Novel developments and applications of two-dimensional correlation spectroscopy

Novel Developments and Progress in Two-Dimensional Correlation Spectroscopy (2D-COS)

This first of the two-part series of the comprehensive survey review on the progress of the two-dimensional correlation spectroscopy (2D-COS) field during the period 2021-2022, covers books, reviews, tutorials, novel concepts and theories, and patent applications that appeared in the last two years, as well as some inappropriate use or citations of 2D-COS. The overall trend clearly shows that 2D-COS is continually growing and evolving with notable new developments. The technique is well recognized as a powerful analytical tool that provides deep insights into systems in many science fields.

Precision in wheat flour classification: Harnessing the power of deep learning and two-dimensional correlation spectrum (2DCOS)

Wheat flour is a ubiquitous food ingredient, yet discerning its various types can prove challenging. A practical approach for identifying wheat flour types involves analyzing one-dimensional near-infrared spectroscopy (NIRS) data. This paper introduces an innovative method for wheat flour recognition, combining deep learning (DL) with Two-dimensional correlation spectrum (2DCOS). In this investigation, 316 samples from four distinct types of wheat flour were collected using a near-infrared (NIR) spectrometer, and the raw spectra of each sample underwent preprocessing employing diverse methods. The discrete generalized 2DCOS algorithm was applied to generate 3792 2DCOS images from the preprocessed spectral data. We trained a deep learning model tailored for flour 2DCOS images - EfficientNet. Ultimately, this DL model achieved 100% accuracy in identifying wheat flour within the test set. The findings demonstrate the viability of directly transforming spectra into two-dimensional images for species recognition using 2DCOS and DL. Compared to the traditional stoichiometric method Partial Least Squares Discriminant Analysis (PLS_DA), machine learning methods Support Vector Machines (SVM) and K-Nearest Neighbors (KNN), and deep learning methods one-dimensional convolutional neural network (1DCNN) and residual neural network (ResNet), the model proposed in this paper is better suited for wheat flour identification, boasting the highest accuracy. This study offers a fresh perspective on wheat flour type identification and successfully integrates the latest advancements in deep learning with 2DCOS for spectral type identification. Furthermore, this approach can be extended to the spectral identification of other products, presenting a novel avenue for future research in the field.

Diverse Applications of Two-Dimensional Correlation Spectroscopy (2D-COS)

This second of the two-part series of a comprehensive survey review provides the diverse applications of two-dimensional correlation spectroscopy (2D-COS) covering different probes, perturbations, and systems in the last two years. Infrared spectroscopy has maintained its top popularity in 2D-COS over the past two years. Fluorescence spectroscopy is the second most frequently used analytical method, which has been heavily applied to the analysis of heavy metal binding, environmental, and solution systems. Various other analytical methods including laser-induced breakdown spectroscopy, dynamic mechanical analysis, differential scanning calorimetry, capillary electrophoresis, seismologic, and so on, have also been reported. In the last two years, concentration, composition, and pH are the main effects of perturbation used in the 2D-COS fields, as well as temperature. Environmental science is especially heavily studied using 2D-COS. This comprehensive survey review shows that 2D-COS undergoes continuous evolution and growth, marked by novel developments and successful applications across diverse scientific fields.

Constrained and Open Mesoporosity in Polypropylene Cracking: Insight From Spectroscopic Investigations of Acidity, Diffusion, and Activity

The outcome of the demetalation process of zeolites depends on applied treatment conditions and can lead to the formation of either open or constrained mesopores. The quaternary ammonium cations as pore-directing agents during desilication are responsible for developing constrained mesoporosity with bottleneck entrances. However, higher mesopore surface area and higher accessibility of acid sites are often found for the hierarchical zeolites with constrained mesopores. This is followed by better catalytic activity in the cracking of vacuum gas oil and polymers. For desilication with pure NaOH, a realumination process is observed and an additional acid-wash step is required to reach their full catalytic potential. Thus, this study aims to analyze the acidic and catalytic properties of hierarchical ZSM-5 zeolites of different mesoporosity types employing in situ and operando FT-IR spectroscopic evaluation of polypropylene cracking. The suitability of constrained mesoporosity is studied by assessing the neopentane diffusion in kinetic adsorption, Monte Carlo calculations, and rapid scan FT-IR spectroscopic measurement analyzed by Crank solution for diffusion. The FT-IR spectroscopic results of in situ and operando studies are supported by two-dimensional correlation analysis, allowing to establish the direction of changes seen on spectra and their order.

