mobility of a sample region, for example, a mixture of polymers, polymers, composites, amorphous, and nanocomposite materials. Thus, a greater number of applications of this technique can be obtained, when seeking information about the homogeneity, compatibility, and purity of polymers or any

The analysis of materials by the MAS technique using a small interval between pulses (ms) can detect only one region or the region that has the highest mobility. This variation in the MAS technique enables, in the case of amorphous polymers, that is, ethylene-*co*-vinyl acetate (EVA), identifies the region of increased molecular mobility, or distinguishes the mobility of

different areas, which cause changes in the properties of the material [6–10].

hydrogen decoupling nucleus observed [90° *<sup>x</sup>* <sup>→</sup> FID <sup>−</sup> *<sup>t</sup>*]*<sup>n</sup>*

*θ*−1. The elimination of these two effects occurs when the solid analyzes are

*θ*−1, aligned with a strong decoupling of the hydro-

(2)

the term 3cos2

information's.

material samples.

54.74°, able to eliminate the term 3cos2

6 Spectroscopic Analyses - Developments and Applications

The employed pulse sequence is simple:

The cross-polarization technique was developed aimed at detection of rare nuclei spins with the aim to minimize the analysis time because of the long relaxation times of these nuclei. This method relies on the transfer of polarization of a nucleus spin abundant, hydrogen nucleus ( 1 H), for example, to rare spin nuclei (i.e., 13C), the cores 13C and 1 H are in thermal contact for a stipulated period of time, called during the cross-polarization contact time at that time the nuclei are kept in contact due to precession frequencies of both nuclei are kept identical, in this case the nuclei are in a condition called condition Hartman-Hahn [1–5], which is an equality where the frequency precession of hydrogen nucleus versus magnetic field of hydrogen are equal to precession of carbon-13 nucleus versus magnetic field of carbon-13, in a period of time: **ωHBH = ωCBC.**

The combined cross-polarization technique with the rotation of the sample at the magic angle and strong hydrogen decoupling (CPMAS), generating NMR spectra of solid high-resolution rare spin nuclei with increasing signal strength in a shorter analysis time than the MAS, considering that the hydrogen nucleus controls the relaxation process [1–10, 13].

The pulse sequence used to obtain the spectra through CPMAS is the same for MAS, but with the inclusion of the condition Hartman-Hahn, which is inserted a contact time between the two nuclei for transferring the polarization between them. Thus, the combination of cross-polarization technique, magic angle spinning process, and strong hydrogen decoupling of carbon-13 nucleus technique informs about the compatibility of polymer blends at the molecular level. The changes in the widths of the lines of NMR and the values of the chemical shifts provide information about changes in mobility at the molecular level.

$$\begin{array}{c} \{\mathsf{-}\mathsf{-CH}\_{2}-\mathsf{CH}\_{2}\mathsf{-}\}\_{n}-\{\mathsf{-}\mathsf{CH}\_{2}-\mathsf{CH}\mathsf{-}\}\_{\mathsf{T}m} \\ \stackrel{\parallel}{\mathsf{O}}\mathsf{-}\cdot\mathsf{C}=\mathsf{O} \\ \stackrel{\parallel}{\mathsf{C}\mathsf{H}\_{3}} \end{array}$$

**Figure 1.** Poly(ethylene-*co*-vinyl acetate) (EVA) chemical structure.

**Figure 2.** Solid-state NMR C-13 MAS spectrum of powder EVA.

**Figure 3** shows the powder EVA CPMAS C-13 NMR spectrum, with 1 ms of contact time. It already showed two signals: one located at short chemical shift, centered at 30.7 ppm referring to mobile region and the other one located at 32.3 ppm due to the segments of rigid region.

One type of solid-state NMR studies is to use a comparison between 13C NMR spectra obtained by techniques MAS and CPMAS, which can first show the different regions of the samples. One example was showed in the literature, which exhibits the MAS and CPMAS solid state NMR spectra of seed flour bourbon mango spectra [15, 16]. It shows that in these spectra have at least two segment areas of different molecular mobilities, and it may also a third due to the interaction of these two domains that may not be detected in this type of measurement.

#### *1.2.1.1.3. Variable contact time (VCT) during polarization transfer*

This technique generates a variation of contact times during the cross-polarization experiment, leading to a series of 13C CPMAS spectra with different contact times, and through this experiment, one can obtain some important information, such as heterogeneity of the sample, material stiffness, different types of domains, and the value of the hydrogen spinlattice relaxation time in the rotating frame (T<sup>1</sup> ρH). This parameter can be obtained from the intensities decay of carbon-13 nucleus during the cross-polarization transfer experiment, according to the changes in the contact time, since the hydrogen nucleus is the one that controls this relaxation process. **Figure 4** exhibits the variable contact-time experiment for powder EVA.

**Figure 3.** Solid-state NMR CPMAS C-13 NMR spectrum of powder EVA.

**Figure 3** shows the powder EVA CPMAS C-13 NMR spectrum, with 1 ms of contact time. It already showed two signals: one located at short chemical shift, centered at 30.7 ppm referring to mobile region and the other one located at 32.3 ppm due to the segments of rigid

One type of solid-state NMR studies is to use a comparison between 13C NMR spectra obtained by techniques MAS and CPMAS, which can first show the different regions of the samples. One example was showed in the literature, which exhibits the MAS and CPMAS solid state NMR spectra of seed flour bourbon mango spectra [15, 16]. It shows that in these spectra have at least two segment areas of different molecular mobilities, and it may also a third due to the interaction of these two domains that may not be detected in this type of measurement.

This technique generates a variation of contact times during the cross-polarization experiment, leading to a series of 13C CPMAS spectra with different contact times, and through this experiment, one can obtain some important information, such as heterogeneity of the sample, material stiffness, different types of domains, and the value of the hydrogen spin-

intensities decay of carbon-13 nucleus during the cross-polarization transfer experiment, according to the changes in the contact time, since the hydrogen nucleus is the one that controls this relaxation process. **Figure 4** exhibits the variable contact-time experiment for

ρH). This parameter can be obtained from the

*1.2.1.1.3. Variable contact time (VCT) during polarization transfer*

lattice relaxation time in the rotating frame (T<sup>1</sup>

**Figure 2.** Solid-state NMR C-13 MAS spectrum of powder EVA.

8 Spectroscopic Analyses - Developments and Applications

region.

powder EVA.

**Figure 4.** Variable contact time experiment of powder EVA.

This experiment shows the decay of both resolved carbon types detected from CPMAS with contact-time variation, showing the rigid part of the sample and part of the mobile one with the increase in the signal related to the CH2 of the nonrigid phase.

#### **2. Case study**

#### **2.1. Example of the determination of T1 ρH for polymer nanocomposites based on poly(3-hydroxy butyrate) (PHB)**

In this study, it was evaluated the T<sup>1</sup> ρH for the PHB/silica (PHB/S) systems contain different proportions of silica. All samples were obtained through solution casting, and the films after being dried were out into the rotor, the analyses were carried out at 30°C, and the values of this parameter are listed in **Table 1**.

From the data listed in **Table 1**, just a small proportion of silica affects the polymer, promoting a formation of a new material. Therefore, the relaxation data for the samples containing 0.5 or more silica exhibit a similar behavior, promoting an increase in this parameter comparing to pure PHB indicating that a new material with good dispersion and distribution of the nanoparticle in the polymer was obtained. The limit of silica is 0.5%, and no more is needed since no change in the T1 ρH for all carbons was detected. The evaluation of this parameter is not very much used for polymer nanocomposites yet. Therefore, studies have been already published by the group for other systems, as blends and composites [24], and show the behavior of these polymer materials [25].


**Table 1.** T1 ρH data for the PHB/S systems, containing different proportions.

#### **3. Low-field NMR**

In low-field NMR equipment due to low intensity and homogeneity of the magnetic field, the chemical shift cannot be used to discriminate between different molecules. The nuclear relaxation processes occurring in the nuclear magnetic resonance phenomenon inherent to spectroscopy are spin-lattice and spin-spin relaxation times; however, they provide detailed information about the molecular dynamics. These relaxation times influence from the structural and microstructural quantitative determination by the study of molecular dynamics. The relaxation processes are associated to the time constant for these processes: T1 , spin-lattice relaxation time, and T2 , spin-spin relaxation time. In the low-field NMR, the relaxation parameters T1 and T2 for the hydrogen nuclei that constitute the samples can be measured directly, using the pulse sequences for such experiments and are widely used to characterize the types of molecular segments present in the samples and the interactions between them [15–20]. The time T1 is associated with the return of the nucleus excited by the absorption of radiation to the equilibrium. While T<sup>2</sup> relaxation is related to the inverse of the half-width of the signal and occurs due to the loss of phase coherence in the precession of the nucleus excited about the direction of the applied magnetic field [1–3].

The relaxation times determined by NMR offer detailed information on the molecular mobility of a material. Thus, one could detect the formation of rigid and flexible segments, plasticization or antiplasticization process, and any other change in the molecular dynamics of the sample or comparing the variation of the molecular mobility of structures from the same type of material, but of different origin. The time of relaxation times T<sup>1</sup> H and T2 H can be measured in a wide temperature range and identifying small differences in similar structures.

#### **3.1. Determination of T1**

This experiment shows the decay of both resolved carbon types detected from CPMAS with contact-time variation, showing the rigid part of the sample and part of the mobile one with

proportions of silica. All samples were obtained through solution casting, and the films after being dried were out into the rotor, the analyses were carried out at 30°C, and the values of

From the data listed in **Table 1**, just a small proportion of silica affects the polymer, promoting a formation of a new material. Therefore, the relaxation data for the samples containing 0.5 or more silica exhibit a similar behavior, promoting an increase in this parameter comparing to pure PHB indicating that a new material with good dispersion and distribution of the nanoparticle in the polymer was obtained. The limit of silica is 0.5%, and no more is needed since no

much used for polymer nanocomposites yet. Therefore, studies have been already published by the group for other systems, as blends and composites [24], and show the behavior of these

**C = O CH2 CH CH3**

In low-field NMR equipment due to low intensity and homogeneity of the magnetic field, the chemical shift cannot be used to discriminate between different molecules. The nuclear relaxation processes occurring in the nuclear magnetic resonance phenomenon inherent to

of the nonrigid phase.

ρH for all carbons was detected. The evaluation of this parameter is not very

**ρH for polymer nanocomposites based on** 

ρH for the PHB/silica (PHB/S) systems contain different

the increase in the signal related to the CH2

10 Spectroscopic Analyses - Developments and Applications

**2.1. Example of the determination of T1**

**poly(3-hydroxy butyrate) (PHB)**

In this study, it was evaluated the T<sup>1</sup>

this parameter are listed in **Table 1**.

**2. Case study**

change in the T1

polymer materials [25].

**Sample T1**

**ρH (ms)**

PHB 13 26 31 17 PHB/S 0.2 15 19 27 19 PHB/S 0.5 33 32 34 32 PHB/S 0.75 31 32 34 30 PHB/S 1.0 31 31 34 30

ρH data for the PHB/S systems, containing different proportions.

**3. Low-field NMR**

**Table 1.** T1

The inversion-recovery pulse sequence is the most accurate technique for measuring the relaxation time spin–lattice process. The T<sup>1</sup> H relaxation time é measured in the frequency of magnetic field generated by the external magnetic field. This relaxation must do with the return of the excited nuclei to its ground state after removal of the excitation frequency, and therefore, it allows to evaluate the molecular mobility of a material, global compatibility and homogeneity, as well as processes and plasticization [1–3, 10–15]. In this process, the excess energy is emitted to the lattice in the form of dipole interaction since there is a lowering of the enthalpy of the nuclear spin system. The return to the magnetization to the equilibrium state is usually exponential, and is a first order process with constant speed, R1 , and time constant T1 .

The applied pulse sequence is described below:

$$\text{Observed nuclei:} \left[ 180^{\circ}\_{\text{x}} - \tau - 90^{\circ}\_{\text{x}} \right]\_{\text{x}} \tag{3}$$

where τ is a time interval between 90 pulses.

The relaxation time T1 H reports on the molecular dynamics of materials. In the case of starches and starch flour, for example, this parameter is sensitive to the formation of domains or segments and structural changes in the range 15–50 nm.

#### **3.2. Determination of T2**

The proton spin-spin relaxation time, T2 H, in principle, can be obtained by measuring the width of the NMR signal at half height. However, the inhomogeneity of the magnetic field causes the magnetization of the different nuclei processes at different rates when removing the RF and a time tau (*τ*) is needed to wait, which is chosen depending on the mobility of the sample; however, this inhomogeneity is refocused after an application of a 180° pulse, generating a single magnetization [1, 15, 16]. The pulse sequence normally used is Carr-Purcell-Meiboom-Gill (CPMG), which contains a train of pulses [1–5].

This relaxation time, and the time constant of spin-lattice relaxation reports about molecular mobility of materials in the molecular level, thereby assess overall molecular dynamics and segmental. The T2 H parameter corroborates data obtained by T1 H and sometimes can inform more detail of the material behavior under observation, if this have some regions or segments containing high-molecular mobility.

In several studies that involve the evaluation of molecular mobility of materials, specially using the NMR relaxometry, it was normally employed the measurements of relaxation times spin-lattice and spin-spin and evaluate the T<sup>1</sup> and T2 times constants of both relaxation phenomena, respectively. This comes from the fact that these parameters are sensitive to dynamic processes that occur at different frequency ranges. Thus, T<sup>1</sup> parameter measures the relaxation of the magnetization component parallel to the external magnetic field, being sensible to fast movements that are sensible to the movements of first order (MHz). The T<sup>1</sup><sup>ρ</sup> relaxation parameter is measured in low frequencies in the range of tens of kilohertz [1, 7, 17–23].

#### **4. Final comments**

In the solids, there is a restricted molecular movement comparing to liquids. However, most of the samples range have a substantial molecular orientation of the line width. This fact stems from the anisotropy of the chemical shift as well as the strong dipolar interaction between the hydrogen and carbon-13. The nature of the sample and the type of nuclei to be observed are two points of fundamental importance to the spectral resolution. The type of answer you want to get on a specific material may be a reason why it must be analyzed by solid-state NMR. Information on the molecular dynamics is of great interest for answers about the correlation structure-molecular-dynamic property. The line width in NMR solid state spectra led to the development of techniques that allows obtaining signals in the solid state most narrow possible, like liquids. Along with the information to be obtained, different techniques are performed to analyze the more different polymer systems.

#### **Author details**

Maria Ines Bruno Tavares

Address all correspondence to: mibt@ima.ufrj.br

Federal University of Rio de Janeiro, Professor Eloisa Mano Macromolecules Institute, Rio de Janeiro, Brazil

#### **References**

causes the magnetization of the different nuclei processes at different rates when removing the RF and a time tau (*τ*) is needed to wait, which is chosen depending on the mobility of the sample; however, this inhomogeneity is refocused after an application of a 180° pulse, generating a single magnetization [1, 15, 16]. The pulse sequence normally used is Carr-Purcell-

This relaxation time, and the time constant of spin-lattice relaxation reports about molecular mobility of materials in the molecular level, thereby assess overall molecular dynamics and

more detail of the material behavior under observation, if this have some regions or segments

In several studies that involve the evaluation of molecular mobility of materials, specially using the NMR relaxometry, it was normally employed the measurements of relaxation times

nomena, respectively. This comes from the fact that these parameters are sensitive to dynamic

ation of the magnetization component parallel to the external magnetic field, being sensible

In the solids, there is a restricted molecular movement comparing to liquids. However, most of the samples range have a substantial molecular orientation of the line width. This fact stems from the anisotropy of the chemical shift as well as the strong dipolar interaction between the hydrogen and carbon-13. The nature of the sample and the type of nuclei to be observed are two points of fundamental importance to the spectral resolution. The type of answer you want to get on a specific material may be a reason why it must be analyzed by solid-state NMR. Information on the molecular dynamics is of great interest for answers about the correlation structure-molecular-dynamic property. The line width in NMR solid state spectra led to the development of techniques that allows obtaining signals in the solid state most narrow possible, like liquids. Along with the information to be obtained, different techniques are

and T2

H and sometimes can inform

times constants of both relaxation phe-

parameter measures the relax-

relaxation

H parameter corroborates data obtained by T1

to fast movements that are sensible to the movements of first order (MHz). The T<sup>1</sup><sup>ρ</sup>

parameter is measured in low frequencies in the range of tens of kilohertz [1, 7, 17–23].

Federal University of Rio de Janeiro, Professor Eloisa Mano Macromolecules Institute,

Meiboom-Gill (CPMG), which contains a train of pulses [1–5].

processes that occur at different frequency ranges. Thus, T<sup>1</sup>

performed to analyze the more different polymer systems.

Address all correspondence to: mibt@ima.ufrj.br

segmental. The T2

**4. Final comments**

**Author details**

Maria Ines Bruno Tavares

Rio de Janeiro, Brazil

containing high-molecular mobility.

12 Spectroscopic Analyses - Developments and Applications

spin-lattice and spin-spin and evaluate the T<sup>1</sup>


**Provisional chapter**

## **Developments in Solid-State NMR Spectroscopy of Polymer Systems Polymer Systems**

**Developments in Solid-State NMR Spectroscopy of** 

DOI: 10.5772/intechopen.70116

Antonio Martínez-Richa and Regan L. Silvestri Regan L. Silvestri

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70116

Antonio Martínez-Richa and

#### **Abstract**

[20] Sebastião PJO, Monteiro MSSB, Brito LM, Rodrigues E, Chávez FV, Tavares MIB. Journal

[21] Tavares MR, Menezes LR, Nascimento DF, Souza DHS, Reynaud F, Marques MFV,

[22] Monteiro MSSB, Tavares MIB, Sebastião PJO. Materials Scince and Applications.

[23] Cunha APCB, Tavares MIB, Silva EO. Materials Sciences and Applications. 2016;**07**:380

[25] Tavares MIB, Nogueira RF, San Gil RAS, Preto M, Silva EO, e Silva MBR, Miguez E.Polymer

Tavares MIB. European Physical Journal Special Topics. 2016;**225**:779

of Nanoscience and Nanotechnology. 2016;**16**:7539

14 Spectroscopic Analyses - Developments and Applications

[24] Preto M, Tavares MIB, Silva EP d. Polymer Testing. 2007;**26**:501

2016;**7**:575

Testing. 2007;**26**:1102

Solid-state nuclear magnetic resonance (NMR) has long emerged as a valuable technique for characterizing the molecular structure, conformation, and dynamics of polymer chains in various polymer systems. The principles of the solid-state 13C NMR cross-polarization experiment are described along with corresponding relaxation measurements. The ensuing recent applications of these techniques to different polymer systems are reviewed, with selected examples that have appeared in the recent literature. All of these applications of solid-state NMR to polymers have one feature in common: the interpretation of spectroscopic observations as related to the structural features and physical properties of the polymer.

**Keywords:** polymers, solid-state NMR, structure-property relationship, polymer morphology, polymer dynamics, NMR relaxation time

#### **1. Introduction**

Solid-state nuclear magnetic resonance (NMR) spectroscopy is at this time well-established as a valuable technique for characterizing a variety of polymer systems. A multitude of NMR experiments can be used to gain valuable practical information about the molecular structure, conformation, and dynamics of polymer chains in various polymer systems. Such information is useful in the design of polymer properties, and therefore the technique of solid-state NMR has been widely applied to numerous polymer systems.

The use of solid-state 13C NMR is well established for elucidation of cross-linking structures in elastomers and bonding structures in adhesives [1], and the technique continues to be applied

to new elastomer and adhesive systems. These same techniques are now being applied to new polymer systems such as self-assembled polymers, advanced functional polymers, electroconducting polymers, microporous materials, and proteins [2].

#### **2. High-resolution 13C NMR spectroscopy of solid polymers**

Nuclei with a spin quantum number of *I* = ½ such as 1 H, 13C, 19F, 29Si, 15N, and 31P yield highresolution NMR spectra and are therefore particularly informative in the study of polymer systems. These nuclei display spectra with unique peaks for each magnetically inequivalent nuclei in the chemical structure, essentially enabling the study of individual atomic positions within the chemical structure of a polymer [3]. As such, localized information can be ascertained about individual atomic sites within the chemical structure of a polymer.

In solution, local magnetic fields experienced by nuclei are averaged by rapid isotropic motions resulting in the observation of relatively sharp NMR peaks. Polymers however are largely used not in the solution state but as structural engineered materials such as plastics and elastomers in the solid state. Therefore, there is a need to study them as solids, to characterize their properties in the solid state, which is the state that they will be used as structural materials. Observation of the 13C nucleus in the solid state is complicated by line broadening caused by strong dipolar interactions with the abundant 1 H isotope. This line broadening is reduced by heteronuclear dipolar decoupling (DD), a high powered radio frequency (rf) pulse at the 1 H frequency during the time in which the 13C signal is observed [4].

The collection of solid-state NMR spectra is also complicated by high chemical shift anisotropy, which is motionally averaged in the liquid state. The line broadening caused by chemical shift anisotropy in the solid state is reduced by a technique termed magic angle spinning (MAS). The broad chemical shift anisotropy pattern of a solid is reduced to a single peak at the isotropic chemical shift by spinning the solid sample, typically at a rate of a few thousand hertz, at an angle of precisely 54.74° relative to the static magnetic field [5].

The 13C isotope being only 1.1% naturally abundant, and the heteronuclear dipolar coupling and chemical shift anisotropy of solids being only partially reduced by DD and MAS, respectively, results in an inherently low signal-to-noise ratio for solid-state spectra. The 13C signal for solid samples is enhanced by a technique termed cross-polarization (CP). Crosspolarization is achieved by simultaneously applying spin locking rf pulses to both 13C and 1 H nuclei. The spin locking rf pulses are adjusted to reach a state where both nuclei process at the same frequency, a special condition referred to as the Hartmann-Hahn match. Under these conditions, magnetization is transferred from the naturally abundant 1 H spin reservoir to the more dilute 13C spin reservoir, resulting in signal enhancement of the 13C spin reservoir. As a result, an enhanced 13C signal can be observed for solid samples [6].

The combination of these three techniques (DD, MAS, and CP) into one experiment provides a method for the collection of high-resolution 13C NMR spectra of solids. The results observed by applying these techniques, in combination progressively and ultimately, simultaneously in one experiment, are shown in **Figure 1** [7]. The method of simultaneously combining DD, MAS, and CP has become routine for solid samples, and applications to polymer systems are sufficiently plentiful to fill entire professional reference textbooks [8]. Particularly, application of the solid-state NMR technique has historically proven to be highly informative in elucidation on the conformational structure of solid polymers via chemical shift analysis and determination of cross-linking structures of cross-linked solid polymers.

to new elastomer and adhesive systems. These same techniques are now being applied to new polymer systems such as self-assembled polymers, advanced functional polymers, electro-

resolution NMR spectra and are therefore particularly informative in the study of polymer systems. These nuclei display spectra with unique peaks for each magnetically inequivalent nuclei in the chemical structure, essentially enabling the study of individual atomic positions within the chemical structure of a polymer [3]. As such, localized information can be ascer-

In solution, local magnetic fields experienced by nuclei are averaged by rapid isotropic motions resulting in the observation of relatively sharp NMR peaks. Polymers however are largely used not in the solution state but as structural engineered materials such as plastics and elastomers in the solid state. Therefore, there is a need to study them as solids, to characterize their properties in the solid state, which is the state that they will be used as structural materials. Observation of the 13C nucleus in the solid state is complicated by line broadening

is reduced by heteronuclear dipolar decoupling (DD), a high powered radio frequency (rf)

H frequency during the time in which the 13C signal is observed [4]. The collection of solid-state NMR spectra is also complicated by high chemical shift anisotropy, which is motionally averaged in the liquid state. The line broadening caused by chemical shift anisotropy in the solid state is reduced by a technique termed magic angle spinning (MAS). The broad chemical shift anisotropy pattern of a solid is reduced to a single peak at the isotropic chemical shift by spinning the solid sample, typically at a rate of a few thousand

The 13C isotope being only 1.1% naturally abundant, and the heteronuclear dipolar coupling and chemical shift anisotropy of solids being only partially reduced by DD and MAS, respectively, results in an inherently low signal-to-noise ratio for solid-state spectra. The 13C signal for solid samples is enhanced by a technique termed cross-polarization (CP). Crosspolarization is achieved by simultaneously applying spin locking rf pulses to both 13C and 1

nuclei. The spin locking rf pulses are adjusted to reach a state where both nuclei process at the same frequency, a special condition referred to as the Hartmann-Hahn match. Under these

more dilute 13C spin reservoir, resulting in signal enhancement of the 13C spin reservoir. As a

The combination of these three techniques (DD, MAS, and CP) into one experiment provides a method for the collection of high-resolution 13C NMR spectra of solids. The results observed by applying these techniques, in combination progressively and ultimately, simultaneously in one experiment, are shown in **Figure 1** [7]. The method of simultaneously combining DD,

H, 13C, 19F, 29Si, 15N, and 31P yield high-

H isotope. This line broadening

H

H spin reservoir to the

conducting polymers, microporous materials, and proteins [2].

Nuclei with a spin quantum number of *I* = ½ such as 1

16 Spectroscopic Analyses - Developments and Applications

caused by strong dipolar interactions with the abundant 1

hertz, at an angle of precisely 54.74° relative to the static magnetic field [5].

conditions, magnetization is transferred from the naturally abundant 1

result, an enhanced 13C signal can be observed for solid samples [6].

pulse at the 1

**2. High-resolution 13C NMR spectroscopy of solid polymers**

tained about individual atomic sites within the chemical structure of a polymer.

Beyond the DD, MAS, and CP experiment to collect high-resolution solid-state spectra, sophisticated and elegant rf pulse sequences are now used to perturb the magnetization in specific ways. As such, observation of the magnetization as it processes back to equilibrium via various cleaver rf pulse sequences allows the collection of information far beyond the simple spectrum.

**Figure 1.** The 13C NMR spectra of poly(methyl methacrylate) in the solid state under various experimental conditions: (a) using the experimental conditions for solution spectra, no discernible peaks are observed for the solid sample; (b) using dipolar decoupling with cross-polarization permits the observation of broad chemical shift anisotropy patterns; (c) using dipolar decoupling with magic angle spinning reduces the broad chemical shift anisotropy patterns to resolvable peaks; and (d) the combination of all three techniques, dipolar decoupling with magic angle spinning and cross-polarization, facilitates the observation of a high-resolution spectrum for the solid sample. Reprinted from Ref. [7].

For example, the study of selectively pulsed magnetization as it relaxes back to equilibrium yields insight into not only the molecular structure, but also the molecular dynamics of a polymer system. Relaxation of a nucleus back to equilibrium is modulated by fluctuations in the local magnetic field which the nucleus experiences, and the local field is modulated due to the local environment, including not only the physical-chemical structure around a nucleus, but also molecular motion that the nucleus is involved in. Various pulse sequences allow the measurement of relaxation parameters including T1 , T2 , and T1ρ, which yield information about molecular motions in different frequency ranges, which occur over different scales of distance [9]. Beyond the direct measurement of these relaxation parameters, other pulse sequences exploit these relaxation phenomena to yield data which can be interpreted in terms of polymer structure and properties.

Two-dimensional (2D) NMR techniques enhance the resolution of a traditional one-dimensional spectrum by spreading the peaks out in a second dimension. Two-dimensional NMR techniques also facilitate the observation of through bond or through space interactions, where through space interactions being particularly related to the physical structure of polymers such as conformation [10]. While 2D NMR techniques are routine for solutions, they are still considered by some to be experimentally cumbersome in the solid state. Nonetheless, there has been considerable progress recently in the development of experimentally practical pulse sequences for 2D NMR of solid samples [11].

#### **3. Applications to various polymer systems**

#### **3.1. Carbohydrates**

Wood is a complex heterogeneous material composed mainly of hemicellulose, cellulose, and lignin. Solid-state NMR spectroscopy can discriminate wood samples based upon their provenance. In that regard, the traceability of wood samples can be undertaken by analyzing the solid-state NMR peak patterns in their MAS and CP-MAS spectra.

This technique has been used to characterize the chemical composition of wood, and the effects of aging, decomposition, and some physical or chemical treatments on the polymer structure. Recently, this technique was used to analyze maple samples from Norway [12] and spruce samples from Finland, Poland, and Italy [13]. The chemical structures of various components in soft wood are shown in **Figure 2**. Carbon-13 CP-MAS NMR spectra for spruce wood from Finland, Poland, and Italy are shown in **Figure 3** with resonance peaks labeled to correspond with the structures shown in **Figure 2**. While the same peak pattern is present in all three samples, small differences (mainly in peak intensity) can be distinguished between the three spectra.

In the spectral region 110–160 ppm, differences in the lignin aromatic components can be distinguished, whereas in the spectral region from 15 to 110 ppm, differences in the signals for cellulose and hemicellulose can be observed. In that regard, the most intense peaks in the spectra 12 and 13 are due to the C-2, C-3, and C-5 carbons of the carbohydrates. The two peaks 10 and 11 are assigned to C-4, in crystalline and amorphous (or less ordered surface) cellulose, Developments in Solid-State NMR Spectroscopy of Polymer Systems http://dx.doi.org/10.5772/intechopen.70116 19

**Figure 2.** Chemical structures of various wood components in softwood. The numbering scheme corresponds to the resonance peaks as labeled in **Figure 3**. Reprinted from Ref. [13].

respectively. Peak 15 is related to C-6 in cellulose and Cγ in lignin. Peak 8 represents the C-1 of cellulose, with a high-field shoulder 9 attributed to hemicellulose (102 ppm). Only two signals can be undoubtedly attributed to hemicellulose: the methyl carbon peak 18 and the carboxylic carbon peak 1; both of these are rather weak in intensity. Three groups of signals in the range 160–105 ppm are attributed to the three aromatic units constituting the lignin lattice. Finally, the small peak 16 is assigned to the lignin methoxyl group.

As differences in peak pattern intensities for the three samples are small, <sup>1</sup> H T1ρ measurements were obtained using a variable CP contact time experiment. The results suggest that higher polymer mobility and a higher homogeneity are observed in spruce wood from Finland, relative to a lower homogeneity measured in samples from both Italy and Poland.

#### **3.2. Protein systems**

For example, the study of selectively pulsed magnetization as it relaxes back to equilibrium yields insight into not only the molecular structure, but also the molecular dynamics of a polymer system. Relaxation of a nucleus back to equilibrium is modulated by fluctuations in the local magnetic field which the nucleus experiences, and the local field is modulated due to the local environment, including not only the physical-chemical structure around a nucleus, but also molecular motion that the nucleus is involved in. Various pulse sequences allow the measurement of relax-

different frequency ranges, which occur over different scales of distance [9]. Beyond the direct measurement of these relaxation parameters, other pulse sequences exploit these relaxation phenomena to yield data which can be interpreted in terms of polymer structure and properties.

Two-dimensional (2D) NMR techniques enhance the resolution of a traditional one-dimensional spectrum by spreading the peaks out in a second dimension. Two-dimensional NMR techniques also facilitate the observation of through bond or through space interactions, where through space interactions being particularly related to the physical structure of polymers such as conformation [10]. While 2D NMR techniques are routine for solutions, they are still considered by some to be experimentally cumbersome in the solid state. Nonetheless, there has been considerable progress recently in the development of experimentally practical

Wood is a complex heterogeneous material composed mainly of hemicellulose, cellulose, and lignin. Solid-state NMR spectroscopy can discriminate wood samples based upon their provenance. In that regard, the traceability of wood samples can be undertaken by analyzing the

This technique has been used to characterize the chemical composition of wood, and the effects of aging, decomposition, and some physical or chemical treatments on the polymer structure. Recently, this technique was used to analyze maple samples from Norway [12] and spruce samples from Finland, Poland, and Italy [13]. The chemical structures of various components in soft wood are shown in **Figure 2**. Carbon-13 CP-MAS NMR spectra for spruce wood from Finland, Poland, and Italy are shown in **Figure 3** with resonance peaks labeled to correspond with the structures shown in **Figure 2**. While the same peak pattern is present in all three samples, small differences (mainly in peak intensity) can be distinguished between

In the spectral region 110–160 ppm, differences in the lignin aromatic components can be distinguished, whereas in the spectral region from 15 to 110 ppm, differences in the signals for cellulose and hemicellulose can be observed. In that regard, the most intense peaks in the spectra 12 and 13 are due to the C-2, C-3, and C-5 carbons of the carbohydrates. The two peaks 10 and 11 are assigned to C-4, in crystalline and amorphous (or less ordered surface) cellulose,

, and T1ρ, which yield information about molecular motions in

ation parameters including T1

18 Spectroscopic Analyses - Developments and Applications

**3.1. Carbohydrates**

the three spectra.

, T2

pulse sequences for 2D NMR of solid samples [11].

**3. Applications to various polymer systems**

solid-state NMR peak patterns in their MAS and CP-MAS spectra.

Solid-state NMR spectroscopy has been widely applied to study a variety of protein systems. Various modern solid-state NMR techniques can be applied to gain insights into biophysics and structural biology in proteins.

**Figure 3.** Solid-state 13C NMR spectra of spruce woods differing in provenance and their peaks assignments. Differences in peak intensities can be used to distinguish between the geographic origins of woods. Reprinted from Ref. [13].

Peptide nanoassemblies have been studied by solid-state NMR. Using the recent development of high-field MAS dynamic nuclear polarization (MAS-DNP), an increase in sensitivity for the peaks of crystalline components of the polymer system can be achieved [14]. Using this approach, self-assembled structures of systems based on diphenylalanine dipeptide (FF) have been studied. These proteins have applications as organic semiconductors, and have been reported as a core motif of Alzheimer's amyloid-β. Supramolecular structural information such as hydrogen bonding and π-π stacking can be improved using dynamic nuclear polarization. Ultimately, an increase in sensitivity by an overall factor of 320 is achieved by using DNP.

Self-assembly peptide nanostructure can be studied by solid-state NMR. MAX8 is an amphiphilic peptide composed of 20 amino acids, having the amino acid sequence VKVKVKVKVDPPTKVEVKVKVNH2, where K and E are hydrophilic residues and V hydrophobic residues [15]. The self-assembled peptide contains a β-strand hairpin structure aligned into antiparallel β-sheets. As is commonly observed, changes in supramolecular structure can be induced by changes in temperature, pH, and ionic strength. The CP-MAS spectra of labeled and unlabeled MAX8 nanofibers are shown in **Figure 4**. The observed chemical shifts for the amino acid residues 1–8 and 13–20 indicates that they form part of a β-hairpin conformation. Polymorphism of K residues occurs uniformly across the MAX8 amino acid system. Calculations of φ and ϕ backbone torsion angles, derived from peak positions using commercial software, were consistent with β-strand secondary structures for residues 1–8 and

**Figure 4.** Solid-state 13C CP-MAS spectra of labeled and unlabeled MAX8 nanofiber, a peptide composed of 20 amino acids. Observed chemical shifts for the amino acid residues allow determination of the three dimensional conformational structure of the peptide. Reprinted from Ref. [15].

13–20. Further evidence of the existence of a close β-hairpin conformation was obtained by (a) the analysis of cross-peaks in a 2D DARR 13C─13C NMR experiment, and (b) 13C─13C dipolar recoupling NMR experiments using the PITHIRDS-CT technique. The PITHIRDS-CT technique is a constant-time dipolar recoupling sequence in solid-state NMR with MAS, which yields experimental data that is insensitive to rf pulse imperfections and nuclear spin relaxation processes. This sequence has been widely used to determine intermolecular distances and molecular conformations in solid 13C and 15N labeled compounds, and as such one of the most important applications of this technique has been the study of biological samples such as amino acids and amyloid fibrils.

Peptide nanoassemblies have been studied by solid-state NMR. Using the recent development of high-field MAS dynamic nuclear polarization (MAS-DNP), an increase in sensitivity for the peaks of crystalline components of the polymer system can be achieved [14]. Using this approach, self-assembled structures of systems based on diphenylalanine dipeptide (FF) have been studied. These proteins have applications as organic semiconductors, and have been reported as a core motif of Alzheimer's amyloid-β. Supramolecular structural information such as hydrogen bonding and π-π stacking can be improved using dynamic nuclear polarization. Ultimately, an increase in sensitivity by an overall factor of 320 is achieved by using DNP. Self-assembly peptide nanostructure can be studied by solid-state NMR. MAX8 is an amphiphilic peptide composed of 20 amino acids, having the amino acid sequence VKVKVKVKVDPPTKVEVKVKVNH2, where K and E are hydrophilic residues and V hydrophobic residues [15]. The self-assembled peptide contains a β-strand hairpin structure aligned into antiparallel β-sheets. As is commonly observed, changes in supramolecular structure can be induced by changes in temperature, pH, and ionic strength. The CP-MAS spectra of labeled and unlabeled MAX8 nanofibers are shown in **Figure 4**. The observed chemical shifts for the amino acid residues 1–8 and 13–20 indicates that they form part of a β-hairpin conformation. Polymorphism of K residues occurs uniformly across the MAX8 amino acid system. Calculations of φ and ϕ backbone torsion angles, derived from peak positions using commercial software, were consistent with β-strand secondary structures for residues 1–8 and

**Figure 3.** Solid-state 13C NMR spectra of spruce woods differing in provenance and their peaks assignments. Differences in peak intensities can be used to distinguish between the geographic origins of woods. Reprinted from Ref. [13].

20 Spectroscopic Analyses - Developments and Applications

In a similar approach, β-sheet nanocrystalline domains in phosphorylated serine-rich motifs in caddisfly larval silk were studied by 13C and 31P solid-state NMR [16]. 13C NMR data from isotopically enriched caddisfly silk, packed in its natural hydrated environment, are shown in **Figure 5**. 13C chemical shifts were identified using 13C─13C DARR and 1 H → 31P → 13C DCP NMR experiments. Differences between CP-MAS and DD-MAS spectra are due to the aqueous environment. Water-solvated residues with a short T1 exhibit enhanced signals in the DD-MAS spectrum, whereas carbons located in more rigid environments are better observed in the CP-MAS spectrum. An enhanced peak for the unmodified serine β carbon is seen in the DD-MAS spectrum, suggesting higher mobility. On the other hand, the signal of the phosphorylated serine β carbon is broader, indicating that these moieties mainly reside in the β-sheet regions. Similar conclusions have been derived for Valine residues. However, glycine and leucine residues, often seen in GGX repeats, exist predominantly in a random or disordered conformation.

**Figure 5.** Solid-state 13C NMR of isotopically enriched caddisfly silk from the species *Hyllisia consimilis* in its natural water-hydrated environment. (A) 1 H → 13C CP-MAS NMR, and (B) 13C DD-MAS NMR using a fast (1 s) repetition time. Peaks, which have a higher intensity without cross-polarization are in more mobile water-solvated regions, whereas peaks which have a higher intensity with cross-polarization are in more rigid environments in the β-sheet regions. Carbonyl spinning side bands are marked with a double asterisks. Reprinted from Ref. [16].

#### **3.3. Conducting polymers**

Advances in conducting and semiconducting materials have led to enhancements in the performance of organic thin transistors, organic photovoltaics, and other devices. High molar mass poly(3-hexylthiophene) (P3HT), an organic semiconductor, has been studied by solidstate 13C CP-MAS NMR. Information at the subnanometer length scale can be obtained via solid-state NMR.

Recently, a modified approach to this technique has facilitated a correlation between peak pattern observed in CP-MAS spectra and the degree of crystallinity [17]. Measurements of order in semicrystalline, high molar mass poly(3-hexylthiophene) (P3HT) were made via solid-state 13C CP-MAS. The relative degrees of order were compared between two films under different drying conditions: one slow-dried and one fast-dried. Ordered and disordered fractions within the polymer were separated using a T1ρ filtered CP-MAS experiment. The spectrum for the ordered P3HT component is then obtained by spectral subtraction, as shown in **Figure 6**. The peak pattern of the crystalline component for slow-dried P3HT is narrower than that observed for the fast-dried sample. NMR does not measure long-range order, but instead is sensitive to order on a subnanometer scale. Line shape analysis shows that chains in noncrystalline regions Developments in Solid-State NMR Spectroscopy of Polymer Systems http://dx.doi.org/10.5772/intechopen.70116 23

**3.3. Conducting polymers**

water-hydrated environment. (A) 1

22 Spectroscopic Analyses - Developments and Applications

solid-state NMR.

Advances in conducting and semiconducting materials have led to enhancements in the performance of organic thin transistors, organic photovoltaics, and other devices. High molar mass poly(3-hexylthiophene) (P3HT), an organic semiconductor, has been studied by solidstate 13C CP-MAS NMR. Information at the subnanometer length scale can be obtained via

**Figure 5.** Solid-state 13C NMR of isotopically enriched caddisfly silk from the species *Hyllisia consimilis* in its natural

Peaks, which have a higher intensity without cross-polarization are in more mobile water-solvated regions, whereas peaks which have a higher intensity with cross-polarization are in more rigid environments in the β-sheet regions.

Carbonyl spinning side bands are marked with a double asterisks. Reprinted from Ref. [16].

H → 13C CP-MAS NMR, and (B) 13C DD-MAS NMR using a fast (1 s) repetition time.

