Frontiers of Two-Dimensional Correlation Spectroscopy. Part 1. New concepts and noteworthy developments

Feasibility of the simultaneous determination of polycyclic aromatic hydrocarbons based on two-dimensional fluorescence correlation spectroscopy

A new approach for quantitative determination of polycyclic aromatic hydrocarbons (PAHs) in environment was proposed based on two-dimensional (2D) fluorescence correlation spectroscopy in conjunction with multivariate method. 40 mixture solutions of anthracene and pyrene were prepared in the laboratory. Excitation-emission matrix (EEM) fluorescence spectra of all samples were collected. And 2D fluorescence correlation spectra were calculated under the excitation perturbation. The N-way partial least squares (N-PLS) models were developed based on 2D fluorescence correlation spectra, showing a root mean square error of calibration (RMSEC) of 3.50μgL^-1 and root mean square error of prediction (RMSEP) of 4.42μgL^-1 for anthracene and of 3.61μgL^-1 and 4.29μgL^-1 for pyrene, respectively. Also, the N-PLS models were developed for quantitative analysis of anthracene and pyrene using EEM fluorescence spectra. The RMSEC and RMSEP were 3.97μgL^-1 and 4.63μgL^-1 for anthracene, 4.46μgL^-1 and 4.52μgL^-1 for pyrene, respectively. It was found that the N-PLS model using 2D fluorescence correlation spectra could provide better results comparing with EEM fluorescence spectra because of its low RMSEC and RMSEP. The methodology proposed has the potential to be an alternative method for detection of PAHs in environment.

Vibrational two-dimensional correlation spectroscopy (2DCOS) study of proteins

A tutorial is provided for the generalized two-dimensional correlation spectroscopy (2DCOS), which is applicable to the vibrational spectroscopic study of proteins and related systems. In 2DCOS, similarity or dissimilarity among variations of spectroscopic intensities, which are induced by applying an external perturbation to the sample, is examined by constructing correlation spectra defined by two independent spectral variable axes. By spreading congested or overlapped peaks along the second dimension, apparent spectral resolution is enhanced and interpretation of complex spectra becomes simplified. A set of simple rules for the intensities and signs of correlation peaks is used to extract insightful information. Simulated IR spectra for a model protein are used to demonstrate the specific utility of 2DCOS. Additional tools useful in the 2DCOS analysis of proteins, such as data segmentation assisted with moving-window analysis, 2D codistribution analysis, Pareto scaling, and null-space projection are also discussed.

Evaluation of the nitrogen content during the new-shoot-growing stage in apple leaves using two-dimensional correlation spectroscopy

The new-shoot-growing stage is an important period of apple tree nutrition distribution. The objective of this study is to provide technical support for apple tree nutrition diagnosis by constructing quantitative evaluation models between the apple leaf nitrogen content during the new-shoot-growing stage and characteristic spectral parameters. The correlation coefficients between the original spectral data and the nitrogen content were calculated. Then, the sensitive bands of the nitrogen content were selected using the theory of two-dimensional (2D) correlation spectroscopy. Finally, partial least squares regression (PLSR) and support vector machine (SVM) evaluation models were established using 2 parameters: Rx (maximum spectral reflectivity in the waveband) and Sx (total spectral reflectivity in the waveband). The results showed that the sensitive bands in the 2D correlation synchronous and asynchronous spectrograms were 537-560 nm and 708-719 nm. The PLSR model can be used to estimate the nitrogen content. Compared with PLSR, SVM provided better modeling and testing results, with a larger coefficient of determination (R2) and a smaller root-mean-square error (RMSE). The SVM model based on Sx was a good backup method. The calibration R2 of the model was 0.821, its RMSE was 0.710 g·kg-1, the validation R2 was 0.768, and its RMSE was 1.019 g·kg-1. The SVM model based on 2D correlation spectroscopy can be used to quantitatively estimate the nitrogen content in apple leaves.