Temperature-Controlled Chain Dynamics in Polyimide Doped with CoCl2 Probed Using Dynamic Mechanical Analysis

Cobalt(II) chloride (CoCl2) being in the vicinity of polyimide chains entails modifications in terms of the molecular dynamics, which are mainly governed by the possible presence of amic acid residual groups, by the transition-metal-type characteristics of cobalt and by the CoCl2 content. Polyimide was synthesized using poly(amic acid) according to the reaction of 2,2'-bis(3,4-dicarboxylphenyl)hexafluoropropane dianhydride (6FDA) with 3,3'-dimethyl-4,4'-diaminodiphenylmethane (MMDA) in N,N-dimethylacetamide. CoCl2 was added before the thermal imidization of the poly(amic acid). An experimental approach was designed to establish the interaction between the polyimide and CoCl2 and whether the interaction depends on the quantity of the salt. Evidence for the existence of residual amic acid groups was obtained using second derivative Fourier Transform Infrared Spectroscopy (FTIR) and with the help of 2D correlation spectroscopy (2D-COS). Moreover, FTIR, along with X-ray photoelectron spectroscopy (XPS), revealed the interaction between the polymer and CoCl2, primarily in the form of Co(II)-N coordinated bonds. Nevertheless, the coordination of cobalt with suitable atoms from the amic acid groups is not precluded. The results of dynamic mechanical analysis (DMA) featured a specific relaxation assigned to the presence of CoCl2 in the polymeric film and demonstrated that its (non)reinforcing effect depends on its content in the polyimide.

Quantitative analysis method of Panax notoginseng based on thermal perturbation terahertz two-dimensional correlation spectroscopy

This paper proposes a Panax notoginseng (P. notoginseng) quantitative analysis based on terahertz time-domain spectroscopy and two-dimensional correlation spectroscopy (2DCOS). By imposing temperature perturbation combined with 2DCOS, the one-dimensional absorbance spectra were transformed into 2DCOS synchronous spectra, which reflected the differences in characteristic information between different P. notoginseng contents more clearly. Then, the feature information of P. notoginseng contents was extracted from the 2DCOS synchronous spectra by a competitive adaptive reweighted sampling (CARS) method and was used to build a quantitative model combined with a support vector regression machine (SVR), called 2DCOS-CARS-SVR. We obtained a more accurate analysis result than the commonly used principal component analysis (PCA)-partial least squares regression (PLSR) and PCA-SVR. The prediction set correlation coefficient and root mean square error reached 0.9915% and 0.8160%, respectively.

A comparative study on the taste quality of Mytilus coruscus under different shucking treatments

Shucking is an indispensable step in the preparation of cooked mussel products, as it facilitates the detachment of meat from the shell. In this study, we comprehensively investigated the effects of boiling, steaming, and microwaving on taste constituents in half-cooked mussel meat. Two-dimensional correlation spectroscopy revealed the key differential taste components of the different shucking groups. Structural equation modeling (SEM) indicated the positive effects of saltiness and bitterness on umami taste, while sweetness and sourness had negative effects on umami taste in half-cooked mussel meat. Furthermore, Glu, Asp, Ala, Arg, betaine, malic acid, succinic acid, glycogen, Cl^-, Na⁺, K⁺, and PO3- 4 were quantitatively determined as the main taste compounds. The steaming shelling group had the most enriched taste components, with the highest equivalent umami concentration compared to the other shelling groups. Hence, steaming shucking may be favored due to abundant tastes and nutrients.

Quantitative analysis of near infrared spectroscopic data based on dual-band transformation and competitive adaptive reweighted sampling

Near infrared (NIR) spectroscopy has the characteristics of rapid processing, nondestructive analysis and on-line detection. This technique has been widely used in the fields of quantitative determination and substance content analysis. However, for complex NIR spectral data, most traditional machine learning models cannot carry out effective quantitative analyses (manifested as underfitting; that is, the training effect of the model is not good). Small amounts of available data limit the performance of deep learning-based infrared spectroscopy methods, while the traditional threshold-based feature selection methods require more prior knowledge. To address the above problems, this paper proposes a competitive adaptive reweighted sampling method based on dual band transformation (DWT-CARS). DWT-CARS includes four types in total: CARS based on integrated two-dimensional correlation spectrum (i2DCOS-CARS), CARS based on difference coefficient (DI-CARS), CARS based on ratio coefficient (RI-CARS) and CARS based on normalized difference coefficient (NDI-CARS). We conducted comparative experiments on three datasets; compared to traditional machine learning methods, our method achieved good results, demonstrating that this method has considerable prospects for the quantitative analysis of near-infrared spectroscopic data. To further improve the performance and stability of this method, we combined the idea of integrated modeling and constructed a partial least squares model based on Monte Carlo sampling for the samples obtained by CARS (DWT-CARS-MC-PLS). Through comparative experiments, we verified that the integrated model could further enhance the accuracy and stability of the results.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS): Part III. Versatile applications