Recently, a modified approach to this technique has facilitated a correlation between peak pattern observed in CP-MAS spectra and the degree of crystallinity [17]. Measurements of order in semicrystalline, high molar mass poly(3-hexylthiophene) (P3HT) were made via solid-state 13C CP-MAS. The relative degrees of order were compared between two films under different drying conditions: one slow-dried and one fast-dried. Ordered and disordered fractions within the polymer were separated using a T1ρ filtered CP-MAS experiment. The spectrum for the ordered P3HT component is then obtained by spectral subtraction, as shown in **Figure 6**. The peak pattern of the crystalline component for slow-dried P3HT is narrower than that observed for the fast-dried sample. NMR does not measure long-range order, but instead is sensitive to order on a subnanometer scale. Line shape analysis shows that chains in noncrystalline regions

**Figure 6.** Solid-state 13C CP-MAS spectra of the fast-dried organic semiconductor poly(3-hexylthiophene) (P3HT) (a) without and (b) with a T1ρH spectral editing (spin-lock) pulse prior to cross-polarization, as well as the difference spectrum: (c) = (b) – (0.35 × (a)). The (d) CP-MAS spectrum for fast-dried P3HT, and (e) its ordered and (f) disordered fractions. The (g) CP-MAS spectrum for slow-dried P3HT, and (h) its ordered and (i) disordered fractions. Reprinted from Ref. [17].

can exhibit uniform local packing, which is presumed to be the result of uniform molecular conformations. Ultimately, observation of a narrower peak pattern of the crystalline component for slow-dried than for fast-dried is interpreted to mean that the quality of order is different, and that P3HT may be classified as a conformationally disordered crystal.

The solid-state NMR technique provides information about the conducting polymer system, which is close to the natural state and natural local conformation and packing arrangement. As such, information from solid-state NMR experiments may be regarded as favored to information derived by other techniques such as wide-angle X-ray scattering and differential scanning calorimetry.

#### **4. NMR relaxation**

The magnetic properties of a nucleus are modulated by the magnetic fields of neighboring nuclei. As molecular motions occur in the local environment changes resulting in altered interactions between nuclear spins. The study of NMR relaxation parameters yields information about the molecular motions in polymer systems.

The NMR relaxation parameters, which are most commonly measured are T1 , T2 , and T1ρ. T1 is the so-called spin-lattice relaxation time, T<sup>2</sup> is the spin-spin relaxation time, and T1ρ is the spin-lattice relaxation time in the rotating frame. These various relaxation parameters are related to molecular motions on varied time scales, and the correlation time of a molecular motion is related to the scale or distance over which a molecular motion occurs. As such, each of the relaxation parameters T1 , T2 , and T1ρ is characteristic of molecular motions involving different frequency ranges, which occur accordingly over different distance scales as shown in **Figure 7**. The relaxation parameter T1 probes fast motions with frequencies in the MHz regime; such fast motions are small-scale short-range motions, which are typically internal to a molecule. The relaxation parameter T1ρ probes slower motions with frequencies in the kHz regime; these relatively slower motions occur over a larger distance and correspond to long chain motions in polymers. The theoretical relationship between the 13C NMR relaxation parameters T1 , T2 , and T1ρ in the solid state and correlation time τ<sup>c</sup> are shown in **Figure 8** [18].

**Figure 7.** The solid-state 13C NMR relaxation parameters T1 , T2, and T1ρ (in seconds) and the corresponding correlation times τ<sup>c</sup> (in seconds) for the motions which they are sensitive to. Each of the relaxation parameters T1 , T2, and T1ρ are characteristic of molecular motions in different frequency ranges which occur over different distance scales.

can exhibit uniform local packing, which is presumed to be the result of uniform molecular conformations. Ultimately, observation of a narrower peak pattern of the crystalline component for slow-dried than for fast-dried is interpreted to mean that the quality of order is differ-

The solid-state NMR technique provides information about the conducting polymer system, which is close to the natural state and natural local conformation and packing arrangement. As such, information from solid-state NMR experiments may be regarded as favored to information derived by other techniques such as wide-angle X-ray scattering and differential

The magnetic properties of a nucleus are modulated by the magnetic fields of neighboring nuclei. As molecular motions occur in the local environment changes resulting in altered interactions between nuclear spins. The study of NMR relaxation parameters yields informa-

spin-lattice relaxation time in the rotating frame. These various relaxation parameters are related to molecular motions on varied time scales, and the correlation time of a molecular motion is related to the scale or distance over which a molecular motion occurs. As such, each

different frequency ranges, which occur accordingly over different distance scales as shown

regime; such fast motions are small-scale short-range motions, which are typically internal to a molecule. The relaxation parameter T1ρ probes slower motions with frequencies in the kHz regime; these relatively slower motions occur over a larger distance and correspond to long chain motions in polymers. The theoretical relationship between the 13C NMR relaxation

, and T1ρ in the solid state and correlation time τ<sup>c</sup>

(in seconds) for the motions which they are sensitive to. Each of the relaxation parameters T1

characteristic of molecular motions in different frequency ranges which occur over different distance scales.

, T2

are shown in **Figure 8** [18].

is the spin-spin relaxation time, and T1ρ is the

, and T1ρ is characteristic of molecular motions involving

probes fast motions with frequencies in the MHz

, T2, and T1ρ (in seconds) and the corresponding correlation

, and T1ρ. T1

, T2, and T1ρ are

ent, and that P3HT may be classified as a conformationally disordered crystal.

The NMR relaxation parameters, which are most commonly measured are T1

, T2

scanning calorimetry.

24 Spectroscopic Analyses - Developments and Applications

**4. NMR relaxation**

tion about the molecular motions in polymer systems.

is the so-called spin-lattice relaxation time, T<sup>2</sup>

in **Figure 7**. The relaxation parameter T1

**Figure 7.** The solid-state 13C NMR relaxation parameters T1

of the relaxation parameters T1

, T2

parameters T1

times τ<sup>c</sup>

**Figure 8.** Theoretical dependence of the relaxation times T1 , T2 , and T1ρ on the correlation time τ<sup>c</sup> of the molecular motions responsible for the relaxation, as predicted by molecular motions that result in changes in dipole-dipole interactions. Region A is characteristic of a rigid lattice, region B of a nonrigid solid, region C of a viscous liquid, and region D of a nonviscous liquid. Reprinted from Ref. [18].

Semi-crystalline polymers are composed of amorphous (noncrystalline) bulk material, which contains crystalline domains. As NMR relaxation is modulated not only by physical-chemical structure, but also by molecular motions, the study of NMR relaxation yield insight into phases and phase structure in such multiphase polymer systems. The different domains present in such polymer materials display differences in molecular mobility, with the motion in crystalline domains being more restricted. Nuclei in amorphous domains show a higher mobility than those of nuclei in more rigid crystalline domains. Insight into polymer phase structure can be gained by the measurement of the NMR relaxation parameters T1 , T2 , and T1ρ [19].

There are numerous examples of how such NMR relaxation studies have been exploited to yield valuable information about the phase structure in polymer blends. In the interest of blending thermoplastics with biodegradable polymers, the degree of crystallinity of microbial poly(ε-llysine) has been estimated via 13C T1 relaxation experiments [20]. In another study, the domain size of poly(ε-l-lysine) blended with poly(vinyl isobutyl ether) was estimated via 1 H spin-lattice relaxation experiments, and further miscibility of blends prepared under various processing conditions was explained in terms of crystallinity observations from the relaxation experiments [21]. In a similar study, phase separation in starch/polycaprolactone blends was investigated and the length scale over which phase separation occurs was determined via 13C T1 , 1 H T1 , and 1 H T1ρ

relaxation experiments [22]. Further, the effect of the concentration of poly(ethylene glycol) in poly(ethylene glycol)/silica blends has been investigated via 13C T1 and 1 H T1ρ relaxation experiments yield information about inhomogeneous separated phases [23]. As a final example, blends of poly(ethylene terephthalate) toughened by natural rubber have been studied by 13C chemical shift and 1 H T1ρ relaxation experiments, yielding evidence of interactions between the carbonyl groups of the poly(ethylene terephthalate) with some functionality in the natural rubber [24].

Likewise, there are numerous examples of how such NMR relaxation studies have been exploited to yield practical and useful information about copolymer systems. For example, poly(styrenebutadiene-styrene) has been found to compatibilize otherwise incompatible blends of polystyrene/polybutadiene, and 1 H T1 , 1 H T2 and 1 H T1ρ relaxation experiments have been used to explain this observation in terms of preferential localization of the copolymers at the polystyrene/polybutadiene interface [25]. Likewise, the content and length of soft/hard segments and microphaseseparated morphology of poly(ether-block-amide) copolymers have been elucidated by and 13C T1 , 13C T1ρ, and 1 H T1ρ relaxation experiments [26]. As a final example, segmented copolymers of poly(N-isopropyl acryl amide) and poly(tetrahydrofuran) have been studied by 1 H T1 and 1 H T1ρ relaxation experiments, to monitor the multiphase characteristics of the segmented copolymer networks as the polymerizable end group of the copolymer was varied [27].

Further, there are numerous examples of how NMR relaxation studies have been exploited to yield practical and useful information about polymer composites. For example, a 1 H T1 and 1 H T1ρ relaxation study of poly(p-phenylene benzobisoxazole) fibers demonstrated the observation of crystalline and noncrystalline regions, and further allowed determination of the crystal size [28]. As another example, the dispersion of organomodified clay fillers in nanocomposites with various thermoplastics was investigated by 1 H T1 relaxation. The comparison in **Figure 9** of the 1 H T1 saturation-recovery curve for polyamide 6 with that of a nanocomposite of polyamide 6

**Figure 9.** Solid-state 1 H T1 saturation-recovery curves for polyamide 6 and a nanocomposite of polyamide 6 with an organomodified clay. The presence of clay shortens the relaxation time, indicating nanodispersion of the clay in the composite. Reprinted from Ref. [29].

with an organomodified clay, shows that the presence of clay shortens the relaxation time. The nanocomposites have a shorter relaxation time due to paramagnetically induced relaxation at the polymer-clay interface, indicating nanodispersion of the clay. Through a detailed and systematic study thereby, quantitative measurements of the degree of nanodispersion have been made [29].

Finally, in an example involving the combination of copolymers and composites, cotton fibers for composites were modified by surface copolymerization of ethyl acrylate followed by styrene. The graft copolymer-encapsulated cotton fibers were studied by <sup>1</sup> H T1 relaxation experiments, yielding the observation of a heterogeneous morphology of the grafted skin [30].

#### **5. Concluding remarks**

relaxation experiments [22]. Further, the effect of the concentration of poly(ethylene glycol) in

ments yield information about inhomogeneous separated phases [23]. As a final example, blends of poly(ethylene terephthalate) toughened by natural rubber have been studied by 13C chemical

groups of the poly(ethylene terephthalate) with some functionality in the natural rubber [24].

Likewise, there are numerous examples of how such NMR relaxation studies have been exploited to yield practical and useful information about copolymer systems. For example, poly(styrenebutadiene-styrene) has been found to compatibilize otherwise incompatible blends of polysty-

this observation in terms of preferential localization of the copolymers at the polystyrene/polybutadiene interface [25]. Likewise, the content and length of soft/hard segments and microphaseseparated morphology of poly(ether-block-amide) copolymers have been elucidated by and 13C

relaxation experiments, to monitor the multiphase characteristics of the segmented copolymer

Further, there are numerous examples of how NMR relaxation studies have been exploited to

T1ρ relaxation study of poly(p-phenylene benzobisoxazole) fibers demonstrated the observation of crystalline and noncrystalline regions, and further allowed determination of the crystal size [28]. As another example, the dispersion of organomodified clay fillers in nanocomposites with

H T1

saturation-recovery curve for polyamide 6 with that of a nanocomposite of polyamide 6

saturation-recovery curves for polyamide 6 and a nanocomposite of polyamide 6 with an

organomodified clay. The presence of clay shortens the relaxation time, indicating nanodispersion of the clay in the

poly(N-isopropyl acryl amide) and poly(tetrahydrofuran) have been studied by 1

yield practical and useful information about polymer composites. For example, a 1

networks as the polymerizable end group of the copolymer was varied [27].

H T1ρ relaxation experiments, yielding evidence of interactions between the carbonyl

H T1ρ relaxation experiments [26]. As a final example, segmented copolymers of

and 1

H T1ρ relaxation experiments have been used to explain

relaxation. The comparison in **Figure 9** of the

H T1ρ relaxation experi-

H T1

and 1

H T1

H T1ρ

 and 1 H

poly(ethylene glycol)/silica blends has been investigated via 13C T1

26 Spectroscopic Analyses - Developments and Applications

H T1 , 1 H T2 and 1

various thermoplastics was investigated by 1

shift and 1

T1

1 H T1

rene/polybutadiene, and 1

, 13C T1ρ, and 1

**Figure 9.** Solid-state 1

H T1

composite. Reprinted from Ref. [29].

Solid-state NMR continues to advance as a valuable technique for characterizing the molecular structure, conformation, and dynamics of polymers. There is already a rich history of applications of various solid-state NMR experiments to numerous polymer systems. Not only are advances occurring in the development of new solid-state NMR techniques, but also techniques which are now considered traditional are finding application to newly developed modern polymer materials. Ultimately, the application of solid-state NMR to polymers provides for the interpretation of spectroscopic observations as related to the structural features and physical properties of the polymer in the solid state, the state in which they are predominately used in as materials.

#### **Author details**

Antonio Martínez-Richa1 \* and Regan L. Silvestri2

\*Address all correspondence to: richa@ugto.mx

1 Universidad de Guanajuato, Guanajuato, Mexico

2 Lorain County Community College, Elyria, USA

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[9] Silvestri RL, Koenig JL. Applications of nuclear magnetic resonance spectrometry to solid polymers. Analytica Chimica Acta. 1993;**283**(3):997-1005. DOI: 10.1016/0003-2670

[10] Ernst RR, Bodenhausen G, Wokaun A. Principles of Nuclear Magnetic Resonance in One

[11] Schmidt-Rohr K, Clauss J, Spiess HW. Correlation of structure, mobility, and morphological information in heterogeneous polymer materials by two-dimensional widelineseparation NMR spectroscopy. Macromolecules. 1992;**25**(12):3273-3277. DOI: 10.1021/

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[16] Addison JB, Ashton NN, Weber WS, Stewart RJ, Holland GP, Yarger JL. β-sheet nanocrystalline domains formed from phosphorylated serine-rich motifs in caddisfly larval silk: A solid state NMR and XRD study. Biomacromolecules. 2013;**14**(4):1140-1148. DOI:

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[7] Fyfe CA. Solid State NMR for Chemists. Ontario: CFC Press; 1983. 593 p

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ma00038a037

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DOI: 10.1002/anie.201210093

10.1021/bm400019d


Provisional chapter

## **Dynamics of Model Membranes by NMR**

DOI: 10.5772/intechopen.69866

Dynamics of Model Membranes by NMR

### Anna Timoszyk

[29] Samyn F, Bourbigot S, Jama C, Bellayer S, Nazare S, Hull R, Castrovinci A, Fina A, Camino G. Crossed characterization of polymer-layered silicate (PLS) nanocomposite morphology: TEM, X-ray diffraction, rheology and solid-state nuclear magnetic resonance measurements. European Polymer Journal. 2008;**44**(6):1642-1653. DOI: 10.1016/j.

[30] Castelvetro V, Geppi M, Giaiacopi S, Mollica G. Cotton fibers encapsulated with homoand block copolymers: Synthesis by the atom transfer radical polymerization graftingfrom technique and solid-state NMR dynamic investigations. Biomacromolecules.

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30 Spectroscopic Analyses - Developments and Applications

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Additional information is available at the end of the chapter Anna Timoszyk

http://dx.doi.org/10.5772/intechopen.69866 Additional information is available at the end of the chapter

#### Abstract

Amphiphilic molecules can create various aggregates in water. Concern about exploring such structures has been unabated for several decades due to the wide range of possible applications of lipid aggregates, from food technology to the pharmaceutical industry. The form of self-assembled structures depends on many factors, such as the type of amphiphilic molecule, the concentration, the level of hydration, the temperature, and the pH. Liposomes and micelles are the most widely known types of closed structures. Liposomes are more often used in the fields of medicine and pharmacy because they consist of nontoxic compounds and their composition and size can be controlled. Nuclear magnetic resonance (NMR) is one of the methods, which is most commonly used to study liposome properties. It can be used to observe changes in the structure, dynamics, and phase transition of lipid membranes. The membrane properties are changed under the influence of external factors, such as temperature, pH, and the presence of ions or drugs. The chapter aims to introduce and discuss the possibilities of the most useful NMR methods, 31P and <sup>1</sup> H, to study the liposome properties. It also aims to show how various changes in the structure or dynamics of lipid molecules are visible in the NMR spectra.

Keywords: lipid aggregates, model membrane, liposome, dynamics, splitting, half-width of signal, <sup>1</sup> H NMR, 31P NMR

#### 1. Introduction

The phenomenon of creating various types of aggregates by lipids in water is of particular interest to professionals in the fields of biophysics, biochemistry, medicine, and pharmacy. The reason for this broad interest is the similarity between formed aggregates and subcellular structures, such as lysosomes and biological membranes. Thus, the structures, particularly those such as bilayers, have been used as models of biological membranes for many years.

© 2017 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.

© 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 eproduction in any medium, provided the original work is properly cited.

The main advantage of this model is its ability to decide the composition, both in terms of lipid and protein content and the environment in which they are located (one in which various types of ions are present). Model membranes enable the study of their thermotropic properties, the transport of ions through them, and the phenomenon of vesicle fusion. Currently, model biological membranes (liposomes) are widely used as drug delivery systems and in various kinds of therapies.

The use of nuclear magnetic resonance (NMR) to study these structures poses several challenges. For instance, the technique uses a method of sample preparation that differs from the standard methods used for measurement in a liquid. An additional problem is the formation of lipid aggregates in water, which exhibits differ in the NMR time scale. This is due to the fact that NMR spectrometer "sees" the hydrated surface of the lipid aggregate as a substance similar to liquid, and the hydrophobic core of the aggregate as something similar to a solid. In fact, biological membranes are in the liquid crystalline phase (Lα); therefore, model membranes are usually studied in this phase. This shows that, in the case of the dispersion of lipids in water, other parameters typical for this type of structure will have a significant impact on the appearance of the NMR spectrum. The main features of lipid aggregates affecting the NMR spectrum include the type of lipid aggregate, its size, the degree of lipid hydration, and the thermodynamic state of the membrane. These four parameters determine the dynamics of lipid molecules and individual chemical groups trapped in a complex structure.

#### 1.1. Amphiphilic molecules self-assembly and critical micelle concentration

Amphiphilic molecules (e.g., phospholipids) have lipophilic parts (hydrophobic) and polar parts (hydrophilic). In aqueous environments, these kinds of molecules undergo two basic effects [1]: the adsorption of water molecules on the surface of lipids and self-association. The result of both effects is that when dispersed in water, amphiphiles spontaneously aggregate. It is precisely this property of phospholipids that makes them the basic material from which the cell membrane is formed. Lipids, due to their ability to self-assemble, are divided by the properties of their polar headgroups; thus, the characteristics of the lipids' headgroups (i.e., non-ionic, zwitterionic, anionic, cationic, and catatonic) are emphasized, while the hydrophobic parts of lipids differ in their number of hydrocarbon chains, in their length (number of carbons in the chain), and in their degree of saturation [1–3]. Therefore, the self-assembly phenomenon occurs as the result of two opposite forces: first, that connected with the hydrophobic effect (the energetically unfavorable contact between fatty acid chains and water) and second, that connected to hydrophilic interactions with water molecules [1]. The result of these effects is the formation of micelles, bilayers, or other aggregates, because only the hydrophilic headgroups of lipids can be exposed to water.

Micelles are the simplest structures that can form amphiphilic lipids in water. The Gibbs phase rule says that at a certain temperature and under certain pressure, lipid molecules and micelles can be in equilibrium only at a fixed value of the mole fraction of hydrocarbon in water [4]. This value of lipid concentration in water is known as critical micelle concentration (CMC). Below CMC value, lipid molecules exist as monomers dispersed in water, whereas above CMC value lipid molecules tend to self-associate, forming micelles, bilayers, or other aggregates. The CMC, which is greater for charged molecules than for uncharged molecules [1], decreases significantly in conjunction with decreases in the length of the fatty acid chains [5]. Lipids with relatively weak headgroups (i.e., with weak opposing forces) form bilayer-like aggregates, such as vesicles, and disc-like micelles [6].

Formed aggregates are usually large in size, mainly because they must take forms in which the fatty acid chains are not exposed to direct contact with water. Moreover, the type of lipid structure depends on the energetic of the lipid-water interface and on the shape of the lipid molecule [2, 3, 6]. Further consideration of this issue must take into account factors that influence the formation of the free energy of micellization and the micelle size. The formation of the free energy of micellization and its dependence on the aggregate size involves the bulk term, surface term, curvature term, and packing term [2–4]. The major driving force in the formation of aggregates is its hydrophobic effect and the contribution to the bulk term; however, it is not associated with the size of the formation, which depends on the free energy of micellization [4]. The hydrophobic interaction between fatty acid chains exposed to water and the different repulsive interactions between headgroups (steric, electrostatic, and hydration) contribute to the surface term. The repulsive interactions increase the surface area, whereas the hydrophobic interactions decrease the surface area [4, 7]; these effects are known as opposite interactions. The molecular conformation and motional properties of polar headgroups and the formed membrane surface, which identify the lipid type, are well known. However, information about the structure of lipid molecules packed at aggregates, especially if more than one kind of lipid is present, is very limited. The study of lipid-lipid interactions at the membrane polar-apolar interface is important because the membrane surface is the most probable site of selective electrostatic or steric associations [2–4]. The existing opposite forces have an influence on the curvature of formed agglomerates and restrict the packing of lipid molecules, contribute to the curvature and packing terms, and result in an optimum aggregate size [4]. All terms involved in the free energy of micellization determine favorable molecular packing, which is directly connected to the formed favorable aggregate structures of a specific type of lipid. Moreover, in the bilayer-like structures, the lipid molecules manifest an asymmetric transmembrane lipid-packing geometry [2, 3]. It follows, then, that the average area per lipid headgroup and the effective length of the lipid molecule are greater in the membrane's outer layer than in its inner layer [4]. Therefore, the packing and curvature terms are closely connected to the lipids' molecular shape and configuration. As a consequence, the micelles of single-chain lipids may be formed favorably as a result of weak packing restrictions, whereas those of double-chain lipids, due to stronger packing restrictions, are favorably formed bilayer-like structures [2].

#### 1.2. Lipid hydration

The main advantage of this model is its ability to decide the composition, both in terms of lipid and protein content and the environment in which they are located (one in which various types of ions are present). Model membranes enable the study of their thermotropic properties, the transport of ions through them, and the phenomenon of vesicle fusion. Currently, model biological membranes (liposomes) are widely used as drug delivery systems and in various

The use of nuclear magnetic resonance (NMR) to study these structures poses several challenges. For instance, the technique uses a method of sample preparation that differs from the standard methods used for measurement in a liquid. An additional problem is the formation of lipid aggregates in water, which exhibits differ in the NMR time scale. This is due to the fact that NMR spectrometer "sees" the hydrated surface of the lipid aggregate as a substance similar to liquid, and the hydrophobic core of the aggregate as something similar to a solid. In fact, biological membranes are in the liquid crystalline phase (Lα); therefore, model membranes are usually studied in this phase. This shows that, in the case of the dispersion of lipids in water, other parameters typical for this type of structure will have a significant impact on the appearance of the NMR spectrum. The main features of lipid aggregates affecting the NMR spectrum include the type of lipid aggregate, its size, the degree of lipid hydration, and the thermodynamic state of the membrane. These four parameters determine the dynamics of lipid

molecules and individual chemical groups trapped in a complex structure.

headgroups of lipids can be exposed to water.

1.1. Amphiphilic molecules self-assembly and critical micelle concentration

Amphiphilic molecules (e.g., phospholipids) have lipophilic parts (hydrophobic) and polar parts (hydrophilic). In aqueous environments, these kinds of molecules undergo two basic effects [1]: the adsorption of water molecules on the surface of lipids and self-association. The result of both effects is that when dispersed in water, amphiphiles spontaneously aggregate. It is precisely this property of phospholipids that makes them the basic material from which the cell membrane is formed. Lipids, due to their ability to self-assemble, are divided by the properties of their polar headgroups; thus, the characteristics of the lipids' headgroups (i.e., non-ionic, zwitterionic, anionic, cationic, and catatonic) are emphasized, while the hydrophobic parts of lipids differ in their number of hydrocarbon chains, in their length (number of carbons in the chain), and in their degree of saturation [1–3]. Therefore, the self-assembly phenomenon occurs as the result of two opposite forces: first, that connected with the hydrophobic effect (the energetically unfavorable contact between fatty acid chains and water) and second, that connected to hydrophilic interactions with water molecules [1]. The result of these effects is the formation of micelles, bilayers, or other aggregates, because only the hydrophilic

Micelles are the simplest structures that can form amphiphilic lipids in water. The Gibbs phase rule says that at a certain temperature and under certain pressure, lipid molecules and micelles can be in equilibrium only at a fixed value of the mole fraction of hydrocarbon in water [4]. This value of lipid concentration in water is known as critical micelle concentration (CMC). Below CMC value, lipid molecules exist as monomers dispersed in water, whereas above CMC value lipid molecules tend to self-associate, forming micelles, bilayers, or other aggregates. The CMC, which is greater for charged molecules than for uncharged molecules [1], decreases

kinds of therapies.

32 Spectroscopic Analyses - Developments and Applications

Amphiphilic lipid self-assembly is a specific equilibrium between hydrophobic and hydrophilic interactions, but the bilayer hydration is determined mainly by interactions between the hydrophilic headgroups and the solvent [2, 3]. The level of hydration affects the self-assembly, curvature, shape and size of the aggregate, and the phase behavior. The hydration of the lipid aggregate depends on the specifics of the lipids (i.e., their headgroups). The hydration of hydrocarbon chains is much smaller and is restricted by the hydrophobic interactions [6]. The hydration process is also connected to the thermodynamic state of the lipid membrane. When the fluidity of fatty acid chains increases, the lipid molecules occupy a larger area, which increases hydration as a result of the increase of exposure of the headgroups and hydrocarbon chains to the water molecules [1]. The properties of interbilayer water differ from those of free bulk water. Thus, each lipid molecule, with its water of hydration, should be treated as a separate thermodynamic and physicochemical entity [3, 4]. In general, it seems that the steric density fluctuations have only a slight influence on hydration parameters; however, they play an extremely important role in the surface hydration [1].

Of particular interest in this area is the use of lipids which build, in nature, biological membranes. The most common amphiphilic glycerophospholipids contained in their polar headgroups include phosphate, carboxyl, carbonyl, and choline residues, all of which take part in creating the hydrogen bonds [1, 2]. The availability of the headgroups for hydrogen bonding with the water molecules is the most important factor in the hydration of the bilayer. The coulombic charges of the lipid molecules participate less in the hydration process, probably because of an insufficient concentration of water molecules [1, 3].

#### 1.2.1. Influence the hydration on lipid dynamics

The motion of phospholipid molecules within the lipid bilayer has been characterized as lateral diffusion, axis rotational Brownian motion of the headgroup, or glycerol backbone, wobbling, and flip-flopping [7–9]. The collective properties are different from those at the local molecular level. The phenomena accompanying the local molecular motion in the lipid aggregate include phase transitions, a morphological change of the lipid membrane as a whole (e.g., fusion/fission), pore formation, and the formation of heterogeneous structures, such as phase separation/domain formation [10]. Thus, the motion of the lipid aggregate as a whole cannot be explained on the basis of the lipid molecule motions (i.e., at the molecular level).

Thus, studies of membrane dynamics are concerned with the molecular motion of lipids. As mentioned previously, the rotational motion of the headgroups relates to hydrophobic interactions, hydrogen bonding, and the curvature of the lipid membrane; in this way, an increase in the curvature of, for example, liposomes, induce the level of hydration [11–16]. The reorientation of the headgroups is also restricted by the intermolecular force between them [1, 19]. Thus, the reorientation of phospholipid headgroups is restricted by breaking the intermolecular bonds (hydrogen bond and/or PO4 /N+ (CH3)3 bond) [10, 16–18]. Thus, the hydration of the polar headgroups weakens the strength of the PO4 /N+ (CH3)3 bond [10, 16, 19]. The dynamics of the lipid membrane interface is also connected with the mobility of the glycerol backbone of phospholipid (PO4 –(CH2)2–N+ (CH3)3) [7, 16, 20]. The mobility of the glycerol backbone is associated with the lateral diffusion of lipid molecules because it promotes hydration and, consequently, the reorientation of the headgroups. The reorientation of the headgroups (i.e., high hydration) causes the hydrocarbon chains to be more greatly exposed to water molecules, which indicates that the increased mobility of the phospholipid headgroups make the membrane polar-apolar surface more hydrophobic [6, 10, 16, 19].

#### 1.3. Model membrane phase transitions

Membranes composed of one type of phospholipid have a clearly defined phase transition, which is caused by temperature variations. The phase transition temperature is primarily dependent upon the type of phospholipid (number and length of hydrocarbon chains) and the level of lipid molecule hydration. The most frequently described phase of self-assembling aggregates is the liquid crystalline phase as a characteristic of cell membranes. Therefore, the most commonly studied phases are lamellar and nonlamellar, such as the hexagonal and cubic phases (normal and inversed).

increases hydration as a result of the increase of exposure of the headgroups and hydrocarbon chains to the water molecules [1]. The properties of interbilayer water differ from those of free bulk water. Thus, each lipid molecule, with its water of hydration, should be treated as a separate thermodynamic and physicochemical entity [3, 4]. In general, it seems that the steric density fluctuations have only a slight influence on hydration parameters; however, they play

Of particular interest in this area is the use of lipids which build, in nature, biological membranes. The most common amphiphilic glycerophospholipids contained in their polar headgroups include phosphate, carboxyl, carbonyl, and choline residues, all of which take part in creating the hydrogen bonds [1, 2]. The availability of the headgroups for hydrogen bonding with the water molecules is the most important factor in the hydration of the bilayer. The coulombic charges of the lipid molecules participate less in the hydration process, probably because of an insufficient concentra-

The motion of phospholipid molecules within the lipid bilayer has been characterized as lateral diffusion, axis rotational Brownian motion of the headgroup, or glycerol backbone, wobbling, and flip-flopping [7–9]. The collective properties are different from those at the local molecular level. The phenomena accompanying the local molecular motion in the lipid aggregate include phase transitions, a morphological change of the lipid membrane as a whole (e.g., fusion/fission), pore formation, and the formation of heterogeneous structures, such as phase separation/domain formation [10]. Thus, the motion of the lipid aggregate as a whole cannot be explained on the basis of the lipid molecule motions (i.e., at the molecular level).

Thus, studies of membrane dynamics are concerned with the molecular motion of lipids. As mentioned previously, the rotational motion of the headgroups relates to hydrophobic interactions, hydrogen bonding, and the curvature of the lipid membrane; in this way, an increase in the curvature of, for example, liposomes, induce the level of hydration [11–16]. The reorientation of the headgroups is also restricted by the intermolecular force between them [1, 19]. Thus, the reorientation of phospholipid headgroups is restricted by breaking the

The dynamics of the lipid membrane interface is also connected with the mobility of the glycerol

backbone is associated with the lateral diffusion of lipid molecules because it promotes hydration and, consequently, the reorientation of the headgroups. The reorientation of the headgroups (i.e., high hydration) causes the hydrocarbon chains to be more greatly exposed to water molecules, which indicates that the increased mobility of the phospholipid headgroups make

Membranes composed of one type of phospholipid have a clearly defined phase transition, which is caused by temperature variations. The phase transition temperature is primarily

/N+

(CH3)3 bond) [10, 16–18]. Thus, the

(CH3)3 bond [10, 16, 19].

/N+

(CH3)3) [7, 16, 20]. The mobility of the glycerol

an extremely important role in the surface hydration [1].

tion of water molecules [1, 3].

1.2.1. Influence the hydration on lipid dynamics

34 Spectroscopic Analyses - Developments and Applications

intermolecular bonds (hydrogen bond and/or PO4

backbone of phospholipid (PO4

1.3. Model membrane phase transitions

hydration of the polar headgroups weakens the strength of the PO4

the membrane polar-apolar surface more hydrophobic [6, 10, 16, 19].

–(CH2)2–N+

The typical phase for lipid membranes at low temperatures is the lamellar crystalline phase LC. As the temperature increases, the van der Waals' interactions decrease, which maintains the order of the hydrocarbon chains in the crystalline phase. The rotational motion of the hydrocarbon chains is then activated by the temperature. The phase transition between crystalline L<sup>C</sup> and gel L<sup>β</sup> phase occurs at Ts temperature [4]. In the lamellar L<sup>β</sup> phase, the lipid molecules take up a larger area and are more hydrated than in the L<sup>C</sup> phase [21]. The correlation time of the rotational motion of the acyl chains is about 10<sup>5</sup> s, which is about 100 times slower than the isomerization of the hydrocarbon chains [22]. Further increases in temperature cause a rise in the quasilamellar segments within the membrane in the intermediate periodic phase Pβ. In this phase, the surface of the membrane is usually rippled, which occurs at Tp temperature [23]. After the intermediate phase, above Tp temperature, the hydrocarbon chains start to melt and form trans-gauche isomers. Internal reorientations, which have stochastic characteristics, are transferred along the acyl chains at times ranging from microseconds to milliseconds [24]. The presence of trans-gauche isomers determines an increase of distance between the lipid molecules in the membrane and decrease van der Waals' interactions. The increase of movement in the hydrophobic and hydrophilic parts of the lipid bilayers is characteristic of the melting state (i.e., the liquid crystalline phase) L<sup>α</sup> [25]. The temperature of transition from the intermediate pleated phase to the liquid crystalline phase is called the melting temperature or the temperature of main phase transition Tt. The value of Tt thus depends on the length and level of the saturation of the hydrocarbon chains as well as on the level of hydration of the lipid molecules. The most important factor in the determination of this value is a hydration level between 0 and 30%. Hydration levels in this range have a major impact on decreases in the temperature Tt. However, because a 30% hydration level mainly increases the amount of water molecules not associated with the membrane (bulk water), changes of the hydration level between 30 and 50% are less likely to influence decreases in the temperature Tt [4].

When CMC values are extremely high, which results in low volumes of water, some kinds of lipids form nonlamellar phases, such as hexagonal (HI) and cubic (CI). Inversed hexagonal (HII) and cubic (CII) phases may be formed in trace amounts of water. Not all lipids can form these phases: their ability to form hexagonal and cubic phases depends on the stereochemical structure of the molecules. Lysophospholipids tend to form normal nonlamellar phases, whereas phosphatidylethanolamine (PE), cholesterol (Ch), cardiolipin (CL), and phosphatidic acid (PA) tend to form inversed nonlamellar phases [26].

However, preferred aggregation structures depend not only on the type of lipid, temperature, and hydration level but also on the pH. Under neutral pH conditions, the phosphatidylcholine (PC) and PE headgroups are electrically neutral, whereas the phosphatidylserine (PS), phosphatidylglycerol (PG), and phosphatidylinositol (PI) headgroups have net negative charges. The mixture of the lipids in the membrane transmits a surface charge density that has an effect on the membrane permeability to ions and charged molecules, on the membrane protein function, and on the thermodynamic phase of the membrane [2–4]. For example, in the case of PE bilayers, which interact with fewer water molecules, the main gel-to-liquid crystalline phase transition (Lβ/Lα) temperature increases by as much as 30C compared to their counterpart PC bilayers (about 20–25C) [4].

#### 2. NMR spectra of model membranes

Amphiphilic lipids form aggregates of many different shapes and sizes; these aggregates can be at different phases. Moreover, minor changes in the concentration, temperature, or chemical structure of the lipid molecules may induce phase transitions between states. Additionally, the effects of molecular interactions and dynamics on macroscopic properties are evident in self-assembly systems [27]. NMR studies of self-assembly systems therefore begin by observing the dynamic parameters, which results in a better understanding of the static properties of the system [1]. Certainly, NMR is the most powerful technique with which to quantify the molecular dynamic in solution; however, in the case of lipid aggregates, it has some limitations.

NMR relaxation studies provide information about local dynamics and the conformational state of lipid hydrocarbon chains. This method is used to study aggregate properties (e.g., the size of micelles) [1]. The reorientation dynamics of aggregated lipid molecules is characterized by a locally preferred orientation; that is, lipid molecules undergo rapid internal motions, such as trans-gauche isomerizations, which are slightly anisotropic. NMR spectra from the lipids in micelles and bilayers are generally in the motional narrowing regime, which is caused by a time scale of lipid reorientation of 10<sup>9</sup> s or less [1–3, 7]. Thus, at conventional magnetic field strengths, essential information about the lipid aggregates is stored in the transverse relaxation rate T2.

Polar headgroups and hydrocarbon chains (typically 12–16 carbons) can be studied using <sup>1</sup> H, 13C, and 31P NMR (e.g., dipole-dipole interactions, scalar interactions, and chemical shift anisotropy (CSA)) [27]. The 31P has relatively large CSA. A complication revealed during the analysis is a change in the degree of the solvent's protonation, which is caused by direct dependency of CSA from the pH. In fact, the relaxation time T2 is also sensitive to changes in micelle/liposome size because the rotational correlation time is proportional to the cube of the radius [1, 27]. Electrostatic and hydrodynamic intermolecular interactions are independent on the rotational diffusion of lipid molecules.

#### 2.1. NMR time scale

The motional model of aggregated lipid molecules concerns the time scale separation of fast local and slow overall motion. The reorientational motion of lipid molecules divides into [4]



These two motions occur on different time scales. Therefore, the special density can be written as the sum of the fast and slow components [28] as follows:

$$j(\omega\_0) = (1 - S^2)j\_f(\omega\_0) + S^2 j\_s(\omega\_0) \tag{1}$$

where jf(ω0) and js(ω0) are reduced spectral density functions that describe the fast and slow motions, respectively; ω<sup>0</sup> is the resonance frequency; and S is the order parameter.

The order parameter can be described as the average [28]

$$S = \frac{1}{2} \left( 3 \cos^2 \theta - 1\_f \right) \tag{2}$$

where θ is the angle between the axis of the maximum component of the electric field gradient tensor and the director axis.

For spherical aggregates such as micelles and liposomes, the slow motion (tumbling and lateral diffusion) is described by the Lorentzian spectral density function [1]:

$$j\_{s(a\upsilon)} = \frac{2\tau\_s}{1 + (a\upsilon\_0\tau\_s)^2} \tag{3}$$

where τ<sup>s</sup> is the correlation time, and the correlation function is [1]

$$
\mathfrak{g}\_s = \mathfrak{g}\_t \mathfrak{g}\_d = \mathfrak{e}^{\overline{\mathfrak{e}}\_t^\dagger} \mathfrak{e}^{\overline{\mathfrak{e}}\_d^\dagger} = \mathfrak{e}^{\overline{\mathfrak{e}}\_t^\dagger},
\tag{4}
$$

where subscripts t and d correspond to the tumbling and lateral diffusion motions, respectively. The correlation time of tumbling and lateral diffusion of the sphere of radius R can be written as [1]

$$
\pi\_t = \frac{4\pi\eta R^3}{3k\_B T} \wedge \pi\_d = \frac{R^2}{6D} \tag{5}
$$

where D is the lateral diffusion coefficient.

Taking into consideration the above equations, it is possible to write the relations for relaxation times [28] as follows:

$$T\_1 = \frac{3\pi^2}{40} \chi^2 \left[ (1 - S^2) 20\tau\_f + S^2 \left( \frac{4\tau\_s}{1 + \left( \omega\_0 \tau\_s \right)^2} + \frac{16\tau\_s}{1 + \left( 2\omega\_0 \tau\_s \right)^2} \right) \right] \tag{6}$$

and

H,

has an effect on the membrane permeability to ions and charged molecules, on the membrane protein function, and on the thermodynamic phase of the membrane [2–4]. For example, in the case of PE bilayers, which interact with fewer water molecules, the main gel-to-liquid crystalline phase transition (Lβ/Lα) temperature increases by as much as 30C compared to their

Amphiphilic lipids form aggregates of many different shapes and sizes; these aggregates can be at different phases. Moreover, minor changes in the concentration, temperature, or chemical structure of the lipid molecules may induce phase transitions between states. Additionally, the effects of molecular interactions and dynamics on macroscopic properties are evident in self-assembly systems [27]. NMR studies of self-assembly systems therefore begin by observing the dynamic parameters, which results in a better understanding of the static properties of the system [1]. Certainly, NMR is the most powerful technique with which to quantify the molecular dynamic in

NMR relaxation studies provide information about local dynamics and the conformational state of lipid hydrocarbon chains. This method is used to study aggregate properties (e.g., the size of micelles) [1]. The reorientation dynamics of aggregated lipid molecules is characterized by a locally preferred orientation; that is, lipid molecules undergo rapid internal motions, such as trans-gauche isomerizations, which are slightly anisotropic. NMR spectra from the lipids in micelles and bilayers are generally in the motional narrowing regime, which is caused by a time scale of lipid reorientation of 10<sup>9</sup> s or less [1–3, 7]. Thus, at conventional magnetic field strengths, essential information about the lipid aggregates is stored in the transverse relaxation

Polar headgroups and hydrocarbon chains (typically 12–16 carbons) can be studied using <sup>1</sup>

13C, and 31P NMR (e.g., dipole-dipole interactions, scalar interactions, and chemical shift anisotropy (CSA)) [27]. The 31P has relatively large CSA. A complication revealed during the analysis is a change in the degree of the solvent's protonation, which is caused by direct dependency of CSA from the pH. In fact, the relaxation time T2 is also sensitive to changes in micelle/liposome size because the rotational correlation time is proportional to the cube of the radius [1, 27]. Electrostatic and hydrodynamic intermolecular interactions are independent on

The motional model of aggregated lipid molecules concerns the time scale separation of fast local and slow overall motion. The reorientational motion of lipid molecules divides into [4]


solution; however, in the case of lipid aggregates, it has some limitations.

counterpart PC bilayers (about 20–25C) [4].