Multiple interaction regulated phase transition behavior of thermo-responsive copolymers containing cationic poly(ionic liquid)s

Schematic illustration of the phase transition mechanism of the P(OEGMA-co-BVIm[SCN]) copolymer.

Chemical composition and surfactant characteristics of marine foams investigated by means of UV-vis, FTIR and FTNIR spectroscopy

In this study, we collected the ultraviolet-visible (UV-vis), Fourier transform infrared (FTIR) and Fourier transform near-infrared (FTNIR) spectra of marine foams from different sites and foams produced by marine living organisms (i.e. algae and molluscs) to retrieve information about their molecular and structural composition. UV-vis spectra gave information concerning the lipid and pigment contents of foams. FTIR spectroscopy gave a more detailed qualitative information regarding carbohydrates, lipids and proteins in addition with information about the mineral contents of foams. FTNIR spectra confirmed the presence of carbohydrates, lipids and proteins in foams. Then, due to the higher content of structural information of FTIR spectroscopy with respect to FTNIR and UV-vis, we join the FTIR spectra of marine foams to those of humic substance from marine sediments and to the spectra of foams obtained by living organisms. We submitted this resulting FTIR spectral dataset to statistical multivariate methods to investigate specific aspects of foams such as structural similarity among foams and in addition, contributions from the organic matter of living organisms. Cluster analysis (CA) evidenced several cases (i.e. clusters) of marine foams having high structural similarity with foams from vegetal and animal samples and with humic substance extracted from sediments. These results suggested that all the living organisms of the marine environment can give contributions to the chemical composition of foams. Moreover, as CA also evidenced cases of structural differences within foam samples, we applied two-dimensional correlation analysis (2DCORR) to the FTIR spectra of marine foams to investigate the molecular characteristics which caused these structural differences. Asynchronous spectra of two-dimensional correlation analysis showed that the structural heterogeneity among foam samples depended reasonably on the presence and on the qualitative difference of electrostatic (hydrogen bonds) and nonpolar (van der Waals and π-π) interactions involving carbohydrate proteins and lipids present. The presence and relevance of these interactions agree with the supramolecular and surfactant characteristics of marine organic matter described in the scientific literature.

On the abnormal “forced hydration” behavior of P(MEA-co-OEGA) aqueous solutions during phase transition from infrared spectroscopic insights

During the phase separation of POEGA in water, C–H groups exhibit dehydration, whereas CO and C–O–C groups present “forced hydration”.

Investigation of intermolecular interactions of mixed extractants of quaternary phosphonium or ammonium chlorides and bis(2,4,4-ethylhexyl)phosphoric acid for metal separation

The adjustable intermolecular interactions of mixed extractants to improve metal separation.

Design of a New Concentration Series for the Orthogonal Sample Design Approach and Estimation of the Number of Reactions in Chemical Systems

A new concentration series is proposed for the construction of a two-dimensional (2D) synchronous spectrum for orthogonal sample design analysis to probe intermolecular interaction between solutes dissolved in the same solutions. The obtained 2D synchronous spectrum possesses the following two properties: (1) cross peaks in the 2D synchronous spectra can be used to reflect intermolecular interaction reliably, since interference portions that have nothing to do with intermolecular interaction are completely removed, and (2) the two-dimensional synchronous spectrum produced can effectively avoid accidental collinearity. Hence, the correct number of nonzero eigenvalues can be obtained so that the number of chemical reactions can be estimated. In a real chemical system, noise present in one-dimensional spectra may also produce nonzero eigenvalues. To get the correct number of chemical reactions, we classified nonzero eigenvalues into significant nonzero eigenvalues and insignificant nonzero eigenvalues. Significant nonzero eigenvalues can be identified by inspecting the pattern of the corresponding eigenvector with help of the Durbin-Watson statistic. As a result, the correct number of chemical reactions can be obtained from significant nonzero eigenvalues. This approach provides a solid basis to obtain insight into subtle spectral variations caused by intermolecular interaction.