In this review, the comprehensive summary of two-dimensional correlation spectroscopy (2D-COS) for the last two years is covered. The remarkable applications of 2D-COS in diverse fields using many types of probes and perturbations for the last two years are highlighted. IR spectroscopy is still the most popular probe in 2D-COS during the last two years. Applications in fluorescence and Raman spectroscopy are also very popularly used. In the external perturbations applied in 2D-COS, variations in concentration, pH, and relative compositions are dramatically increased during the last two years. Temperature is still the most used effect, but it is slightly decreased compared to two years ago. 2D-COS has been applied to diverse systems, such as environments, natural products, polymers, food, proteins and peptides, solutions, mixtures, nano materials, pharmaceuticals, and others. Especially, biological and environmental applications have significantly emerged. This survey review paper shows that 2D-COS is an actively evolving and expanding field.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS), part I. Yesterday and today

This comprehensive survey review, as the first of three parts, compiles past developments and early concepts of two-dimensional correlation spectroscopy (2D-COS) and subsequent evolution, as well as its early applications in various fields for the last 35 years. It covers past review articles, books, proceedings, and numerous research papers published on 2D-COS. 2D-COS continues to evolve and grow with new significant developments and versatile applications in diverse scientific fields. The healthy, vigorous, and diverse progress of 2D-COS studies in many fields confirms that it is well accepted as a powerful analytical technique to provide the in-depth understanding of systems of interest.

Application of 2D correlation analysis in FT - Raman investigations of quinidine aqueous solutions with varying pH

An analysis of FT-Raman spectra of quinidine (C₂₀H₂₄N₂O₂) aqueous solutions with varying pH (which was regarded as an external perturbation) was performed using the 2D correlation method. The main course of changes in the quinidine solution appears to be: protonation changes of the quinuclidine nitrogen N1, followed by protonation changes of nitrogen N13 in the quinoline, leading to the appearance of cross-peaks in the synchronous and asynchronous correlation maps. The intensity changes of peaks at 1369 cm^-1 for the unprotonated quinidine molecule, and characteristic peaks at 1387 cm^-1 and 1389 cm^-1 for protonated quinuclidine and double protonated quinidine, respectively, along with the decrease in pH, confirmed that the change in the pH of the quinidine solution has an influence on the protonation process of the Cinchona alkaloid. The negative synchronous and asynchronous cross-peaks at (1385, 823) cm^-1 and (1387, 822) cm^-1, respectively, indicate the importance of remodeling the quinoline fragment, during the process of a double protonation of the quinidine molecule. Bands correlating with 2809 cm^-1 confirmed the importance of the methoxy group in the process of quinidine protonation. The creation of hydrogen bonds after double protonation of the Cinchona alkaloids, assisted by the CH₃-O group, give an interesting insight into the changes in the studied compound occurring along with a decrease in pH.

Slice spectra approach to synchronous Two-dimensional correlation spectroscopy analysis for milk adulteration discriminate

The discrimination approach of adulterated milk was proposed combined synchronous two-trace two-dimensional (2T2D) correlation slice spectra at the characteristic wavebands of adulterant in milk with multivariate method. Two common adulterants, melamine and urea, were analyzed to demonstrate useful by the method. 2T2D (near infrared) NIR slice spectra at characteristic wavebands of adulterant were extracted from the synchronous 2T2D correlation spectra, and were input to construct the N-way partial least squares discriminant analysis (NPLS-DA) models. One-dimensional (1D) spectroscopy featuring all the present components in the samples combined with partial least squares discriminant analysis (PLS-DA) was also evaluated for comparison. The results indicated that for one kind of adulterant in model, prediction accuracies of slice spectral models were both 100% for melamine-adulterated and urea-adulterated samples discrimination. Moreover, for two kinds of adulterants in model, prediction accuracies of slice spectral models were 90.57% and 100% for melamine-adulterated and urea-adulterated discrimination, respectively, which was better than those of 1D whole models based on PLS-DA (only 81.13% and 98.15%, respectively). The comparison informs that the 2T2D slice spectra extracted at the characteristic wavebands of adulterant highlighted the adulterant spectral features and was obviously advantage to improve the discrimination accuracy. Meanwhile, the complexity of slice spectra is significantly reduced compared with the whole matrix of synchronous 2T2D correlation spectra.