36 Spectroscopic Analyses - Developments and Applications

2. NMR spectra of model membranes

the rotational diffusion of lipid molecules.


2.1. NMR time scale

within the membrane surface).

rate T2.

$$T\_2 = \frac{3\pi^2}{40} \chi^2 \left[ (1 - S^2) 20\tau\_f + S^2 \left( 6\tau\_s + \frac{10\tau\_s}{1 + \left( \omega\_0 \tau\_s \right)^2} + \frac{4\tau\_s}{1 + \left( 2\omega\_0 \tau\_s \right)^2} \right) \right] \tag{7}$$

where subscripts s and f correspond to slow and fast motions, respectively; χ is the gyromagnetic ratio.

#### 2.2. Preparation of the NMR sample

Liposomes are most often used in NMR studies as models of biological membranes. Liposomes, spherical structures consisting of one (large LUV or small SUV unilamellar vesicle) or more (multilamellar vesicles (MLV)) lipid bilayers, are divided by the number of bilayers as well as by size (Figure 1).

The classical preparation MLV method consists of hydrating the thin lipid film. Suitable amounts and types of lipids are dissolved in organic solvent (e.g., chloroform) and are predried under a stream of dry nitrogen. After the formation of a thin lipid film, the sample is allowed to continue drying in a vacuum evaporator for 1–12 h, after which it is hydrated [16]. In the preparation of the NMR sample, deuterated solvents (deuterated water) must be used. An appropriate amount of water should be added to the sample to obtain a final lipid concentration of not less than 20 mg/ml. The sample is then gently mixed, often in a water bath, at a temperature close to the main phase transition. After removing the thin lipid film from the glass walls, it is vortexed for 5–7 min. After completion of the procedure, a sample containing MLV is obtained [16]. When are need LUV or SUV, other methods (most commonly ultrasound disintegration and extrusion) are used. The sonication is carried out in an ice-water bath for 15–45 min, depending on the unit capacity and the expected size of the liposomes [16]. In the case of extrusion, special filters with a proper pore size and pressurized MLV are forced through the pores, thus depriving them of the unwanted bilayers. Combined methods are frequently used (e.g., sonication combined with extrusion). Extrusion is then used to calibrate the liposomes (i.e., to reduce deviations in the size distribution) [29]. Sonication is used more frequently than other methods due to the procedure's lower cost.

Figure 1. Types of the liposomes.

#### 2.3. Lipid membrane dynamic studies

where subscripts s and f correspond to slow and fast motions, respectively; χ is the gyromag-

Liposomes are most often used in NMR studies as models of biological membranes. Liposomes, spherical structures consisting of one (large LUV or small SUV unilamellar vesicle) or more (multilamellar vesicles (MLV)) lipid bilayers, are divided by the number of bilayers as

The classical preparation MLV method consists of hydrating the thin lipid film. Suitable amounts and types of lipids are dissolved in organic solvent (e.g., chloroform) and are predried under a stream of dry nitrogen. After the formation of a thin lipid film, the sample is allowed to continue drying in a vacuum evaporator for 1–12 h, after which it is hydrated [16]. In the preparation of the NMR sample, deuterated solvents (deuterated water) must be used. An appropriate amount of water should be added to the sample to obtain a final lipid concentration of not less than 20 mg/ml. The sample is then gently mixed, often in a water bath, at a temperature close to the main phase transition. After removing the thin lipid film from the glass walls, it is vortexed for 5–7 min. After completion of the procedure, a sample containing MLV is obtained [16]. When are need LUV or SUV, other methods (most commonly ultrasound disintegration and extrusion) are used. The sonication is carried out in an ice-water bath for 15–45 min, depending on the unit capacity and the expected size of the liposomes [16]. In the case of extrusion, special filters with a proper pore size and pressurized MLV are forced through the pores, thus depriving them of the unwanted bilayers. Combined methods are frequently used (e.g., sonication combined with extrusion). Extrusion is then used to calibrate the liposomes (i.e., to reduce deviations in the size distribution) [29]. Sonication is used more

frequently than other methods due to the procedure's lower cost.

netic ratio.

2.2. Preparation of the NMR sample

38 Spectroscopic Analyses - Developments and Applications

well as by size (Figure 1).

Figure 1. Types of the liposomes.

The 31P NMR technique provides information about the local order, the mobility of the phosphate part of the lipid head, and the overall structure of the lipid aggregate [30]. The lineshape of 31P NMR spectra is closely related with the CSA tensor and to the orientation of the lipid molecules relative to the applied magnetic field [31]. Thus, the CSA Δσ depends on the phosphate group motion and on the temperature. The 31P NMR spectrum shows the characteristic lamellar lineshape (σ⊥—high-field maximum) and low-field shoulder (σ∥). Δσ can be calculated from the following expression [30]:

$$
\Delta \sigma = \mathfrak{Z} \{ \sigma\_{\parallel} + \sigma\_{\perp} \},
\tag{8}
$$

where σ<sup>∥</sup> and σ<sup>⊥</sup> are the values of 31P shielding of the lipid molecules, oriented parallel or perpendicular relative to the magnetic field.

The spectral second moment is a measure of the shape of the 31P signal related to the various motions of the headgroup. The second moment S2 can be calculated from the following formula [30]:

$$S\_2 = \frac{\int\_{-\infty}^{+\infty} \nu^2 f(\nu) d\nu}{\int\_{-\infty}^{+\infty}},\tag{9}$$

where ν is frequency and f(ν) is the lineshape.

The CSA for lipid molecules ordered in water is about 100 ppm; for lipid aggregates, it decreases to about 50 ppm due to lateral diffusion of the lipid molecules, leading to further averaging; for liposomes larger than 200 nm, the CSA is reduced to 40 ppm [31]. Thus, the 31P lineshape depends on the size of the lipid aggregate. The CSA value decreases as the liposome size decreases, that is, the liposome curvature increases. In the case of small aggregates (e.g., SUV), the CSA can be reduced to 10 ppm.

Analysis methods of 31P NMR spectra most often are used to test functionalized liposomes that are used as drug carriers, the best known being PEGylated liposomes. The polyethylene glycol (PEG) caps the liposome, which gives it a longer circulation time in the blood, meaning that it decreases the uptake of the liposomes by the reticulum endothelium system (RES) and allows the drug to be released gradually [32]. In addition, PEG is biocompatible, which enables the possibility of further functionalization of the liposomes by attaching antibodies or ligands [33, 34]. The 31P spectra analysis of PEGylated liposomes obtained using the thin film method revealed information about the amount of free lipids or building micelles (narrow line) and lipids building MLV (broad shoulder) [31, 35]. It is also possible to obtain more than one narrow signal (Figure 2).

Figure 2. The 31P NMR spectrum of the PEGylated DPPE/DPPC/Ch (phosphatidylethanolamine/dipalmitoylphosphocholine/cholesterol) multilamellar vesicles obtained at 333 K.

The number of narrow peaks depends on the number of phospholipid types used in the experiment. Then, each phosphate group is in a different chemical surrounding, which causes different chemical shifts. Splitting (δ) between narrow signals also depends on motional averaged CSA rather than on an isotropic chemical shift [31]. Moreover, it may affect the value of the chemical shift and cause difficulties in the assignment of peaks. As mentioned previously, the lineshape depends on the orientation and motion of the lipid molecules and all aggregates. Thus, the temperature of measure is very important. Additionally, in the case of lipid aggregates, a change in temperature causes a change in the phase/physical state. Temperature changes have a slight impact on narrow signals but a significant impact on the broad shoulder [31]. The 31P NMR spectrum of MLV in the low-field shoulder is extremely broad below the temperature during the major phase transition.

The 31P NMR studies of the influence of drugs on the organization and fluidity of a liposome membrane as a function of temperature have been previously reported [30]. The presence of the antibiotic azithromycin affects the thermotropic behavior of DOPC (1,2-dioleoyl-snglycero-3-phosphocholine) and DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine) membranes. Moreover, temperatures between 35 and 45C affect the 31P lineshape of DOPC and DPPC liposomes, as follows: the position of the narrow peak and CSA values does not change; however, the lineshape in a part of the broad shoulder does. The monitoring of the lineshape at the same range of temperatures of DPPC or DOPC liposomes with azithromycin revealed the following new information: the presence of the antibiotic causes smoothing of the line and a decrease in CSA. In fact, only above 40C did the narrow line stay within the spectrum, and the CSA value averaged zero. The azithromycin molecules increased the membrane fluidity below the main phase transition temperature [30].

The example of hydrophobic molecules contained in the lipid membrane and its influence on the dynamics of the lipid bilayer were presented in Ref. [36]. β-carotene, a well-known hydrocarbon carotenoid, appeared in photosynthetic membranes. The presence of β-carotene in a DPPC liposome membrane fulfilled opposite roles in different membrane states. The 31P spectra of β-carotene/DPPC MLV as a function of β-carotene concentration and temperature showed changes in the 31P resonance lineshape [36]. In both cases, the CSA decreased and the spectral line smoothed. Thus, at temperatures above those in the main phase transition for DPPC, the β-carotene caused a fluidization effect on the membrane (in the liquid crystalline state). The effect is also connected to a decreased temperature in the main phase transition. However, at temperatures below those in the main phase transition, β-carotene rigidified the membrane (in the fluid state) [36]. This effect manifested itself as a broadening of the 31P signal. The similar effect can be observed in the case of the PC/octadecylamine MLV contained lycopene (Figure 3).

In the <sup>1</sup> H NMR spectra of LUV/SUV, the most useful parameter for analyzing the spectrum is the half-width (Δν1/2) of the signals, because the Δν1/2 of the resonance signals is directly connected to the motional freedom of particular chemical groups. The increase of the Δν1/2 of

The number of narrow peaks depends on the number of phospholipid types used in the experiment. Then, each phosphate group is in a different chemical surrounding, which causes different chemical shifts. Splitting (δ) between narrow signals also depends on motional averaged CSA rather than on an isotropic chemical shift [31]. Moreover, it may affect the value of the chemical shift and cause difficulties in the assignment of peaks. As mentioned previously, the lineshape depends on the orientation and motion of the lipid molecules and all aggregates. Thus, the temperature of measure is very important. Additionally, in the case of lipid aggregates, a change in temperature causes a change in the phase/physical state. Temperature changes have a slight impact on narrow signals but a significant impact on the broad shoulder [31]. The 31P NMR spectrum of MLV in the low-field shoulder is extremely broad below the

Figure 2. The 31P NMR spectrum of the PEGylated DPPE/DPPC/Ch (phosphatidylethanolamine/dipalmitoylpho-

The 31P NMR studies of the influence of drugs on the organization and fluidity of a liposome membrane as a function of temperature have been previously reported [30]. The presence of the antibiotic azithromycin affects the thermotropic behavior of DOPC (1,2-dioleoyl-snglycero-3-phosphocholine) and DPPC (1,2-dipalmitoyl-sn-glycero-3-phosphocholine) membranes. Moreover, temperatures between 35 and 45C affect the 31P lineshape of DOPC and DPPC liposomes, as follows: the position of the narrow peak and CSA values does not change; however, the lineshape in a part of the broad shoulder does. The monitoring of the lineshape at the same range of temperatures of DPPC or DOPC liposomes with azithromycin revealed the following new information: the presence of the antibiotic causes smoothing of the line and a decrease in CSA. In fact, only above 40C did the narrow line stay within the spectrum, and the CSA value averaged zero. The azithromycin molecules increased the membrane fluidity below

temperature during the major phase transition.

sphocholine/cholesterol) multilamellar vesicles obtained at 333 K.

40 Spectroscopic Analyses - Developments and Applications

the main phase transition temperature [30].

Figure 3. The 31P NMR spectra of the positively charged PC/octadecylamine MLVs (containing 5 mol% of octadecylamine) obtained at 288 K (A and C) and at 308 K (B and D) with 5% of the lycopene (C and D).

Figure 4. The 31P NMR spectra of the PC MLVs (A). The temperature (B) and polysialic acid (C) effect of narrowing the 31P NMR spectra of PC MLVs.

the <sup>1</sup> H resonance signal indicates a restriction of the motion. A change in the Δν1/2 signal assigned to a choline group from the outer layer indicates that the studied drug interacts only with the liposome surface; in other words, it does not penetrate the hydrophobic core of the membrane. This effect was observed in the case of amphotericin B [37], which rigidified the hydrophilic surface of the PC membrane; this effect increased the fluidity of the hydrophobic part of the lipid bilayer. It is manifested as a decrease in the Δν1/2 signals assigned to protons from the –(CH2)n and –CH3 groups of hydrocarbon chains [37].

Quite the opposite effect was observed in the case of polysialic acid (Figure 4). The 31P NMR spectra of PC MLVs showed a slight narrowing of the isotropic part and a broadening of the anisotropic part of the resonance line at a temperature range of 10–30C [38].

However, when the polysialic acid was involved in several cell processes in the external environment of the liposome, the effect was even more noticeable. The interaction between well-hydrated and anionic polysialic acid and the polar headgroups of PC increased the fluidity of the hydrophilic part (decrease of Δν1/2) and simultaneously rigidified the hydrophobic core (increase broad shoulder) of the membrane [38].

While the soy isoflavone, genistein, reduces the hydration level of the phosphate groups (hydrophilic part), i.e. decreases its mobility, and rigidified the hydrophobic part of the asolectine liposomes [35]. It also was found that isoflavone prevents lipid molecules from peroxidation [35].

#### 2.4. Phase transitions of lipid membrane studies

Phase transition studies via the use of NMR are based on the fact that residual couplings depend on the extension of the anisotropic domains in combination with the rate of molecular diffusion [39]. The isotropic phases are perfectly visible in <sup>1</sup> H and 13C NMR spectra, but anisotropic phases from liquid crystals are much more difficult to observe. The broadening of 1 H and 13C spectra can provide some information about non-isotropic phases but do not bring detailed information about phase transition. In this case, the 31P NMR technique is the one that is most useful. If the phase is isotropic on the NMR time scale, static dipolar, quadrupolar, and shift anisotropy interactions are averaged to zero by molecular motion. When the phase is anisotropic, however, a static interaction effect should be seen on the spectrum [39].

Some of the first and most comprehensive studies on the physical properties of liposomes have been presented in Ref. [40]. The authors analyzed the changes of the 31P spectra of DPPC and DPPE MLV membranes with the addition of a different concentration of piracetam. An additional narrow peak appeared on the spectrum assigned to piracetam. The intensity of the signal was dependent on the piracetam-to-lipid molar ratio [40]. Temperature had a significant influence on the lipid bilayer's physical properties. Fortunately, the possible effect of temperature on the main phase transition of the lipid membrane caused by the drug could be observed in the 31P spectra. The presence of piracetam decreased CSA and increased the mobility of the lipid polar headgroup, manifested as a narrowing 31P line and suggesting that piracetam molecules are inserted between lipid molecules at the hydrophilic part of the membrane [40]. Thus, the presence of hydrophilic piracetam molecules decreased the temperature of the main phase transition. In the HII phase, which can be the transient form in the fusion process, the piracetam resonance signal was no longer distinguishable. Finally, it can be concluded that piracetam combines with lipid molecules, which is exhibited as one signal due to the isotropic motion of the entire complex [40].

the <sup>1</sup>

31P NMR spectra of PC MLVs.

42 Spectroscopic Analyses - Developments and Applications

peroxidation [35].

H resonance signal indicates a restriction of the motion. A change in the Δν1/2 signal assigned to a choline group from the outer layer indicates that the studied drug interacts only with the liposome surface; in other words, it does not penetrate the hydrophobic core of the membrane. This effect was observed in the case of amphotericin B [37], which rigidified the hydrophilic surface of the PC membrane; this effect increased the fluidity of the hydrophobic part of the lipid bilayer. It is manifested as a decrease in the Δν1/2 signals assigned to protons

Figure 4. The 31P NMR spectra of the PC MLVs (A). The temperature (B) and polysialic acid (C) effect of narrowing the

Quite the opposite effect was observed in the case of polysialic acid (Figure 4). The 31P NMR spectra of PC MLVs showed a slight narrowing of the isotropic part and a broadening of the

However, when the polysialic acid was involved in several cell processes in the external environment of the liposome, the effect was even more noticeable. The interaction between well-hydrated and anionic polysialic acid and the polar headgroups of PC increased the fluidity of the hydrophilic part (decrease of Δν1/2) and simultaneously rigidified the hydropho-

While the soy isoflavone, genistein, reduces the hydration level of the phosphate groups (hydrophilic part), i.e. decreases its mobility, and rigidified the hydrophobic part of the asolectine liposomes [35]. It also was found that isoflavone prevents lipid molecules from

Phase transition studies via the use of NMR are based on the fact that residual couplings depend on the extension of the anisotropic domains in combination with the rate of molecular

from the –(CH2)n and –CH3 groups of hydrocarbon chains [37].

bic core (increase broad shoulder) of the membrane [38].

2.4. Phase transitions of lipid membrane studies

anisotropic part of the resonance line at a temperature range of 10–30C [38].

The 31P method, therefore, also may be used to fix the temperature of the MLV phase transition [41–44]. The temperature studies of PC/Ch MLV revealed the changes of lineshape ranging from 10 to 40C (Figure 5). Temperature changes could be observed during the phase transition between L<sup>α</sup> and HII [41].

The monitoring of the 31P lineshape every 2C led to observations of intermediate lineshapes between those characteristic of L<sup>α</sup> and HII and allowed us to precisely fix the temperature of the phase transition [41].

Figure 5. The 31P NMR spectra of PC/Ch MLVs obtained in different temperatures. The characteristic 31P lineshape for lamellar phase at 293 K (A), transient form at 308 K (B) and nonlamellar phase (inversed hexagonal) at 313 K (C).

#### 2.5. Usage of paramagnetic ions as a chemical shift reagent and transport of ions through lipid bilayer

Paramagnetic ions are used to distinguish signals. The most frequently used are praseodymium (Pr3+) ions or other ions from the lanthanides group [37]. The concentration of paramagnetic ions added to the external environment of the liposomes is important. The shift reagent could distinguish the signals within a few ppms; however, if the concentration is too great, it could drastically broaden the studied signal or even broaden the entire spectrum. In this case, the paramagnetic effect is dominant, and paramagnetic interactions may destroy the membrane structure [45]. It may be observed in the <sup>1</sup> H NMR spectra of DOPC SUV as broadened signals due to Eu3+ ions. In fact, this effect is associated with the properties of Eu3+ ions, which interact to the same extent with the hydrophobic and hydrophilic parts of the lipid bilayer. Moreover, the Δν1/2 of the signal assigned to water also increased, indicating that the Eu3+ ions also interact with water molecules from the hydration shell of the liposome [45].

The Pr3+ ions enabled the distinguishing of signals assigned to the polar headgroups of lipids from the inner and outer layers of liposomes in the <sup>1</sup> H spectra. The splitting of choline signals of PC/Ch SUVs is showed in Figure 6. The signal corresponding to the protons from the – N+ (CH3)3 groups split due to interaction with paramagnetic ions in the external environment of LUV/SUV [46].

The signal shifted toward lower magnetic field values was assigned to protons from the outer layer, and the signal shifted to higher magnetic field values was assigned to protons from the inner layer [37]. The splitting of the –N+ (CH3)3 signal is strongly dependent on geometric

Figure 6. The <sup>1</sup> H NMR spectrum of choline groups of PC/Ch SUVs in the absence (A) and presence (B) of Pr3+ ions (5 mM).

conditions and axial symmetry at the lipid-lanthanide binding site [37, 46]. The ratio of the area under the signal corresponded to the outer layer and the area under the signal corresponded to the inner layer (Io/Ii), thereby providing information about the size of the liposome [46]. Along with decreases in liposome size, the number of lipid molecules in the inner layer decreased. Thus, the areas under the signals from the inner and outer layers differed. The distinguishing of signals from the choline groups in the inner and outer layers of the membrane presents new possibilities for interpreting the results. For example, the addition of the amphotericin B to the external environment of the PC SUV liposome (after hydration of the lipid bilayer) did not have an effect on the size of the liposomes because there was no change in the Io/Ii ratio. However, the Pr3+ ions could interact with the carboxylic group of amphotericin B due to increased splitting of the choline group signals [37].

2.5. Usage of paramagnetic ions as a chemical shift reagent and transport of ions through

Paramagnetic ions are used to distinguish signals. The most frequently used are praseodymium (Pr3+) ions or other ions from the lanthanides group [37]. The concentration of paramagnetic ions added to the external environment of the liposomes is important. The shift reagent could distinguish the signals within a few ppms; however, if the concentration is too great, it could drastically broaden the studied signal or even broaden the entire spectrum. In this case, the paramagnetic effect is dominant, and paramagnetic interactions may destroy the mem-

signals due to Eu3+ ions. In fact, this effect is associated with the properties of Eu3+ ions, which interact to the same extent with the hydrophobic and hydrophilic parts of the lipid bilayer. Moreover, the Δν1/2 of the signal assigned to water also increased, indicating that the Eu3+ ions

The Pr3+ ions enabled the distinguishing of signals assigned to the polar headgroups of lipids

of PC/Ch SUVs is showed in Figure 6. The signal corresponding to the protons from the –

The signal shifted toward lower magnetic field values was assigned to protons from the outer layer, and the signal shifted to higher magnetic field values was assigned to protons from the

H NMR spectrum of choline groups of PC/Ch SUVs in the absence (A) and presence (B) of Pr3+ ions

(CH3)3 groups split due to interaction with paramagnetic ions in the external environment

also interact with water molecules from the hydration shell of the liposome [45].

H NMR spectra of DOPC SUV as broadened

H spectra. The splitting of choline signals

(CH3)3 signal is strongly dependent on geometric

lipid bilayer

N+

of LUV/SUV [46].

Figure 6. The <sup>1</sup>

(5 mM).

brane structure [45]. It may be observed in the <sup>1</sup>

44 Spectroscopic Analyses - Developments and Applications

from the inner and outer layers of liposomes in the <sup>1</sup>

inner layer [37]. The splitting of the –N+

The 31P NMR spectra can reveal information about the transport through membrane or about ion competing binding sites in lipids and in other biomolecules. This is very important in the assay of biological membranes, since ion transport defects may cause various illnesses, such as manic depressive and neurodegenerative diseases [47]. The adenosine triphosphate (ATP) could be used as a model membrane ligand of metal cations [47]. In these types of studies, it is very important to keep a constant pH and temperature during the experiment. It is well known that the binding of metal cations is dependent on both parameters. The narrowing/ broadening of the 31P signal or changes in the distance (splitting) between the three phosphate signals could be the effect of complexes created by ATP and Mg2+/Li+ ions [47]. The analysis of 31P spectra led to the conclusion that the biochemical action of Li+ ions may be explained as their ability to compete with Mg2+ binding sites. Thus, the therapeutic role of Li+ in maniacdepressive illness is enabled by modulating the activity of G proteins in signal transduction [47]. It has been suspected that the Mn2+ ions also can complete Mg2+ binding sites. This ability of Mn2+ ions probably pays a significant role in course of neurodegenerative illnesses [48]. Thus, the same effect can be observed in the case of Mn2+ ions (Figure 7).

The <sup>1</sup> H and 31P NMR may also be used to study the macroscopic rearrangement of liposome membrane as, for example, a fusion process [41]. A number of authors have suggested that the fusion process is associated with the development of transient forms related to the appearance of the HII phase [41, 49, 50]. To induce the fusion process of PE/PS/PC liposomes, Ca2+ ions should be used as a fusogenic agent [41]. The 31P spectra of MLV showed changes in resonance lineshapes with an increased molar ratio of Ca2+ ions to PS (Figure 8).

The characteristic lineshape for the nonlamellar phase, HII, was revealed when the molar ratio of Ca2+/PS was 2.0 [41]. The <sup>1</sup> H and 31P NMR spectra of SUV, after the addition of Pr3+ ions, demonstrated splitting of the resonance signals. In both cases, there was an overall decrease in splitting and even in the intensity of the split signals [41]. Only the Pr3+ ions are associated with the outer layer of the membrane. During the fusion process, because the lipid molecules translocation from the outer layer to the inner layer due to transient form (inversed micelle) formation, the Pr3+ ions with the translocated lipids moved to the internal water portion of the liposome [41]. This effect determined the decrease in the splitting. In fact, during the fusion process, the internal and external chemical environments of the polar heads became identical, and the size of the liposomes increased [41].

Figure 7. The 31P NMR spectra of ATP in the presence of Mg2+ ions (A) and Mn2+ ions (B, C).

Figure 8. The changes of the 31P resonance lineshape of PC/Ch MLVs caused by fusogenic reagent (Ca2+ ions) (A); the time changes of the <sup>1</sup> H NMR spectra (B) and the 31P NMR spectra (C) of PE/PS/PC SUVs in the presence of Ca2+/PS molar ratio 2.0 after addition of 0.5 mM Pr3+ ions.

#### 2.6. Drug delivery study

Figure 7. The 31P NMR spectra of ATP in the presence of Mg2+ ions (A) and Mn2+ ions (B, C).

46 Spectroscopic Analyses - Developments and Applications

Figure 8. The changes of the 31P resonance lineshape of PC/Ch MLVs caused by fusogenic reagent (Ca2+ ions) (A); the

H NMR spectra (B) and the 31P NMR spectra (C) of PE/PS/PC SUVs in the presence of Ca2+/PS molar

time changes of the <sup>1</sup>

ratio 2.0 after addition of 0.5 mM Pr3+ ions.

The potential use of LUV/SUV as a drug carrier to cells is attractive as a therapy for increasing therapeutic effects and for reducing drug toxicity in normal cells. The concept of the application of temperature-sensitive liposomes is based on an increase in the permeability of the lipid bilayer at a proper temperature, due to rearrangement of the molecules from one stable state to another [51–53]. Temperature-sensitive liposomes may be used with local hyperthermia for the treatment of cancer via chemotherapy [51, 54, 55]. The release rate of the drug depends on the rate of change in temperature and by the serum compounds (i.e., lipoproteins) [56]. Thus, as drug carriers, the liposomes should be stable in the serum and release the drug slowly at a proper temperature [34, 57]. The <sup>1</sup> H spectra of PC and PC/octadecylamine (positively charged) LUV showed changes of the chemical shift of signals with increased temperatures ranging from 5 to 50C (Figure 9).

For both types of liposomes, the values of chemical shift increased; that is, the spectral lines shifted toward the direction of the lower magnetic field [51, 57]. This effect is typical for lipid membranes. The <sup>1</sup> H spectra also revealed the narrowing of spectral lines (decrease in Δν1/2) assigned to –N+ (CH3)3, –(CH2)n, and –CH3. Moreover, the largest changes were observed in the –(CH2)n signal from the hydrophobic core of the membrane [51]. Studies of the splitting of signals from the choline groups have demonstrated decreased splitting with increased temperatures, the result of increased liposome size. The PC liposome size changes from 20–30 nm to 1 μm. In fact, between temperatures 35 and 40C, the structure of the PC liposomes becomes damaged and unstable. On the other hand, the size of the PC/octadecylamine liposomes changes slightly from 20 to 60 nm and seems to be stable at temperatures of 40–50C [51]. Additionally, temperature-sensitive liposomes at higher temperatures may aggregate or fuse [49]. It is possible for temperature-sensitive PC/octadecylamine liposomes to transfer drug to cells by fusion or via an endocytosis process in moderate hyperthermia [51].

The <sup>1</sup> H NMR can also be used to study the permeability of lipid membrane. As mentioned before, the controlled release of drugs is very important. The PA/Ch/PEG-Ch (palmitic acid/ cholesterol/PEGylated cholesterol) liposomes exhibit no permeability of drugs (calcein and doxorubicin) up to 20 mol% PEGylated cholesterol concentration, but in 10 mol% PEG-Ch concentration the permeability of membrane limited and can be controlled [34]. Moreover, the PA/Ch/PEG-Ch liposomes are stable in various pHs [34].

The release of drugs (cytosine 1-β-D-arabinofuranoside and 5-fluorouracil) from the DPPC liposomes was studied [57]. The <sup>1</sup> H spectra showed the shifting signals and the changes in splitting of signals dependent from temperature. The temperature-dependent controlled release of 5-fluorouracil was successfully provided [57].

The 31P NMR technique also can be used to study liposomes used as drug carriers, such as in the case of cisplatin-loaded PEGylated LUV. The 31P NMR technique has been used to measure the chemical shift of placebo (control) liposomes and cisplatin-loaded liposomes at room temperature and at 60C [58]. The results revealed a characteristically broadened signal at temperatures below those in L<sup>β</sup> to L<sup>α</sup> phase transition (52.5C for PC). At a temperature of 60C, sharp signals were obtained in both cases. The analysis of spectra revealed some asymmetry in peaks on the

Figure 9. The effect of temperature on half-width and splitting of the <sup>1</sup> H resonance signals of PC/octadecylamine LUVs at 298 K (A), at 308 K (B), and at 318 K (C).

right side. This effect is expected in the case of phospholipid LUV. The monitoring of the Δν1/2 signal can reveal information about interactions between cisplatin and phospholipid molecules. The Δν1/2 signal has a lower value for cisplatin-loaded liposomes than that for control liposomes [58]. Because both types of LUV have the same lipid composition and concentration and similar size distributions, the implication is that differences in Δν1/2 are caused by interactions between cisplatin and phospholipid molecules. This effect is probably a result of the hydration process [58].

#### 3. Conclusions

The NMR techniques usually are used to determine the molecular structure but, in the case of lipid aggregates, are more important to know a nature of interactions between the molecules and their dynamics. Thus, the most often are used the <sup>1</sup> H and 31P NMR techniques. The <sup>1</sup> H and 31P spectra of liposomes led to observe the dynamics changes in the hydrophilic and hydrophobic part of membrane (half-width of signal). The changes of molecules/chemical groups dynamics can be caused by various substances added to liposome membrane, loaded to liposome, or coated a liposome. Moreover, the changes in splitting of signals can revealed the information about permeability of liposome membrane. These parameters are important to characterize the properties of liposome membrane. Additionally, the measurement can be provided in various physicochemical conditions. The pH, temperature, and concentration of added substances have significant influence on the physical state of membrane, the dynamics of molecules, the interactions between molecules, and the processes occurred on the membrane surface. Thus, the NMR technique is a proper tool to study the phase behavior, the transport of ions, the diffusion of drugs through the membrane, the membrane permeability, and the stability of membrane in various conditions.

#### Author details

Anna Timoszyk

Address all correspondence to: a.timoszyk@wnb.uz.zgora.pl

Faculty of Biological Sciences, University of Zielona Góra, Zielona Góra, Poland

#### References

Figure 9. The effect of temperature on half-width and splitting of the <sup>1</sup>

298 K (A), at 308 K (B), and at 318 K (C).

48 Spectroscopic Analyses - Developments and Applications

H resonance signals of PC/octadecylamine LUVs at

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### **Homo- and Hetero-Covariance NMR Spectroscopy and Applications to Process Analytical Technology** Homo- and Hetero-Covariance NMR Spectroscopy and

DOI: 10.5772/intechopen.68981

Applications to Process Analytical Technology

Martin Jaeger and Robin Legner

Additional information is available at the end of the chapter Martin Jaeger and Robin Legner Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.68981

#### Abstract

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0885328213515288

DOI: 10.1126/science.432641

54 Spectroscopic Analyses - Developments and Applications

10.1023/A:1016206631006

Covariance processing of data and spectra has established itself among the computerbased NMR spectroscopy methodologies to increase sensitivity and resolution and to facilitate spectral analysis. While homo-correlations yield two-dimensional (2D) diagonally symmetric or antisymmetric spectra, hetero-covariance transformations allow to transfer NMR chemical shift information to other spectroscopic techniques, such as near infra-red or Raman. This is visualized as a 2D correlation map, provided a common indirect or perturbation domain, such as time, concentration change, and pressure. Covariance spectra can be generated as synchronous or asynchronous maps. The synchronous map relates the signals of species, e.g., educts and products. The asynchronous spectrum allows to derive the sequential order in which such species occur relative to each other. After a theoretical introduction into covariance NMR, its application in process analytical technology is discussed for wine fermentation, a radical polymerization reaction, a continuous process ethanol production using immobilized yeast, and a Knoevenagel condensation in a microreaction system. The covariance approach is extended toward two perturbation variables and quantitative relationships through PARAFAC kernel analysis and is illustrated for the preparation of polylactic acid nanocomposites. The advantages and added values of using synchronous and asynchronous spectra to gain process knowledge and control are demonstrated.

Keywords: homo- and hetero-correlation spectroscopy, covariance NMR, synchronous and asynchronous spectra, process analytical technology, Raman spectroscopy

#### 1. Introduction

Striving for enhanced sensitivity, specificity, and resolution NMR spectroscopy traditionally turned to creating stronger magnets, thus higher magnetic field strengths. The implementation of pulsed-field gradients and the development of cryogenically cooled probes contributed

© 2017 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.

© 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 eproduction in any medium, provided the original work is properly cited.

further to increasing instrumental sensitivity. In recent years, vivid interest was paid to socalled fast NMR methods for taking another step in ameliorating the signal-to-noise ratio. Fast methods followed several approaches. These consisted of pulse-sequence-based methods, such as time-shared experiments, hardware oriented strategies, such as parallel acquisition and detection, and the combination of two or more NMR experiments into one pulse sequence. They all aimed at optimization to take advantage of a given experimental timeframe. Not only the long-time used spectral acquisition schemes were re-evaluated, the spectral processing procedure was also equally subjected to re-investigation. As a consequence, the so-far untouched Fourier Transformation (FT), being at the heart of multi-dimensional NMR spectroscopy, was challenged. Statistic data treatment turned out to transform experimentally acquired data into spectra evenly well. Covariance transformations were applied to raw data sets as well as pre-processed data. Covariance NMR and covariance processing methods have been recently reviewed in great detail [1–7]. Due to the purely mathematical nature, the computer power and the algorithms applied determine the speed with which covariance spectra can be obtained. The experimentally acquired data determine the sensitivity observed in the covariance spectrum [8].

Beyond NMR, covariance transformations have been known to be of a very general nature according to Eq. (1) [9, 10]. The potential of generalized covariance processing was soon recognized, thus allowing traditional one-dimensional (1D) spectroscopic techniques such as infra-red (IR) and Raman spectroscopy to yield two-dimensional (2D) spectra [11, 12]. To fully exploit Eq. (1), data matrices of two distinct spectroscopic techniques, such as NMR and IR, were transformed to yield a two-dimensional IR-NMR spectrum, and the technique was baptized hetero-spectroscopy [13, 14]. As a prerequisite for its application, the spectra need to possess a common dimension prior to transformation, e.g., reaction time or change in sample pressure, called the perturbation dimension. The technique proved not only suitable for the transformation of heterogeneous data arrays or spectra but also helpful to visualize valuable information via correlation signals and their phases [12, 15]. Correlation signals indicated spectral constituents that share a common fate. The phases reflect simultaneous or asynchronous increase or decrease of the spectral constituents.

In this report, covariance NMR spectroscopy, in particular correlation and hetero-covariance NMR, shall be described in theory and practice for the investigation of chemical reactions and batch characterization. Illustrative examples shall be given how NMR spectroscopy can help attribute and distinguish signals from different spectroscopic techniques that provide lower spectral resolution or ambiguity for the assignment. In this respect, contributions of correlation spectroscopy, homo- and hetero-covariance NMR spectroscopy to the field of Process Analytical Technologies (PAT), shall be reported.

#### 2. The concept of homo- and hetero-covariance spectroscopy

Covariance stems from statistical mathematics. Variances represent the deviation from the mean of a series of data. The covariance C in matrix form according to Eq. (1) is understood as the difference between the correlated and the uncorrelated products of a series of data [9, 10, 16].

further to increasing instrumental sensitivity. In recent years, vivid interest was paid to socalled fast NMR methods for taking another step in ameliorating the signal-to-noise ratio. Fast methods followed several approaches. These consisted of pulse-sequence-based methods, such as time-shared experiments, hardware oriented strategies, such as parallel acquisition and detection, and the combination of two or more NMR experiments into one pulse sequence. They all aimed at optimization to take advantage of a given experimental timeframe. Not only the long-time used spectral acquisition schemes were re-evaluated, the spectral processing procedure was also equally subjected to re-investigation. As a consequence, the so-far untouched Fourier Transformation (FT), being at the heart of multi-dimensional NMR spectroscopy, was challenged. Statistic data treatment turned out to transform experimentally acquired data into spectra evenly well. Covariance transformations were applied to raw data sets as well as pre-processed data. Covariance NMR and covariance processing methods have been recently reviewed in great detail [1–7]. Due to the purely mathematical nature, the computer power and the algorithms applied determine the speed with which covariance spectra can be obtained. The experimentally acquired data determine the sensitivity observed

Beyond NMR, covariance transformations have been known to be of a very general nature according to Eq. (1) [9, 10]. The potential of generalized covariance processing was soon recognized, thus allowing traditional one-dimensional (1D) spectroscopic techniques such as infra-red (IR) and Raman spectroscopy to yield two-dimensional (2D) spectra [11, 12]. To fully exploit Eq. (1), data matrices of two distinct spectroscopic techniques, such as NMR and IR, were transformed to yield a two-dimensional IR-NMR spectrum, and the technique was baptized hetero-spectroscopy [13, 14]. As a prerequisite for its application, the spectra need to possess a common dimension prior to transformation, e.g., reaction time or change in sample pressure, called the perturbation dimension. The technique proved not only suitable for the transformation of heterogeneous data arrays or spectra but also helpful to visualize valuable information via correlation signals and their phases [12, 15]. Correlation signals indicated spectral constituents that share a common fate. The phases reflect simultaneous or asynchro-

In this report, covariance NMR spectroscopy, in particular correlation and hetero-covariance NMR, shall be described in theory and practice for the investigation of chemical reactions and batch characterization. Illustrative examples shall be given how NMR spectroscopy can help attribute and distinguish signals from different spectroscopic techniques that provide lower spectral resolution or ambiguity for the assignment. In this respect, contributions of correlation spectroscopy, homo- and hetero-covariance NMR spectroscopy to the field of Process Analyt-

Covariance stems from statistical mathematics. Variances represent the deviation from the mean of a series of data. The covariance C in matrix form according to Eq. (1) is understood

2. The concept of homo- and hetero-covariance spectroscopy

in the covariance spectrum [8].

56 Spectroscopic Analyses - Developments and Applications

nous increase or decrease of the spectral constituents.

ical Technologies (PAT), shall be reported.

$$\mathbf{C}(\mathbf{x}, y) = \langle (\mathbf{x} - \langle \mathbf{x} \rangle)(y - \langle y \rangle) \rangle = \langle \mathbf{x}y \rangle - \langle \mathbf{x} \rangle \langle y \rangle \tag{1}$$

where 〈x〉 and 〈y〉 are the mean values, and 〈 〉 represents any type of correlation function.

Let x and y in Eq. (1) be spectroscopic data series and be arranged such that S represents a spectrum of N<sup>1</sup> data points, and the elements Cij of the covariance matrix or covariance map C are calculated in Eq. (2) as follows:

$$\mathcal{C}\_{ij} = \frac{1}{N\_1 - 1} \sum\_{k=1}^{N\_1} \left( S(k, i) - \langle S(i) \rangle \right) \left( S(k, j) - \langle S(j) \rangle \right) \tag{2}$$

$$\langle S(i)\rangle = \frac{1}{N\_1} \sum\_{k=1}^{N\_1} S(k, i) \tag{3}$$

where the average spectrum is defined as 〈S(i)〉 in Eq. (3). Substitution of i by j defines 〈S(j)〉 analogously. In mathematical contexts, Eqs. (1) and (2) are common. For spectroscopy, the symbols for time and frequency, t and ν or ω, are more often used. Applying Parseval´s theorem (4) to Eqs. (1) and (2), the covariance matrix can be expressed by Eq. (5).

$$\int\_{-\infty}^{\infty} f(t)g^\*(t)dt = \frac{1}{2\pi} \int\_{-\infty}^{\infty} F(\omega)G^\*(\omega)d\omega \tag{4}$$

The two data sets denoted either s, S, Φ, or Ψ in Eq. (5) consist of mixed time-frequency data before and frequency-frequency data after transformation. They also share a common indirect dimension. The latter can be interpreted in terms of a perturbation, and the dimension is hence called perturbation dimension [9].

$$\begin{split} \mathcal{L}(\boldsymbol{\omega}\_{2,A\prime}\boldsymbol{\omega}\_{2,B}) &= \langle \mathbf{s}(\boldsymbol{t}\_{\mathrm{inc}},\boldsymbol{\omega}\_{2,A}) \cdot \mathbf{s}(\boldsymbol{t}\_{\mathrm{inc}},\boldsymbol{\omega}\_{2,B}) \rangle \\ &= \frac{1}{2\pi(T\_{\max}-T\_{\min})} \int\_{-\infty}^{\infty} S(\boldsymbol{\omega}\_{\mathrm{inc}},\boldsymbol{\omega}\_{2,A}) \cdot S^\*(\boldsymbol{\omega}\_{\mathrm{inc}},\boldsymbol{\omega}\_{2,B}) d\boldsymbol{\omega}\_{\mathrm{inc}} \\ &= \Phi(\boldsymbol{\omega}\_{2,A\prime}\boldsymbol{\omega}\_{2,B}) + \mathcal{N}(\boldsymbol{\omega}\_{2,A\prime}\boldsymbol{\omega}\_{2,B}) \end{split} \tag{5}$$

The index inc refers to the second or indirect spectral dimension. In a typical experiment, this dimension is recorded as discrete time intervals between a maximum limit Tmax and a minimum limit Tmin. The direct dimension may stem from two different data sets, A 6¼ B, or from the same data set, A = B. In the latter case, the data sets are transposed with respect to each other.