Identification of Serine Conformers by Matrix-Isolation IR Spectroscopy Aided by Near-Infrared Laser-Induced Conformational Change, 2D Correlation Analysis, and Quantum Mechanical Anharmonic Computations

The conformers of α-serine were investigated by matrix-isolation IR spectroscopy combined with NIR laser irradiation. This method, aided by 2D correlation analysis, enabled unambiguously grouping the spectral lines to individual conformers. On the basis of comparison of at least nine experimentally observed vibrational transitions of each conformer with empirically scaled (SQM) and anharmonic (GVPT2) computed IR spectra, six conformers were identified. In addition, the presence of at least one more conformer in Ar matrix was proved, and a short-lived conformer with a half-life of (3.7 ± 0.5) × 10(3) s in N2 matrix was generated by NIR irradiation. The analysis of the NIR laser-induced conversions revealed that the excitation of the stretching overtone of both the side chain and the carboxylic OH groups can effectively promote conformational changes, but remarkably different paths were observed for the two kinds of excitations.

Comparison of LCST-transitions of homopolymer mixture, diblock and statistical copolymers of NIPAM and VCL in water

The LCST-transitions of linear, well-defined polymers of N-isopropylacrylamide (NIPAM) and N-vinylcaprolactam (VCL), including a homopolymer mixture, diblock and statistical copolymers, in water are explored and compared by applying turbidity and FTIR measurements in combination with two-dimensional correlation spectroscopy (2Dcos). Only one transition is observed in all polymer systems, suggesting a dependent aggregation of poly(N-isopropylacrylamide) (PNIPAM) and poly(N-vinylcaprolactam) (PVCL) parts in the phase transition processes. With the help of 2Dcos analysis, it is discovered that the hydrophobic interaction among C-H groups is the driving force for simultaneous collapse of the two distinct thermo-responsive segments. Additionally, the delicate differences within the LCST-transitions thereof have been emphasized, where the phase separation temperatures of the homopolymer mixture and the diblock copolymer are close while that of the statistical copolymer is relatively higher. Moreover, both diblock and statistical copolymers exhibit rather sharp phase transitions while the homopolymer mixture demonstrates a moderately continuous one.

Two-dimensional correlation spectroscopy in polymer study

This review outlines the recent works of two-dimensional correlation spectroscopy (2DCOS) in polymer study. 2DCOS is a powerful technique applicable to the in-depth analysis of various spectral data of polymers obtained under some type of perturbation. The powerful utility of 2DCOS combined with various analytical techniques in polymer studies and noteworthy developments of 2DCOS used in this field are also highlighted.

Two-dimensional asynchronous spectrum with auxiliary cross peaks in probing intermolecular interactions

A new approach called “asynchronous spectrum with auxiliary peaks (ASAP)” is proposed for generating a 2D asynchronous spectrum to investigate the intermolecular interaction between two solutes (P and Q) dissolved in the same solution.

Two dimensional NMR spectroscopic approaches for exploring plant metabolome: A review

Today, most investigations of the plant metabolome tend to be based on either nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), with or without hyphenation with chromatography. Although less sensitive than MS, NMR provides a powerful complementary technique for the identification and quantification of metabolites in plant extracts. NMR spectroscopy, well appreciated by phytochemists as a particularly information-rich method, showed recent paradigm shift for the improving of metabolome(s) structural and functional characterization and for advancing the understanding of many biological processes. Furthermore, two dimensional NMR (2D NMR) experiments and the use of chemometric data analysis of NMR spectra have proven highly effective at identifying novel and known metabolites that correlate with changes in genotype or phenotype. In this review, we provide an overview of the development of NMR in the field of metabolomics with special focus on 2D NMR spectroscopic techniques and their applications in phytomedicines quality control analysis and drug discovery from natural sources, raising more attention at its potential to reduce the gap between the pace of natural products research and modern drug discovery demand.