Two-trace two-dimensional (2T2D) correlation applied to a number of spectra beyond a simple pair

The application of two-trace two-dimensional (2T2D) correlation analysis to a number of spectra consisting of more than a simple pair is explored, especially when such spectra are randomly collected without knowing the sampling order. Calculation and interpretation of 2T2D correlation spectra are briefly reviewed, and a systematic procedure to identify the set of characteristic bands, which are mutually asynchronous and least overlapped with each other, is described. 2T2D correlation is applied to individual spectra by selecting a representative reference spectrum, such as the average of the whole dataset. A slice of an asynchronous 2T2D spectrum at a characteristic band is devoid of the spectral contribution from the species represented by the band. Since 2T2D analysis may be applied to the whole set of spectra, and each 2T2D asynchronous spectrum yields a set of slices for different characteristic bands, it is possible to generate a series of 2T2D slices obtained at a given characteristic band. By applying the generalized 2D correlation or a successive 2T2D analysis to such slices, one can obtain excellent estimates of the pure component spectra of the mixture, which are comparable to the results from other curve resolution techniques.

Interactions between polypropylene microplastics (PP-MPs) and humic acid influenced by aging of MPs

As an emerging pollutant, microplastics (MPs) may interact with dissolved organic matter (DOM) which is prevalent in the aqueous environment. Meanwhile, the aging of MPs in the actual environment increases the uncertainty of their environmental fate. Here, the interaction mechanisms between pristine and aged polypropylene microplastics (PP-MPs) and humic acid (HA) at pH 7.0 were explored. Microstructural changes of HA were examined by fluorescence and Fourier transformation infrared (FT-IR) spectroscopy. Atomic force microscopy coupled with infrared (AFM-IR) and micro-Raman techniques were used to characterize and analyze the interacted PP-MPs. The addition of HA increased the surface roughness of both pristine and aged PP-MPs. Results of AFM-IR and Raman spectra showed that the interaction of PP-MPs with HA accelerated their surface oxidation and enhanced the characteristic signals. XPS spectra showed that the oxygen content ratio of pristine and aged PP-MPs increased by 0.95% and 1.48% after the addition of HA, respectively. PP-MPs after aging interacted more strongly with HA and there was a higher affinity between them. Two-dimensional correlation spectroscopy (2D-COS) combined with FT-IR spectra further elucidated the interaction mechanism at the molecular level. This work will help to evaluate the environmental impact of MPs in ecosystems and understand their interactions with DOM.

Estimating more than two pure component spectra from only two mixture spectra using two-dimensional correlation

A procedure is described to estimate the pure component spectra of mixtures from only a pair of available spectra even when there are more than two component species present in the system. In contrast, traditional multivariate curve resolution (MCR) technique cannot be used for such a case. The method relies on the use of two-trace two-dimensional (2T2D) correlation spectroscopy. Asynchronous 2T2D spectrum is used to identify the characteristic bands most strongly associated with the individual mixture component species. Correlation coefficients derived from the synchronous 2T2D spectrum are used to obtain a set of correlative filtering functions to distribute the spectral intensity of the average spectrum among the estimates of the pure component spectra. Efficacy of the method was demonstrated using a pair of ATR IR spectra obtained for two solution mixtures containing three main ingredients with very similar compositions. Relatively congested and overlapped spectral region was used first for the demonstration, and reasonable resolution was accomplished yielding a set of the estimates of pure component spectra with most of the expected pertinent features included. The analysis was then extended to a broader spectral region containing well-isolated spectral signatures of individual components for positive validation. While traditional MCR technique seems to perform better with a large number of spectra, this technique can be effectively used in conjunction with MCR to improve its stability and performance, especially under some challenging conditions.