The spectra or maps Φ and Ψ are defined according to Eqs. (6) and (7).

$$\Phi(\omega\_{2,A\prime}\omega\_{2,B}) = \frac{1}{T\_{\max} - T\_{\min}} \int\_{T\_{\max}}^{T\_{\min}} \mathbf{s}(t\_{\mathrm{inc}\prime}\omega\_{2,A}) \cdot \mathbf{s}(t\_{\mathrm{inc}\prime}\omega\_{2,B})dt\_{\mathrm{inc}} \tag{6}$$

$$
\Psi(\omega\_{2,A}, \omega\_{2,B}) = \frac{1}{T\_{\max} - T\_{\min}} \int\_{T\_{\max}}^{T\_{\min}} \mathbf{s}(t\_{\mathrm{inc}}, \omega\_{2,A}) \cdot \hbar \cdot \mathbf{s}(t\_{\mathrm{inc}}, \omega\_{2,B}) dt\_{\mathrm{inc}} \tag{7}
$$

where h is the Noda-Hilbert transform [15]. The reader is also referred to Eqs. (17) and (18) for definition and matrix notation. Integration of Eqs. (6) and (7) results in Eqs. (8) and (9).

$$\Phi(\omega\_{2,A}, \omega\_{2,B}) = p(\cos \phi)^{A,B} \text{Abs}(\omega\_{2,A}) \text{Abs}(\omega\_{2,B}) \tag{8}$$

$$
\Psi(\omega\_{2,A}, \omega\_{2,B}) = q(\sin \varphi)^{A,B} A \text{bs}(\omega\_{2,A}) A \text{bs}(\omega\_{2,B}) \tag{9}
$$

Equations (8) and (9) are lengthy expressions when fully written for p and q. Yet, the phase ϕ is readily recognized. It may be considered as an internal reference according to Eqs. (10) and (11), which present the important parts of the complete definition for p and q.

$$p(\cos \phi)^{A,B} \sim \cos \left(\omega\_{2,a} t\_{\text{inc}} + \phi\right), \; \alpha = A, B \tag{10}$$

$$q(\sin \phi)^{A,B} \sim \sin \left(\omega\_{2,a} t\_{inc} + \phi\right), \ \alpha = A, B \tag{11}$$

The comparison of Eqs. (11) and (12), the latter being an analogous expression but obtained after Fourier Transformation, readily reveals that an internal reference ϕ is absent in Eq. (12), i.e., manual phase correction after FT is required in contrast to the covariance transformed version of the spectral representation.

$$S(\omega\_{\rm inc}, \omega\_2) = \int \mathbf{s}(\omega\_{\rm inc}, \omega\_2) \exp\left(-i\omega\_2 t\_{\rm inc}\right) dt\_{\rm inc}$$

$$= \int \mathbf{s}(t\_{\rm inc}, \omega\_2) \cos(\omega\_{\rm inc}, t\_{\rm inc}) dt\_{\rm inc} \tag{12}$$

$$+ i \int \mathbf{s}(t\_{\rm inc}, \omega\_2) \sin(\omega\_{\rm inc}, t\_{\rm inc}) dt\_{\rm inc}$$

A spectrum after FT often consists of the real part data, with the imaginary part discarded. Yet, the phase still needs to be adjusted. The interested reader is referred to NMR textbooks and to the recent works in the context of covariance NMR [17, 18].

Equation (13) is the general form of Eq. (3). Here, f and ω denote spectral variables, such as frequencies, that may be recorded using any type of spectroscopy. A common perturbation such as a time domain t relates them to each other. Nevertheless, the perturbation could also be a series of samples, pressure, crystallization, etc.

$$\mathbf{C}(f,\omega) = \langle \mathbf{s}\_1(f,t) \cdot \mathbf{s}\_2(\omega,t) \rangle \tag{13}$$

Spectra generated using Eq. (13) represent hetero-spectral correlation maps [14]. For pure NMR spectroscopy, unsymmetrical indirect covariance NMR was the first type of hetero-correlation spectroscopy, relating, e.g., 15N and 13C signals via the proton dimension, to each other [19–21]. Taken a step further, NMR and IR or NMR and mass spectrometry data were correlated to each other [22].

The covariance matrix contains as its elements the covariance Cij, i.e., the amplitudes of positions i and j of the 1D spectra. Rewriting Eq. (2) in matrix form yields the relationship between C and the spectroscopic data set S. The matrix multiplication of S with its transpose ST is equal to C<sup>2</sup> , cf. Eq. (14).

where h is the Noda-Hilbert transform [15]. The reader is also referred to Eqs. (17) and (18) for definition and matrix notation. Integration of Eqs. (6) and (7) results in Eqs. (8) and (9).

A,B

Equations (8) and (9) are lengthy expressions when fully written for p and q. Yet, the phase ϕ is readily recognized. It may be considered as an internal reference according to Eqs. (10) and

The comparison of Eqs. (11) and (12), the latter being an analogous expression but obtained after Fourier Transformation, readily reveals that an internal reference ϕ is absent in Eq. (12), i.e., manual phase correction after FT is required in contrast to the covariance transformed

A spectrum after FT often consists of the real part data, with the imaginary part discarded. Yet, the phase still needs to be adjusted. The interested reader is referred to NMR textbooks and to

Equation (13) is the general form of Eq. (3). Here, f and ω denote spectral variables, such as frequencies, that may be recorded using any type of spectroscopy. A common perturbation such as a time domain t relates them to each other. Nevertheless, the perturbation could also be

Spectra generated using Eq. (13) represent hetero-spectral correlation maps [14]. For pure NMR spectroscopy, unsymmetrical indirect covariance NMR was the first type of hetero-correlation spectroscopy, relating, e.g., 15N and 13C signals via the proton dimension, to each other [19–21]. Taken a step further, NMR and IR or NMR and mass spectrometry data were correlated to each

The covariance matrix contains as its elements the covariance Cij, i.e., the amplitudes of positions i and j of the 1D spectra. Rewriting Eq. (2) in matrix form yields the relationship

sðωinc, ω2Þ exp ð�iω2tincÞdtinc

sðtinc, ω2Þcosðωinc, tincÞdtinc

sðtinc, ω2Þsinðωinc, tincÞdtinc

A,BAbsðω2,AÞAbsðω2,BÞ ð8<sup>Þ</sup>

A,B � cos <sup>ð</sup>ω2,αtinc <sup>þ</sup> <sup>ϕ</sup>Þ, <sup>α</sup> <sup>¼</sup> A, B <sup>ð</sup>10<sup>Þ</sup>

A,B � sin <sup>ð</sup>ω2,αtinc <sup>þ</sup> <sup>ϕ</sup>Þ, <sup>α</sup> <sup>¼</sup> A, B <sup>ð</sup>11<sup>Þ</sup>

Cðf , ωÞ ¼ 〈s1ðf,tÞ � s2ðω, tÞ〉 ð13Þ

Absðω2,AÞAbsðω2,BÞ ð9Þ

ð12Þ

Фðω2,A, ω2,BÞ ¼ pðcosϕÞ

Ψðω2,A, ω2,BÞ ¼ qðsinϕÞ

pðcosϕÞ

qðsinϕÞ

Sðωinc, ω2Þ ¼

the recent works in the context of covariance NMR [17, 18].

a series of samples, pressure, crystallization, etc.

other [22].

version of the spectral representation.

58 Spectroscopic Analyses - Developments and Applications

(11), which present the important parts of the complete definition for p and q.

ð

¼ ð

þ i ð

$$\mathbf{C}^2 = \mathbf{S}^T \cdot \mathbf{S} \tag{14}$$

The complete mathematical derivation and proofs have been accomplished by Brüschweiler et al. and Noda et al. [16, 23, 24].

Defining S as the mixed time-frequency matrix, S(t1,ω2), the product S<sup>T</sup> S is the symmetric matrix C(ω1,ω2). A common two-dimensional NMR spectroscopic data set S often has N<sup>1</sup> =2k and N<sup>2</sup> = 256 k data points. Hence, the resulting covariance map will be of dimensions N<sup>1</sup> x N<sup>2</sup> = 2 k x 2 k. This has been assumed as a projection of the direct or acquisition dimension onto the indirect or incremented dimension. It is readily recognized that the indirect dimension is thus substantially enlarged. Two data matrices F<sup>T</sup> and F that have been the results of twodimensional Fourier transformation may also be multiplied to form the covariance spectrum according to Eq. (15).

$$\mathbf{C}^2 = \mathbf{S}^\mathsf{T} \cdot \mathbf{S} = F^\mathsf{T} \cdot F \tag{15}$$

The equality of transformations of the mixed time-frequency data and the completely Fourier transformed data is a consequence of Parseval´s theorem (4) and ensures that the transformations of the mixed time-frequency data and the Fourier transformed data are equal [16, 24]. From another perspective, the spectral reconstruction can be considered as relating two direct dimensions through an indirect dimension or perturbation, which is discarded. The physical meaning of the indirect dimension is therefore of little importance. Thus, it relates Noda´s model two IR wavenumber dimensions via a common perturbation, which may be time, pressure, temperature, sample space, or many more [13]. The matrix representation form reveals that Noda´s synchronous matrix Φ, in Eqs. (6) and (16), corresponds to the covariance map according to Eq. (15), if mean centered spectra are the elements of the data matrices giving Φ. The asynchronous map Ψ of Eqs. (7) and (17) corresponds to the indirect covariance correlation spectrum. Equations (15) and (13) further extend covariance spectroscopy to hetero-correlation spectroscopy.

Eqs. (16) and (17) finally represent the matrix notation of equations as the synchronous map or spectrum and as the asynchronous map.

$$
\Phi = \overline{X}^{\overline{T}} \cdot \overline{X} \tag{16}
$$

$$
\Psi = \overline{X}^{\overline{r}} \cdot N \cdot \overline{X} \tag{17}
$$

where X is the matrix of mean-centered spectra and N the Noda-Hilbert orthogonalization matrix with Nik = 0 if i = k and 1/(π(k � i)) otherwise.

Synchronous and asynchronous maps or spectra have some particular features [11]. Since synchronous homo-correlation spectra are computed from a data matrix and its transposed matrix, they are symmetric. They exhibit diagonal peaks, also called autopeaks, that are the autocorrelation functions of spectral intensity variations. They hence reflect the amount of change the corresponding signal experiences along the perturbation dimension. Off-diagonal signals correlate two signals changing simultaneously or coincidently under the influence of the perturbation. When both signals increase or decrease, the sign of the crosspeak is equal to that of the diagonal peaks. If they behave adversely, the sign is opposite. It is readily recognized that the resolution of spectra can be enhanced by the spread into two dimensions. Furthermore, the occurrence of two or more components, such as educt and product, can be readily seen and facilitate signal assignments. An example for a synchronous spectrum is given in Figure 1(a). As will be shown below, synchronous spectra are useful in homo- and hetero-covariance NMR spectroscopy.

The asynchronous spectrum in general is less easily interpreted. As a consequence of the Noda-Hilbert orthogonalization, cf. Eq. (17), no diagonal peaks are observed. The spectrum visualizes successive or sequential changes of signal intensities, which forbids the occurrence of autopeaks. The asynchronous map is antisymmetric with respect to the diagonal. Noda has shown that Ψðωi, ωjÞ¼ �Ψðωj, ωiÞ. [11]. The sign of a crosspeak is positive—positive is defined as in phase with the diagonal peak in the corresponding synchronous spectrum—if the intensity in dimension 1 changes predominantly before that in dimension 2 in the sequence of the perturbation. This is valid for crosspeaks above the diagonal, i.e., ω<sup>1</sup> > ω2. A negative crosspeak is obtained when the order is reversed. An illustration is given in Figure 1(b). Specie B of the example hence occurs before A, and C before D. Thorough derivations and discussions have been accomplished previously [11].

Despite its ability to correlate non-simultaneous occurrence of signals, the asynchronous map does not allow the analysis of population dynamics as in a two-step chemical reaction. As a

Figure 1. Schematic contour map of synchronous (a) and asynchronous (b) 2D correlation spectra. Peaks located at the diagonal are autopeaks. The signs of the correlation peaks are indicated. The intensity changes and signs are interpreted according to Noda's rules [11].

remedy to this problem, Noda devised two-dimensional codistribution spectroscopy [25]. Here, a moment analysis of spectral intensity distribution over the perturbation dimension was included, which accounted for the sequential attribution of species within a model chemical reaction A!B!C.

autocorrelation functions of spectral intensity variations. They hence reflect the amount of change the corresponding signal experiences along the perturbation dimension. Off-diagonal signals correlate two signals changing simultaneously or coincidently under the influence of the perturbation. When both signals increase or decrease, the sign of the crosspeak is equal to that of the diagonal peaks. If they behave adversely, the sign is opposite. It is readily recognized that the resolution of spectra can be enhanced by the spread into two dimensions. Furthermore, the occurrence of two or more components, such as educt and product, can be readily seen and facilitate signal assignments. An example for a synchronous spectrum is given in Figure 1(a). As will be shown below, synchronous spectra are useful in homo- and

The asynchronous spectrum in general is less easily interpreted. As a consequence of the Noda-Hilbert orthogonalization, cf. Eq. (17), no diagonal peaks are observed. The spectrum visualizes successive or sequential changes of signal intensities, which forbids the occurrence of autopeaks. The asynchronous map is antisymmetric with respect to the diagonal. Noda has shown that Ψðωi, ωjÞ¼ �Ψðωj, ωiÞ. [11]. The sign of a crosspeak is positive—positive is defined as in phase with the diagonal peak in the corresponding synchronous spectrum—if the intensity in dimension 1 changes predominantly before that in dimension 2 in the sequence of the perturbation. This is valid for crosspeaks above the diagonal, i.e., ω<sup>1</sup> > ω2. A negative crosspeak is obtained when the order is reversed. An illustration is given in Figure 1(b). Specie B of the example hence occurs before A, and C before D. Thorough derivations and discussions

Despite its ability to correlate non-simultaneous occurrence of signals, the asynchronous map does not allow the analysis of population dynamics as in a two-step chemical reaction. As a

Figure 1. Schematic contour map of synchronous (a) and asynchronous (b) 2D correlation spectra. Peaks located at the diagonal are autopeaks. The signs of the correlation peaks are indicated. The intensity changes and signs are interpreted

hetero-covariance NMR spectroscopy.

60 Spectroscopic Analyses - Developments and Applications

have been accomplished previously [11].

according to Noda's rules [11].

Out of the manifold of variations to combine raw and Fourier transformed data, a variety of covariance-transformed spectral representations have been introduced and their applications have been demonstrated: Among those used in NMR spectroscopy, the most often used or described were direct covariance, indirect covariance, doubly indirect covariance, unsymmetrical indirect covariance, generalized indirect covariance, which replaced the previous one, multidimensional covariance in form of Triple-Rank Covariance and 4D Covariance [2, 26– 29]. Furthermore, the family of Statistical Correlation Spectroscopy (STOCSY) has been introduced, and its usefulness is demonstrated in many applications [22, 30–32].

For other spectroscopic techniques or combinations thereof, covariance spectroscopy is often referred to as 2D correlation spectroscopy, and hetero-covariance spectroscopy is called heterospectral, hetero-perturbation, and hetero-sample correlation spectroscopy [33]. Noda has further coined the term multiple perturbation 2D correlation, where the use of the parallel factor (PARAFAC) kernel analysis may play a key role in future spectral analysis [34–36]. As another variant, orthogonal sample design (OSD) was introduced and applied [37–39].

Multiple perturbation 2D correlation spectroscopy has been introduced recently by Shinzawa et al. [40, 41]. It is based on the extension of Eq. (3) yielding Eqs. (18) and (19) as follows:

$$\langle S\_p(\omega, q) \rangle = \frac{1}{P} \sum\_{p=1}^{P} S(\omega, p, q) \tag{18}$$

$$
\tilde{S}(\omega, p, q) = S(\omega, p, q) - \langle S\_p(\omega, q) \rangle \tag{19}
$$

where S is a set of spectra depending on frequency ω exposed to multiple perturbations p = 1,2,…P and q = 1,2,…Q, such as time, temperature, concentration, etc. 〈 〉 denote the average spectrum. Partial synchronous and asynchronous correlation spectra are computed according to Eqs. (20) and (21) in analogy to Eqs. (6) and (7).

$$\Phi\_p(\omega\_1, \omega\_2, q) = \frac{1}{P-1} \sum\_{p=1}^p \tilde{S}\_p(\omega\_1, p, q) \cdot \tilde{S}\_p(\omega\_2, p, q) \tag{20}$$

$$\Psi\_p(\omega\_1, \omega\_2, q) = \frac{1}{P-1} \sum\_{p=1}^P \tilde{S}\_p(\omega\_1, p, q) \cdot \tilde{S}\_p^\neq(\omega\_2, p, q) \tag{21}$$

where S~6¼ <sup>p</sup> denotes the Hilbert-Noda transformation in this case given by Eq. (22).

$$\tilde{\mathcal{S}}\_p^\#(\omega\_2, p, q) = \sum\_{r=1}^p N\_{pr} \tilde{\mathcal{S}}\_p(\omega\_2, r, q) \tag{22}$$

with Npr = 0 for p = r and Npr = 1/((r � p)π) otherwise.

The PARAFAC kernel decomposes the data into scores and loading vectors. The original threeway data array is rearranged into a two-way data array by means of the so-called Kathri-Rao (|⊗|) product, which implies the use of the Kronecker product ⊗. The matrix decomposition is usually achieved through solving an alternating least-squares problem iteratively. Disregarding the matrix of the residuals for the minimization problem, Eq. (23) is the fundamental matrix representation of the multiple perturbation correlation analysis.

$$X = \mathcal{A}(\mathbf{C}|\otimes|\mathcal{B})^{\mathsf{T}} \tag{23}$$

where X contains spectral data, A and C refer to perturbations 1 and 2, and B contains the spectral variable. The p-synchronous and p-asynchronous kernel matrices are similar to their analogs in Eqs. (16) and (17) but formed mean-centered and normalized score-vector matrix A. The ij-element of the p-synchronous kernel matrix as well as of the asynchronous one assumes values between �1 and +1, giving a similarity measure in the synchronous case and a dissimilarity measure in the asynchronous case between the score vectors of the ith and jth components. Evenly comparable, the sequential order of signal changes can be derived from the signs of the kernel matrix elements. The signal of the ith species changes before that of the jth when the signs of the ij-elements of the synchronous and asynchronous kernel matrix are the same. The order is reverted if the elements possess opposite signs. Spectral analysis can be carried out as well by performing the computation with the score matrix C instead of A. Complete mathematical descriptions have been published by Shinzawa et al. [34, 41].

Software suitable for covariance processing has recently been reviewed as well [3, 42]. With respect to some of the work performed in this report, we would like to direct the reader's attention to 2DShige. While this program is not especially dedicated to NMR spectroscopy, it is capable of performing hetero-spectroscopic covariance transformations. The program was devised by Morita and may be accessed for download via https://sites.google.com/site/ shigemorita/home/2dshige. Covariance transformations applied therein follow the work by Noda. Synchronous and asynchronous maps are computed from data in CSV format.

The following section will focus on Process Analytical Technology (PAT) such that the stage will be set for the applications of covariance processing and NMR spectroscopy to process monitoring or process understanding.

#### 3. A brief outline of process analytical technologies and microreaction processes

Process analytical technologies (PAT) have grown into an integral part of industrial manufacturing processes. The development of a process on a laboratory scale, the collection of data as well as monitoring of the production process in place are directed toward a well-understood process to ensure final product quality [43, 44].

This knowledge first enables process control and then process improvement. The envisaged process optimization is aimed at cost reduction, sustainability, and safety. Generally, production processes proceed on a large scale. The analytical instruments used close to the process are robust, relatively easy to operate instruments. Only for the development or validation of the analytical method are the dimensions of such large-scale processes reduced to laboratory scales. The analytical instruments yet may be of the same size but more complex and of higher sensitivity and resolution.

(|⊗|) product, which implies the use of the Kronecker product ⊗. The matrix decomposition is usually achieved through solving an alternating least-squares problem iteratively. Disregarding the matrix of the residuals for the minimization problem, Eq. (23) is the fundamental

X ¼ AðCj ⊗ jBÞ

where X contains spectral data, A and C refer to perturbations 1 and 2, and B contains the spectral variable. The p-synchronous and p-asynchronous kernel matrices are similar to their analogs in Eqs. (16) and (17) but formed mean-centered and normalized score-vector matrix A. The ij-element of the p-synchronous kernel matrix as well as of the asynchronous one assumes values between �1 and +1, giving a similarity measure in the synchronous case and a dissimilarity measure in the asynchronous case between the score vectors of the ith and jth components. Evenly comparable, the sequential order of signal changes can be derived from the signs of the kernel matrix elements. The signal of the ith species changes before that of the jth when the signs of the ij-elements of the synchronous and asynchronous kernel matrix are the same. The order is reverted if the elements possess opposite signs. Spectral analysis can be carried out as well by performing the computation with the score matrix C instead of A. Complete

Software suitable for covariance processing has recently been reviewed as well [3, 42]. With respect to some of the work performed in this report, we would like to direct the reader's attention to 2DShige. While this program is not especially dedicated to NMR spectroscopy, it is capable of performing hetero-spectroscopic covariance transformations. The program was devised by Morita and may be accessed for download via https://sites.google.com/site/ shigemorita/home/2dshige. Covariance transformations applied therein follow the work by

The following section will focus on Process Analytical Technology (PAT) such that the stage will be set for the applications of covariance processing and NMR spectroscopy to process

Process analytical technologies (PAT) have grown into an integral part of industrial manufacturing processes. The development of a process on a laboratory scale, the collection of data as well as monitoring of the production process in place are directed toward a well-understood process

This knowledge first enables process control and then process improvement. The envisaged process optimization is aimed at cost reduction, sustainability, and safety. Generally, production processes proceed on a large scale. The analytical instruments used close to the process are robust, relatively easy to operate instruments. Only for the development or validation of the analytical method are the dimensions of such large-scale processes reduced to laboratory

Noda. Synchronous and asynchronous maps are computed from data in CSV format.

3. A brief outline of process analytical technologies and microreaction

<sup>T</sup> <sup>ð</sup>23<sup>Þ</sup>

matrix representation of the multiple perturbation correlation analysis.

62 Spectroscopic Analyses - Developments and Applications

mathematical descriptions have been published by Shinzawa et al. [34, 41].

monitoring or process understanding.

to ensure final product quality [43, 44].

processes

Process analytical technologies often make use of spectroscopic and chromatographic as well as of integral methods. Today, Raman spectroscopy and near IR (NIR) spectroscopy play major roles, whereas pH, pressure, and refractivity techniques are typical non-specific methods, inexpensive still ubiquitous, and powerful within well-controlled processes [45]. The conditions of the production process often demand for greater robustness, stability, and performance of the analytical instruments, because of the close proximity to the manufacturing line. Process monitoring and control require prompt or real-time data recording, processing, and feeding the data back to the process control unit. These constraints necessitate in-line, on-line, or at least at-line analytical methods [46].

Microprocesses or microreactions are conducted in very small-scale reactors and mixing devices equipped with tubing, pumps, and valves. The reaction set-up is composed in a Legolike manner, cf. Figure 2. Microdevices allow for a highly efficient heat transfer as compared to

Figure 2. Microreaction assembly with on-line low-field <sup>1</sup> H-NMR spectrometer (bottom); process flow chart of the set-up of the microprocess analytics (top left): (1) storage vessel, (2) transflectance NIR immersion probe, (3) pump; zoom of the microreactor assembly (top right).

large-scale vessels. While they sometimes enable a superior mass transfer, they sometimes cause an inferior mixing of the reactants due to microfluidic effects. Typical yields may range from milligrams to a few grams per day depending on the reaction conducted in batch or flow mode [47–49].

Microprocesses with respect to scale, volumetric flow, and yield demand for microanalytics if implemented in-line or on-line. At-line installations merely require a sample cell of suitable size and sensitivity. Two different ways have been described to monitor microprocesses in-line or on-line with spectroscopic methods. The probes or sample cells were located either in the reaction vessel or a by-pass similar to large-scale facilities. Alternatively, the reaction was conducted within the sample cell of a spectrometer, e.g., UV/Vis or Nuclear Magnetic Resonance. Miniaturized analytical devices are preferable in case of microreaction vessels, whereas standard laboratory instruments may be used for the second case. So-called bench-top instruments are particularly interesting for microprocess analytical technology. Bench-top instruments may be found as the size of a microwave oven [50–53].

In the following sections, illustrative examples for the application of NMR spectroscopy, covariance, homo- and hetero-correlation spectroscopy to process monitoring, and process understanding will be given.

#### 4. Applications of homo- and hetero-covariance spectroscopy

Covariance transformations of NMR data with or without prior Fourier transformation today are widely applied. Prominent examples comprise generalized indirect covariance and multidimensional covariance NMR as well as the combination of covariance and non-uniform sampling of data [54–57]. While the concept of homo- and hetero-covariance spectroscopy was developed nearly three decades ago, there are relatively few reports on the use of synchronous and asynchronous spectra involving NMR spectroscopy [3, 14, 55, 58, 59]. In contrast, an abundant number of investigations have applied so-called statistical hetero-spectroscopy (STOCSY) that has delivered important contributions to the field of metabolomics and whose variants have recently been depicted like a phylogenetic tree [22, 32, 60]. In the current report, the focus is however laid on examples from chemical processes rather than metabolomics.

#### 4.1. Reaction monitoring of a wine fermentation

Kirwan et al. monitored a wine fermentation by <sup>1</sup> H NMR spectroscopy, drawing samples daily [61]. After careful preprocessing by segmentation, alignment, normalization, and smoothing, the data were covariance transformed, yielding homo-spectral synchronous and asynchronous matrices. While the synchronous map was found less prone to small chemical shift and linewidth variations, the asynchronous matrix was very sensitive. Sasic had also reported on the effects of linewidth [62]. In his metabonomics study on vasculitis analyzing rat urine samples, butterfly-like signal shapes were observed as a result of shifting peak positions. The lack of uniform pre-processing led to numerous artifacts and problems that severely hampered spectral interpretation in contrast to the wine study. The spectra recorded in the wine fermentation study were hence ameliorated in a successive approach by imposing a fixed linewidth prior to covariance transformation such that the effects of linewidths changing during the fermentation were compensated for [63]. Extracted regions of both spectra are shown in Figure 3.

large-scale vessels. While they sometimes enable a superior mass transfer, they sometimes cause an inferior mixing of the reactants due to microfluidic effects. Typical yields may range from milligrams to a few grams per day depending on the reaction conducted in batch or flow

Microprocesses with respect to scale, volumetric flow, and yield demand for microanalytics if implemented in-line or on-line. At-line installations merely require a sample cell of suitable size and sensitivity. Two different ways have been described to monitor microprocesses in-line or on-line with spectroscopic methods. The probes or sample cells were located either in the reaction vessel or a by-pass similar to large-scale facilities. Alternatively, the reaction was conducted within the sample cell of a spectrometer, e.g., UV/Vis or Nuclear Magnetic Resonance. Miniaturized analytical devices are preferable in case of microreaction vessels, whereas standard laboratory instruments may be used for the second case. So-called bench-top instruments are particularly interesting for microprocess analytical technology. Bench-top instru-

In the following sections, illustrative examples for the application of NMR spectroscopy, covariance, homo- and hetero-correlation spectroscopy to process monitoring, and process

Covariance transformations of NMR data with or without prior Fourier transformation today are widely applied. Prominent examples comprise generalized indirect covariance and multidimensional covariance NMR as well as the combination of covariance and non-uniform sampling of data [54–57]. While the concept of homo- and hetero-covariance spectroscopy was developed nearly three decades ago, there are relatively few reports on the use of synchronous and asynchronous spectra involving NMR spectroscopy [3, 14, 55, 58, 59]. In contrast, an abundant number of investigations have applied so-called statistical hetero-spectroscopy (STOCSY) that has delivered important contributions to the field of metabolomics and whose variants have recently been depicted like a phylogenetic tree [22, 32, 60]. In the current report, the focus is however laid on examples from chemical processes rather than metabolomics.

daily [61]. After careful preprocessing by segmentation, alignment, normalization, and smoothing, the data were covariance transformed, yielding homo-spectral synchronous and asynchronous matrices. While the synchronous map was found less prone to small chemical shift and linewidth variations, the asynchronous matrix was very sensitive. Sasic had also reported on the effects of linewidth [62]. In his metabonomics study on vasculitis analyzing rat urine samples, butterfly-like signal shapes were observed as a result of shifting peak positions. The lack of uniform pre-processing led to numerous artifacts and problems that severely hampered spectral interpretation in contrast to the wine study. The spectra recorded

H NMR spectroscopy, drawing samples

4. Applications of homo- and hetero-covariance spectroscopy

ments may be found as the size of a microwave oven [50–53].

4.1. Reaction monitoring of a wine fermentation Kirwan et al. monitored a wine fermentation by <sup>1</sup>

mode [47–49].

64 Spectroscopic Analyses - Developments and Applications

understanding will be given.

The spectra contained strong signals from sugars, fructose, and glucose, in the early period. In the later phase, ethanol signals became predominant. Other molecular species were emerging and vanishing as well. Their temporal relationship was said difficult to assess, which can be seen from inspection of Figure 3. A manifold of correlations are present in the covariance maps. Most clearly, the interdependence of the sugar and ethanol signals is recognized. Kirwan et al. already pointed out the difficulty of interpreting the spectra due to the high resolution of the initial <sup>1</sup> H NMR spectra leading to the large number of signals and correlations [61]. The authors suggested the use of slices through the synchronous map allowing the signal attribution and further extraction of the sequential information out of the corresponding slices of the asynchronous map. Careful analysis revealed that glucose was consumed and transformed at a higher rate than fructose, which was interpreted in terms of the different diffusion rates of the two sugars across the fermenting yeast cell membrane. The authors thus demonstrated the usefulness of correlation NMR spectroscopy for monitoring concentrations and sequential relationships in a biochemical process.

#### 4.2. IR-NMR hetero-covariance spectroscopy applied to radical polymerization

Ryu et al. used 2D IR-NMR hetero-spectroscopy to characterize a chain transfer reaction during the radical polymerization of N-vinylpyrrolidone (NVP) [64]. Polyvinylpyrrolidone (PVP) was polymerized to form nanoparticles through a chain transfer reaction initiated by silver nitrate. Upon reduction via electron transfer, PVP polymer silver nanoparticles were

Figure 3. The synchronous (a) and asynchronous (b) maps of a section of the mean-centered 1D <sup>1</sup> H NMR spectra at 500 MHz of a series of wine fermentation samples. Reprinted from Kirwan et al. [63]. Copyright 2008, with permission from Elsevier.

formed. The resulting nanoparticles possessed a carbon-carbon double bond at the end of the PVP chain after chain transfer termination. Radical formation was initiated through azobisisobutyronitrile. The reaction was monitored using IR and 1D <sup>1</sup> H NMR spectroscopy. That is, a series of IR and NMR spectra depending on reaction time as perturbation domain were obtained. In the IR synchronous homo-correlation spectrum, bands at 1660 and 1676 cm-1 were revealed that could be attributed to the stretching vibration of the carbon-carbon double bond and of the carbonyl group, respectively. The asynchronous map was interpreted in terms of an intensity decrease of the band at 1660 cm-1 preceding the increase of the carbonyl band at 1676 cm-1, cf. Figure 4.

Following Noda's rules on analyzing the synchronous and asynchronous spectral matrices, one might also come to a reversed conclusion concerning the sequential order [11, 12]. Both educt and product after chain transfer termination do exhibit carbon-carbon double bonds, where the NMR signals of the monomeric educts should lead to more intense signals due to less relaxation broadening. Yet, IR-NMR hetero-spectral correlation maps were used to unequivocally attribute the less-resolved IR bands in the product to the carbon-carbon double

Figure 4. Synchronous (a) and asynchronous (b) 2D FTIR correlation spectra of PVP during polymerization with 400 ppm silver nitrate. The autopower spectrum extracted along the diagonal line in the synchronous 2D correlation spectrum is given on the top of (a). The solid and dashed lines in the spectra represent the positive and negative crosspeaks, respectively. Reprinted from Ryu et al. [64]. Copyright 2012, with permission from Elsevier.

bond and to the carbonyl group. Thus, both homo- and hetero-spectral correlations are of considerable value to increase spectral resolution and cross-fertilize the spectral analysis or assignment of one spectroscopic technique by taking advantage of another technique. This is especially helpful in process analytical technologies when signal crowding or strong overlap due to conditions unfavorable for a certain spectroscopic method occurs frequently.

formed. The resulting nanoparticles possessed a carbon-carbon double bond at the end of the PVP chain after chain transfer termination. Radical formation was initiated through azobisiso-

series of IR and NMR spectra depending on reaction time as perturbation domain were obtained. In the IR synchronous homo-correlation spectrum, bands at 1660 and 1676 cm-1 were revealed that could be attributed to the stretching vibration of the carbon-carbon double bond and of the carbonyl group, respectively. The asynchronous map was interpreted in terms of an intensity decrease of the band at 1660 cm-1 preceding the increase of the carbonyl band at

Following Noda's rules on analyzing the synchronous and asynchronous spectral matrices, one might also come to a reversed conclusion concerning the sequential order [11, 12]. Both educt and product after chain transfer termination do exhibit carbon-carbon double bonds, where the NMR signals of the monomeric educts should lead to more intense signals due to less relaxation broadening. Yet, IR-NMR hetero-spectral correlation maps were used to unequivocally attribute the less-resolved IR bands in the product to the carbon-carbon double

Figure 4. Synchronous (a) and asynchronous (b) 2D FTIR correlation spectra of PVP during polymerization with 400 ppm silver nitrate. The autopower spectrum extracted along the diagonal line in the synchronous 2D correlation spectrum is given on the top of (a). The solid and dashed lines in the spectra represent the positive and negative crosspeaks,

respectively. Reprinted from Ryu et al. [64]. Copyright 2012, with permission from Elsevier.

H NMR spectroscopy. That is, a

butyronitrile. The reaction was monitored using IR and 1D <sup>1</sup>

66 Spectroscopic Analyses - Developments and Applications

1676 cm-1, cf. Figure 4.

#### 4.3. Study of polylactic acid nanocomposites at varied temperatures and compositions using PARAFAC kernel analysis

Shinzawa et al. investigated polylactic acid nanocomposites using solid-state cross-polarization magic angle spinning (CP-MAS) 13C NMR experiments [34]. They prepared four samples with varying clay content through a melt-blend process to obtain pellets. The properties of the sample exposed to temperature variation were studied by thermomechanical analysis. The elongation of the sample measured under imposture of a load occurred most notably at the glass transition temperature of the samples around 60C. After a certain increase, a plateau was reached. The finding was interpreted that the plastic deformation observed was related to the glass-to-rubber transition of the amorphous polylactic acid component. When the elongation did no longer increase, a network structure due to physical crosslinkage induced by the crystalline domain was assumed. The dependence on the clay content suggested that with increasing clay inclusion, the tendency to elongate with temperature decreases. Thus, inclusion of clay led to enhanced stiffness. By applying NMR spectroscopy, Shinzawa et al. strove to probe the macroscopic properties on a molecular scale. To this purpose, they inspected the 13C NMR resonance around 170 ppm, which originates from two peaks at 169 ppm and 170 ppm attributed to the crystalline and amorphous phases, respectively. Since NMR spectra depended on two separate perturbations, i.e., clay content and temperature, the PARAFAC kernel analysis according to Eq. (23) was employed for a detailed analysis. As described above, two sets of synchronous and asynchronous correlation spectra were obtained after the covariance transformations and matrix decompositions: the temperature-dependent and the clay-dependent homo-correlations. The partial correlations from composition-dependent NMR spectra at fixed temperature are exemplarily presented in Figure 5. Whereas the partial temperature-dependent correlation spectra revealed

Figure 5. Partial synchronous correlation (a) and partial asynchronous correlation (b) spectra calculated from clay weight-dependent 1D CP-MAS 13C NMR spectra recorded at 100.56 MHz. Reproduced from Shinzawa et al. [34] with permission of The Royal Society of Chemistry (RSC).

that the amorphous preceded the crystalline component upon temperature increase, the spectra in Figure 5 showed that the amorphous content occurred predominantly before the crystalline content on increasing clay content. This was assumed due to the clay acting as a nucleating agent. It would foster additional crystallization of the polylactic acid. Upon decrease of the amorphous phase, the phase transitioning from glass to rubber should be reduced. These results were supported by the thermomechanical analysis.

The added value of the PARAFAC kernel analysis is that it furnishes quantitative data. The score, A and C, and loading, B, matrices reflect the change in signal intensity separated into composition and temperature dependence. They also provide abstract information on the dynamic behaviors of the crystalline and amorphous phases. The synchronous and asynchronous pair of the kernel matrix is exemplarily presented in Figure 6 for the spectral intensity change of the nanocomposite samples due to clay content variation. The so-called q-synchronous correlation intensity, cf. above, H<sup>q</sup> amorphous, crystalline = 0.98 and q-asynchronous correlation intensity K<sup>q</sup> amorphous, crystalline = 0.06 were interpreted in terms of similarity of changes in the amorphous and crystalline components due to the presence of clay. Yet, the negative sign indicated opposite direction, i.e., increase in clay content augmented the crystalline and decreased the amorphous phase, which agreed well with the homo-spectral correlation results. In practice, the application of PARAFAC kernel analysis was envisioned to provide opportunities to gain detailed information on sequences of species occurring under multiple perturbations.

#### 4.4. Monitoring of ethanol production from immobilized yeast using homo- and hetero-covariance spectroscopy

As an example for process monitoring of biochemical processes, the conversion of glucose into alcohol by Saccharomyces cerevisiae, baker's or brewer's yeast, was monitored using low-field 1D <sup>1</sup> H NMR and Raman spectroscopy [65]. Monitoring of fermentation processes was described

Figure 6. Representations of the q-synchronous kernel (a) and q-asynchronous kernel (b) matrices computed from the score matrix C of the clay weight-dependent 1D CP-MAS 13C NMR spectra recorded at 100.56 MHz as used in the PARAFAC kernel analysis [34].

earlier, and NIR became the standard methodology [66, 67]. Later, attempts were made to use Raman spectroscopy [68]. Recently, hetero-spectral correlation NIR-IR spectroscopy was applied [69]. The fermentation described in the current report was conducted as a continuous process feeding glucose solution at a constant flow into a 2 L fermenter. Yeast immobilized within an alginate hydrocolloid converted the sugar to ethanol. The aqueous ethanolic solution was diverted at a constant flow. The flow rate was optimized such that during the residence time of a given volume, the glucose was fully converted into ethanol. On-line monitoring, i.e., through analysis of the ethanol signals and potential remainders of the glucose signals, was applied to control the efficiency of the process from the initial induction phase to the final stable production. After optimization, a sugar concentration of about 17% could be successfully transformed into ethanol.

that the amorphous preceded the crystalline component upon temperature increase, the spectra in Figure 5 showed that the amorphous content occurred predominantly before the crystalline content on increasing clay content. This was assumed due to the clay acting as a nucleating agent. It would foster additional crystallization of the polylactic acid. Upon decrease of the amorphous phase, the phase transitioning from glass to rubber should be reduced. These results

The added value of the PARAFAC kernel analysis is that it furnishes quantitative data. The score, A and C, and loading, B, matrices reflect the change in signal intensity separated into composition and temperature dependence. They also provide abstract information on the dynamic behaviors of the crystalline and amorphous phases. The synchronous and asynchronous pair of the kernel matrix is exemplarily presented in Figure 6 for the spectral intensity change of the nanocomposite samples due to clay content variation. The so-called q-synchronous correlation intensity, cf. above, H<sup>q</sup> amorphous, crystalline = 0.98 and q-asynchronous correlation intensity K<sup>q</sup> amorphous, crystalline = 0.06 were interpreted in terms of similarity of changes in the amorphous and crystalline components due to the presence of clay. Yet, the negative sign indicated opposite direction, i.e., increase in clay content augmented the crystalline and decreased the amorphous phase, which agreed well with the homo-spectral correlation results. In practice, the application of PARAFAC kernel analysis was envisioned to provide opportunities to gain detailed information on sequences of species occurring under multiple perturbations.

4.4. Monitoring of ethanol production from immobilized yeast using homo- and

As an example for process monitoring of biochemical processes, the conversion of glucose into alcohol by Saccharomyces cerevisiae, baker's or brewer's yeast, was monitored using low-field

Figure 6. Representations of the q-synchronous kernel (a) and q-asynchronous kernel (b) matrices computed from the score matrix C of the clay weight-dependent 1D CP-MAS 13C NMR spectra recorded at 100.56 MHz as used in the

H NMR and Raman spectroscopy [65]. Monitoring of fermentation processes was described

were supported by the thermomechanical analysis.

68 Spectroscopic Analyses - Developments and Applications

hetero-covariance spectroscopy

PARAFAC kernel analysis [34].

1D <sup>1</sup>

Since no deuterated solvents were used, the series of 1D <sup>1</sup> H NMR spectra exhibited a dominant water signal and the typical ethanol resonances, cf. projections in Figure 7.