Process monitoring of photocatalytic degradation of 2,4-dinitrotoluene by Au-decorated Fe3O4@TiO2 nanoparticles: surface-enhanced Raman scattering method

Recently, the degradation and detection of 2,4-dinitrotoluene (2,4-DNT) capable of producing 2,4,6-trinitrotoluene (TNT) for environmental and human health risks have been developed. We prepared photoresponsive Au-decorated Fe₃O₄@TiO₂ nanoparticles (Fe₃O₄@TiO₂-Au NPs) under sunlight simulated Xe lamp irradiation. The photodegradation process of 2,4-DNT by Fe₃O₄@TiO₂-Au NPs was successfully monitored by surface-enhanced Raman scattering (SERS). Since SERS monitoring shows intrinsic information about the molecular structure, it was possible to predict the photodegradation of 2,4-DNT. The 2,4-DNT photodegradation mechanism based on two-dimensional correlation spectroscopy (2D-COS), which provides very beneficial information for a deeper understanding of systems, has been identified. We confirmed that Fe₃O₄@TiO₂-Au NPs can be widely used in organic pollutant degradation under sunlight. Furthermore, the combination of SERS based process monitoring and 2D-COS can be a convincing analytical technique for photodegradation studies of organic pollutants.

Insights into enzymatic mimicking activity of silver nanoprisms: spectral monitoring and analysis

Peroxidase-like reaction process involving o-phenylenediamine (OPD) and silver nanoprisms in the presence of hydrogen peroxide (H₂O₂) was monitored using time-resolved ultraviolet-visible (UV-Vis) absorption spectroscopy. The oxidation of OPD and etching of silver nanoprisms were investigated by analyzing the dynamic spectral data. Two-dimensional correlation spectroscopy (2D-COS) and principal component analysis (PCA) were employed to gain insights into the correlation between catalytic oxidation of OPD and etching of silver nanoprisms. It was found that OPD offered significant protection effect for silver nanoprisms so that morphologies of silver nanoprisms maintained at the beginning period after addition of H₂O₂. Moreover, silver nanoprisms accelerated the oxidation of OPD by H₂O₂, demonstrating enzymatic mimicking activity of silver nanoprisms. The combination of time-resolved UV-Vis absorption spectroscopy and spectral calculation methods could be used for exploration of complex reaction systems with spectral variations.

Copper-binding properties of microplastic-derived dissolved organic matter revealed by fluorescence spectroscopy and two-dimensional correlation spectroscopy

Despite numerous studies on microplastics (MPs), little attention has been paid to the dissolved organic substances leached from MPs and their environmental fate. In this study, we explored the copper-binding characteristics of MP-derived dissolved organic matter (MP-DOM) leached from several MP types, including commercial polypropylene, polyvinylchloride, and expanded polystyrene, under dark and UV irradiation conditions. The copper-binding affinity of MP-DOM was examined using fluorescence quenching method based on different fluorophores identified via the excitation emission matrix-parallel factor analysis (EEM-PARAFAC). The heterogeneous distribution of binding sites across the functional groups of MP-DOM was further elucidated by utilizing two-dimensional correlation spectroscopy (2D-COS) based on Fourier transform infrared spectroscopy (FTIR). Phenol/protein-like fluorescence prevailed in all MP-DOM samples, whereas humic-like fluorescence was more pronounced in the irradiated MP-DOM. For all tested plastic types, two plastic-derived fluorescent components (C2 and C3) exhibited substantial fluorescence quenching with increasing copper concentrations. The calculated stability constants showed larger differences between the two leaching conditions than between the three MP types with higher log K_M values for the UV-irradiated (4.08-5.36) than dark-treated MP-DOM (1.05-3.60). The binding constants were comparable to those of natural organic matter with aquatic/terrestrial origins. The 2D-COS results further revealed that the oxygen-containing structures in MP-DOM generated by UV irradiation might be responsible for the higher binding affinity of the irradiated MP-DOM. This is the first study demonstrating the environmental reactivity of MP-DOM towards metal binding, highlighting the importance of leaching conditions for the metal-binding behavior of MP-DOM.

A Study on Blend Ratio-dependent Far-IR and Low-frequency Raman Spectra and WAXD Patterns of Poly(3-hydroxybutyrate)/poly(4-vinylphenol) Using Homospectral and Heterospectral Two-dimensional Correlation Spectroscopy

An intensive analysis of far-infrared (far-IR), low-frequency Raman, and wide angle X-ray diffraction (WAXD) data has been performed by two-dimensional correlation spectroscopy (2D-COS) as a function of the blend ratio of poly(3-hydroxybutyrate)/poly(4-vinylphenol) (PHB/PVPh). Homospectral 2D-COS revealed that a weak band at 128 cm^-1 in the far-IR spectra appeared more clearly in the 2D correlation spectra. Heterospectral 2D-COS (far-IR/low-frequency Raman and far-IR/WAXD) provided very important results that were hardly detected in the conventional 2D-COS. A far-IR peak at 130 cm^-1 in the heterospectral 2D-COS had negative correlations with the peaks in the low-frequency Raman spectra at 81, 100, and 110 cm^-1 and WAXD profile 8.78 and 11.01°. These results indicated that those peaks have different origins; the 130 cm^-1 peak comes from the intermolecular C=O···H-O hydrogen bond between PHB and PVPh, while those for low-frequency Raman and WAXD peaks are the features of PHB crystalline structure.

PC 2D-COS: A Principal Component Base Approach to Two-Dimensional Correlation Spectroscopy

This paper introduces the newly developed principal component powered two-dimensional (2D) correlation spectroscopy (PC 2D-COS) as an alternative approach to 2D correlation spectroscopy taking advantage of a dimensionality reduction by principal component analysis. It is shown that PC 2D-COS is equivalent to traditional 2D correlation analysis while providing a significant advantage in terms of computational complexity and memory consumption. These features allow for an easy calculation of 2D correlation spectra even for data sets with very high spectral resolution or a parallel analysis of multiple data sets of 2D correlation spectra. Along with this reduction in complexity, PC 2D-COS offers a significant noise rejection property by limiting the set of principal components used for the 2D correlation calculation. As an example for the application of truncated PC 2D-COS a temperature-dependent Raman spectroscopic data set of a fullerene-anthracene adduct is examined. It is demonstrated that a large reduction in computational cost is possible without loss of relevant information, even for complex real world data sets.

Detection of pesticide in water using two-dimensional fluorescence correlation spectroscopy and N-way partial least squares

To determine the concentration of carbaryl and chlorothalonil in water, the potential of two-dimensional (2D) fluorescence correlation spectra with N-way partial least squares (N-PLS) was investigated. A total of 40 mixture solutions of carbaryl and chlorothalonil were prepared and 27 of them were used to form a calibration set. The excitation-emission matrix (EEM) fluorescence spectra of all samples were measured. Under the excitation perturbation, 2D fluorescence correlation spectra of all samples were calculated and formed a 2D correlation spectral matrix. And N-PLS models for determination of carbaryl and chlorothalonil in water were built based on 2D correlation fluorescence spectral matrix and traditional EEM spectral matrix, respectively. Finally, the performances of N-PLS models using both methods were compared. For chlorothalonil, the root mean square error of calibration (RMSEC) were 3.43 × 10^-6 g L^-1 and 5.08 × 10^-6 g L^-1, the root mean square errors of prediction (RMSEP) were 5.86 × 10^-6 g L^-1 and 8.99 × 10^-6 g L^-1 for 2D correlation spectra and EEM spectra, respectively. For carbaryl, the RMSEC were 5.24 × 10^-7 g L^-1 and 6.18 × 10^-7, the RMSEP were 9.20 × 10^-7 g L^-1 and 9.63 × 10^-7 g L^-1 for 2D correlation spectra and EEM spectra, respectively. From the results of this study, it may conclude that 2D fluorescence correlation spectra is superior over the traditional EEM fluorescence spectra in terms of predictability and can be used as an alternative method for detection of organic pollutants in environment.

Development of correlation spectroscopy (COS) method for analyzing fluorescence excitation emission matrix (EEM): A case study of effluent organic matter (EfOM) ozonation

Two-dimensional correlation spectroscopy (2DCOS) has been used as a powerful tool for analyzing spectral features, but it has never been applied to fluorescence excitation-emission matrix (EEM) data due to the incompatible dimensions. This study first investigated EEM-COS by reducing the dimensions of the EEM (using parallel factor analysis, PARAFAC) for fitting to 2DCOS (EEM-PARAFAC-COS). The fluorescence changes of effluent organic matter (EfOM) during ozonation were studied using EEM-COS and synchronous fluorescence (SF)-2DCOS. The conventionally used SF-2DCOS proved to be biased due to the intrinsic drawback of SF, while the EEM-PARAFAC-COS gave accurate and trustworthy results. Homo-EEM-PARAFAC-COS indicated that the fluorescence protein-like and fulvic-like substances in EfOM were preferentially ozonated compared to humic-like substances. Hetero-EEM-PARAFAC-COS analyses on the EEM, FTIR, UV-vis absorbance, and size-exclusion chromatography showed that the fluorescence protein-like and fulvic-like substances in EfOM were associated with lower molecular weight (MW, ∼0.95 kDa), UV absorbance at ∼280 nm, and more electron-enriched aromatics (with amide and phenolic groups), which explained their ozonation preference, while humic-like substances were related to carboxylic groups, UV absorbance at ∼255 nm, and organics at MW of ∼4.50 kDa. This work demonstrated the great potential of EEM-PARAFAC-COS in studying fluorescence change and correlating fluorescence with other spectra.