Homo- and hetero-covariance transformations were computed after spectral alignment and normalization to the water resonance at 4.8 ppm. The synchronous NMR spectrum displayed the expected positive intra-ethanol correlation at (3.8 ppm, 1.2 ppm). It exhibited further positive correlations between the signal at 4.8 ppm and the ethanol resonances at 1.2 and 3.8 ppm, suggesting that both signals increased or decreased in phase. As the spectra were normalized to the water resonance, the tentative change was traced back to changes in the linewidth of the water signal and should therefore not further be considered. Inspection of the asynchronous spectrum, cf. Figure 7, showed no intramolecular correlations at 3.8 and 1.2 ppm as would be expected, since the ethanol signals would change in phase. Yet, correlations between the signal at 4.8 ppm and the ethanol resonances were observed. The sign of the correlation suggested that water or an underlying component would grow before ethanol

Figure 7. Synchronous (left) and asynchronous (right) 2D NMR homo-correlation spectra of ethanol production by immobilized yeast using on-line 1D <sup>1</sup> H NMR spectroscopy (82 MHz, T = 36C).

increased. Since change on the water resonance was traced back to linewidth variations, no conclusion with respect to the sequence of change should be drawn. Taking into account the earlier observation by Kirwan et al. and Sasic with respect to changes in linewidth and spectral alignment, the described preprocessing procedures were found difficult to apply to low-field spectra with relatively poor resolution and signals with strongly differing linewidths.

In contrast, the hetero-covariance NMR-Raman spectrum proved very useful for the quick analysis and assignment of the signals in the Raman spectrum, cf. Figure 8.

Only the band at 1360 cm-1 showed a negative correlation with the NMR resonances of ethanol, thus identifying this band as educt related. All other Raman bands were found in phase with the ethanol NMR signals and could thus serve for product monitoring. The heterocorrelation spectrum was hence able to readily visualize that nearly all Raman bands at least predominantly originated from ethanol, but in contrast to low-field NMR signals provided an educt signal, which appeared only as a shoulder in the corresponding 1D Raman spectrum.

#### 4.5. Reaction monitoring of a Knoevenagel condensation in a microreaction system

A Knoevenagel condensation reaction was conducted in a microreaction system, cf. Figure 2 [70]. Neat malonic acid diethylester and 2-propanal were flowed through the microreactor at a

Figure 8. 2D NMR-Raman hetero-correlation spectra of ethanol production by immobilized yeast using on-line 1D <sup>1</sup> H NMR spectroscopy (82 MHz, T = 36C) and in-line Raman spectroscopy (laser wavelength 785 nm).

temperature of 82C. Butylidene malonic acid diethylester and water were obtained as products. The solution was re-circulated for 1200 min and monitored using on-line low-field benchtop 1D <sup>1</sup> H NMR (82 MHz), in-line NIR, and in-line Raman spectroscopy (laser excitation wavelength 785 nm). Despite the relatively poor resolution of the low-field instrument, the series of 1D <sup>1</sup> H NMR spectra showed well-resolved signals for each educt and product, cf. Figure 9. Therefore, signals could be integrated and concentration-time plots were established.

increased. Since change on the water resonance was traced back to linewidth variations, no conclusion with respect to the sequence of change should be drawn. Taking into account the earlier observation by Kirwan et al. and Sasic with respect to changes in linewidth and spectral alignment, the described preprocessing procedures were found difficult to apply to low-field

In contrast, the hetero-covariance NMR-Raman spectrum proved very useful for the quick

Only the band at 1360 cm-1 showed a negative correlation with the NMR resonances of ethanol, thus identifying this band as educt related. All other Raman bands were found in phase with the ethanol NMR signals and could thus serve for product monitoring. The heterocorrelation spectrum was hence able to readily visualize that nearly all Raman bands at least predominantly originated from ethanol, but in contrast to low-field NMR signals provided an educt signal, which appeared only as a shoulder in the corresponding 1D Raman spectrum.

spectra with relatively poor resolution and signals with strongly differing linewidths.

4.5. Reaction monitoring of a Knoevenagel condensation in a microreaction system

A Knoevenagel condensation reaction was conducted in a microreaction system, cf. Figure 2 [70]. Neat malonic acid diethylester and 2-propanal were flowed through the microreactor at a

Figure 8. 2D NMR-Raman hetero-correlation spectra of ethanol production by immobilized yeast using on-line 1D <sup>1</sup>

NMR spectroscopy (82 MHz, T = 36C) and in-line Raman spectroscopy (laser wavelength 785 nm).

H

analysis and assignment of the signals in the Raman spectrum, cf. Figure 8.

70 Spectroscopic Analyses - Developments and Applications

The covariance transformation to synchronous and asynchronous homo-spectral correlation maps helped quickly visualize the interdependence of the signals, cf. Figure 10. The assignment of educt and product signals was in agreement with correlation crosspeaks and their signs. The signals were attributed as 3.2 ppm for malonic acid diethylester, 6.8 ppm for the product butylidene malonic diethylester, and 9.5 ppm for 2-propanal. Since the intensity of the autopeaks in the homo-covariance map reflects the amount of change, peaks appeared at strongly different intensity levels such that representations of the spectra should be prepared using different thresholds with emphasis on either strong or weak signals. Nevertheless, the sign of the crosspeaks was found in accordance with the expectancy values. With respect to the

Figure 9. 1D <sup>1</sup> H NMR spectra (82 MHz, T = 36C) recorded for 1200 min during on-line monitoring of a Knoevenagel condensation of neat malonic acid diethylester and 2-propanal yielding butylidene malonic acid diethylester conducted in a microreaction system presented in Figure 2.

Figure 10. Synchronous (left) and asynchronous (right) 2D NMR correlation spectra of a Knoevenagel condensation of neat malonic acid diethylester and 2-propanal yielding butylidene malonic acid diethylester conducted in a microreaction system and monitored during 1200 min at a reaction temperature of 82C using on-line 1D <sup>1</sup> H NMR (82 MHz, T = 36C).

asynchronous map, the positive crosspeak at 9.5 and 6.8 ppm was seen indicative for the aldehyde reaction preceding the final product formation, i.e., the formation of the double bond.

Although the interpretation of the 1D <sup>1</sup> H NMR spectra was readily achieved, the use of in-line applicable techniques such as Raman and NIR spectroscopy was considered preferable from a process analytical perspective. This required the interpretation of the vibrational spectra. The increasing intensity of the Raman band at 1600 cm-1, which originated from the carbon-carbon double bond vibration, was to some extent obvious in the series of 1D Raman spectra recorded. Further attribution of bands useful for reaction component monitoring was not readily achieved. To this purpose, hetero-correlation maps were computed from NMR and Raman spectra as well as from NMR and NIR, shown in Figure 11. Preprocessing of all spectra with respect to baseline correction, alignment, normalization, and data reduction or binning was found of utmost importance. The NMR signal assignment was readily transferred to the bands at 1600 and 800 cm-1 through correlations. The band at 800 cm-1 exhibited negative correlations to the product chemical shift and was hence found due to one of the educts. On inspection of the aldehyde resonance at 9.5 ppm, positive signs were found, which would be expected for a correlation between educts. The band at 1450 cm-1, which was assigned to a methylene group bending vibration, showed only weak correlations. One of them correlated that band to the resonance at 3.2 ppm, indicating an educt-educt relationship. Analyzing the NIR-NMR heterocovariance spectra, the enhancing power of NMR spectroscopy becomes even more evident. While NIR provides very broad bands that are due to either C-H or O-H overtone or combination frequencies and thus seemingly non-specific, the well-resolved signals of NMR spectroscopy assist in finding regions that can be attributed to educts or products and thus used for

Homo- and Hetero-Covariance NMR Spectroscopy and Applications to Process Analytical Technology http://dx.doi.org/10.5772/intechopen.68981 73

Figure 11. Synchronous Raman-NMR (top row) and NIR-NMR (bottom row) hetero-correlation spectra of a Knoevenagel condensation of neat malonic acid diethylester and 2-propanal yielding butylidene malonic acid diethylester conducted in a microreaction system and monitored during 1200 min at a reaction temperature of 82C using on-line 1D <sup>1</sup> H NMR (82 MHz, T = 36C), in-line NIR and in-line Raman spectroscopy (laser wavelength of 785 nm); full spectrum (left) and enlarged region (right), 1D spectra recorded at 1200 min are shown top and right of the correlation map.

asynchronous map, the positive crosspeak at 9.5 and 6.8 ppm was seen indicative for the aldehyde reaction preceding the final product formation, i.e., the formation of the double bond.

Figure 10. Synchronous (left) and asynchronous (right) 2D NMR correlation spectra of a Knoevenagel condensation of neat malonic acid diethylester and 2-propanal yielding butylidene malonic acid diethylester conducted in a microreaction

system and monitored during 1200 min at a reaction temperature of 82C using on-line 1D <sup>1</sup>

applicable techniques such as Raman and NIR spectroscopy was considered preferable from a process analytical perspective. This required the interpretation of the vibrational spectra. The increasing intensity of the Raman band at 1600 cm-1, which originated from the carbon-carbon double bond vibration, was to some extent obvious in the series of 1D Raman spectra recorded. Further attribution of bands useful for reaction component monitoring was not readily achieved. To this purpose, hetero-correlation maps were computed from NMR and Raman spectra as well as from NMR and NIR, shown in Figure 11. Preprocessing of all spectra with respect to baseline correction, alignment, normalization, and data reduction or binning was found of utmost importance. The NMR signal assignment was readily transferred to the bands at 1600 and 800 cm-1 through correlations. The band at 800 cm-1 exhibited negative correlations to the product chemical shift and was hence found due to one of the educts. On inspection of the aldehyde resonance at 9.5 ppm, positive signs were found, which would be expected for a correlation between educts. The band at 1450 cm-1, which was assigned to a methylene group bending vibration, showed only weak correlations. One of them correlated that band to the resonance at 3.2 ppm, indicating an educt-educt relationship. Analyzing the NIR-NMR heterocovariance spectra, the enhancing power of NMR spectroscopy becomes even more evident. While NIR provides very broad bands that are due to either C-H or O-H overtone or combination frequencies and thus seemingly non-specific, the well-resolved signals of NMR spectroscopy assist in finding regions that can be attributed to educts or products and thus used for

H NMR spectra was readily achieved, the use of in-line

H NMR (82 MHz, T = 36C).

Although the interpretation of the 1D <sup>1</sup>

72 Spectroscopic Analyses - Developments and Applications

reaction monitoring. The NIR-NMR correlation signals in Figure 11, bottom row, indicate that the O-H resonance around 7000 cm-1 stemmed from product water, while that around 5200 cm-1 was due to an educt C-H combination frequency. Thus, two potential monitoring frequency ranges could be identified.

Based on the thus identified and attributed signals, intensity-time plots and hence concentrationtime curves could be extracted from the series of one-dimensional NIR spectra. This allowed the comparison of reaction monitoring by three different spectroscopic techniques, NIR, Raman, and NMR. The results were found in rather good agreement with each other. The concentration-time curves could be computed using chemical kinetic models from which reaction rate constants and half-lives were obtained. The reaction was found to follow first- or pseudo first-order reaction kinetics. It was expected that the knowledge of reaction parameters could later be transformed into automatic process control [70].

#### 5. Conclusion

Covariance NMR has become a valuable tool in the ensemble of NMR methodologies. Generalized covariance was often performed with techniques other than NMR to profit from synchronous and asynchronous correlation maps. The synchronous map as a substitute to or along with the traditional Fourier transformed spectrum was nevertheless employed quite frequently in NMR. Hetero-spectroscopic covariance was used to concatenate NMR and mass spectrometry, NIR, and Raman data allowing combining the information of two techniques. Resolution improvement was reported an advantage of both the homo- and hetero-covariance processing, since information could be transferred from the well-resolved NMR domain into the less obvious to interpret vibrational domains. Here, the synchronous spectrum helped to increase resolution and assign signals to either the same or different species. As had been reported for vibrational spectroscopy, homo-covariance transformation also gives rise to two-dimensional data when only series of 1D NMR spectra are available, e.g., due to the application of low-field NMR instruments. Although the asynchronous map provides information on the sequential occurrence of signals, it has been relatively rarely exploited for NMR purposes. In a more recent study, Noda showed that more sophisticated mathematical processing was needed to derive the order of three or more species within a chemical reaction. When the asynchronous spectra were computed and analyzed, the sequential attribution feature proved very useful for PAT applications, such as in fermentation or reaction monitoring. Examples of wine fermentation, ethanol production using immobilized yeast, and monitoring of a radical polymerization and a Knoevenagel condensation in a microreaction system with a low-field NMR instrument were discussed. For quantitation of signal intensity changes and conclusions therefrom, the PARAFAC kernel analysis applied to polylactic acid nanocomposites with various clay content and at varied temperatures was summarized.

The opportunities of homo- and hetero-covariance spectroscopy in the field of NMR combined with other spectroscopic and spectrometric techniques are numerous. Still, new mathematical extensions continue to be devised. The authors therefore expect that with commercial software becoming more available for non-developing users, the reports on applications of homo- and hetero-covariance spectroscopy yielding synchronous and asynchronous spectra to chemical problems will steadily grow.

#### Acknowledgements

R. Legner is very grateful for a grant from the German Academic Scholarship Foundation. The authors thank the Niederrhein University of Applied Sciences for financial support. They are indebted to Professor Dr. Anna Nickisch-Hartfiel and Professor Dr. Peter Naderwitz for biochemical and technical expertise.

#### Author details

kinetics. It was expected that the knowledge of reaction parameters could later be transformed

Covariance NMR has become a valuable tool in the ensemble of NMR methodologies. Generalized covariance was often performed with techniques other than NMR to profit from synchronous and asynchronous correlation maps. The synchronous map as a substitute to or along with the traditional Fourier transformed spectrum was nevertheless employed quite frequently in NMR. Hetero-spectroscopic covariance was used to concatenate NMR and mass spectrometry, NIR, and Raman data allowing combining the information of two techniques. Resolution improvement was reported an advantage of both the homo- and hetero-covariance processing, since information could be transferred from the well-resolved NMR domain into the less obvious to interpret vibrational domains. Here, the synchronous spectrum helped to increase resolution and assign signals to either the same or different species. As had been reported for vibrational spectroscopy, homo-covariance transformation also gives rise to two-dimensional data when only series of 1D NMR spectra are available, e.g., due to the application of low-field NMR instruments. Although the asynchronous map provides information on the sequential occurrence of signals, it has been relatively rarely exploited for NMR purposes. In a more recent study, Noda showed that more sophisticated mathematical processing was needed to derive the order of three or more species within a chemical reaction. When the asynchronous spectra were computed and analyzed, the sequential attribution feature proved very useful for PAT applications, such as in fermentation or reaction monitoring. Examples of wine fermentation, ethanol production using immobilized yeast, and monitoring of a radical polymerization and a Knoevenagel condensation in a microreaction system with a low-field NMR instrument were discussed. For quantitation of signal intensity changes and conclusions therefrom, the PARAFAC kernel analysis applied to polylactic acid nanocomposites with various clay content and at varied temperatures was summarized.

The opportunities of homo- and hetero-covariance spectroscopy in the field of NMR combined with other spectroscopic and spectrometric techniques are numerous. Still, new mathematical extensions continue to be devised. The authors therefore expect that with commercial software becoming more available for non-developing users, the reports on applications of homo- and hetero-covariance spectroscopy yielding synchronous and asynchronous spectra to chemical

R. Legner is very grateful for a grant from the German Academic Scholarship Foundation. The authors thank the Niederrhein University of Applied Sciences for financial support. They are indebted to Professor Dr. Anna Nickisch-Hartfiel and Professor Dr. Peter Naderwitz for bio-

into automatic process control [70].

74 Spectroscopic Analyses - Developments and Applications

problems will steadily grow.

Acknowledgements

chemical and technical expertise.

5. Conclusion

Martin Jaeger\* and Robin Legner

\*Address all correspondence to: martin.jaeger@hs-niederrhein.de

Department of Chemistry, Instrumental Analytical Chemistry and ILOC Institute for Coatings and Surface Chemistry, Niederrhein University, Krefeld, Germany

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**1H and 13C NMR for the Profiling of Natural Product** 

DOI: 10.5772/intechopen.71040

Fabian M. Dayrit and Angel C. de Dios Fabian M. Dayrit and Angel C. de Dios Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.71040

#### **Abstract**

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80 Spectroscopic Analyses - Developments and Applications

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the principal methods of metabolomics, the branch of '-omics' that deals with small molecules. Although MS is gaining popularity in metabolomics, NMR enjoys a number of key advantages because it is nondestructive, unbiased, quantitative, does not require separation or derivatization, and is amenable to compounds that are difficult to analyze by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). There are two general approaches to the use of NMR for profiling studies: an untargeted approach, which uses chemometric analysis; and a targeted approach, which aims to quantify known compounds in the extract. These approaches, however, are not mutually exclusive and will likely converge in the future. This paper will describe the basic theoretical principles that should be considered to develop NMR into a standard quantitative method. Although 1H NMR is more sensitive, 13C NMR spectra are simpler with less overlapping signals and are less affected by different magnetic field strengths. Various applications of 1H and 13C NMR for the profiling of natural products are described. The use of two-dimensional 1H NMR has been used to overcome problems of spectral overlap. The standardization of the NMR protocol will make it a more useful tool for the profiling of natural products extracts.

**Keywords:** nuclear magnetic resonance, 1H NMR, 13C NMR, natural products profiling, metabolomics, chemometrics

#### **1. Introduction**

The objective of this paper is to review the applications of 1H and 13C nuclear magnetic resonance (NMR) for the quantitative profiling of plant natural products extracts and the theoretical parameters that should be considered, if it is to become a more useful tool.

© 2016 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. © 2017 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.

NMR and mass spectrometry (MS) are the principal methods of metabolomics, the branch of '-omics' that deals with small molecules. The Metabolomics Society describes metabolomics as: "the comprehensive characterization of the small molecule metabolites in biological systems" [1]. NMR has a number of characteristics that meet the requirements of metabolomics: it is accurate, quantitative, comprehensive, unbiased, and is able to provide information that can be used to determine molecular structure. The review will discuss these aspects in detail.

#### **1.1. NMR and MS**

Although MS techniques, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), are most commonly used in metabolomics, NMR still enjoys a number of key advantages. In particular, NMR is nondestructive, unbiased, quantitative, does not require separation or derivatization, and is amenable to compounds that are difficult to analyze by GC-MS and LC-MS. For example, GC-MS often requires derivatization of compounds, such as sugars and amines. LC-MS, on the other hand, generally requires sample preparation, chromatographic separation, specific experimental and ionization conditions, instrumentation and operator skill [2]. These make it difficult to standardize MS analysis. In contrast, NMR does not require elaborate sample preparation and fractionation, is highly reproducible, and is able to provide both qualitative and quantitative information on chemically diverse compounds [3, 4]. The standardization of the NMR protocol will further improve the usefulness of NMR as a tool for the profiling of natural products extracts. Because NMR is able to detect compounds only down to 0.1% level, it is not suitable for the detection of trace components. NMR is less sensitive than MS, which can detect compounds down to parts per million (ppm) levels. Because of the distinct advantages of each method, NMR and MS are considered as complementary techniques.

NMR is a quantitative spectroscopic tool because the intensity of the peaks is directly proportional to the number of nuclei. With improvements in electronics and the use of higher magnetic field strengths, the sensitivity and resolving power of NMR has improved. However, the lack of standardized protocols has limited its quantitative application and many consider NMR mainly as a qualitative method, mainly for chemical structure determination and molecular dynamics [5].

The use of NMR as a quantitative method has been expanding, giving rise to the term "quantitative NMR" (qNMR). The pharmaceutical industry, which has stringent requirements of analysis, has been turning to the use of qNMR in early drug development to address the need for rapid, selective, and accurate analysis without requiring expensive and tedious chromatographic methods. It is also worth noting that qNMR meets the stringent regulatory standards of the pharmaceutical industry, including the International Conference on Harmonization. qNMR has been applied mainly to 1H nuclei although 19F and 31P NMR have also been used where appropriate because of their 100% isotopic abundance [6]. The main advantages of qNMR are its accuracy, reproducibility, and flexibility with respect to the nature of the analyte, the only requirement being the presence of protons and carbon, and its ability to simultaneously quantify multiple analytes, especially when validated using external calibration. Quantitative 1H NMR (qHNMR) has been shown to have an accuracy and precision of ±1% and an uncertainty of measurement of less than 0.1%. This makes it suitable as a metrological technique for the certification of purity of organic compounds [7].

There are two general approaches to the use of NMR for profiling or metabolomics studies. In the first approach, only the spectral patterns (chemical shifts and intensities) are recorded and are used to compare and group samples. In this approach, compounds are not initially identified. Because statistical tools, such as principal components analysis (PCA) are used, this is sometimes called a chemometric approach. In the second approach, particular compounds which are known to be present in the extract are identified and quantified using a reference spectral library. This approach is referred to as quantitative or targeted metabolomics [8]. These approaches, however, are not mutually exclusive and will likely converge in the future with improved statistical tools and bigger NMR spectral databases.

Because of the large amount of data that are produced, statistical methods, known as chemometrics, are applied to reduce the number of variables. Chemometrics is a family of statistical techniques that are applied to large sets of chemical data, such as NMR chemical shift peaks, with the objective of gaining insights into the characteristics of the samples through the use of graphical representation [9]. Because chemometrics is able to process large amounts of data, it is an ideal tool for NMR which produces a lot of data (chemical shifts). This can be used to find patterns of groupings and correlations among natural product samples which can be used for quality control and standardization [10]. Since chemometrics started to be applied to NMR around the year 2000, progress has been very rapid. Chemometrics has been used to classify whole plant samples based on their NMR profiles according to species, origin, processing treatment, age, and various quality parameters [11].

#### **2. 1H and 13C NMR as profiling methods**

In a talk given during the William Draper Harkins Lecture, University of Chicago in 1991, Alexander Pines mentioned that his organic chemistry colleagues at Berkeley consider two vital instruments in a research laboratory: a balance and an NMR spectrometer. His view is not surprising as decades of improvement in both instrumentation and techniques had rendered the NMR spectrometer as a tool of choice in characterizing molecules, from the structures of natural products and synthetic organic compounds to biomolecules and organometallic complexes. NMR spectroscopy takes advantage of the interaction between nuclei that are acting as tiny magnets and an external magnetic field and this provides a powerful means of probing the chemical bonding and environment of the nucleus. These phenomena are key to the applicability of 1H and 13C NMR to natural products.

#### **2.1. 1H NMR spectroscopy**

NMR and mass spectrometry (MS) are the principal methods of metabolomics, the branch of '-omics' that deals with small molecules. The Metabolomics Society describes metabolomics as: "the comprehensive characterization of the small molecule metabolites in biological systems" [1]. NMR has a number of characteristics that meet the requirements of metabolomics: it is accurate, quantitative, comprehensive, unbiased, and is able to provide information that can be used to determine molecular structure. The review will discuss these aspects in detail.

Although MS techniques, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), are most commonly used in metabolomics, NMR still enjoys a number of key advantages. In particular, NMR is nondestructive, unbiased, quantitative, does not require separation or derivatization, and is amenable to compounds that are difficult to analyze by GC-MS and LC-MS. For example, GC-MS often requires derivatization of compounds, such as sugars and amines. LC-MS, on the other hand, generally requires sample preparation, chromatographic separation, specific experimental and ionization conditions, instrumentation and operator skill [2]. These make it difficult to standardize MS analysis. In contrast, NMR does not require elaborate sample preparation and fractionation, is highly reproducible, and is able to provide both qualitative and quantitative information on chemically diverse compounds [3, 4]. The standardization of the NMR protocol will further improve the usefulness of NMR as a tool for the profiling of natural products extracts. Because NMR is able to detect compounds only down to 0.1% level, it is not suitable for the detection of trace components. NMR is less sensitive than MS, which can detect compounds down to parts per million (ppm) levels. Because of the distinct advantages of each

NMR is a quantitative spectroscopic tool because the intensity of the peaks is directly proportional to the number of nuclei. With improvements in electronics and the use of higher magnetic field strengths, the sensitivity and resolving power of NMR has improved. However, the lack of standardized protocols has limited its quantitative application and many consider NMR mainly as a qualitative method, mainly for chemical structure determination and

The use of NMR as a quantitative method has been expanding, giving rise to the term "quantitative NMR" (qNMR). The pharmaceutical industry, which has stringent requirements of analysis, has been turning to the use of qNMR in early drug development to address the need for rapid, selective, and accurate analysis without requiring expensive and tedious chromatographic methods. It is also worth noting that qNMR meets the stringent regulatory standards of the pharmaceutical industry, including the International Conference on Harmonization. qNMR has been applied mainly to 1H nuclei although 19F and 31P NMR have also been used where appropriate because of their 100% isotopic abundance [6]. The main advantages of qNMR are its accuracy, reproducibility, and flexibility with respect to the nature of the analyte, the only requirement being the presence of protons and carbon, and its ability to simultaneously quantify multiple analytes, especially when validated using external calibration. Quantitative 1H NMR (qHNMR) has been shown to have an accuracy and precision of ±1%

method, NMR and MS are considered as complementary techniques.

**1.1. NMR and MS**

82 Spectroscopic Analyses - Developments and Applications

molecular dynamics [5].

Hydrogen is present in almost every organic molecule, and its major isotope, 1H, has an abundance of 98.985%. The 1H nucleus reports a frequency specific to its immediate vicinity in an NMR spectrum. This frequency is extremely sensitive to the electronic environment thus giving each 1H nucleus in an organic compound a type of identification number, called the NMR chemical shift. Magnetic nuclei, such as 1H, also interact with each other. In solution or liquid-state NMR spectroscopy, these interactions, called couplings, are observed as "splitting" of lines in an NMR spectrum. The magnitude of these couplings not only depends on the number and type of bonds separating the interacting pair of 1H nuclei but also on the spatial orientation between the nuclei. Both NMR chemical shifts and coupling constants provide immense information regarding structure and environment. Hence, NMR spectroscopy has become a powerful tool for the determination of organic structure.

These NMR interactions (chemical shifts and coupling constants), although very sensitive, are quite weak such that improvements in their detection have been one of the primary goals of developments in NMR instrumentation. Such limitations are no longer severe. The use of pulses and data processing by Fourier transformation, first introduced by Ernst and Anderson [12] and the availability of high-field superconducting magnets have allowed for efficient signal averaging such that nowadays, with an 11 T magnet (500 MHz), a 1H NMR spectrum can be obtained even from very dilute solutions (micromolar concentration).

Pulse Fourier transform NMR spectroscopy, as in other spectroscopic methods, involves transitions between energy levels. However, unlike other spectroscopic methods, the transition probability in an NMR excitation is the same regardless of chemical environment. NMR spectroscopy does not need to consider oscillator strengths or extinction coefficients, which are important for infrared and UV-visible spectroscopy, respectively. The intensity of an NMR signal is determined solely by the excitation pulse, strength of the external magnetic field, and temperature. The magnetic field strength and temperature determine the Boltzmann population difference between the two energy levels while the excitation pulse dictates the extent of the transition. Since only one pulse is often used to excite all of the 1H nuclei in a sample, the extent of transitions is the same for all. Furthermore, the NMR chemical shift, which reflects the differences in resonance frequencies of inequivalent 1H nuclei, is very small: the differences are in parts per million (ppm). Hence, the Boltzmann distribution for the two spin states is essentially the same for every 1H in a molecule. Indeed, as early as 1963, the area under each peak in a 1H NMR spectrum has been shown to correspond proportionally to the number of hydrogen atoms sharing the same environment in a given compound [13]. This quantitative aspect applies not only to pure substances but also to mixtures. In fact, during the same year, a successful quantitative analysis by 1H NMR spectroscopy of a mixture of aspirin, phenacetin, and caffeine was demonstrated [14].

#### **2.2. 13C NMR spectroscopy**

13C also has a spin of ½ and is therefore likewise NMR active. However, because the 13C isotope occurs at only 1.108%, it is difficult to observe. (The major carbon isotope, 12C, is not NMR-active.) David Grant and coworkers published a series of papers on 13C NMR spectroscopy that spanned two decades [15, 16]. In the first paper of this series, inherent difficulties in observing 13C NMR spectra were addressed by proton decoupling and sample spinning. Since carbon atoms are frequently attached to hydrogen atoms in organic compounds, 13C-1H coupling is present and leads to splitting of 13C resonances. Proton decoupling removes this interaction, consolidating multiple 13C peaks into a single taller peak. Moreover, additional enhancement of 13C signals is observed when the 1H spin populations are perturbed, similar to the effect observed by Overhauser with electron spins [17]. Taking advantage of both the nuclear Overhauser effect (NOE) and the increased signal due to the collapse of multiple peaks, measurement of 13C NMR spectra became routine and easy to interpret. Being in the proximity of more than one pair of electrons, 13C nuclei offer a much wider range of chemical shifts than 1H (200 ppm for 13C versus 10 ppm for 1H). In addition, since the probability that a 13C nucleus is attached to another 13C nucleus is very small (about 0.0001), 13C-13C couplings are usually not observed thereby providing a much simpler 13C NMR spectrum.

NMR chemical shift. Magnetic nuclei, such as 1H, also interact with each other. In solution or liquid-state NMR spectroscopy, these interactions, called couplings, are observed as "splitting" of lines in an NMR spectrum. The magnitude of these couplings not only depends on the number and type of bonds separating the interacting pair of 1H nuclei but also on the spatial orientation between the nuclei. Both NMR chemical shifts and coupling constants provide immense information regarding structure and environment. Hence, NMR spectroscopy has

These NMR interactions (chemical shifts and coupling constants), although very sensitive, are quite weak such that improvements in their detection have been one of the primary goals of developments in NMR instrumentation. Such limitations are no longer severe. The use of pulses and data processing by Fourier transformation, first introduced by Ernst and Anderson [12] and the availability of high-field superconducting magnets have allowed for efficient signal averaging such that nowadays, with an 11 T magnet (500 MHz), a 1H NMR spectrum can

Pulse Fourier transform NMR spectroscopy, as in other spectroscopic methods, involves transitions between energy levels. However, unlike other spectroscopic methods, the transition probability in an NMR excitation is the same regardless of chemical environment. NMR spectroscopy does not need to consider oscillator strengths or extinction coefficients, which are important for infrared and UV-visible spectroscopy, respectively. The intensity of an NMR signal is determined solely by the excitation pulse, strength of the external magnetic field, and temperature. The magnetic field strength and temperature determine the Boltzmann population difference between the two energy levels while the excitation pulse dictates the extent of the transition. Since only one pulse is often used to excite all of the 1H nuclei in a sample, the extent of transitions is the same for all. Furthermore, the NMR chemical shift, which reflects the differences in resonance frequencies of inequivalent 1H nuclei, is very small: the differences are in parts per million (ppm). Hence, the Boltzmann distribution for the two spin states is essentially the same for every 1H in a molecule. Indeed, as early as 1963, the area under each peak in a 1H NMR spectrum has been shown to correspond proportionally to the number of hydrogen atoms sharing the same environment in a given compound [13]. This quantitative aspect applies not only to pure substances but also to mixtures. In fact, during the same year, a successful quantitative analysis by 1H NMR spectros-

become a powerful tool for the determination of organic structure.

84 Spectroscopic Analyses - Developments and Applications

be obtained even from very dilute solutions (micromolar concentration).

copy of a mixture of aspirin, phenacetin, and caffeine was demonstrated [14].

13C also has a spin of ½ and is therefore likewise NMR active. However, because the 13C isotope occurs at only 1.108%, it is difficult to observe. (The major carbon isotope, 12C, is not NMR-active.) David Grant and coworkers published a series of papers on 13C NMR spectroscopy that spanned two decades [15, 16]. In the first paper of this series, inherent difficulties in observing 13C NMR spectra were addressed by proton decoupling and sample spinning. Since carbon atoms are frequently attached to hydrogen atoms in organic compounds, 13C-1H coupling is present and leads to splitting of 13C resonances. Proton decoupling removes this interaction, consolidating multiple 13C peaks into a single taller peak.

**2.2. 13C NMR spectroscopy**

Using 13C NMR spectroscopy as a powerful analytical tool can be easily appreciated by considering the three isomers of a simple hydrocarbon C5 H12 (see **Figure 1**). n-Pentane (CH3 CH2 CH2 CH2 CH3 ), produces three peaks with a 1:2:2 intensity ratio, 2-methylbutane ((CH3 ) 2 CHCH2 CH3 ) displays four peaks with a 1:1:2:1 intensity ratio, and neopentane ((CH3 )4 C) gives two peaks of 4:1 intensity ratio. For the above reasons, a qualitative and quantitative analysis that is nondestructive and requires no separation is possible with 13C NMR spectroscopy [18]. All that one needs is a library of 13C NMR spectra of all possible components, a good spectral prediction software, and an efficient algorithm that can do the search and construct a simulated spectrum that matches the observed spectrum. All of these requirements are already available today. A similar treatment has been shown to be feasible in determining the acyl profile in various vegetable oils [19] and in characterizing the various sesquiterpenes in essential oils from juniper, rosemary, cedarwood, and ginger [20].

**Figure 1.** 13C NMR spectra of (a) n-pentane, (b) 2-methylbutane, and (c) neopentane.

The promise of a wealth of information that NMR spectroscopy offers, however, comes also with challenges. Since the frequencies observed depend on the magnetic field strength, the peaks' shapes and widths are sensitive to the homogeneity of the magnetic field throughout the sample. Experimentally, corrections to field homogeneity are done through a process called shimming, which involves adding small magnetic field gradients. Shimming used to be an art and both symmetry and narrowness of an NMR peak depended on the expertise of the NMR operator. Fortunately, with new superconducting magnets and automated shimming, 13C NMR spectra can now be made reproducible and comparable regardless of who operates the spectrometer. However, there are still numerous factors that are independent of the NMR operator which can affect the appearance of an NMR spectrum.

#### **2.3. NMR chemical shifts and coupling constants**

Since the frequencies (in hertz) observed for each NMR-active nucleus are dependent on the field strength, chemical shifts are reported in dimensionless units of parts per million (ppm), which then becomes independent of the magnetic field strength. Interactions between nuclei, on the other hand, are independent of field strength, so these are recorded in units of frequency, hertz. Since the ppm equivalent of a hertz is determined by the strength of the magnetic field, splittings will appear narrower in a high-field magnet than in a low-field magnet. When the coupling interactions are of the same magnitude as the chemical shift differences, the coupling pattern is complex [21]. A hypothetical example for 1H NMR is shown in **Figure 2**, where the coupling constant is equal to the chemical shift difference in a spectrometer operating with a 1H frequency of 100 MHz. As the strength of the magnetic field increases, chemical shift differences (in hertz) also increase, which can dramatically change the appearance of the spectrum. In this particular example, the spectrum only begins to appear simpler with a spectrometer operating at 1 GHz, in which the chemical shift difference is now 10 times bigger than the coupling constant; this is called a first-order spectrum. Thus, 1H spectra taken at different magnetic field strengths appear different. On the other hand, 13C spectra appear similar at different magnetic field strengths. This is because 13C-13C coupling is not observed due to low natural abundance, 13C-1H couplings, although present, are always several orders of magnitude lower than the frequency difference between these two nuclei, and proton-decoupled 13C NMR spectra are singlets. Therefore, although 13C presents detection challenges due to its lower frequency and low natural abundance, 13C has the advantage over 1H with regard to simplicity of NMR spectra.

Absolute frequencies for NMR transitions are seldom used since these numbers are dependent on the strength of the external magnetic field. Chemical shift differences are instead reported in ppm, which is the ratio of the absolute frequency with respect to the frequency of a reference compound, such as tetramethylsilane (TMS). Alternatively, the solvent can be utilized as internal reference. Due to the sensitivity of the NMR chemical shift, intermolecular effects are also frequently observed [22]. Since solvents are known to induce shifts, it is important that when comparing different spectra, the same solvent should be used. Since 13C has a much wider chemical shift range, the effect of solvent on chemical shift is smaller for 13C (2/200) than that of 1H (0.7/10). Furthermore, since carbon atoms, unlike hydrogen atoms, reside on the interior of the molecule, 13C is generally shielded from environmental effects, such as intermolecular interactions and solvent effects. This is one reason why 13C NMR chemical shifts are nearly exclusively dependent only on its covalent bonding interactions [23]. The greater susceptibility of 1H NMR chemical shifts to solvent effects makes 13C NMR spectroscopy a better alternative in profiling natural products. Solvent effects on both 1H and 13C NMR chemical shifts are expected to be dominated by van der Waals interactions with the solvent. These interactions are largely nonspecific thus an approximation that the solvent simply causes a constant offset on all resonances may be valid. Using an internal reference can therefore easily remove effects of the medium on the observed chemical shifts. Attention, however, is still required for sites that can participate in electrostatic interactions and hydrogen bonding. 13C in carbonyl groups is one example [24].

The promise of a wealth of information that NMR spectroscopy offers, however, comes also with challenges. Since the frequencies observed depend on the magnetic field strength, the peaks' shapes and widths are sensitive to the homogeneity of the magnetic field throughout the sample. Experimentally, corrections to field homogeneity are done through a process called shimming, which involves adding small magnetic field gradients. Shimming used to be an art and both symmetry and narrowness of an NMR peak depended on the expertise of the NMR operator. Fortunately, with new superconducting magnets and automated shimming, 13C NMR spectra can now be made reproducible and comparable regardless of who operates the spectrometer. However, there are still numerous factors that are independent of the NMR

Since the frequencies (in hertz) observed for each NMR-active nucleus are dependent on the field strength, chemical shifts are reported in dimensionless units of parts per million (ppm), which then becomes independent of the magnetic field strength. Interactions between nuclei, on the other hand, are independent of field strength, so these are recorded in units of frequency, hertz. Since the ppm equivalent of a hertz is determined by the strength of the magnetic field, splittings will appear narrower in a high-field magnet than in a low-field magnet. When the coupling interactions are of the same magnitude as the chemical shift differences, the coupling pattern is complex [21]. A hypothetical example for 1H NMR is shown in **Figure 2**, where the coupling constant is equal to the chemical shift difference in a spectrometer operating with a 1H frequency of 100 MHz. As the strength of the magnetic field increases, chemical shift differences (in hertz) also increase, which can dramatically change the appearance of the spectrum. In this particular example, the spectrum only begins to appear simpler with a spectrometer operating at 1 GHz, in which the chemical shift difference is now 10 times bigger than the coupling constant; this is called a first-order spectrum. Thus, 1H spectra taken at different magnetic field strengths appear different. On the other hand, 13C spectra appear similar at different magnetic field strengths. This is because 13C-13C coupling is not observed due to low natural abundance, 13C-1H couplings, although present, are always several orders of magnitude lower than the frequency difference between these two nuclei, and proton-decoupled 13C NMR spectra are singlets. Therefore, although 13C presents detection challenges due to its lower frequency and low natural abundance, 13C has the advantage over 1H with regard to simplicity of NMR spectra. Absolute frequencies for NMR transitions are seldom used since these numbers are dependent on the strength of the external magnetic field. Chemical shift differences are instead reported in ppm, which is the ratio of the absolute frequency with respect to the frequency of a reference compound, such as tetramethylsilane (TMS). Alternatively, the solvent can be utilized as internal reference. Due to the sensitivity of the NMR chemical shift, intermolecular effects are also frequently observed [22]. Since solvents are known to induce shifts, it is important that when comparing different spectra, the same solvent should be used. Since 13C has a much wider chemical shift range, the effect of solvent on chemical shift is smaller for 13C (2/200) than that of 1H (0.7/10). Furthermore, since carbon atoms, unlike hydrogen atoms, reside on the interior of the molecule, 13C is generally shielded from environmental effects, such as intermolecular interactions and

operator which can affect the appearance of an NMR spectrum.

**2.3. NMR chemical shifts and coupling constants**

86 Spectroscopic Analyses - Developments and Applications

Temperature can also affect observed chemical shifts through changes in the density of the sample as well as changes in the internal motions of the molecule [25]. For a fair comparison of library and sample spectra, it is important that spectra are taken at the same temperature.

Lastly, a quantitative 13C NMR spectrum requires uniform excitation of all 13C nuclei. The wider chemical shift range and lower frequency for 13C necessitate excitation pulses with much higher power with a pulse that is less than 15 μs long so that the entire chemical shift

**Figure 2.** 1H NMR spectra of strongly coupled nuclei at various magnetic field strengths.

range is uniformly irradiated [26]. Furthermore, proton decoupling is also regularly used to collapse multiple 13C peaks, but this can lead to NOEs which enhance 13C nuclei that are directly bound to protons, making 13C NMR no longer uniform for carbon nuclei with different numbers of attached protons. The inverse-gated 13C NMR experiment can be used to overcome these problems. This involves turning the proton decoupler on only during acquisition and providing adequate time for all the 13C nuclei to relax [27]. 13C nuclei are most often relaxed by a nearby 1H nucleus. Thus, the needed relaxation time (equal to 5 × *T*<sup>1</sup> ) can be quite long for compounds that contain quaternary carbons. These quaternary 13C nuclei may require minutes to relax and this dramatically increases the time required for NMR experiments. Because running such a lengthy 13C NMR experiment is not practical, it is normal practice to run proton-decoupled 13C NMR using standard conditions and to use the resulting spectra for pattern recognition but not for quantitation.

#### **2.4. Reproducibility of NMR spectra**

The use of a library of NMR spectra in the analysis of a mixture of natural products requires reproducibility of both chemical shift and peak intensity. Since samples of natural products are often dissolved in either dimethyl sulfoxide or methanol, confining both library and sample data to these two solvents can easily ameliorate the confounding effects of the solvent on the observed chemical shifts. Modern NMR spectrometers are normally equipped with temperature control so the measurements can be made at a given temperature, which also avoids the temperature dependence of NMR chemical shifts, thus eliminating this problem. The reproducibility of peak intensities, however, requires additional considerations.