Two-Dimensional Correlation Spectroscopy (2D-COS) for Analysis of Spatially Resolved Vibrational Spectra

The last two decades have seen tremendous progress in the application of two-dimensional correlation spectroscopy (2D-COS) as a versatile analysis method for data series obtained using a large variety of different spectroscopic modalities, including infrared (IR) and Raman spectroscopy. The analysis technique is applicable to a series of spectra recorded under the influence of an external sample perturbation. Two-dimensional COS analysis is not only helpful to decipher correlations, which may exist between distinct spectral features, but can also be utilized to obtain the sequence of individual spectral changes. The focus of this review article is on the application of 2D-COS for analyzing spatially resolved data with special emphasis on hyperspectral imaging (HSI) study. In this review, we briefly introduce the fundamentals of the generalized 2D-COS analysis approach, discuss specific points of 2D-COS application to spatially resolved spectra and demonstrate essential aspects of data pre-processing for 2D-COS analysis of spatially resolved spectra. Based on illustrative examples, we show that 2D-COS is useful for spectral band assignment in HSI applications and demonstrate its utility for detecting subtle correlations between spectra features, or between features from different imaging modalities in the case of heterospectral (multimodal) HSI. Furthermore, a short overview on existing 2D-COS software tools is provided. It is hoped that this article represents not only a useful guideline for 2D-COS analyses of spatially resolved hyperspectral data but supports also further dissemination of the 2D-COS analysis method as a whole.

Two-dimensional correlation and codistribution spectroscopy (2DCOS and 2DCDS) analyses of time-dependent ATR IR spectra of d-glucose anomers undergoing mutarotation process in water

Two cyclic diastereoisomeric structures, known as α- and β-anomers of d-glucose with different configurations around C1 with OH groups in axial or equitroial positions, undergo the mutarotation conversion to each other in water. Two-dimensional correlation and codistribution spectroscopy (2DCOS and 2DCDS) analyses were applied to the time-dependent ATR IR spectra of aqueous solutions of α- and β-d-glucose undergoing such mutarotation conversion. 2DCOS analysis reveals that the increase and decrease in the IR intensities after the dissolution of α- or β-d-glucose are not fully synchronized, suggesting the mutarotation of d-glucose in water is not a simple binary conversion process but a multi-step reaction involving an intermediate species with a finite and observable concentration level and lifetime. 2DCDS analysis of the time-dependent ATR IR spectra clearly demonstrated the presence of intermediate species contributing to the band positions overlapped close to bands for α- and β-d-glucose. The fact that band positions identified for the intermediate species for α- to β-d-glucose conversion are the same for the reverse reaction suggests that they arise from the same species, most likely the open-ring structure produced by the hydrolysis.

Two-dimensional correlation spectroscopic studies on coordination between organic ligands and Ni2+ ions

³A_2g→³T_1g(P) transition band of Ni²⁺ is used to probe the coordination of Ni²⁺. Two-dimensional asynchronous spectra (2DCOS) are generated using the Double Asynchronous Orthogonal Sample Design (DAOSD), Asynchronous Spectrum with Auxiliary Peaks (ASAP) and Two-Trace Two-Dimensional (2T2D) approaches. Cross peaks relevant to the ³A_2g→³T_1g(P) transition band of Ni²⁺ are utilized to probe coordination between Ni²⁺ and various ligands. We studied the spectral behavior of the ³A_2g→³T_1g(P) transition band when Ni²⁺ is coordinated with ethylenediaminetetraacetic acid disodium salt (EDTA). The pattern of cross peaks in 2D asynchronous spectrum demonstrates that coordination brings about significant blue shift of the band. In addition, the absorptivity of the band increases remarkably. The interaction between Ni²⁺ and galactitol is also investigated. Although no clearly observable change is found on the ³A_2g→³T_1g(P) transition band when galactitol is introduced, the appearance of cross peak in 2D asynchronous spectrum demonstrates that coordination indeed occurs between Ni²⁺ and galactitol. Furthermore, the pattern of cross peak indicates that peak position, bandwidth and absorptivity of the ³A_2g→³T_1g(P) transition band of Ni(galactitol)_x²⁺ is considerably different from those of Ni(H₂O)₆²⁺. Thus, 2DCOS is helpful to reveal subtle spectral variation, which might be helpful in shedding light on the physical-chemical nature of coordination.

Smooth Factor Analysis (SFA) to Effectively Remove High Levels of Noise from Spectral Data Sets

Smooth factor analysis (SFA) is introduced as an effective method of removing heavy noise from spectral data sets. A modified form of the nonlinear iterative partial least squares (NIPALS) algorithm involving the smoothing of factors at each step is used in SFA. Compared with the conventional smoothing techniques for individual spectra, SFA is much more effective in the treatment of very noisy spectra (∼40% noise level). Smooth factor analysis invokes a large number of smooth factors to retain pertinent spectral information for high fidelity without distortion. This approach can be used as an effective general pretreatment procedure for multivariate spectral data analysis, such as principal component analysis (PCA) and partial least squares (PLS). This SFA method was also applied to the real experimental data, and its results successfully demonstrated the powerful potential for effective noise removal. Furthermore, this treatment is found to be very helpful to assist effective interpretation of two-dimensional correlation spectroscopy (2D-COS) spectra with very high noise level, which was not possible before.

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.

Using two-dimensional correlation size exclusion chromatography (2D-CoSEC) to explore the size-dependent heterogeneity of humic substances for copper binding

Knowledge of the heterogeneous distribution of humic substances (HS) reactivities along a continuum of molecular weight (MW) is crucial for the systems where the HS MW is subject to change. In this study, two dimensional correlation spectroscopy combined with size exclusion chromatography (2D-CoSEC) was first utilized to obtain a continuous and heterogeneous presence of copper binding characteristics within bulk HS with respect to MW. HS solutions with varying copper concentrations were directly injected into a size exclusion chromatography (SEC) system with Tris-HCl buffer as a mobile phase. Several validation tests confirmed neither structural disruption of HS nor competition effect of the mobile phase used. Similar to batch systems, fluorescence quenching was observed in the chromatograms over a wide range of HS MW. 2D-CoSEC maps of a soil-derived HS (Elliot soil humic acid) showed the greater fluorescence quenching degrees with respect to the apparent MW on the order of 12500 Da > 10600 Da > 7000 Da > 15800 Da. The binding constants calculated based on modified Stern-Volmer equation were consistent with the 2D-CoSEC results. More heterogeneity of copper binding affinities within bulk HS was found for the soil-derived HS versus an aquatic HS. The traditional fluorescence quenching titration method using ultrafiltered HS size fractions failed to delineate detailed distribution of the copper binding characteristics, exhibiting a much shorter range of the binding constants than those obtained from the 2D-CoSEC. Our proposed technique demonstrated a great potential to describe metal binding characteristics of HS at high MW resolution, providing a clear picture of the size-dependent metal-HS interactions.

Investigation on the relationship between solubility of artemisinin and polyvinylpyrroli done addition by using DAOSD approach

In this work, we investigated the influence of polyvinylpyrrolidone (PVP) on the solubility of artemisinin in aqueous solution by using quantitative ¹H NMR. Experimental results demonstrate that about 4 times of incremental increase occurs on the solubility of artemisinin upon introducing PVP. In addition, dipole-dipole interaction between the ester group of artemisinin and the amide group of N-methylpyrrolidone (NMP), a model compound of PVP, is characterized by two-dimensional (2D) correlation FTIR spectroscopy with the DAOSD (Double Asynchronous Orthogonal Sample Design) approach developed in our previous work. The observation of cross peaks in a pair of 2D asynchronous spectra suggests that dipole-dipole interaction indeed occurs between the ester group of artemisinin and amide group of NMP. Moreover, the pattern of cross peaks indicates that the carbonyl band of artemisinin undergoes blue-shift while the bandwidth and absorptivity increases via interaction with NMP, and the amide band of NMP undergoes blue-shift while the absorptivity increases via interaction with artemisinin. Dipole-dipole interaction, as one of the strongest intermolecular interaction between artemisinin and excipient, may play an important role in the enhancement of the solubility of artemisinin in aqueous solution.

Intra-molecular interactions dominating the dehydration of a poly(2-isopropyl-2-oxazoline)-based densely grafted polymer comb in aqueous solution and hysteretic liquid–liquid phase separation

Temperature-induced association and hysteretic LLPS process of a poly(2-isopropyl-2-oxazoline) (PiPOx)-based polymer comb in water.