The robustness of current NMR instrumentation is evident in successful indirect detection methods during which resonances from 1H nuclei bound to 12C are separated from those attached to 13C [28]. Indirect detection is possible only if the scans or transients are highly reproducible such that these can be added to extract the desired resonances and remove completely the unwanted signals. However, this robustness only entails the reproducibility of an NMR experiment from one transient to the next. It does not address the reproducibility of NMR experiments among different laboratories. Thus, there is a need to standardize both NMR acquisition conditions and processing parameters.

The intensity of an NMR peak depends on the duration of the pulse. Equalizing the m = +½ and m = −½ spin populations requires what is called in NMR spectroscopy as a 90° pulse. Peak intensities are at a maximum with this pulse. Since all nuclei in a sample are subject to the same pulse, it is not necessary that a 90° pulse is always employed. For an NMR spectrum to be quantitative, the relative, not the absolute, peak intensities are sufficient. However, the extent of the pulse determines how much time is required for relaxation between transients. For signal averaging to be effective, one still needs to make sure that the spins have reached equilibrium before applying the next pulse so as to avoid saturation, which leads to loss of signal [29]. When a 90° pulse is employed, the time between transients must be at least five times as long as the relaxation time. The time required between pulses can be reduced by using a smaller flip angle. For example, a 30° pulse requires a delay that is three times shorter. This reduces the peak intensity for each scan but reduces the delay time required between scans enabling the acquisition of more scans for the same amount of time. Another parameter that can affect the appearance of an NMR spectrum is acquisition time, which determines spectral resolution. What is directly acquired from an NMR experiment is a free induction decay (FID), which still needs to be processed to produce the frequency spectrum. During processing, apodization, zero-filling, and baseline and phase corrections are normally applied. All of these can significantly alter the integrated areas under the peaks of an NMR spectrum. Thus, a list of universal parameters for quantitative NMR has been established by national and international round robin tests [30] which includes temperature (300 K), pulse angle (30°), preacquisition delay (5 s), acquisition time (3.4 s), relaxation delay (7/3 of relaxation time), and line broadening (0.3 Hz). For processing, careful manual phase and baseline corrections are recommended since automated features of popular NMR processing software packages are unreliable. This validation has been performed with 1H NMR, but these can be applied to 13C. With 13C, relaxation times are appreciably longer so relaxation agents such as paramagnetic compounds have been used as in the earlier work on petroleum distillates [31].

#### **2.5. Sensitivity and dynamic range**

range is uniformly irradiated [26]. Furthermore, proton decoupling is also regularly used to collapse multiple 13C peaks, but this can lead to NOEs which enhance 13C nuclei that are directly bound to protons, making 13C NMR no longer uniform for carbon nuclei with different numbers of attached protons. The inverse-gated 13C NMR experiment can be used to overcome these problems. This involves turning the proton decoupler on only during acquisition and providing adequate time for all the 13C nuclei to relax [27]. 13C nuclei are most

quite long for compounds that contain quaternary carbons. These quaternary 13C nuclei may require minutes to relax and this dramatically increases the time required for NMR experiments. Because running such a lengthy 13C NMR experiment is not practical, it is normal practice to run proton-decoupled 13C NMR using standard conditions and to use the result-

The use of a library of NMR spectra in the analysis of a mixture of natural products requires reproducibility of both chemical shift and peak intensity. Since samples of natural products are often dissolved in either dimethyl sulfoxide or methanol, confining both library and sample data to these two solvents can easily ameliorate the confounding effects of the solvent on the observed chemical shifts. Modern NMR spectrometers are normally equipped with temperature control so the measurements can be made at a given temperature, which also avoids the temperature dependence of NMR chemical shifts, thus eliminating this problem. The repro-

The robustness of current NMR instrumentation is evident in successful indirect detection methods during which resonances from 1H nuclei bound to 12C are separated from those attached to 13C [28]. Indirect detection is possible only if the scans or transients are highly reproducible such that these can be added to extract the desired resonances and remove completely the unwanted signals. However, this robustness only entails the reproducibility of an NMR experiment from one transient to the next. It does not address the reproducibility of NMR experiments among different laboratories. Thus, there is a need to standardize both

The intensity of an NMR peak depends on the duration of the pulse. Equalizing the m = +½ and m = −½ spin populations requires what is called in NMR spectroscopy as a 90° pulse. Peak intensities are at a maximum with this pulse. Since all nuclei in a sample are subject to the same pulse, it is not necessary that a 90° pulse is always employed. For an NMR spectrum to be quantitative, the relative, not the absolute, peak intensities are sufficient. However, the extent of the pulse determines how much time is required for relaxation between transients. For signal averaging to be effective, one still needs to make sure that the spins have reached equilibrium before applying the next pulse so as to avoid saturation, which leads to loss of signal [29]. When a 90° pulse is employed, the time between transients must be at least five times as long as the relaxation time. The time required between pulses can be reduced by using a smaller flip angle. For example, a 30° pulse requires a delay that is three times shorter. This reduces the peak intensity for each scan but reduces the delay time required between scans enabling the acquisition of more scans for the same amount of time. Another

ducibility of peak intensities, however, requires additional considerations.

) can be

often relaxed by a nearby 1H nucleus. Thus, the needed relaxation time (equal to 5 × *T*<sup>1</sup>

ing spectra for pattern recognition but not for quantitation.

NMR acquisition conditions and processing parameters.

**2.4. Reproducibility of NMR spectra**

88 Spectroscopic Analyses - Developments and Applications

For the unbiased profiling of natural products extracts, one needs to consider the problems of sensitivity and dynamic range. A natural product extract typically contains major and minor components. Oftentimes, in order to detect minor components, it is necessary to employ separation techniques, such as successive fractionation and chromatography which have the effect of increasing sensitivity to minor constituents and improving dynamic range. However, this introduces bias.

Limits of detection and quantification are often given in terms of signal to noise ratios. The International Conference on Harmonization of Technical Requirements recommends a signal to noise ratio of 3 and 10 for the detection limit and quantification limit, respectively (ICH Expert Working Group, 1994). In practice, for error values less than 1%, a signal to noise ratio of 150 is recommended [30]. The signal-to-noise ratio (S/N) in NMR spectroscopy however depends not only on concentration but also on other factors [32]:

$$\frac{S}{N} \approx \frac{N \, \gamma \, ^{\lambda}\_{\overline{n}} B\_{\overline{\delta}}^{\lambda} T\_2 \sqrt{m} \overline{s}}{T} \tag{1}$$

In this equation, *N* is concentration, *γ<sup>n</sup>* is the magnetogyric ratio of the nucleus, *B*<sup>0</sup> is the strength of the external field, *T*<sup>2</sup> is the transverse relaxation time, *ns* is the number of transients, and *T* is temperature. Considering both magnetogyric ratio and natural abundance, one can therefore estimate that the detection limit for 13C will be orders of magnitude higher than that of 1H. Since the number of transients depends on how much time is available for data acquisition, one can improve S/N by simply taking more scans for 13C measurements. Since nuclei with longer relaxation times give sharper lines, these likewise yield higher S/N, making the detection limit dependent on the size of the molecule and the solvent. The above equation does not include factors dependent on the spectrometer's probe, receiver, and filters. In an analysis of diesel fuel, detection limits of 0.01 and 0.5 mol% are cited for 1H and 13C, respectively [33].

Another consideration is dynamic range. For 1H NMR, signals arising from the solvent, in particular water, can easily use up most of the higher bits in a spectrometer's digitizer thereby decreasing the precision of signals coming from the natural product constituents. This can be alleviated by suppressing solvent resonances, but this introduces the problem of reproducibility between runs and remains a problem for components which have signals near the solvent.

A quantitative comparison using three magnetic field strengths—300, 400, and 500 MHz showed that there was no difference in the sensitivity and that the standard protocol could differentiate plant samples which were spiked with 0.2 mg/mL of rutin (MW 610.5; 328 μM). This is due to the mild dependence of S/N on the field strength.

For the application of 1H NMR for pattern recognition, the use of the magnitude spectrum has been suggested [34]. The standard 1H NMR spectrum utilizes the phase-corrected real component of the Fourier transform of the free induction decay (FID), discarding the imaginary component. This yields the absorption spectrum which is useful for normal qualitative analysis due to its good peak resolution. However, this procedure sacrifices reproducibility. The use of the magnitude spectrum, which utilizes the absolute value of both the real and imaginary components of the FID improves the reproducibility of the spectra thereby improving its accuracy for pattern recognition. This method is applicable to one-dimensional 1H NMR.

Peak integrals in an NMR spectrum unfortunately are also sensitive to data processing. Apodization, zero-filling, phase and baseline corrections, and the integration itself can affect the signal-to-noise ratio of an NMR spectrum. Thus, the current limit in the sensitivity of NMR-based metabolomics is not due to magnetic field strength, but is due to the current data processing methodology which uses spectral binning (alternatively called bucketing) and PCA. The usual bin size for 1H NMR is 0.04 ppm. This divides a 10 ppm 1H spectrum into 250 bins, which effectively becomes the resolution of the method. A smaller bin size can be used if the variability in the chemical shift can be minimized. Another problem observed is the effect of different solvent (see below) to move the position of chemical shifts, which will make identification using database comparisons difficult [35].

#### **2.6. Effect of solvent**

Because plant samples contain a wide variety of compounds with corresponding differences in polarity, the solvent used for extraction and the NMR analysis is very important. The solvent system must balance the ability to perform a comprehensive extraction with solvent complexity and reproducibility. In particular, multi-component solvent systems are prone to variation, and if there is a wide difference in vapor pressures (boiling points), the solvent composition may change if care is not taken. Acetone and acetonitrile are effective solvents but their use is limited by their low boiling points. The use of methanol-D4 in combination with deuterated water (1:1) have been reported. By using these deuterated solvents, the extracts can be measured directly after extraction without need for evaporation and reconstitution. However, use of water will introduce a strong water peak in the 1H NMR spectrum that must be irradiated. This becomes a source of variability around the water peak across different operators and instruments. To avoid shifts due to differences of pH in 1H NMR measurements a buffer, such as KH<sup>2</sup> PO<sup>4</sup> , is used [36].

#### **3. Recent applications**

decreasing the precision of signals coming from the natural product constituents. This can be alleviated by suppressing solvent resonances, but this introduces the problem of reproducibility between runs and remains a problem for components which have signals near the solvent. A quantitative comparison using three magnetic field strengths—300, 400, and 500 MHz showed that there was no difference in the sensitivity and that the standard protocol could differentiate plant samples which were spiked with 0.2 mg/mL of rutin (MW 610.5; 328 μM).

For the application of 1H NMR for pattern recognition, the use of the magnitude spectrum has been suggested [34]. The standard 1H NMR spectrum utilizes the phase-corrected real component of the Fourier transform of the free induction decay (FID), discarding the imaginary component. This yields the absorption spectrum which is useful for normal qualitative analysis due to its good peak resolution. However, this procedure sacrifices reproducibility. The use of the magnitude spectrum, which utilizes the absolute value of both the real and imaginary components of the FID improves the reproducibility of the spectra thereby improving its accuracy for pattern recognition. This method is applicable

Peak integrals in an NMR spectrum unfortunately are also sensitive to data processing. Apodization, zero-filling, phase and baseline corrections, and the integration itself can affect the signal-to-noise ratio of an NMR spectrum. Thus, the current limit in the sensitivity of NMR-based metabolomics is not due to magnetic field strength, but is due to the current data processing methodology which uses spectral binning (alternatively called bucketing) and PCA. The usual bin size for 1H NMR is 0.04 ppm. This divides a 10 ppm 1H spectrum into 250 bins, which effectively becomes the resolution of the method. A smaller bin size can be used if the variability in the chemical shift can be minimized. Another problem observed is the effect of different solvent (see below) to move the position of chemical shifts, which will

Because plant samples contain a wide variety of compounds with corresponding differences in polarity, the solvent used for extraction and the NMR analysis is very important. The solvent system must balance the ability to perform a comprehensive extraction with solvent complexity and reproducibility. In particular, multi-component solvent systems are prone to variation, and if there is a wide difference in vapor pressures (boiling points), the solvent composition may change if care is not taken. Acetone and acetonitrile are effective solvents but

deuterated water (1:1) have been reported. By using these deuterated solvents, the extracts can be measured directly after extraction without need for evaporation and reconstitution. However, use of water will introduce a strong water peak in the 1H NMR spectrum that must be irradiated. This becomes a source of variability around the water peak across different operators and instruments. To avoid shifts due to differences of pH in 1H NMR measure-

in combination with

This is due to the mild dependence of S/N on the field strength.

make identification using database comparisons difficult [35].

their use is limited by their low boiling points. The use of methanol-D4

, is used [36].

PO<sup>4</sup>

to one-dimensional 1H NMR.

90 Spectroscopic Analyses - Developments and Applications

**2.6. Effect of solvent**

ments a buffer, such as KH<sup>2</sup>

NMR is capable of providing simultaneous access to both qualitative (chemical structure) and quantitative information. Unfortunately, NMR has been more generally associated with multidimensional qualitative NMR used in structural analysis and qNMR has been living under this shadow. Fan (1996) pointed out that comprehensive metabolite profiling of complex food products can be done using one- and two-dimensional NMR analysis [37]. However, it is in the use of NMR combined with chemometric methods that the extraordinary potential of both the qualitative and quantitative applications have been realized [38].

In view of its ability to be used as an exhaustive molecular fingerprinting technique, 1H NMR has been found to be a suitable method for the identification, quality control, and fraud detection of essential oils, a function normally reserved for GC-MS [39]. NMR fingerprinting involves obtaining 1H or 13C spectra of whole solvent extracts under standardized conditions and ignoring, at least initially, the assignment of peaks. Multivariate statistical methods, such as PCA, are used to compare spectra from the samples to identify clusters so that inferences can be drawn about the classification of individual plant samples. The identities of metabolites responsible for differences between groups can be investigated from loadings plots generated by PCA [40]. The following section will cover applications of 1H NMR in one- and twodimensions and 13C NMR together with the statistical tools.

#### **3.1. Metabolomic profiling using 1H NMR**

One-dimensional 1H NMR (1D HNMR) can be used in the untargeted and targeted mode. The earliest use of 1D HNMR for the profiling of complex extracts had the objective of monitoring the major components of exudates of plants, such as its root system. The relative increase or decrease of primary metabolites, such as lactate, ethanol, and certain amino acids, could be observed [41]. However, its application to natural product compounds is more challenging due to their more complex structures and lower concentrations. Because of its simplicity and speed, 1D HNMR in the untargeted mode can be used by itself or as a first-pass screening to obtain cluster and profile information using HCA and PCA [42]. The majority of HNMR studies combine 1D HNMR for PCA analysis with two-dimensional homonuclear (1H-1H) or heteronuclear (1H-13C) NMR methods for identification of natural product metabolites.

#### *3.1.1. One-dimensional 1H NMR*

This section discusses applications that make use of 1D HNMR alone. The number of such studies is limited because of the presence of overlapping signals and the need for high magnetic fields. 1D HNMR at 500 MHz was used to authenticate grapes for wine making by analyzing their skin and pulp at maturity. Spectral data were reduced by binning using 0.04 ppm bin size and normalized to generate 183 variables to describe each spectrum. Chemometric methods, in particular PCA and partial least squares (PLS), enabled the identification of compounds that contributed to differences between berries, due to the sugars (glucose, fructose, and sucrose), organic acids (tartaric, malic, citric, and succinic acids), and amino acids (proline, arginine, gamma-aminobutyric acid, valine, alanine, leucine, and isoleucine) [43].

A set of green teas selected from a Japanese tea contest were analyzed by 1D HNMR at 750 MHz to classify tea quality with respect to that judged by tea tasters and to propose a quality prediction model. PCA metabolomics profiling revealed a separation between the high- and the low-quality green teas. The taste marker compounds contributing to the discrimination of tea quality were identified from 1D HNMR as caffeine, theanine, epigallocatechin-3-gallate, epigallocatechin, epicatechin-3-gallate, and epicatechin [44].

The use of the magnitude spectrum showed good reproducibility in the analysis of 4 diverse natural product samples (12 tea extracts, 8 liquor samples, 9 hops extracts, and 25 cannabis extracts) using 1D HNMR at 500-MHz and various statistical tools [45].

#### *3.1.2. Two-dimensional 1H NMR*

Because of problems of signal overlaps in 1D HNMR spectra, two-dimensional NMR techniques are usually used to overcome these limitations. The 2D methods include 1H *J*-resolved NMR (2D JNMR), 1H-1H correlation spectroscopy (2D COSY) and total correlation spectroscopy (2D TOCSY), 1H-13C heteronuclear single quantum coherence (2D HSQC), and 1H-13C heteronuclear multiple bond coherence (2D HMBC).

1D and 2D NMR at 600 MHz together with chemometric analysis were used to differentiate the origin, purity, and processing methods of chamomile flowers which were obtained from three different countries. The extracts were dissolved in D<sup>2</sup> O phosphate buffer adjusted to pH 7.4. 1D NMR data were analyzed by PCA analysis to determine the groupings by pattern recognition and 2D COSY and 2D TOCSY pulse sequences were used to assign the resonances and identify constituents [46].

Several NMR-based metabolomic studies have been done on green tea (*Camellia sinensis*, L.). In one study, 191 green tea samples from different countries were analyzed using 1D HNMR and 2D NMR at 400 MHz to determine origin, quality, effects of climate and season, growth conditions, and even plucking position. The highest quality Chinese tea showed higher levels of theanine, gallic acid, caffeine, epigallocatechin gallate, and epicatechin gallate and lower levels of epigallocatechin when compared with other teas. These new markers were suggested to be useful for the authentication of tea [47]. In another study, the effects of climatic conditions (temperature, sun exposure, and precipitation) and plucking positions on the tea plant were investigated using 1D HNMR profiling combined with multivariate pattern recognition methods. Assignment of NMR signals was done using 2D TOCSY, 2D HMBC, and 2D HSQC. The variations in the composition of specific tea compounds were obtained [48, 49]. The sensitivity of the NMR method at 400 MHz was demonstrated in a study on three different varieties of green tea. 1D HNMR, 2D JNMR, and 2D COSY spectra were run and identification of constituents was done using MestRenova version 11.0.0. The following compounds were identified: theanine, alanine, threonine, succinic acid, aspartic acid, lactic acid, caffeine, and derivatives of epigallocatechin [50].

The same strategy was used for chemotaxonomic classification of 11 South American *Ilex* species. Data from 1D HNMR at 600 MHz were combined with PCA, partial least squarediscriminant analysis (PLS-DA), and hierarchical cluster analysis (HCA) to reveal four distinct groups. 1H signal overlaps were addressed using 2D JNMR and 2D HSQC. The combined use of 1D- and 2D-NMR and chemometric analysis enabled unambiguous chemotaxonomic discrimination of the *Ilex* species and varieties [51].

1D HNMR fingerprinting followed by 2D TOCSY and 2D HSQC methods were used to distinguish four Asian and four Korean ginseng products, as well as their commercial products. In this way, the major metabolites—glutamine, arginine, sucrose, malate, and myo-inositol were identified as chemical markers for quality assurance [52]. In a study on Indian ginseng, *Withania somnifera* (L.) Dun., 1D HNMR profiling was performed on the leaves, stems, and roots to obtain a profile of this plant. PCA and hierarchical cluster analysis (HCA) were performed to group samples which were collected from six different regions of India. 2D JNMR, 2D COSY, 2D HSQC, and 2D HMBC, were then used to identify specific metabolites. The ratio of two withanolides was found to be a key discriminating feature of *W. somnifera* leaf samples from different regions [53].

This NMR-based metabolomic strategy was applied to analyze seven spices used in traditional Mediterranean cuisine and to detect metabolic changes over different seasons. Both primary and secondary metabolites were identified and quantified. The major secondary metabolites identified were polyphenols, including flavonoids (apigenin, quercetin, and kaempferol derivatives) and phenylpropanoid derivatives (chlorogenic and rosmarinic acid). This study was performed using a 300 MHz NMR instrument [54].

The application of NMR-based metabolomics method in plant breeding has been reported. Using a 500 MHz instrument, the NMR-based metabolomics was applied to the identification of sugar beet (*Beta vulgaris* L.) genotypes which were susceptible to the *Cercospora* leaf diseases of sugar beet plants worldwide. This approach was able to successfully profile foliar metabolites without inoculation tests which would have required a significant amount of time and effort. In this study, field-grown leaves which had different levels of resistance were collected from 12 sugar beet genotypes at 4 growth time points. The aqueous extracts were studied using 1D HNMR, 2D COSY, 2D TOCSY, and 2D HSQC. Thirty metabolites were identified and annotated using the SpinAssign program from the PRIMe web service. PCA of the NMR data revealed clear differences among the growth stages, in terms of the content of sugar, glycine betaine, and choline [55].

#### **3.2. Metabolomic profiling using 13C NMR**

and sucrose), organic acids (tartaric, malic, citric, and succinic acids), and amino acids (proline, arginine, gamma-aminobutyric acid, valine, alanine, leucine, and isoleucine) [43].

A set of green teas selected from a Japanese tea contest were analyzed by 1D HNMR at 750 MHz to classify tea quality with respect to that judged by tea tasters and to propose a quality prediction model. PCA metabolomics profiling revealed a separation between the high- and the low-quality green teas. The taste marker compounds contributing to the discrimination of tea quality were identified from 1D HNMR as caffeine, theanine, epigallocate-

The use of the magnitude spectrum showed good reproducibility in the analysis of 4 diverse natural product samples (12 tea extracts, 8 liquor samples, 9 hops extracts, and 25 cannabis

Because of problems of signal overlaps in 1D HNMR spectra, two-dimensional NMR techniques are usually used to overcome these limitations. The 2D methods include 1H *J*-resolved NMR (2D JNMR), 1H-1H correlation spectroscopy (2D COSY) and total correlation spectroscopy (2D TOCSY), 1H-13C heteronuclear single quantum coherence (2D HSQC), and 1H-13C

1D and 2D NMR at 600 MHz together with chemometric analysis were used to differentiate the origin, purity, and processing methods of chamomile flowers which were obtained from

pH 7.4. 1D NMR data were analyzed by PCA analysis to determine the groupings by pattern recognition and 2D COSY and 2D TOCSY pulse sequences were used to assign the resonances

Several NMR-based metabolomic studies have been done on green tea (*Camellia sinensis*, L.). In one study, 191 green tea samples from different countries were analyzed using 1D HNMR and 2D NMR at 400 MHz to determine origin, quality, effects of climate and season, growth conditions, and even plucking position. The highest quality Chinese tea showed higher levels of theanine, gallic acid, caffeine, epigallocatechin gallate, and epicatechin gallate and lower levels of epigallocatechin when compared with other teas. These new markers were suggested to be useful for the authentication of tea [47]. In another study, the effects of climatic conditions (temperature, sun exposure, and precipitation) and plucking positions on the tea plant were investigated using 1D HNMR profiling combined with multivariate pattern recognition methods. Assignment of NMR signals was done using 2D TOCSY, 2D HMBC, and 2D HSQC. The variations in the composition of specific tea compounds were obtained [48, 49]. The sensitivity of the NMR method at 400 MHz was demonstrated in a study on three different varieties of green tea. 1D HNMR, 2D JNMR, and 2D COSY spectra were run and identification of constituents was done using MestRenova version 11.0.0. The following compounds were identified: theanine, alanine, threonine, succinic acid, aspartic acid, lactic acid, caffeine,

O phosphate buffer adjusted to

chin-3-gallate, epigallocatechin, epicatechin-3-gallate, and epicatechin [44].

extracts) using 1D HNMR at 500-MHz and various statistical tools [45].

heteronuclear multiple bond coherence (2D HMBC).

three different countries. The extracts were dissolved in D<sup>2</sup>

*3.1.2. Two-dimensional 1H NMR*

92 Spectroscopic Analyses - Developments and Applications

and identify constituents [46].

and derivatives of epigallocatechin [50].

Because of its lower sensitivity and longer acquisition time, 13C NMR is used less often than 1H NMR. However, 13C NMR spectra are simpler, have less severe problems with overlapping peaks, are more comparable across different magnetic field strengths, and are less susceptible to solvent effects. In addition, the singlet nature of 13C NMR signals makes it easier to determine the identity of individual compounds in a mixture.

13C NMR methodology was used to study the triacylglycerols of the oil extracted from the seeds of *Moringa oleifera*, Lam. It was able to simultaneously detect specific unsaturated acyl chains according to their positions on the glycerol backbone through carboxylic, olefinic, and methylene carbons [56]. However, at this time, its use was not specifically identified as a profiling method. Later, 13C NMR was applied to the fingerprinting of lipids for the authentication of marine and fish oils. In this work, 13C NMR was combined with chemometrics and database information and compared with relevant authentic samples [57]. 13C NMR in combination with multivariate data analysis have been used in the analysis of lipids from various fishes. In one application, this method was used to discriminate between farmed and wild Atlantic salmon (*Salmo salar*, L.), between samples from different geographical origins [58], and to detect mislabeling and adulteration [59].

13C NMR was used in a dereplication strategy for the identification of natural product compounds directly from plant extracts. The whole extract was first separated into fractions of simpler composition, which were then analyzed by 13C NMR. The 13C spectra of all the fractions were aligned and subjected to pattern recognition by HCA. This yielded correlations among 13C signals within each fraction which were visualized as chemical shift clusters, which were assigned to specific compounds in a 13C database. This strategy was applied to the analysis of 5 g of a bark extract from the African tree *Anogeissus leiocarpus* which resulted in the unambiguous identification of seven major compounds [60].

Chemical profiling and standardization of the methanol extract from the leaves of *Vitex negundo*, L. were carried out using 13C NMR followed by chemometric analysis. Because PCA analysis gave an explained variability of only 41% for PC1 and PC2, an alternative method, called k-means clustering, was employed. This was able to successfully differentiate samples that were deliberately allowed to degrade. The multivariate control chart, which is analogous to the analytical control chart method, classified samples whose quality exceeded the upper control limit (UCL). The plant samples were also analyzed by quantitative thin layer chromatography (qTLC) using agnuside as marker compound. Comparison of the univariate qTLC results with the multivariate control chart showed poor correspondence: some samples that gave high agnuside values exceeded the UCL while others that had low agnuside values were below the UCL. This means that a univariate analysis of a plant sample using a marker compound does not adequately represent the overall plant profile [61].

13C NMR is being used more often for dereplication of natural product extracts without fractionation. This approach is being enhanced by availability of 13C NMR databases and predictive software which list compounds that are most likely to be present in the extract. These results have been found to be comparable to those obtained using LC-MS and GC-MS, which require fractionation and sample preparation [62].

The combined use of high-resolution 1H and 13C NMR analysis has the potential to reveal more details that are not available using only one technique. This combined approach was employed to detect and quantify a wide range of triacylglycerols and their component fatty acids in marine cod liver oil supplements. The combination of 1H and 13C spectra permitted the detailed analysis of components, including sn-1 monoacylglycerols, sn-1,2- and sn-1,3-diacylglycerol adducts, and other minor components, such as trans-fatty acids, free glycerol and cholesterol, and added vitamins A and E and synthetic compounds, such as ethyl docosahexaenoate or eicosopentaenoate. The identity of each compound was confirmed using 2D COSY [63].

#### **4. Future prospects**

13C NMR methodology was used to study the triacylglycerols of the oil extracted from the seeds of *Moringa oleifera*, Lam. It was able to simultaneously detect specific unsaturated acyl chains according to their positions on the glycerol backbone through carboxylic, olefinic, and methylene carbons [56]. However, at this time, its use was not specifically identified as a profiling method. Later, 13C NMR was applied to the fingerprinting of lipids for the authentication of marine and fish oils. In this work, 13C NMR was combined with chemometrics and database information and compared with relevant authentic samples [57]. 13C NMR in combination with multivariate data analysis have been used in the analysis of lipids from various fishes. In one application, this method was used to discriminate between farmed and wild Atlantic salmon (*Salmo salar*, L.), between samples from different geographical origins

13C NMR was used in a dereplication strategy for the identification of natural product compounds directly from plant extracts. The whole extract was first separated into fractions of simpler composition, which were then analyzed by 13C NMR. The 13C spectra of all the fractions were aligned and subjected to pattern recognition by HCA. This yielded correlations among 13C signals within each fraction which were visualized as chemical shift clusters, which were assigned to specific compounds in a 13C database. This strategy was applied to the analysis of 5 g of a bark extract from the African tree *Anogeissus leiocarpus* which resulted

Chemical profiling and standardization of the methanol extract from the leaves of *Vitex negundo*, L. were carried out using 13C NMR followed by chemometric analysis. Because PCA analysis gave an explained variability of only 41% for PC1 and PC2, an alternative method, called k-means clustering, was employed. This was able to successfully differentiate samples that were deliberately allowed to degrade. The multivariate control chart, which is analogous to the analytical control chart method, classified samples whose quality exceeded the upper control limit (UCL). The plant samples were also analyzed by quantitative thin layer chromatography (qTLC) using agnuside as marker compound. Comparison of the univariate qTLC results with the multivariate control chart showed poor correspondence: some samples that gave high agnuside values exceeded the UCL while others that had low agnuside values were below the UCL. This means that a univariate analysis of a plant sample using a marker com-

13C NMR is being used more often for dereplication of natural product extracts without fractionation. This approach is being enhanced by availability of 13C NMR databases and predictive software which list compounds that are most likely to be present in the extract. These results have been found to be comparable to those obtained using LC-MS and GC-MS, which

The combined use of high-resolution 1H and 13C NMR analysis has the potential to reveal more details that are not available using only one technique. This combined approach was employed to detect and quantify a wide range of triacylglycerols and their component fatty acids in marine cod liver oil supplements. The combination of 1H and 13C spectra permitted the detailed analysis of components, including sn-1 monoacylglycerols, sn-1,2- and sn-1,3-diacylglycerol adducts, and other minor components, such as trans-fatty acids, free

[58], and to detect mislabeling and adulteration [59].

94 Spectroscopic Analyses - Developments and Applications

in the unambiguous identification of seven major compounds [60].

pound does not adequately represent the overall plant profile [61].

require fractionation and sample preparation [62].

The use of 1H and 13C NMR for the profiling of natural products extracts is a rapidly growing branch of metabolomics. It will further accelerate with the increasing use of NMR in quality management, the growth of NMR databases, the development of portable and benchtop NMR instrumentation, and advances in the use of statistical analysis. Despite its considerable potential, the routine application of this method is limited by the lack of expertise to run sophisticated NMR experiments and the lack of computational tools for NMR spectral deconvolution, in particular of 1H spectra [64].

#### **4.1. NMR in quality management**

NMR has been used for the monitoring and quality management of foods, beverages, cosmetics, and pharmaceuticals. The same can be done for the profiling of natural products. In order to ensure reproducibility and reliability and to minimize experimental artifacts, the entire process—from sample collection and storage, extraction, NMR measurement and data processing, and statistical analysis—should be optimized and standardized [65, 66]. The NMR solvent is of particular importance because of its influence on the chemical shift positions of protons in phenolic compounds [67] and other solvent effects. This problem is more severe for 1H as compared with 13C NMR.

It has been claimed that periodic calibration can deliver accuracy as high as 99.9% and precision as good as 0.59%, and if calibration is performed with each study, the accuracy and precision can reach 100 and 0.35%, respectively [68]. The various experimental parameters are listed below:


#### **4.2. NMR databases in natural products**

The usefulness of NMR databases is premised on the reproducibility of the NMR experiment—starting with sample preparation, NMR acquisition, and processing—across different laboratories. It is important to avoid conditions that alter the position of chemical shifts, which will make identification using database comparisons difficult. Open-access and user-contributed 1H and 13C NMR spectral databases have a high potential as a useful tool for natural products researchers provided that sample preparation, instrumentation, and acquisition parameters are standardized. For sample preparation, only selected NMR solvents should be used. Magnetic field strength is more critical for 1H than 13C NMR. Acquisition and processing parameters should be standardized. As of 2015, 1829 1H NMR and 1383 13C NMR spectra have been available in open-access chemical databases. To further promote participation by researchers, the entire process, from data acquisition, conversion of vendor-specific raw data files, and data deposition have to be simplified and standardized [69].

#### **4.3. Portable and benchtop NMR instrumentation**

NMR is usually considered to be an expensive analytical technique which is used for research purposes only. However, for NMR to become more useful for the natural products industry where many of the companies are small to medium in size, more affordable instrumentation is needed. There have been numerous announcements regarding the development of portable and benchtop NMR instruments with full spectrum 1H and 13C NMR capability using microcoils with small portable magnets of up to 2 T (approximately 85 MHz 1H) [70]. Although these are limited in capability and reproducibility compared with a full laboratory NMR instrument, they can be used in the field or production site where cryogenic liquids and stable power are not available. Because there is a demand for such instrumentation for other purposes, such as forensic investigation, detection of explosives, and medical diagnostics, their development is certain to accelerate. This will expand the use of NMR for the profiling of natural products.

#### **4.4. Advances in the use of statistical analysis**

Although the use of NMR in the analysis of biological extracts was already being done in the 1980s, it was the application of statistical methods that enabled researchers to make use the large amount of NMR data to find patterns and correlations. The first step usually involves the simplification of large NMR data sets to find relationships, groupings, or dependencies using PCA. Second, the groups can be classified with or without a training set which has known information or characteristics against which other sample sets are compared. Linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA) are used for this purpose. For quantitative analysis of constituents, in particular for strongly overlapping peaks, principal component regression (PCR) or PLS regression can be used [71]. Although these statistical techniques are now commonly used, new ones continue to be developed and reported.

One of the most exciting areas of development is the use of statistical methods to correlate NMR signals with biological activity. Since the NMR signals can be related to specific compounds, this in effect allows one to correlate specific compounds with biological activity. Although it has to be emphasized that correlation is not proof of biological activity, this strategy nevertheless allows one to shortcut the process of discovering bioactive compounds in a complex natural product mixture. This also allows one to detect multiple active compounds.

#### **5. Conclusions**

products researchers provided that sample preparation, instrumentation, and acquisition parameters are standardized. For sample preparation, only selected NMR solvents should be used. Magnetic field strength is more critical for 1H than 13C NMR. Acquisition and processing parameters should be standardized. As of 2015, 1829 1H NMR and 1383 13C NMR spectra have been available in open-access chemical databases. To further promote participation by researchers, the entire process, from data acquisition, conversion of vendor-specific raw data

NMR is usually considered to be an expensive analytical technique which is used for research purposes only. However, for NMR to become more useful for the natural products industry where many of the companies are small to medium in size, more affordable instrumentation is needed. There have been numerous announcements regarding the development of portable and benchtop NMR instruments with full spectrum 1H and 13C NMR capability using microcoils with small portable magnets of up to 2 T (approximately 85 MHz 1H) [70]. Although these are limited in capability and reproducibility compared with a full laboratory NMR instrument, they can be used in the field or production site where cryogenic liquids and stable power are not available. Because there is a demand for such instrumentation for other purposes, such as forensic investigation, detection of explosives, and medical diagnostics, their development is certain to accelerate. This will expand the use of NMR for the profiling

Although the use of NMR in the analysis of biological extracts was already being done in the 1980s, it was the application of statistical methods that enabled researchers to make use the large amount of NMR data to find patterns and correlations. The first step usually involves the simplification of large NMR data sets to find relationships, groupings, or dependencies using PCA. Second, the groups can be classified with or without a training set which has known information or characteristics against which other sample sets are compared. Linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA) are used for this purpose. For quantitative analysis of constituents, in particular for strongly overlapping peaks, principal component regression (PCR) or PLS regression can be used [71]. Although these statistical techniques are now commonly used, new ones continue to be devel-

One of the most exciting areas of development is the use of statistical methods to correlate NMR signals with biological activity. Since the NMR signals can be related to specific compounds, this in effect allows one to correlate specific compounds with biological activity. Although it has to be emphasized that correlation is not proof of biological activity, this strategy nevertheless allows one to shortcut the process of discovering bioactive compounds in a complex natural product mixture. This also allows one to detect multiple active

files, and data deposition have to be simplified and standardized [69].

**4.3. Portable and benchtop NMR instrumentation**

96 Spectroscopic Analyses - Developments and Applications

**4.4. Advances in the use of statistical analysis**

of natural products.

oped and reported.

compounds.

1H and 13C NMR are rapidly expanding it role from its traditional use mainly as a qualitative spectroscopic technique for the determination of chemical structure to a quantitative tool for the metabolomic study of natural product extracts, whether for quality control of phytomedicine products, analysis of the metabolome for plant profiling, identification of constituents as plant markers, or for plant biotechnology. A major enabler for the use of NMR for metabolomic studies is the application of various statistical techniques which are able to find patterns and correlations in the large NMR data sets. The continued expansion of the use of NMR for the metabolomic profiling of natural product extracts will likely depend on the further development of statistical methods and the availability of NMR databases for both 1H and 13C nuclei. It is likely that more compounds will be identified as techniques are improved.

An NMR spectrum is quantitative. An understanding of the physical principles of NMR provides the theoretical basis for its use as a quantitative tool. NMR spectroscopy does not require a standard for each component since the intensity of each signal is directly proportional to the number of nuclei being observed regardless of environment. NMR spectroscopy also offers detailed information regarding molecular structure. Using NMR spectroscopy as a tool in the profiling of natural product extracts therefore not only provides accurate and precise composition, but also structural evidence for each of the components. Since the NMR signal dependence on various factors is already well known, resonance positions and intensities are highly reproducible. These are important characteristics which give NMR a unique advantage over other analytical methods.

#### **Abbreviations**



#### **Author details**

Fabian M. Dayrit<sup>1</sup> \* and Angel C. de Dios2

\*Address all correspondence to: fdayrit@ateneo.edu

1 Department of Chemistry, Ateneo de Manila University, Quezon City, Philippines

2 Department of Chemistry, Georgetown University, Washington, DC, USA

#### **References**


[8] Wishart DS. Quantitative metabolomics using NMR. Trends in Analytical Chemistry. 2008;**27**(3):228-237

PCA Principal components analysis

qHNMR Quantitative proton (1H) NMR

PLS-DA Partial least squares-discriminant analysis

qTLC Quantitative thin layer chromatography

\* and Angel C. de Dios2

1 Department of Chemistry, Ateneo de Manila University, Quezon City, Philippines

[1] Metabolomics Society. Metabolomics. [Cited 14-09-2014]. Available from: http://www.

[2] Commisso M, Strazzer P, Toffal K, Stocchero M, Guzzo F. Untargeted metabolomics: An emerging approach to determine the composition of herbal products. Computational and Structural Biotechnology Journal. 2013;**4**(5):e201301007. Available from: http://dx.doi.

[3] Wishart DS. Quantitative metabolomics using NMR. Trends in Analytical Chemistry.

[4] Markley JL, Bruschweiler R, Edison AS, Eghbalnia HR, Powers R, Raftery D, Wishart DS. The future of NMR-based metabolomics. Current Opinion in Biotechnology.

[5] Malz F, Jancke H. Validation of quantitative NMR. Journal of Pharmaceutical and

[6] Webster GK, Kumar S. Expanding the analytical toolbox: Pharmaceutical application of

[7] Simmler C, Kulakowski D, Lankin DC, McAlpine JB, Chen SN, Pauli GF. Holistic analysis enhances the description of metabolic complexity in dietary natural products.

quantitative NMR. Analytical Chemistry. 2014;**86**:11474-11480

2 Department of Chemistry, Georgetown University, Washington, DC, USA

\*Address all correspondence to: fdayrit@ateneo.edu

PLS Partial least squares

98 Spectroscopic Analyses - Developments and Applications

qNMR Quantitative NMR

metabolomicssociety.org/

org/10.5936/csbj.201301007

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**Author details**

Fabian M. Dayrit<sup>1</sup>

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[33] Hsieh PY, Widegren JA, Slifka AJ, Hagen AJ, Rorrer RA. Direct measurement of trace polycyclic aromatic hydrocarbons in diesel fuel with 1H and 13C NMR spectroscopy:

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**Provisional chapter**

#### **Application of Mass Spectroscopy in Pharmaceutical and Biomedical Analysis and Biomedical Analysis**

**Application of Mass Spectroscopy in Pharmaceutical** 

DOI: 10.5772/intechopen.70655

Uttam Singh Baghel, Atamjit Singh, Deeksha Singh and Manish Sinha Deeksha Singh and Manish Sinha Additional information is available at the end of the chapter

Uttam Singh Baghel, Atamjit Singh,

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70655

#### **Abstract**

Mass spectrometry (MS) is a powerful analytical tool with many applications in pharmaceutical and biomedical field. The increase in sensitivity and resolution of the instrument has opened new dimensions in analysis of pharmaceuticals and complex metabolites of biological systems. Compared with other techniques, mass spectroscopy is only the technique for molecular weight determination, through which we can predict the molecular formula. It is based on the conversion of the sample into ionized state, with or without fragmentation which are then identified by their mass-to-charge ratios (m/e). Mass spectroscopy provides rich elemental information, which is an important asset to interpret complex mixture components. Thus, it is an important tool for structure elucidation of unknown compounds. Mass spectroscopy also helps in quantitative elemental analysis, that is, the intensity of a mass spectra signal is directly proportional to the percentage of corresponding element. It is also a noninvasive tool that permits *in vivo* studies in humans. Recent research has looked into the possible applications of mass spectrometers in biomedical field. It is also used as a sensitive detector for chromatographic techniques like LC–MS, GC–MS and LC/MS/MS. These recent hyphenated technological developments of the technique have significantly improved its applicability in pharmaceutical and biomedical analyses.

**Keywords:** mass spectrometry, pharmaceutical, biomedical, phytochemical, structure elucidation

#### **1. Introduction**

Mass spectrometry (MS) is an advanced technique for determining the molecular weight of a compound. The first mass spectrometer was developed in 1912 by J.J. Thompson. The instrument

has now a wide range of applications in pharmaceutical (drug discovery, pharmacokinetics, drug metabolism), clinical (neonatal screening, hemoglobin analysis, drug testing), environmental (water quality, food contamination, pollutant determination), geological (oil composition, hydrocarbon fraction determination in petroleum industry), metallurgy (determination of rare earth metals and metals at ppq (parts per quadrillion)), sports (dope test of drugs in athletes), forensic (poison and drug metabolite determination) and biotechnology (proteins, peptide analysis) like fields.

#### **2. Principle**

The mass spectroscopy is based on the positive ion generation. For its most popular model, the electron impact ionization with magnetic sector analyzer, the sample under investigation is converted into vapor phase and bombarded with electrons having energy sufficient to knock out one electron from it (>10 eV) to produce a positively charged ion called molecular ion or parent ion which is denoted by M+ .

Positively charged molecule M<sup>+</sup> is often unstable, and with increase in energy (10–70 eV) according to bond strength, they break into fragments called fragment or daughter ion which is denoted by M+1. Ions formed are separated in analyzer under the influence of electric and magnetic field and are recorded by the detector to give rise a mass spectrum (**Figure 1**).

**Figure 1.** Ionization of molecule by electron bombardment.

#### **3. Components of mass spectrometer**

Mass spectrometer mainly consists of following components:

**1.** Inlet system

has now a wide range of applications in pharmaceutical (drug discovery, pharmacokinetics, drug metabolism), clinical (neonatal screening, hemoglobin analysis, drug testing), environmental (water quality, food contamination, pollutant determination), geological (oil composition, hydrocarbon fraction determination in petroleum industry), metallurgy (determination of rare earth metals and metals at ppq (parts per quadrillion)), sports (dope test of drugs in athletes), forensic (poison and drug metabolite determination) and biotechnology (proteins, peptide anal-

The mass spectroscopy is based on the positive ion generation. For its most popular model, the electron impact ionization with magnetic sector analyzer, the sample under investigation is converted into vapor phase and bombarded with electrons having energy sufficient to knock out one electron from it (>10 eV) to produce a positively charged ion called molecular

according to bond strength, they break into fragments called fragment or daughter ion which is denoted by M+1. Ions formed are separated in analyzer under the influence of electric and magnetic field and are recorded by the detector to give rise a mass spectrum

is often unstable, and with increase in energy (10–70 eV)

.

ysis) like fields.

**2. Principle**

(**Figure 1**).

ion or parent ion which is denoted by M+

106 Spectroscopic Analyses - Developments and Applications

**Figure 1.** Ionization of molecule by electron bombardment.

Positively charged molecule M<sup>+</sup>


The inlet system transfers the gaseous form of sample into the vacuum of the ion generation chamber of mass spectrometer. In the ion generation chamber, neutral sample molecules are ionized and then accelerated into the mass analyzer tube. The mass analyzer tube is the most important part on which a range of the mass spectrometer depends. This segment separates generated ions, either in space or in time, according to their mass-to-charge ratio (m/e). Once the ions are separated, they are collected and detected in ion collector chamber. Then, the signal is transferred to a data collection system for data investigation. The high vacuum is applied between the ion generation chamber, analyzer tube and ion collector. The vacuum system is maintaining the low pressure which minimizes the chances of ion-molecule reaction, scattering and neutralization of the ions (**Figure 2**).

**Figure 2.** Components of mass spectrometer.

### **4. Applications**

#### **4.1. Phytochemical analysis**

Mass spectroscopy is widely employed in phytochemical analysis due to its capability to identify and measure metabolites having very low molecular weight at very low concentration ranges below nanogram per milliliter (ng/mL). Therefore, it is considered as trace analysis methodology. A variety of analyte separation techniques like capillary electrophoresis, gas chromatography and high-performance liquid chromatography are united with mass spectroscopy for simultaneous separation and determination of analytes called CE-MS, GC–MS and HPLC-MS, respectively. Mass spectrometers like quadrupole or quadrupole-time-of-flight (Q-TOF) are frequently employed in combination along with gas chromatographic system. Several phytoconstituents are volatile and thermolabile, and they can be analyzed by electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). ESI is commonly employed in HPLC-MS and CE-MS. Fourier transform ion cyclotron resonance (FT-ICR), orbitrap and TOF are emerged as high-performance mass analyzers that are able to screen metabolites with fraction of seconds due to their high resolution. Combination of TOF with one (Q-TOF) or two quadrupoles (Qq-TOF) is emerged as hybrid mass spectrometers that are able to cover unlimited mass range with high scan rates up to 10<sup>6</sup> u/s and high resolving power. Analytes having high molecular weight and temperature sensitive can be efficiently analyzed by HPLC coupled with atmospheric pressure ionization-mass spectrometer (API-MS) [1]. Some of the recent research articles depicting the application of mass spectrometry for the phytochemical analysis are listed in **Table 1**.


**Table 1.** Applications of mass spectroscopy in phytochemical analysis.

#### **4.2. Structure elucidation**

united with mass spectroscopy for simultaneous separation and determination of analytes called CE-MS, GC–MS and HPLC-MS, respectively. Mass spectrometers like quadrupole or quadrupole-time-of-flight (Q-TOF) are frequently employed in combination along with gas chromatographic system. Several phytoconstituents are volatile and thermolabile, and they can be analyzed by electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). ESI is commonly employed in HPLC-MS and CE-MS. Fourier transform ion cyclotron resonance (FT-ICR), orbitrap and TOF are emerged as high-performance mass analyzers that are able to screen metabolites with fraction of seconds due to their high resolution. Combination of TOF with one (Q-TOF) or two quadrupoles (Qq-TOF) is emerged as hybrid mass spectrometers that are able to cover unlimited mass range with

weight and temperature sensitive can be efficiently analyzed by HPLC coupled with atmospheric pressure ionization-mass spectrometer (API-MS) [1]. Some of the recent research articles depicting the application of mass spectrometry for the phytochemical analysis are

u/s and high resolving power. Analytes having high molecular

**Sample source Analytes Reference**

sesquiterpene

2-propynoic acid

2-propynoic acid

*Radix astragali* Calycosin, calycosin-7-O-β-D-glycoside,

one flavonoid

geraniol

Fatty acids, sucrose, diterpenes,

octadecane, 9-octadecenoic acid,

like daidzein, genistein, glycitein

ɑ-Pinene, myrcene, limonene, citrinellal,

(R)-(+)-ç-Valerolactone, 5,14-di (*N*-butyl) octadecane, 9-octadecenoic acid,

Prenylated isoflavonoids and isoflavonoids

formononetin, formononetin-7-O-glycoside

and glycosides; hydroxybenzoic acids and

Prenylated flavonoids [11]

Glycyrrhizic acid, liquorice saponin G2, liquiritin, licuraside, ononin, glycycoumarin

Vitamin E, gentisic acid, 1-pentadecyne [4]

[2]

[3]

[5]

[6]

[7]

[8]

[9]

[10]

high scan rates up to 10<sup>6</sup>

1 HPLC-ESI-MS *Leontopodium* species

108 Spectroscopic Analyses - Developments and Applications

2 GC × GC–MS Essential oil of *Pelargonium graveolens*

3 GC–MS Methanolic fruit extract of

5 GC–MS Ethanolic extract of *Azolla* 

6 UHPLC-ESI-MS *Rhizopus microsporus* var. *oryzae*

8 HPLC–MS/MS *Glycyrrhiza uralensis* Fisch. extract

10 UHPLC–MS *Licorice* root extract in 70%

acetate

**Table 1.** Applications of mass spectroscopy in phytochemical analysis.

*microphylla*

(Asteraceae)

*Momordica charantia*

challenged soya bean seedlings

ethanol, ethanol and ethyl

4 GC–MS Extracts of *Aerva lanata* (R)-(+)-ç-Valerolactone, 5,14-di (*N*-butyl)-

9 LC/MS/MS Dried plums Hydroxycinnamics, including acids, esters

listed in **Table 1**.

**S. no. Analytical technique**

7 HPLC-ESI-MS/ MS

Mass spectroscopy has major use in structure elucidation of compounds. Mass spectrum is produced in the form of bar graph which is interpreted by using the following peaks.


$$m^\* = \frac{\left(m\_2^\*\right)^2}{\left(m\_1^\*\right)^2}$$

Here, *m*\* is the mass of metastable ion observed in mass spectrum.

There are some rules which are employed in interpretation of mass spectra in structure elucidation process. These are:

	- **i.** If *m*/*e* value of molecular ion peak is odd number, then it may contain odd number of nitrogen atoms.
	- **ii.** If *m*/*e* value of molecular ion peak is even number, then it may or may not contain even number of nitrogen atoms.

**2.** *Hydrogen deficiency index* **(HDI)**: Number of pairs of hydrogen required to saturate the compound is called hydrogen deficiency index (HDI). Hydrogen deficiency index is also called unsaturation index which gives the information about the number of π-bonds and/ or rings present in a molecular structure.

#### *Steps for determination of hydrogen deficiency index*:

	- **A.** For group V elements (N, P, As, Sb, Bi): Addition of one hydrogen atom is required with each added element.
	- **B.** For group VI elements (O, S, Se, Te): There is no need of addition of any hydrogen atom in the formula.
	- **C.** For group VII elements (F, Cl, Br, I): The removal of one hydrogen atom is required with each added element.

*Interpretation of hydrogen deficiency index*:


We can understand this application by the following examples:

Example 1: Calculate the HDI of C2 H4 .

C2 H4 has two carbon atoms. Therefore, base molecular formula will be:

$$\begin{aligned} & \mathbf{-C\_nH\_{2n+2}}, \\ & \mathbf{-C\_7H\_{(2\times 2)\times 2}}, \\ & \mathbf{-C\_7H\_8}. \end{aligned}$$

Hydrogen atoms in predicted base molecular formula = 6.

Hydrogen atoms in actual molecular formula of compound = 4.

Difference in hydrogen atoms between two formulas (6–4) = 2 (which corresponds to one pair of hydrogen atom).

Hydrogen deficiency index is 1, because one pair of hydrogen atom is required to saturate the compound.

Example 2: Calculate the HDI of C<sup>6</sup> H6 .

C6 H6 has six carbon atoms. Therefore, base molecular formula will be:

=CnH2n+2.

**2.** *Hydrogen deficiency index* **(HDI)**: Number of pairs of hydrogen required to saturate the compound is called hydrogen deficiency index (HDI). Hydrogen deficiency index is also called unsaturation index which gives the information about the number of π-bonds and/

**1.** Make the correction in the predicted base formula with respect to the elements obtained from other spectral data, and the correction requires addition or removal of hydrogen at-

**A.** For group V elements (N, P, As, Sb, Bi): Addition of one hydrogen atom is required with

**B.** For group VI elements (O, S, Se, Te): There is no need of addition of any hydrogen atom

**C.** For group VII elements (F, Cl, Br, I): The removal of one hydrogen atom is required with

**2.** After specific needed corrections, compare molecular formula of unknown compound

**3.** Calculate the difference in hydrogen atoms between two formulas and corresponding

**1.** If hydrogen deficiency index is one, there must be one double bond or one ring present in

**2.** If hydrogen deficiency index is two, there must be triple bond or two double bonds, two

**3.** Similarly, benzene ring has hydrogen deficiency index four because it contains three dou-

**4.** Any substance with hydrogen deficiency index four or more possibly contains a benzenoid ring in it, and the compounds with hydrogen deficiency index less than four cannot con-

rings, or one double bond and one ring present in the structure.

We can understand this application by the following examples:

H4 .

has two carbon atoms. Therefore, base molecular formula will be:

or rings present in a molecular structure.

110 Spectroscopic Analyses - Developments and Applications

*Steps for determination of hydrogen deficiency index*:

with the formula of saturated hydrocarbon.

each added element.

each added element.

pairs of hydrogen atom.

the structure.

*Interpretation of hydrogen deficiency index*:

ble bonds and one ring in it.

Example 1: Calculate the HDI of C2

tain such type of ring.

C2 H4

=C2

=C2 H6 .

=CnH2n+2.

H(2 × 2)+2.

in the formula.

oms, which depends upon the type of element added.

=C<sup>6</sup> H(2 × 6)+2.

=C<sup>6</sup> H14.

Hydrogen atoms in predicted base molecular formula = 14.

Hydrogen atoms in actual molecular formula of compound = 6.

Difference in hydrogen atoms between two formulas (14–6) = 8 (which corresponds to four pairs of hydrogen atom).

Hydrogen deficiency index is 4, because four pairs of hydrogen atoms are required to saturate the compound.

Fragmentation pattern is also an important component of mass spectra from which qualitative analysis of compounds can be done, and it is also useful in elucidation of structural arrangement of compound. From Beynon table, one can predict the possible elemental arrangement or composition of particular mass and determine the molecular formula of compound. The following examples from the literature support the present application of mass spectroscopy.

The structure of flavonoid monoglycosides like genistein-7-O-glucoside, genistein-4′-Oglucoside, 2′-hydroxygenistein-7-O-glucoside and apigenin, isolated from shoot of lupin (*Lupinus luteus* L.), was elucidated by using LSI-MS and EI-MS with double-focusing reversed geometry between mass spectrometer [12].

The analysis of sulfated heparin-like glycosaminoglycan oligosaccharides was done with the help of tandem mass spectroscopy (MS/MS) using quadrupole ion trap mass spectrometer and quadrupole orthogonal acceleration time-of-flight mass spectrometer, and their fragmentation pattern was also studied. This study suggested the use of tandem mass instruments like Q-TOF and metal cations in mass spectroscopy of heparin-like glycosaminoglycan oligosaccharides [13].

A one-step complete analysis method was developed for galacto-oligosaccharide mixtures obtained in lactose transgalactosylation using β-galactosidase from *Aspergillus oryzae* based on ionmobility spectrometry-tandem mass spectrometry (IMS-MS/MS) with electrospray ionization [14].

The characterization of commercial prebiotic galacto-oligosaccharide mixture was done with linear ion-trap mass spectrometer coupled with high-performance anion-exchange chromatography (HPAEC) using electrospray ionization combination with 1 H NMR and 13C NMR [15].

The synthesis of a novel sequence of di- and tri-organotin (IV) compounds which contains germanium having the general formula R4−nSnLn along with characterization was performed by elemental analysis, FT-IR, multinuclear NMR (1 H,13C,119Sn) and mass spectrometry by double-focusing mass spectrometer [16].

The characterization of polyisobutylenes was done by various mass spectrometry techniques like tandem mass spectroscopy with MALDI-TOF and ESI-QIT. The primary structure was determined by multistage mass spectrometric analysis, the presence of specific functional groups (e.g., OH or OCH<sup>3</sup> ) was confirmed, and also differentiation between isomeric functional groups was done [17].

#### **4.3. Peptide and protein sequence/structure analysis**

Mass spectroscopy has an important application in analysis of sequence of amino acids in proteins and peptides, that is, analysis of structure of proteins and peptides, and this is employed increasingly. This can be performed by stepwise hydrolysis accompanied with chromatography. Peptides are converted into amino alcohols which are volatile in nature. These amino alcohols derivatized and analyzed in mass spectrometer which aids sequence analysis. However, sequencing of underivatized peptides as in fast atom bombardment mass spectrometry (FABMS) is also employed. New techniques like MALDI and tandem mass spectroscopy are also in trend [18, 19]. Various examples from the literature support the present application.

The peptide sequence was analyzed using combination of gas-phase ion/ion chemistry and tandem mass spectrometry. The quadrupole linear ion trap with electrospray ionization and chemical ionization was also utilized in the analysis to characterize the primary structure of intact proteins [20].

Similarly, RNA polymerase II (Pol II) transcription initiation complex structure was analyzed by cross-linking and mass spectroscopy. They employed linear ion trap quadrupole (LTQ) orbitrap spectrometer and recorded Fourier transform mass spectrometer (FTMS) spectra at 100,000 resolutions. The cross-linking/MS was used as an integrated structure analysis tool for large multi-protein complexes [21].

A new procedure was revealed which enabled selective sequencing and detection of serine-, threonine- and tyrosine-phosphopeptides at very low level of femto mole in protein digests with electrospray mass spectroscopy (ES-MS) using quadrupole mass spectrometer [22].

Another similar study revealed a method for determination of amino acid sequence of fractions of peptides from apolipoprotein B by tandem mass spectrometry. In this, triple quadrupole mass spectrometer along with LSI-MS was employed [23].

#### **4.4. Clinical studies**

Implementation of mass spectroscopy in clinical laboratory resulted in significant advancements. Sometimes greater degree of sensitivity is required when analyte quantity is too low and mass spectroscopy due to its higher sensitivity marks a valuable place in clinical analysis [24]. In any disease condition, the chemistry of body changes which results in the changes in products in body fluids and excretion products can be detected for the diagnosis purpose by chromatographic instrument like gas chromatography equipped with mass spectroscopy [18]. Matrixassisted laser desorption/ionization mass spectrometry (MALDI-MS) is now in trend that is used to directly analyze and image pharmaceutical compounds in intact tissue [25].

The synthesis of a novel sequence of di- and tri-organotin (IV) compounds which contains germanium having the general formula R4−nSnLn along with characterization was performed

The characterization of polyisobutylenes was done by various mass spectrometry techniques like tandem mass spectroscopy with MALDI-TOF and ESI-QIT. The primary structure was determined by multistage mass spectrometric analysis, the presence of specific functional

Mass spectroscopy has an important application in analysis of sequence of amino acids in proteins and peptides, that is, analysis of structure of proteins and peptides, and this is employed increasingly. This can be performed by stepwise hydrolysis accompanied with chromatography. Peptides are converted into amino alcohols which are volatile in nature. These amino alcohols derivatized and analyzed in mass spectrometer which aids sequence analysis. However, sequencing of underivatized peptides as in fast atom bombardment mass spectrometry (FABMS) is also employed. New techniques like MALDI and tandem mass spectroscopy are also in trend [18, 19]. Various examples from the literature support the pres-

The peptide sequence was analyzed using combination of gas-phase ion/ion chemistry and tandem mass spectrometry. The quadrupole linear ion trap with electrospray ionization and chemical ionization was also utilized in the analysis to characterize the primary structure of

Similarly, RNA polymerase II (Pol II) transcription initiation complex structure was analyzed by cross-linking and mass spectroscopy. They employed linear ion trap quadrupole (LTQ) orbitrap spectrometer and recorded Fourier transform mass spectrometer (FTMS) spectra at 100,000 resolutions. The cross-linking/MS was used as an integrated structure analysis tool for

A new procedure was revealed which enabled selective sequencing and detection of serine-, threonine- and tyrosine-phosphopeptides at very low level of femto mole in protein digests with electrospray mass spectroscopy (ES-MS) using quadrupole mass spectrometer [22].

Another similar study revealed a method for determination of amino acid sequence of fractions of peptides from apolipoprotein B by tandem mass spectrometry. In this, triple quadru-

Implementation of mass spectroscopy in clinical laboratory resulted in significant advancements. Sometimes greater degree of sensitivity is required when analyte quantity is too low and mass spectroscopy due to its higher sensitivity marks a valuable place in clinical analysis [24]. In

pole mass spectrometer along with LSI-MS was employed [23].

) was confirmed, and also differentiation between isomeric func-

H,13C,119Sn) and mass spectrometry by dou-

by elemental analysis, FT-IR, multinuclear NMR (1

**4.3. Peptide and protein sequence/structure analysis**

ble-focusing mass spectrometer [16].

112 Spectroscopic Analyses - Developments and Applications

groups (e.g., OH or OCH<sup>3</sup>

ent application.

intact proteins [20].

**4.4. Clinical studies**

large multi-protein complexes [21].

tional groups was done [17].

Organic acidurias are an inherited disorder of metabolism in man, and gas chromatography coupled with mass spectroscopy is used to define an organic aciduria involving isovaleric acid. This technique is used in diagnosis and characterization of inborn errors of organic acid metabolism [26]. A simplified method was developed for clinical diagnosis of organic aciduria with gas chromatography–mass spectrometry (GC–MS) using quadrupole mass spectrometer. The urine samples were analyzed from patients, and acids were identified like methylcitric acid, margaric acid and glutaric acid [27].

Matrix-assisted laser desorption/ionization imaging mass spectrometry is emerged as a potent instrument for the investigation of small molecules and proteins in biological systems by *in situ* analysis of tissue sections [28]. A new technique was developed for the identification of proteins on tissue using tryptic digestion followed by matrix-assisted laser desorption/ionization imaging mass spectrometry with tandem mass spectrometry analysis. They used MALDI-TOF for their study [29]. Likewise, the level of antitumor drug SCH 226374 was determined in mouse tumor tissue using MALDI-QqTOF mass spectrometer. In whole brain homogenates, the concentration of drug was determined at nanogram levels with high-performance liquid chromatography/tandem mass spectrometry using triple quadrupole mass spectrometer [25].

Matrix-assisted laser desorption ionization-Fourier transform ion cyclotron resonance (MALDI-FTICR) is also an efficient technique for imaging of drugs and metabolites in tissue. A method based on MALDI-FTICR for imaging of olanzapine in kidney and liver as well as imatinib in glioma was described [30].

There is dramatic amplification in interest and implementation of clinical mass spectrometry for testing of vitamin D. LC–MS/MS method enables to distinguish between vitamin D2 and vitamin D<sup>3</sup> and also provides information on the vitamin D epimeric form, both of which are not currently possible with existing immunoassays. Mass spectroscopy is the favored method for endocrine disorders analysis, for example, steroid analysis which requires technical competence, skill and experience for the needed improvement [24].

Mass spectroscopy can also be used for the investigation of bile acids in biological fluids. Bile has bile acids as the major constituents which are synthesized in liver and secreted in gall bladder or in intestine. Bile acids have many vital physiological functions like lipid absorption and cholesterol homeostasis. Under normal healthy condition, only small quantities of bile acids are found in peripheral circulation and urine, but in hepatobiliary and intestinal diseases it will get affected. This occurs due to disturbances in synthesis and pharmacokinetics in the body. Hence, the evaluation of bile acid can become useful for investigating the liver or intestinal functions along with the diagnosis of various diseases such as cholestasis, colon and liver cancer. The complex structure and low concentration of bile acids in biological fluids make their analysis technically difficult. For many years, GC–MS has been used but LC–MS has also been used for qualitative analysis of bile acids. A rapid, accurate, sensitive and reproducible method was developed using liquid chromatography–electrospray tandem mass spectrometry (LC–MS/MS) to investigate conjugated and total bile acids in samples of human bile and mixture of bile acid standards. The results coincide with the results obtained by the GC–MS technique. This method has important advantages over others because of the high specificity, sensitivity and selectivity of tandem mass spectrometry [31].

Mass spectroscopy has also application in clinical microbiology. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been freshly adapted for the recognition of whole microorganisms from their colonies on media or directly from cultures in blood and urine. This technique can precisely identify even those bacteria which are difficult by conventional methods and that day is not far away when this technology will complement the conventional microbiologic identification methods. In this technique, a portion of an isolated colony is loaded in the instrument and the comparison of spectrogram is done to a library by a proprietary algorithm to identify the organism. The ease of use, ability to run large numbers of isolates per batch, simplicity of setup, automation, rapid turnaround time and low reagent costs are the major advantages. By optimization, the cost of operation reduces to one-tenth that of conventional method with automated biochemical testing platforms. A Swiss study has done a comparison between MALDI-TOF MS system and conventional methods for the identification of 1371 routine bacteria and yeast isolates. MALDI-TOF MS provided identifications for 98.5% of the isolates, including 93.2% at the species level and 5.3% at the genus level. Of the species-level identifications, 95.1% matched conventional identifications. Important deficiencies in present MALDI-TOF MS platforms include misclassification such as of *Shigella* as *Escherichia coli* and *Streptococcus pneumoniae* as *Streptococcus mitis* and, additionally, poor performance with polymicrobial samples. In some cases, instruments have identified only one organism without indicating the presence of others. Despite the need for improvement, mass spectrometry will become popular in the near future with fast turnaround times, ease of use and potential operational cost savings [32].

#### **4.5. Pharmaceutical analysis**

Mass spectroscopy emerged as a powerful tool for various operations in pharmaceutical field mainly in drug development. New methods and instruments in mass spectroscopy are developed at a very high rate. Mass spectroscopy now becomes an irreplaceable tool in all types of drug discoveries due to its high sensitivity, speed, versatility and selectivity [33].

Mass spectroscopy is widely used for detection of impurities in samples. Likewise, the use of LC–MS for multidimensional evaluation of impurities during drug development is described. They used peptide drugs as an example and used ion trap mass spectrometer with electrospray ionization in their method [34]. Similarly, it can also be used for detecting the purity profile of active pharmaceutical ingredients (API), that are, MK-0969, an M3 antagonist; MK-0677, an oral-active growth hormone secretagogue and API-A, a cathepsin K inhibitor. The elucidation of impurity structure was made by utilization of LC–MS using quadrupole ion trap mass spectrometer equipped with an electrospray ionization or an atmospheric pressure chemical ionization (APCI) interface [35]. A protocol for qualitative and quantitative analysis of pharmaceutical compounds by MALDI-TOF mass spectrometry was described. Two drugs lopinavir and ritonavir were analyzed and described that HIV protease inhibitors can successfully be quantified in peripheral blood mononuclear cells using MALDI-TOF mass spectrometry [36].

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) emerged as a valuable tool in direct analysis of pharmaceutical formulations. MALDI-MSI can be used for direct analysis of homogeneity of the active drug compound throughout the excipients contained in tablets. A direct analysis in real-time ion source coupled with a time-of-flight mass spectrometer (DART-MS) method for screening of pharmaceutical formulations was developed. A library of compounds were analyzed using mass spectra data collected by DART-MS operated in switching mode at 20, 60 and 90 V settings. This library consisted of 17 commonly encountered drugs in parenteral pharmaceutical formulations, that is, surgical analgesic: fentanyl, hydromorphone and morphine; anesthetic: baclofen, bupivacaine, ketamine, midazolam, ropivacaine and succinylcholine; and a mixture of other drug classes: caffeine, clonidine, dexamethasone, ephedrine, heparin, methadone, oxytocin and phenylephrine [37].

#### **4.6. Forensic applications**

their analysis technically difficult. For many years, GC–MS has been used but LC–MS has also been used for qualitative analysis of bile acids. A rapid, accurate, sensitive and reproducible method was developed using liquid chromatography–electrospray tandem mass spectrometry (LC–MS/MS) to investigate conjugated and total bile acids in samples of human bile and mixture of bile acid standards. The results coincide with the results obtained by the GC–MS technique. This method has important advantages over others because of the high specificity,

Mass spectroscopy has also application in clinical microbiology. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been freshly adapted for the recognition of whole microorganisms from their colonies on media or directly from cultures in blood and urine. This technique can precisely identify even those bacteria which are difficult by conventional methods and that day is not far away when this technology will complement the conventional microbiologic identification methods. In this technique, a portion of an isolated colony is loaded in the instrument and the comparison of spectrogram is done to a library by a proprietary algorithm to identify the organism. The ease of use, ability to run large numbers of isolates per batch, simplicity of setup, automation, rapid turnaround time and low reagent costs are the major advantages. By optimization, the cost of operation reduces to one-tenth that of conventional method with automated biochemical testing platforms. A Swiss study has done a comparison between MALDI-TOF MS system and conventional methods for the identification of 1371 routine bacteria and yeast isolates. MALDI-TOF MS provided identifications for 98.5% of the isolates, including 93.2% at the species level and 5.3% at the genus level. Of the species-level identifications, 95.1% matched conventional identifications. Important deficiencies in present MALDI-TOF MS platforms include misclassification such as of *Shigella* as *Escherichia coli* and *Streptococcus pneumoniae* as *Streptococcus mitis* and, additionally, poor performance with polymicrobial samples. In some cases, instruments have identified only one organism without indicating the presence of others. Despite the need for improvement, mass spectrometry will become popular in the near future with

fast turnaround times, ease of use and potential operational cost savings [32].

drug discoveries due to its high sensitivity, speed, versatility and selectivity [33].

Mass spectroscopy emerged as a powerful tool for various operations in pharmaceutical field mainly in drug development. New methods and instruments in mass spectroscopy are developed at a very high rate. Mass spectroscopy now becomes an irreplaceable tool in all types of

Mass spectroscopy is widely used for detection of impurities in samples. Likewise, the use of LC–MS for multidimensional evaluation of impurities during drug development is described. They used peptide drugs as an example and used ion trap mass spectrometer with electrospray ionization in their method [34]. Similarly, it can also be used for detecting the purity profile of active pharmaceutical ingredients (API), that are, MK-0969, an M3 antagonist; MK-0677, an oral-active growth hormone secretagogue and API-A, a cathepsin K inhibitor. The elucidation of impurity structure was made by utilization of LC–MS using quadrupole ion trap mass spectrometer equipped with an electrospray ionization or an

**4.5. Pharmaceutical analysis**

sensitivity and selectivity of tandem mass spectrometry [31].

114 Spectroscopic Analyses - Developments and Applications

In forensic study, sample is in minute quantity; therefore, high sensitivity is required for analysis. Mass spectroscopy coupled with gas chromatography emerged as an indispensable tool in forensic field as well as LC–MS has also wide utility in forensic study. In forensic studies, the use of mass spectroscopy is becoming significant because of increase in the demand to investigate use of illegal drugs through analyzing body fluids and tissues. The sample for forensics in the case of drug abuse is mainly urine, hair and blood. Some of the drugs in routine analysis include opiates, cocaine, marihuana, lysergic acid diethylamide (LSD) and amphetamines. However, cases of murders or death due to poisoning and drug overdose are also the prime targets for these drug candidates' analysis [38].

A liquid chromatographic thermospray tandem mass spectrometric method was developed for quantitative analysis of some drugs having hypnotic, sedative and tranquilizing properties, that is, benzodiazepine, thioxanthene, butyrophenone, methadone and diphenylbutylpiperidine in whole blood. A triple-stage quadrupole mass spectrometer was used in the analysis at a very low detection limit of 0.05–0.5 ng/ml [39]. Similarly, a method was developed for determining common drugs of abuse in body fluids using liquid chromatography-atmospheric pressure chemical ionization mass spectrometry (LC-APCI-MS). Drugs analyzed were opiate agonists (morphine, morphine-3-glucuronide, morphine-6-glucuronide, 6-monoacetylmorphine, codeine, codeine-6-glucuronide, dihydrocodeine, dihydromorphine, buprenorphine, methadone, tramadol, and ibogaine), cocaine and its metabolites (benzoylecgonine and ecgonine methyl ester) and lysergic acid diethylamide in serum, blood, urine and other biological matrices by using single quadrupole instrument [40]. Determination of 11-nor-9-D-tetrahydrocannabinol-9-carboxylic acid (THC-COOH) in urine [41], alfentanil, fentanyl and its derivatives with other opioid drugs like morphine, buprenorphine, codeine, heroin, methadone, naloxone, naltrexone, tramadol, pentazocine, pethidine and others in hair [42] has been done by LC–MS and LC–MS/MS. Analysis of methadone and its metabolites with other illicit drugs like cocaine, phencyclidine, heroin and 6-acetylmorphine in hair by GC–MS is another successful application of mass spectroscopy [43].

#### **4.7. Metabolites analysis**

Determination of metabolic pathway and different metabolites of a drug or xenobiotics is very important to assess its different parameters of pharmacokinetics. Drug metabolic reactions can be divided into two parts: 1. Phase I or functionalization reactions and 2. Phase II or conjugation reactions. Both of these transformations involve changes in the molecular weight. These changes can be accurately measured by mass spectrometer.

In structural characterization by mass spectrometry, the exchange of labile hydrogen with deuterium (H/D exchange) in small organic molecules has been widely used and this occurs in solution containing functional groups which have labile hydrogen(s) such as -SH, −OH, −N(R)H, −NH2 and -COOH. During biotransformation, attachment of polar functional groups occurs, which causes changes in the number of exchangeable hydrogens. The number of exchangeable hydrogens in metabolites can give additional information to facilitate structural elucidation. This approach was applied to differentiate sulfoxide and sulfone metabolites from the isomeric mono- and di-hydroxylated metabolites, respectively. For example, the H/D exchange method was used for the drug metabolism studies of denopamine and promethazine in which N- or S-oxide was easily distinguished from the hydroxylated metabolites. A triple-stage quadrupole mass spectrometer equipped with electron impact (EI), FAB, APCI, ESI and thermospray (TSP) systems was utilized in the study [44].

Oxidation of a tertiary amino group to form an N-oxide is an important biotransformation pathway for many drugs and xenobiotics. N-oxide metabolites have the same elemental composition as those metabolites resulting from hydroxylation. Differentiation by mass spectrometry is a challenging task because these analytes exhibit the same m/z for their protonated or deprotonated molecules and their product ion mass spectra are usually very similar. Deoxygenation of N-oxides during atmospheric pressure chemical ionization represents potential way to differentiate N-oxides from hydroxylated metabolites. 6-OH desloratadine and N-oxides can be clearly differentiated as the major fragment ion from N-oxides was due to the loss of an oxygen atom while the prominent fragment ion from 6-OH desloratadine was due to loss of H2 O [45].

Stable isotope-labeled (<sup>2</sup> H, 13C, 15N, 18O, 34S and others) xenobiotics can facilitate metabolite detection and identification by mass spectrometry, especially when radiolabeled parent drug is not available [46–48]. Custom-designed isotopic clusters resulting from the mixture of natural and synthetically enriched isotopes can greatly facilitate the detection and identification of metabolites. For example, the detection and identification of ribavirin metabolites in rats was done with the aid of stable isotope labeled drug [49]. Similarly, a fast and sensitive liquid chromatography–tandem mass spectrometry method was developed for simultaneous determination of acetaminophen and its glucuronide and sulfate metabolites (APAP-GLU and APAP-SUL) in small plasma volumes. The tandem triple quadrupole mass spectrometer equipped with an electrospray ionization source was used in the study [50].

#### **5. Conclusion**

heroin, methadone, naloxone, naltrexone, tramadol, pentazocine, pethidine and others in hair [42] has been done by LC–MS and LC–MS/MS. Analysis of methadone and its metabolites with other illicit drugs like cocaine, phencyclidine, heroin and 6-acetylmorphine in hair by

Determination of metabolic pathway and different metabolites of a drug or xenobiotics is very important to assess its different parameters of pharmacokinetics. Drug metabolic reactions can be divided into two parts: 1. Phase I or functionalization reactions and 2. Phase II or conjugation reactions. Both of these transformations involve changes in the molecular weight.

In structural characterization by mass spectrometry, the exchange of labile hydrogen with deuterium (H/D exchange) in small organic molecules has been widely used and this occurs in solution containing functional groups which have labile hydrogen(s) such as -SH, −OH,

occurs, which causes changes in the number of exchangeable hydrogens. The number of exchangeable hydrogens in metabolites can give additional information to facilitate structural elucidation. This approach was applied to differentiate sulfoxide and sulfone metabolites from the isomeric mono- and di-hydroxylated metabolites, respectively. For example, the H/D exchange method was used for the drug metabolism studies of denopamine and promethazine in which N- or S-oxide was easily distinguished from the hydroxylated metabolites. A triple-stage quadrupole mass spectrometer equipped with electron impact (EI), FAB,

Oxidation of a tertiary amino group to form an N-oxide is an important biotransformation pathway for many drugs and xenobiotics. N-oxide metabolites have the same elemental composition as those metabolites resulting from hydroxylation. Differentiation by mass spectrometry is a challenging task because these analytes exhibit the same m/z for their protonated or deprotonated molecules and their product ion mass spectra are usually very similar. Deoxygenation of N-oxides during atmospheric pressure chemical ionization represents potential way to differentiate N-oxides from hydroxylated metabolites. 6-OH desloratadine and N-oxides can be clearly differentiated as the major fragment ion from N-oxides was due to the loss of an oxygen atom while the prominent fragment ion from 6-OH desloratadine was

detection and identification by mass spectrometry, especially when radiolabeled parent drug is not available [46–48]. Custom-designed isotopic clusters resulting from the mixture of natural and synthetically enriched isotopes can greatly facilitate the detection and identification of metabolites. For example, the detection and identification of ribavirin metabolites in rats was done with the aid of stable isotope labeled drug [49]. Similarly, a fast and sensitive liquid chromatography–tandem mass spectrometry method was developed for simultaneous determination of acetaminophen and its glucuronide and sulfate metabolites (APAP-GLU and APAP-SUL) in small plasma volumes. The tandem triple quadrupole mass spectrometer

equipped with an electrospray ionization source was used in the study [50].

and -COOH. During biotransformation, attachment of polar functional groups

H, 13C, 15N, 18O, 34S and others) xenobiotics can facilitate metabolite

GC–MS is another successful application of mass spectroscopy [43].

These changes can be accurately measured by mass spectrometer.

APCI, ESI and thermospray (TSP) systems was utilized in the study [44].

**4.7. Metabolites analysis**

116 Spectroscopic Analyses - Developments and Applications

−N(R)H, −NH2

due to loss of H2

Stable isotope-labeled (<sup>2</sup>

O [45].

Mass spectrometry is a very sensitive technique which can analyze even minute quantities of the molecule. This ability is utilized for various purposes like phytochemical, clinical, pharmaceutical and forensic analyses. This technique, not only elucidates the structure of the compounds, but also provides the information of molecular formula and the isotopic abundance of particular molecular formula. The availability of interphases made it possible to hyphenate this sophisticated technique with the different chromatographic techniques. This opened the new horizons of its applicability. The variations and permutation combinations of different ionization techniques with the different analyzers provide the analysis of diversified chemical entities at the femtogram level. The uniqueness of the technique of making fragments of the compound under investigation provides valuable structural information. This is helpful in the study of metabolite, peptide sequencing and macromolecules. This information is directly applicable in pharmaceutical and biomedical analysis. The development of double and triple quad techniques and their application have definitely uplifted the level of research and analysis in biomedical field, and this chapter gives the update on the topic.

#### **Author details**

Uttam Singh Baghel1 \*, Atamjit Singh2 , Deeksha Singh<sup>3</sup> and Manish Sinha<sup>2</sup>

\*Address all correspondence to: drusb1985@yahoo.com

1 Department of Pharmaceutical Chemistry and Analysis, Kota College of Pharmacy, Kota, India

2 Department of Pharmaceutical Chemistry, Laureate Institute of Pharmacy, Kangra, India

3 Primary Health Centre, Meenabadoda, Sawai Madhopur, India

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**Provisional chapter**

## **Metal Complexes of Pharmaceutical Substances**

**Metal Complexes of Pharmaceutical Substances**

DOI: 10.5772/65390

Tünde Jurca, Eleonora Marian, Laura Graţiela Vicaş, Mariana Eugenia Mureşan and Luminiţa Fritea Vicaş, Mariana Eugenia Mureşan and Luminiţa Fritea

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

Tünde Jurca, Eleonora Marian, Laura Graţiela

http://dx.doi.org/10.5772/65390

#### **Abstract**

Significant progresses have been made in the inorganic and organic chemistry up to the present concerning the synthesis, characterization, and application of the metal complexes of pharmaceutical substances. From the wide range of fields in which these coordination compounds find their application, many efforts were focused on the study of their importance in the biological processes. The coordination complexes of many pharmaceutical substances having different pharmacological effects e.g., pyrazinamide (PZA), nicotinamide (NAM), nicotinic acid (NIC), theophylline (TEO), captopril (CPL), tolbutamide (TBA), clonidine (CLN), guanfacine (GUAF), etc. with transition metals were synthesized and used in order to improve their pharmacological and pharmacotechnical properties and also for the drug analysis and control. Several techniques such as Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), X-ray spectroscopy, mass spectrometry, ultraviolet-visible (UV-Vis) spectrophotometry, electron paramagnetic resonance (EPR) spectroscopy, X-ray diffraction, elemental analysis, electrochemical methods, thermal methods, and scanning electron microscopy were used for the physicochemical characterization of the complex composition. A significant interest in the development of metal complex-based drugs with unique research and therapeutic and diagnostic opportunities is currently observed in the medicinal inorganic chemistry area.

**Keywords:** coordination complexes, transition metals, pharmaceutical substances, characterization methods, medicinal chemistry

#### **1. Introduction**

The coordination complexes have been studied since 1798 starting with the Tassaert studies, and till nowadays significant progresses have been made in the inorganic and organic

chemistry concerning the synthesis, characterization, and application of this large group of metal complexes. Concerning their structure, complexes were considered those compounds which do not fit within the classical theory of valence, meaning that the combination ratio of the elements exceeded their valences. This coordination theory elaborated by Alfred Werner indicated that the secondary valences of the elements are involved in the formation of the second-order combinations leading to the actual representation of the complexes formed by the first coordination sphere marked between brackets [central atom (ligand)] and the second coordination sphere (ionization sphere) coming outside of the brackets. The central atom can be any chemical element; meanwhile, the ligands can be ions, atoms, or neutral molecules, which can act as donors [1]. Neutral molecules or mono-/polyatomic anions which have one or more unshared electron pairs can act as mono-/polydentate ligands, the latter ones form complexes with cyclic structure known as chelates. A large number of pharmaceutical substances behave in vivo or in vitro conditions as ligands and chelating agents [2].

The number and the large structural variety of these complexes could not allow a rigorous systematization, even though some attempts by using certain classification criteria have been made such as the number of the central atoms, the charge of the complex ion, the type of ligands, and the coordination number. The coordination compounds were classified into Werner complexes, complexes with metal-metal bonds, metal carbonyls, clusters, complexes with macrocyclic ligands, molecular complexes (adducts, clathrates), chelates, and metalorganic complexes [1].

Natural metal complexes consisting of a central metal atom or ion (especially of the 3D transition metals) are involved in a plenty of biological mechanisms among which photosynthesis, transport of oxygen in blood, coordination of some metabolic processes, pathological states, enzymatic reactions, etc., even though the metallic ions represent only 3% of the body composition. Many biomolecules (amino acids, peptides, carboxylic acids, etc.) can form metal complexes with different stabilities having biomedical importance. Some drugs have a certain therapeutic effect (e.g., antimicrobial, diuretic, antidepressant) due to the complexation of the metallic ion (Cu2+, Zn2+, Fe2+, Mg2+, etc.) essential for a certain biochemical process. Metal complexes and products containing oligoelements are widely used in therapy due to their pharmacodynamic properties, bioavailability enhancement, and toxicity decrease of some metal ions [1].

The main aspects concerning the formation of complexes between pharmaceutical substances and various ligands are supported by several observations. According to the biological, physiological, and pathophysiological role of metal ions and ligands with pharmacological effect, metal ions present a great importance in carrying out the vital functions of living organisms acting as complexes or chelates and also in the analysis and control methods of drug substances by forming complexes that can be detected by spectral techniques. The use of ligands, chelating agents, or complexes in medicine and biology concerns several purposes such as antidotes in poisoning with metal ions or hydrocyanic acid or cyanides; introduction in the living organisms of some essential metal ions found to be deficient; depriving bacteria, viruses, or microbial enzyme systems of micronutrients essential for their work; or providing toxic metals for the pathogenic agents [2].

Many coordination complexes have been used in medicine containing metals such as platinum (cisplatin as anticancer chemotherapy drug), gold (as auranofin used for rheumatoid arthritis), technetium and rhenium (as radiopharmaceuticals used in imaging and radiotherapy), ruthenium (as anticancer drug), gadolinium, cobalt, lithium, bismuth, iron, calcium, lanthanum, gallium, tin, arsenic, rhodium, copper, zinc, aluminum, lutetium, vanadium, manganese, etc. [3, 4]. Only a reduced number of Co(III) complexes can be mentioned as having biochemical properties: vitamin B12, a natural organometallic complex of Co(III) with glyoxime. Other important examples are the series of Co(III) complexes containing N- and O-donor ligands based on a chelating Schiff base (imidazole, methylimidazole) with efficiency in the treatment of epithelial herpetic keratitis (the molecular target is supposed to be a virus protease containing histidine), adenovirus keratoconjunctivitis, and human immunodeficiency virus type 1. [Co(NH3 )6 ]Cl3 presents potent antiviral activity (against Sindbis virus). Some studies reported also the antibacterial activity of Co(II) and Co(III) complexes against *Bacillus subtilis*, *Enterobacter aeruginosa*, *Escherichia coli*, *Staphylococcus aureus*, etc. [3].

It was demonstrated that the antibacterial activity was increased upon chelation making the ligand a more powerful agent [5, 6]. The complexation of derivatives of sterically hindered *o*-diphenols and *o*-aminophenols with Cu(II), Co(II), Ni(II), and Zn(II) ions exhibited antioxidant, antiviral, and antimicrobial activity with low toxicity. Their synthesis, their separation as crystalline powders, the composition, and physicochemical characteristics of the complexes were also studied in Ref. [7].

Metal complexes have become an emerging tool in drug discovery being widely used as therapeutic compounds to treat several human diseases such as carcinomas, lymphomas, infection control, diabetes, anti-inflammatory, and neurological disorders [8, 9]. Due to various implications and applications of complexes (especially the chelates) in the biomedical field, many aspects are required to be studied such as their nature, their stability, the factors determining their formation and stability, and possibilities for preventing some reactions and for releasing a metal ion from a complex; all these are necessary in order to understand how they act in biological processes [2].

### **2. Physicochemical characterization of metal complexes of some pharmaceuticals**

The coordination complexes of a wide range of pharmaceutical substances [pyrazinamide (PZA), nicotinamide (NAM), nicotinic acid (NIC), tolbutamide (TBA), theophylline (TEO), captopril (CFL), clonidine (CLN), and guanfacine (GUAF)] with transition metals [Cu(II), Cd(II), Ni(II), Mn(II), Zn(II), and Co(II)] were synthesized and then characterized by using various techniques such as elemental analysis, spectral, electrochemical, thermal, and microscopic methods.

#### **2.1. Metal complexes of pyrazinamide**

chemistry concerning the synthesis, characterization, and application of this large group of metal complexes. Concerning their structure, complexes were considered those compounds which do not fit within the classical theory of valence, meaning that the combination ratio of the elements exceeded their valences. This coordination theory elaborated by Alfred Werner indicated that the secondary valences of the elements are involved in the formation of the second-order combinations leading to the actual representation of the complexes formed by the first coordination sphere marked between brackets [central atom (ligand)] and the second coordination sphere (ionization sphere) coming outside of the brackets. The central atom can be any chemical element; meanwhile, the ligands can be ions, atoms, or neutral molecules, which can act as donors [1]. Neutral molecules or mono-/polyatomic anions which have one or more unshared electron pairs can act as mono-/polydentate ligands, the latter ones form complexes with cyclic structure known as chelates. A large number of pharmaceutical substances

The number and the large structural variety of these complexes could not allow a rigorous systematization, even though some attempts by using certain classification criteria have been made such as the number of the central atoms, the charge of the complex ion, the type of ligands, and the coordination number. The coordination compounds were classified into Werner complexes, complexes with metal-metal bonds, metal carbonyls, clusters, complexes with macrocyclic ligands, molecular complexes (adducts, clathrates), chelates, and metal-

Natural metal complexes consisting of a central metal atom or ion (especially of the 3D transition metals) are involved in a plenty of biological mechanisms among which photosynthesis, transport of oxygen in blood, coordination of some metabolic processes, pathological states, enzymatic reactions, etc., even though the metallic ions represent only 3% of the body composition. Many biomolecules (amino acids, peptides, carboxylic acids, etc.) can form metal complexes with different stabilities having biomedical importance. Some drugs have a certain therapeutic effect (e.g., antimicrobial, diuretic, antidepressant) due to the complexation of the metallic ion (Cu2+, Zn2+, Fe2+, Mg2+, etc.) essential for a certain biochemical process. Metal complexes and products containing oligoelements are widely used in therapy due to their pharmacodynamic properties, bioavailability enhancement, and toxicity decrease of some

The main aspects concerning the formation of complexes between pharmaceutical substances and various ligands are supported by several observations. According to the biological, physiological, and pathophysiological role of metal ions and ligands with pharmacological effect, metal ions present a great importance in carrying out the vital functions of living organisms acting as complexes or chelates and also in the analysis and control methods of drug substances by forming complexes that can be detected by spectral techniques. The use of ligands, chelating agents, or complexes in medicine and biology concerns several purposes such as antidotes in poisoning with metal ions or hydrocyanic acid or cyanides; introduction in the living organisms of some essential metal ions found to be deficient; depriving bacteria, viruses, or microbial enzyme systems of micronutrients essential for their work; or providing

behave in vivo or in vitro conditions as ligands and chelating agents [2].

organic complexes [1].

124 Spectroscopic Analyses - Developments and Applications

metal ions [1].

toxic metals for the pathogenic agents [2].

Pyrazinamide (PZA) (pyrazine carboxamide) is a nicotinamide analogue used as a first-line drug to treat tuberculosis. The complexes of PZA with Cu(II) were assessed by different techniques such as elemental analysis, spectral methods [Fourier transform infrared spectroscopy (FTIR), FT-Raman spectrometry, mass spectrometry], and scanning electron microscopy (SEM) coupled with X-ray spectroscopy [energy-dispersive spectroscopy (EDS)] [1, 10–13].

The elemental analysis indicated that the combination ratio of metal:ligand (Me:L) is 1:2 for [Cu(PZA)<sup>2</sup> ]Cl<sup>2</sup> and [Cu(PZA)<sup>2</sup> ](C<sup>6</sup> H5 COO)<sup>2</sup> complexes. The mass spectra of the complex of PZA with Co(II) benzoate revealed the identity and the purity of PZA and of the complex fragments confirming its structure (**Figure 1**) [1, 10].

The FTIR spectra of the complexes highlighted that –C═O groups and nitrogen from the pyrazine ring are implied in the coordination process (**Table 1**) [11]. Comparing the Raman spectra of PZA and of [Cu(PZA)<sup>2</sup> ]Cl<sup>2</sup> , another analytical evidence for the complex formation is obtained. The appearance of new band characteristic for the Me:L bonds can be observed analyzing in detail the spectral region of low values of wave number (**Figure 2**) [1, 11, 12].

**Figure 1.** The mass spectra of PZA (A) and [Cu(PZA)<sup>2</sup> ](C<sup>6</sup> H5 COO)<sup>2</sup> (B) [1, 10]. Reprinted with permission of Revista de Chimie and of Editura Universităţii din Oradea.


Note: v, very; s, strong; m, medium; w, weak; *ν*, stretching; *δ*, in plane bending; ρ, rocking. Source: Reprinted with permission of Farmacia and of Editura Universităţii din Oradea.

such as elemental analysis, spectral methods [Fourier transform infrared spectroscopy (FTIR), FT-Raman spectrometry, mass spectrometry], and scanning electron microscopy (SEM) cou-

The elemental analysis indicated that the combination ratio of metal:ligand (Me:L) is 1:2 for

PZA with Co(II) benzoate revealed the identity and the purity of PZA and of the complex

The FTIR spectra of the complexes highlighted that –C═O groups and nitrogen from the pyrazine ring are implied in the coordination process (**Table 1**) [11]. Comparing the Raman

is obtained. The appearance of new band characteristic for the Me:L bonds can be observed analyzing in detail the spectral region of low values of wave number (**Figure 2**) [1, 11, 12].

> 50 100 150 200 250 300 350 m/z

> 50 100 150 200 250 300 350 m/z

<sup>39</sup> <sup>52</sup> <sup>94</sup> <sup>107</sup> <sup>129</sup> 157 171 <sup>212</sup> 235 3 253 3 <sup>280</sup> <sup>304</sup> <sup>27</sup> <sup>39</sup>

](C<sup>6</sup> H5 COO)<sup>2</sup>

<sup>81</sup> <sup>124</sup> <sup>78</sup> <sup>40</sup> <sup>54</sup> <sup>105</sup> <sup>125</sup> <sup>142</sup> <sup>155</sup> <sup>168</sup> <sup>201</sup> <sup>212</sup> <sup>229</sup> 253 3 267 2 <sup>281</sup> <sup>89</sup> 308 327 <sup>41</sup>

complexes. The mass spectra of the complex of

, another analytical evidence for the complex formation

A

B

(B) [1, 10]. Reprinted with permission of Revista de

pled with X-ray spectroscopy [energy-dispersive spectroscopy (EDS)] [1, 10–13].

](C<sup>6</sup> H5 COO)<sup>2</sup>

]Cl<sup>2</sup>

[Cu(PZA)<sup>2</sup>

0

0

20

51 50

40

60

80

100

20

40

60

80

100

]Cl<sup>2</sup>

spectra of PZA and of [Cu(PZA)<sup>2</sup>

[ ]

79

[ ]

77

53 52

44

and [Cu(PZA)<sup>2</sup>

126 Spectroscopic Analyses - Developments and Applications

fragments confirming its structure (**Figure 1**) [1, 10].

80 123

105 122

76 78 106 123

**Figure 1.** The mass spectra of PZA (A) and [Cu(PZA)<sup>2</sup>

Chimie and of Editura Universităţii din Oradea.

**Table 1.** Assignment of the characteristic IR bands of the metal complexes of PZA [1, 14].

**Figure 2.** Raman spectra of PZA and of [Cu(PZA)<sup>2</sup> ]Cl<sup>2</sup> [1, 12]. Reprinted with permission of Studia Universitatis Babes-Bolyai and of Editura Universităţii din Oradea.

The morphology and the crystal structure of the two complexes were revealed by the SEM images and EDS spectra (**Figures 3** and **4**). The first complex, [Cu(PZA)<sup>2</sup> ](C<sup>6</sup> H5 COO)<sup>2</sup> , presented irregular conglomeration with different shapes and dimensions (**Figure 3A**); meanwhile, the second one, Cu(PZA)<sup>2</sup> ]Cl<sup>2</sup> , presented acicular and elongated particles with an average size of about 1.5 microns (**Figure 4A**) [1, 14].

#### **2.2. Metal complexes of nicotinamide**

Nicotinamide (NAM) (3-pyridine carboxylic acid amide) is the amide of nicotinic acid playing an important role in the biosynthesis of pyridine nucleotides, and it is a reactive moiety of the coenzyme nicotinamide adenine dinucleotide, a soluble electron carrier in biochemical reactions. The NAM complexes with transition metals [Cu(II), Cd(II), Hg(II)] were synthesized and characterized by using elemental analysis, UV-Vis, and FTIR spectroscopy [1, 15, 16]. The spectral data confirmed tetradentate coordination of NAM with Hg(II), Cd(II), and hexadentate coordination with Cu(II). In the FTIR spectra of these complexes, it can be observed that the characteristic bands of NAM are slightly shifted after coordination (**Table 2**) [16]. The slight shifting of the bands from NAM complexes with Hg may be explained by the stereochemistry of HgCl<sup>2</sup> , which is less bulky than Cu(C<sup>6</sup> H5 COO)<sup>2</sup> and Cd(SCN)<sup>2</sup> .

#### **2.3. Metal complexes of nicotinic acid**

Nicotinic acid (NIC) (pyridine-3-carboxylic acid) known as vitamin B3 , niacin, has two important pharmacological properties: peripheral vasodilator and hypocholesterolemic drug. Its complexes with Co(II) and Cu(II) were synthesized and characterized by elemental analysis and spectral methods [FTIR spectroscopy, Raman spectroscopy, and surface-enhanced

**Figure 3.** SEM image (A) and EDS spectrum (B) of [Cu(PZA)<sup>2</sup> ](C<sup>6</sup> H5 COO)<sup>2</sup> [1, 14]. Reprinted with permission of Farmacia and of Editura Universităţii din Oradea.

**Figure 4.** SEM image (A) and EDS spectrum (B) of [Cu(PZA)<sup>2</sup> ]Cl<sup>2</sup> [1, 14]. Reprinted with permission of Farmacia and of Editura Universităţii din Oradea.

Raman spectroscopy (SERS)] (**Figure 5**). The significant differences observed from the spectral data of the metal complexes can be attributed to the coordination process with the metal ions: the stretching vibrations ν(C─C) from the pyridine ring (1500–1600 cm−1) and *ν*(ring) of NIC (1037 cm−1) are shifted; meanwhile, the vibration band *γ*(CH) of the ring at 811 cm−1 is shifted and also splitted indicating the ring deformation during the coordination process. There appear new bands corresponding to the Me:L bonds (at about 500 cm−1) (**Table 3**). The spectral results confirmed the monodentate coordination of NIC with Cu(II) and Co(II) [17].

#### **2.4. Metal complexes of guanfacine**

The morphology and the crystal structure of the two complexes were revealed by the SEM

sented irregular conglomeration with different shapes and dimensions (**Figure 3A**); mean-

Nicotinamide (NAM) (3-pyridine carboxylic acid amide) is the amide of nicotinic acid playing an important role in the biosynthesis of pyridine nucleotides, and it is a reactive moiety of the coenzyme nicotinamide adenine dinucleotide, a soluble electron carrier in biochemical reactions. The NAM complexes with transition metals [Cu(II), Cd(II), Hg(II)] were synthesized and characterized by using elemental analysis, UV-Vis, and FTIR spectroscopy [1, 15, 16]. The spectral data confirmed tetradentate coordination of NAM with Hg(II), Cd(II), and hexadentate coordination with Cu(II). In the FTIR spectra of these complexes, it can be observed that the characteristic bands of NAM are slightly shifted after coordination (**Table 2**) [16]. The slight shifting of the bands from NAM complexes with Hg may be explained by the stereo-

> H5 COO)<sup>2</sup>

tant pharmacological properties: peripheral vasodilator and hypocholesterolemic drug. Its complexes with Co(II) and Cu(II) were synthesized and characterized by elemental analysis and spectral methods [FTIR spectroscopy, Raman spectroscopy, and surface-enhanced

> ](C<sup>6</sup> H5 COO)<sup>2</sup>

](C<sup>6</sup> H5 COO)<sup>2</sup>

, presented acicular and elongated particles with an

and Cd(SCN)<sup>2</sup>

.

[1, 14]. Reprinted with permission of Farmacia

, niacin, has two impor-

, pre-

images and EDS spectra (**Figures 3** and **4**). The first complex, [Cu(PZA)<sup>2</sup>

]Cl<sup>2</sup>

, which is less bulky than Cu(C<sup>6</sup>

Nicotinic acid (NIC) (pyridine-3-carboxylic acid) known as vitamin B3

while, the second one, Cu(PZA)<sup>2</sup>

chemistry of HgCl<sup>2</sup>

**2.2. Metal complexes of nicotinamide**

128 Spectroscopic Analyses - Developments and Applications

**2.3. Metal complexes of nicotinic acid**

**Figure 3.** SEM image (A) and EDS spectrum (B) of [Cu(PZA)<sup>2</sup>

and of Editura Universităţii din Oradea.

average size of about 1.5 microns (**Figure 4A**) [1, 14].

Guanfacine (GUAF) (*N*-(diaminomethylidene)-2-(2,6-dichlorophenyl)acetamide), used as antihypertensive drug, is able to form colored complexes (combination ratio Me:L 1:2) with Mn(II) and Cd(II) having different spectral characteristics. These complexes were analyzed by using spectral techniques such as FTIR and Raman spectroscopy. The imine group vibration from the FTIR data of GUAF (ν C═<sup>N</sup> at 1700 cm−1) was shifted (Δ = 10–60 cm−1) in the spectra of GUAF complexes with Mn(II) (ν C═<sup>N</sup> at 1710 cm−1) and Cd(II) (ν C═<sup>N</sup> at 1760 cm−1) showing the imine group involvement in the complex formation. The formation of new bonds Me:L was observed at around 500 cm−1 in the case of the two mentioned complexes. Significant differences appeared in the Raman spectra of the complexes in the region 1100– 1250 cm−1 due to the electronic delocalization from NH═C─NH<sup>2</sup> (**Figure 6**). After coordination, in the case of both complexes, two distinct bands were revealed at 1212 cm−1 for NH─C─NH<sup>2</sup> and at 1174 cm−1 for NH═C─NH<sup>2</sup> . The spectral data indicated that GUAF is coordinated by nitrogen atoms, and the results confirmed a tetradentate coordination of Cd(II) complexes [18].


Note: v, very; s, strong; m, medium; w, weak; sh, shoulder; sp, splitting; *ν*, stretching; *β*, in-plane bending; *γ*, out-of-plane bending; *δ*, in-plane bending; *ω*, out-of-plane wag.

Source: Reprinted with permission of Revista de Chimie.

**Table 2.** Assignment of the characteristic IR bands of the metal complexes of NAM [16].

#### **2.5. Metal complexes of theophylline**

Theophylline (TEO) (3,7-dihydro-1,3-dimethyl,1H-purine-2,6-dione) also known as 1,3-dimethylxanthine belongs to the class of peripheral and cerebral vasodilator drugs. Metal complexes of TEO were synthesized having the general formula: [Me<sup>n</sup> (TEO)x ]Am ⋅ yH<sup>2</sup> O, where Me = Cu(II), Co(II), Cd(II), Zn(II), and Ni(II) and A = CH3 COO− , C<sup>6</sup> H5 COO− ; n = 1, x = 1 or 2, m = 2, and y = 2 or 4. The combination ratio was determined by using elemental analysis and conductometric titration; meanwhile, the number of water molecules was determined by using thermal analysis [2, 19–22].

**Figure 5.** Raman (A) and SERS (B) spectra of NIC (a) and its complex with Cu(II) (b) and Co(II) (c) [17]. Reprinted with permission of Revista de Chimie.


Note: v, very; s, strong; m, medium; w, weak; *ν*, stretching; *γ*, out-of-plane bending; *δ*, in-plane bending. Source: Reprinted with permission of Revista de Chimie.

**2.5. Metal complexes of theophylline**

bending; *δ*, in-plane bending; *ω*, out-of-plane wag. Source: Reprinted with permission of Revista de Chimie.

**NAM [Hg(NAM)2**

130 Spectroscopic Analyses - Developments and Applications

**]Cl2 [Cu(NAM)2**

**(C6 H5 COO)2 2H2 O**

3364vs 3363s 3369s 3479s *ν*as(NH<sup>2</sup>

3065sh 3071sh 3071sh 3072w *ν*(CH) 1654s 1654vs 1668vs 1667vs *ν*(CO) 1622ws 1623ws 1632ws 1618m *δ*(NH<sup>2</sup>

1449m 1449m 1490s 1485m *β*(CH)

1297m 1296m 1301w 1331m *ν*(CC)

1141m 1142s 1153sh 1153m *ν* (CN) 1120m 1119s 1116m 1112m *ρ*(NH<sup>2</sup>

1022m 1024w 1025m 1040m *υ*(CNS) – 919m 928w 937w *γ*(CH) ring – 844s 853m 840m *ν*as(C─CH3

771m 786s 775w 770s *γ*(CH) ring 698m 700ws 719w 719w *ω*(NH<sup>2</sup>

684m 686ws 687s 687ws *δ*(ring)NAM 633s 641s 655w 657ws *γ*(NH)

1577ws 1577vs 1596s 1577s *ν*(CN) + *ν*(CC)

1395ws 1400m 1377vs 1400s *ν*(CN) amide

1178m 1179m 1193w 1204s *ν*(ring) NAM

3167s 3171s 3207vs 3176m *ν*<sup>s</sup>

**]** 

**[Cd(NAM)2**

**](SCN)2 Assignment**

)

)

)

)

)

(NH<sup>2</sup> )

3531w (OH)

Co(II), Cd(II), Zn(II), and Ni(II) and A = CH3

[2, 19–22].

TEO were synthesized having the general formula: [Me<sup>n</sup>

**Table 2.** Assignment of the characteristic IR bands of the metal complexes of NAM [16].

Theophylline (TEO) (3,7-dihydro-1,3-dimethyl,1H-purine-2,6-dione) also known as 1,3-dimethylxanthine belongs to the class of peripheral and cerebral vasodilator drugs. Metal complexes of

Note: v, very; s, strong; m, medium; w, weak; sh, shoulder; sp, splitting; *ν*, stretching; *β*, in-plane bending; *γ*, out-of-plane

COO− , C<sup>6</sup> H5 COO−

or 4. The combination ratio was determined by using elemental analysis and conductometric titration; meanwhile, the number of water molecules was determined by using thermal analysis

(TEO)x

]Am ⋅ yH<sup>2</sup>

O, where Me = Cu(II),

; n = 1, x = 1 or 2, m = 2, and y = 2

**Table 3.** Assignment of the characteristic Raman and SERS bands of the metal complexes of NIC [17].

**Figure 6.** Raman spectra of GUAF and of its metal complexes [19].

The combination ratio Me:TEO is 1:2 for the complexes having the acetate anion. The complex [Cu(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> has a high thermal instability even at 40°C, its thermal decomposition being already started. On the thermal curves, eight stages of decomposition, all scarcely separable, can be observed. The first five were weakly endothermic, and three were strongly exothermic. The X-ray diffractogram revealed that this complex crystallizes in the monoclinic system. The microscopic analysis showed a mixture of particles with different shapes: acicular, flake, irregular, and lamellar (**Figure 7**) [2, 19–22].

In the case of [Cd(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> , the last stage of thermal decomposition was not achieved in the investigated temperature range; therefore, heating was required up to a higher temperature (850°C) when constant weight was reached corresponding to the cadmium oxide. The complex crystallizes in the monoclinic system, and it presents microcrystals with parallelepiped shape (**Figure 8**) [2, 19, 21, 22].

The thermal decomposition of [Co(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> takes place in four stages: one endothermic and three exothermic. It presents monoclinic crystal system, and the microcrystals have a tabular form (**Figure 9**). The complex [Zn(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> presented similar properties as [Cd(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> complex [2, 19, 21, 22].

The endothermic peak at 272°C, which is characteristic for TEO decomposition, is not found in the differential scanning calorimetry (DSC) curves of the complexes, being a credible argument for the complex synthesis and not as a simple mechanical mixture (**Figure 10**) [2, 19].

**Figure 7.** Thermogramms TG, DTG, and DTA (A); X-ray diffractogram; (B) and SEM images (C) of [Cu(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> [2, 19, 21, 22]. Reprinted with permission of Revista de Chimie, Farmacia and of Editura Politehnica Timişoara.

The combination ratio Me:TEO is 1:2 for the complexes having the acetate anion. The complex

tion being already started. On the thermal curves, eight stages of decomposition, all scarcely separable, can be observed. The first five were weakly endothermic, and three were strongly exothermic. The X-ray diffractogram revealed that this complex crystallizes in the monoclinic system. The microscopic analysis showed a mixture of particles with different shapes: acicu-

in the investigated temperature range; therefore, heating was required up to a higher temperature (850°C) when constant weight was reached corresponding to the cadmium oxide. The complex crystallizes in the monoclinic system, and it presents microcrystals with paral-

](CH3

complex [2, 19, 21, 22].

thermic and three exothermic. It presents monoclinic crystal system, and the microcrystals

The endothermic peak at 272°C, which is characteristic for TEO decomposition, is not found in the differential scanning calorimetry (DSC) curves of the complexes, being a credible argument for the complex synthesis and not as a simple mechanical mixture (**Figure 10**)

COO)<sup>2</sup>

](CH3

has a high thermal instability even at 40°C, its thermal decomposi-

, the last stage of thermal decomposition was not achieved

COO)<sup>2</sup>

takes place in four stages: one endo-

presented similar proper-

[Cu(TEO)<sup>2</sup>

](CH3

In the case of [Cd(TEO)<sup>2</sup>

ties as [Cd(TEO)<sup>2</sup>

[2, 19].

COO)<sup>2</sup>

132 Spectroscopic Analyses - Developments and Applications

lelepiped shape (**Figure 8**) [2, 19, 21, 22].

The thermal decomposition of [Co(TEO)<sup>2</sup>

](CH3

lar, flake, irregular, and lamellar (**Figure 7**) [2, 19–22].

**Figure 6.** Raman spectra of GUAF and of its metal complexes [19].

](CH3

have a tabular form (**Figure 9**). The complex [Zn(TEO)<sup>2</sup>

COO)<sup>2</sup>

COO)<sup>2</sup>

The FTIR data also indicated the complex formation: the disappearance of the symmetric vibration band of ─C═O from TEO at 1717 cm−1 in the complexes spectra indicating that this bond is involved in the formation of Me:TEO coordinative bond; the deformation vibration of Me:N bond found at 570–685 cm−1, the appearance of symmetric and asymmetric stretching vibrations of the ─COOH group (1260–1250 and 1535–1530 cm−1), and the possibility of coordinating also the water of crystallization (appearance of large bands at 3050–3500 cm−1) (**Figure 11**) [2, 19, 21, 22].

The combination ratio Me:TEO is 1:1 for the complexes having the benzoate anion: [Co(TEO)] (C<sup>6</sup> H5 COO)<sup>2</sup> ·2H<sup>2</sup> O, [Ni(TEO)](C<sup>6</sup> H5 COO)<sup>2</sup> ·2H<sup>2</sup> O, and [Cu(TEO)](C<sup>6</sup> H5 COO)<sup>2</sup> ·2H<sup>2</sup> O. Their thermal decomposition takes place in four stages, the first one being the stage of loss of water of crystallization (**Figure 12A**). The FTIR data are similar with those of the complexes mentioned above (having the acetate group as anion); in addition, the specific vibration band

**Figure 8.** Thermogramms TG, DTG, and DTA (A); X-ray diffractogram; (B) and SEM images (C) of [Cd(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> [2, 19, 21, 22]. Reprinted with permission of Revista de Chimie, Farmacia and of Editura Politehnica Timişoara.

of the aromatic ring (1438, 1442, 1440 cm−1) appears. The microscopic image of [Co(TEO)] (C<sup>6</sup> H5 COO)<sup>2</sup> showed the acicular shape of the particles (**Figure 12B**) [2, 20].

#### **2.6. Metal complexes of captopril**

The chemical structure of captopril (CPL), a dipeptide derivative of *L*-alanine-*L*-proline with antihypertensive effect, contains bonds such as ─C═O and ─N(─CH<sup>2</sup> )2 with donor atoms capable of forming Me:L bonds. The interaction between the metal ions such as Mn(II), Co(II), Zn(II), Ni(II), and Cd(II) with N and O atoms from the peptide (which act as donors) leads to the formation of stable chelate cycles. These complexes were characterized by elemental analysis obtaining the results presented in **Table 4** [23, 24].

CPL forms complexes with transition metals mentioned above in the presence of tetraiodomercurate anion, [HgI<sup>4</sup> ]2−. The formation and the structure of these complexes are observed in the data of the elemental analysis and in the UV and IR spectra of the complexes with changes of the wavelength values and of absorbance due to the presence of Me:CPL bonds. In the IR spectra of the complexes, a diminution of the band at 1748 cm−1 of ─C═O from the carboxyl group, in comparison with the IR spectrum of CPL, was observed. A wider band appeared

**Figure 9.** Thermogramms TG, DTG, and DTA (A); X-ray diffractogram; (B) and SEM images (C) of [Co(TEO)<sup>2</sup> ](CH3 COO)<sup>2</sup> [2, 19, 21, 22]. Reprinted with permission of Revista de Chimie, Farmacia and of Editura Politehnica Timişoara.

at 1600 cm−1 due to the overlapping of the bands corresponding to ─C═O from the amide group. In addition, a new band is observed at 1450 cm−1 due to ─C═O from the carboxyl group (─COO− ). In the IR spectra of the Zn:CPL complex, the band corresponding to ─C═O from carboxyl group decreased. It is possible that the reaction with some metals was not completely performed or some degradation products of CPL may be involved in the complexation reaction. In the case of the complex Cu<sup>2</sup> IICPL<sup>2</sup> (H<sup>2</sup> O)<sup>2</sup> , the IR spectra have indicated the participation of ─COOH, ─C═O, and ─SH groups in coordination along with H<sup>2</sup> O included in the inner coordination sphere [23, 24].

The UV spectra of the complexes were compared to the UV spectrum of CPL in dimethylformamide establishing the parameters presented in **Table 5** (A% 1 cm = 190 for 2.5 μg% CPL) [23, 24].

#### **2.7. Metal complexes of tolbutamide**

of the aromatic ring (1438, 1442, 1440 cm−1) appears. The microscopic image of [Co(TEO)]

The chemical structure of captopril (CPL), a dipeptide derivative of *L*-alanine-*L*-proline with

capable of forming Me:L bonds. The interaction between the metal ions such as Mn(II), Co(II), Zn(II), Ni(II), and Cd(II) with N and O atoms from the peptide (which act as donors) leads to the formation of stable chelate cycles. These complexes were characterized by elemental

CPL forms complexes with transition metals mentioned above in the presence of tetraiodo-

the data of the elemental analysis and in the UV and IR spectra of the complexes with changes of the wavelength values and of absorbance due to the presence of Me:CPL bonds. In the IR spectra of the complexes, a diminution of the band at 1748 cm−1 of ─C═O from the carboxyl group, in comparison with the IR spectrum of CPL, was observed. A wider band appeared

]2−. The formation and the structure of these complexes are observed in

)2

with donor atoms

](CH3

COO)<sup>2</sup>

showed the acicular shape of the particles (**Figure 12B**) [2, 20].

**Figure 8.** Thermogramms TG, DTG, and DTA (A); X-ray diffractogram; (B) and SEM images (C) of [Cd(TEO)<sup>2</sup>

[2, 19, 21, 22]. Reprinted with permission of Revista de Chimie, Farmacia and of Editura Politehnica Timişoara.

antihypertensive effect, contains bonds such as ─C═O and ─N(─CH<sup>2</sup>

analysis obtaining the results presented in **Table 4** [23, 24].

(C<sup>6</sup> H5 COO)<sup>2</sup>

**2.6. Metal complexes of captopril**

134 Spectroscopic Analyses - Developments and Applications

mercurate anion, [HgI<sup>4</sup>

Tolbutamide (TBA) (*N-p*-tolylsulfonyl-*N′-n*-butylcarbamide) is the first generation of sulfonylurea oral hypoglycemic drug. Three complexes of TBA with Cu(II) were synthesized,

**Figure 10.** DSC thermogramms of metal complexes of TEO [2, 19]. Reprinted with permission of Revista de Chimie and of Editura Politehnica Timişoara.

**Figure 11.** FTIR spectra of TEO and of its metal complexes (acetate anion).

**Figure 10.** DSC thermogramms of metal complexes of TEO [2, 19]. Reprinted with permission of Revista de Chimie and

2

](CH3COO)2

](CH3COO)2

](CH3COO)2

](CH3COO)

4000 3500 3000 2500 2000 1500 1000 500

Wavenumber (cm-1)

Wavenumber (1/cm)

of Editura Politehnica Timişoara.

136 Spectroscopic Analyses - Developments and Applications

 TEO [Cu(TEO)2

[Co(TEO)2

[Zn(TEO)2

[Cd(TEO)2

**Figure 11.** FTIR spectra of TEO and of its metal complexes (acetate anion).


0.0

0.2

0.4

0.6

Absorbance (a.u.)

0.8

1.0

1.2

1.4

**Figure 12.** Thermogramms TG, DTG, and DTA (A) and SEM images (B) of [Co(TEO)](C<sup>6</sup> H5 COO)<sup>2</sup> [2, 20]. Reprinted with permission of Revista de Chimie and of Editura Politehnica Timişoara.

[Cu(TBA)<sup>2</sup> ](SCN)2, [Cu(TBA)<sup>2</sup> ]Cl<sup>2</sup> ·2H<sup>2</sup> O, and [Cu(TBA)<sup>2</sup> ][Hg(SCN)<sup>4</sup> ]. H2 O and then were characterized by elemental analysis, FTIR spectroscopy, electron paramagnetic resonance (EPR) spectroscopy, and thermal methods establishing the combination ratio Cu:TBA 1:2, the presence of water of crystallization, and the coordination system. The FTIR spectral studies indicated that the three mentioned complexes were coordinated through the carbonyl group. The EPR spectra showed that the Cu2+ ions were disposed in an octahedral vicinity of axial symmetry with a different hyperfine structure of the three complexes [25–27].


Source: Reprinted with permission of Farmacia and of Editura Universităţii din Oradea.

**Table 4.** Physicochemical characterization of the metal complexes of CPL [23, 24].


Source: Reprinted with permission of Editura Universităţii din Oradea.

**Table 5.** The parameters of the metal complexes of CPL from UV spectra [23].

**Figure 13.** Raman spectra of CLN and of its metal complexes.

#### **2.8. Metal complexes of clonidine**

**The molecular formula and weight**

> ][HgI<sup>4</sup> ]

][HgI<sup>4</sup> ]

][HgI<sup>4</sup> ]

][HgI<sup>4</sup> ]

][HgI<sup>4</sup> ]

> 3320 3073 3059 2978

0.000 0.005 0.010 0.015 0.020 0.025 0.030

Ram an Intens ity

[Cd(CPL)<sup>2</sup>

[Zn(CPL)<sup>2</sup>

[Ni(CPL)<sup>2</sup>

[Co(CPL)<sup>2</sup>

M = 1199.68

[Mn(CPL)<sup>2</sup>

M = 1195.68

M = 1244.18

M = 1199.48

M = 1255.18

**Color Melting point (°C)**

Source: Reprinted with permission of Farmacia and of Editura Universităţii din Oradea.

CPL–Cd 300 270 5 CPL–Zn 300 400 5 CPL–Ni 300 475 4 CPL–Co 300 250 8 CPL–Mn 321 520 4.5

[Cd(CLN)2][HgI4]

[Mn(CLN)2][HgI4]

[Cu(CLN)2][HgI4]

[Ni(CLN)2][HgI4]

CLN

**Figure 13.** Raman spectra of CLN and of its metal complexes.

1576 1566 1483 1464 1244 1202 1155 1089 1067 934 860

3000 2500 2000 1500 1000 500 0 -500 W avenumber c m-1

Wavenumber/ cm-1

**Table 4.** Physicochemical characterization of the metal complexes of CPL [23, 24].

**Complex λ (nm) A%**

Source: Reprinted with permission of Editura Universităţii din Oradea.

**Table 5.** The parameters of the metal complexes of CPL from UV spectra [23].

Greenish yellow

138 Spectroscopic Analyses - Developments and Applications

**C% Found/ calculated** **H% Found/ calculated**

170 18.07/18.01 3.022/2.5 1.955/2.33 6.083/5.33

White 210 17.09/17.21 2.56/2.39 1.881/2.23 5.579/5.099

White 165 16.94/17.8 3.019/2.48 1.866/2.31 5.547/5.29

Light pink 180 17.84/18.01 2.866/2.51 1.938/2.31 6.148/5.43

White crystals 182 18.04/18.06 2.648/2.50 1.946/2.34 5.85/5.35

**N% Found/ calculated**

**1 cm Concentration (μg %)**

646

505

443

407

331

294

215

198

144

128

3




**S% Found/ calculated**

Clonidine (CLN) (2[(2,6-dichlorophenyl)imino]-imidazolidine) is a centrally acting α<sup>2</sup> adrenergic agonist used as antihypertensive drug. Metal complexes of CLN such as [Me(CLN)<sup>2</sup> ] [HgI<sup>4</sup> ] where Me = Cd(II), Mn(II), Ni(II), and Cu(II) were synthesized and studied by elemental analysis, FTIR spectroscopy, Raman spectroscopy (**Figure 13**), and EPR spectroscopy confirming the structure and the changes in the complex conformation [28].

#### **3. Biomedical significance of metal complexes with pharmaceuticals**

The study of the complexes structure and of their biological importance represented the major research interest toward the use of organic drugs as ligands in coordination chemistry for their application in the biomedical field.

The molecules of the pharmaceutical substances have one or more unshared electron pairs that can function as ligands. In fact, many of the basic components of living organisms (amino acids, peptides, proteins, hormones, lipids, carbohydrates, etc.) may function as ligands because they contain donor atoms in their molecules such as nitrogen, oxygen, sulfur, and phosphorus. It is well known that many molecules of drug substances act as ligands both in vitro and in vivo conditions. It is noteworthy to mention that in vivo these ligands will compete for a particular metal ion with a variety of other ligands determining that the extrapolation of this in vitro behavior should be done with moderation. It should always be taken into consideration that the therapeutic effect will be mainly influenced by the conformation of the drug ligands molecules and by their ability to combine with receptors.

Thus, the use of these metal complexes in the biomedical field can be realized by various purposes such as the introduction in the body of deficient metal ions, the use of the ligands as antidotes in various intoxications with metals, and the acquirement of pharmacotherapy effects by blocking metal ions essential for some enzymatic systems. Metal ions are of great importance not only in the vital functions of living organisms, but also they can be intensively used in analysis and control methods for pharmaceutical substances by forming complexes that can be detected by using different physicochemical methods such as spectroscopy, chromatography, microscopy, etc.

#### **4. Conclusions**

Transition metal complexes find their application in catalysis, material synthesis, photochemistry, therapy, and diagnostics. Various chemical, optical, and magnetic properties of the metal complexes of some pharmaceutical substances (pyrazinamide, nicotinamide, nicotinic acid, tolbutamide, theophylline, captopril, clonidine, and guanfacine) have been studied by using a wide range of techniques. The spectral methods such as Fourier transform infrared spectroscopy, Raman spectroscopy, surface-enhanced Raman spectroscopy, X-ray spectroscopy, mass spectrometry, ultraviolet*-*visible spectrophotometry, electron paramagnetic resonance spectroscopy, and X-ray diffraction provided information about the complexes and ligand structure. Other techniques such as elemental analysis, electrochemical, and thermal methods were also employed for the assessment of the complexation ratio. The scanning electron microscopy images revealed the morphology of the metal complexes underlying their crystalline or amorphous character. Many studies were conducted concerning the synthesis and the investigation of metal complexes in which the pharmaceutical substances play the role of ligand highlighting their increasing clinical and commercial importance.

#### **Author details**

Tünde Jurca, Eleonora Marian, Laura Graţiela Vicaş, Mariana Eugenia Mureşan and Luminiţa Fritea\*

\*Address all correspondence to: fritea\_luminita@yahoo.com

Faculty of Medicine and Pharmacy, University of Oradea, Oradea, Romania

#### **References**


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and ligand structure. Other techniques such as elemental analysis, electrochemical, and thermal methods were also employed for the assessment of the complexation ratio. The scanning electron microscopy images revealed the morphology of the metal complexes underlying their crystalline or amorphous character. Many studies were conducted concerning the synthesis and the investigation of metal complexes in which the pharmaceutical substances play

Tünde Jurca, Eleonora Marian, Laura Graţiela Vicaş, Mariana Eugenia Mureşan and Luminiţa

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the role of ligand highlighting their increasing clinical and commercial importance.

\*Address all correspondence to: fritea\_luminita@yahoo.com

Faculty of Medicine and Pharmacy, University of Oradea, Oradea, Romania

Timişoara: Editura Politehnica; 2009. 189 p. ISBN: 978-973-625-876-3.

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**Author details**

140 Spectroscopic Analyses - Developments and Applications

Fritea\*

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