Curing reaction of glycidylthioether resins: Kinetic model study by near infrared spectroscopy and multivariate curve resolution

The reactivity of sulfur‐based epoxy monomers was studied by monitoring of a model system involving phenylglycidylthioether and aniline. The reaction was carried out under isothermal conditions and monitored in situ by near infrared spectroscopy. Using multivariate curve resolution‐alternating least squares made it possible to obtain the concentration and spectral profiles of each species throughout the reaction. To obtain the kinetic rate constants, the values of the recovered concentration profiles were fitted to a kinetic model proposed for the reaction. Reactivity was evaluated by comparing the concentration profiles and kinetic rate constants obtained with the same parameters obtained for phenylglycidylether/aniline as a reference system. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 4846–4856, 2006     

Optical coefficient‐based multivariate calibration on near‐infrared spectroscopy

The time and expense of calibration development limit the feasibility of NIR spectroscopy for many industrial applications, with a major portion of the costs being related to creation of a sufficient set of calibration samples. Net analyte signal (NAS) and generalized least squares (GLS) pre‐processing have been proposed in the literature as methods to simplify multivariate calibration by reducing the quantity of calibration samples by orthogonalizing or shrinking interference signals. Synthetic calibration has also been reported as a method to combine interference signals with pure component spectra to generate virtual calibration models, thereby reducing the number of real calibration samples required. The goals of this paper were to (1) compare theoretical and practical differences between NAS and GLS pre‐processing and (2) explore the potential of simplified NIR calibrations, both empirical and synthetic, constructed using optical coefficient‐based signal processing on predicting chemical compositions of pharmaceutical powder mixtures. A reduced calibration dataset including only one pharmaceutical powder mixture composition and pure component spectra was used for both empirical and synthetic calibrations. Absorption and reduced scattering coefficients, obtained from spatially‐resolved spectroscopy, were used herein as interference signals in NAS/GLS pre‐processing for both calibrations. As a result, NAS and GLS were shown to be equivalent in both theoretical and practical senses. After optical coefficient‐based signal processing, simplified calibrations, both empirical and synthetic, were demonstrated to have similar model performance as generic pre‐processing methods such as SNV and derivative, while requiring fewer principal components and achieving a lower prediction error. Copyright © 2010 John Wiley & Sons, Ltd.     

Application of two‐dimensional near‐infrared (2D‐NIR) correlation spectroscopy to the discrimination of three species of Dendrobium

The objective of this paper was to apply two‐dimensional (2D) near‐infrared (NIR) correlation spectroscopy to the discrimination of three species of Dendrobium. Generalized 2D‐NIR correlation spectroscopy was able to enhance spectral resolution, simplify the spectrum with overlapped bands and provide information about temperature‐induced spectral intensity variations that was hard to obtain from one‐dimensional NIR spectroscopy. The FT‐NIR spectra were measured over a temperature range of 30–140°C. The 2D synchronous and asynchronous spectra showed remarkable differences within the range of 5600–4750 cm⁻¹ between different species of Dendrobium. Copyright © 2009 John Wiley & Sons, Ltd.     

A heuristic and parallel simulated annealing algorithm for variable selection in near‐infrared spectroscopy analysis

A new heuristic and parallel simulated annealing algorithm was proposed for variable selection in near‐infrared spectroscopy analysis. The algorithm employs a parallel mechanism to enhance the search efficiency, a heuristic mechanism to generate high‐quality candidate solutions, and the concept of Metropolis criterion to estimate accuracy of the candidate solutions. Several near‐infrared datasets have been evaluated under the proposed new algorithm, with partial least squares leading to improved analytical figures of merit upon wavelength selection. Improved robust and predictive regression models were obtained by the new algorithm. The method could also be helpful in other chemometric activities such as classification or quantitative structure‐activity relationship problems.     

Use of indirect multivariate calibration for quality control of agricultural products by near infrared spectroscopy

In the near infrared (NIR) region, (=800–2500 nm) of the spectrum, most organic molecules have weak but reproducibly measurable absorption bands. This phenomenon has been increasingly exploited for the rapid, quantitative analysis of major constituents of agricultural products. As there is strong spectral overlap and an interaction of constituents in NIR, the calibration of instrumentation has to be performed indirectly with a training set of samples applying multivariate methods. A software package for IBM compatible personal computers includes programs to select samples to be used for calibration, to compute multiple linear regression equations, to cross-validate regression equations and to detect unusual samples. These methods are applied to rapidly determine the oil content of over a thousand rapeseed samples of the harvest of 1986. A considerable saving of time, labour, and costs can be achieved, the agreement with the standard laboratory method is very satisfactory.     

Two-dimensional correlation spectroscopy and multivariate curve resolution for the study of lipid oxidation in edible oils monitored by FTIR and FT-Raman spectroscopy

Accelerate oxidative degradation of six vegetable oils was monitored using FTIR and FT-Raman spectroscopy. Two-dimensional correlation spectroscopy and multivariate curve resolution alternating least squares (MCR-ALS) were applied to the analysis of the data. The use of hetero-spectral two-dimensional correlation of FTIR and FT-Raman data allowed the use of well established band assignments to interpret less clearly assigned spectral features. With a moving window approach it was possible to obtain simplified two-dimensional correlation maps and to detect compounds evolving with different kinetic. Simultaneous analysis of the oxidation experiments of the six different oils monitored by both spectroscopic techniques was performed using MCR-ALS. Although a complete resolution of the data was not possible, the spectral changes occurring during the oxidative degradation of the oils were described with a five-component model. The two fundamentally different chemometric approaches lead to coincident results.     

Quantitative analysis of tea using ytterbium‐based internal standard near‐infrared spectroscopy coupled with boosting least‐squares support vector regression

The present study demonstrated the possibility of utilizing the ytterbium (Yb)‐based internal standard near‐infrared (NIR) spectroscopic measurement technique coupled with multivariate calibration for quantitative analysis of tea, including total free amino acids and total polyphenols in tea. Yb is a rare earth element aimed to compensate for the spectral variation induced by the alteration of sample quantity during the spectral measurement of the powdered samples. Boosting was invoked to be combined with least‐squares support vector regression (LS‐SVR), forming boosting least‐squares support vector regression (BLS‐SVR) for the multivariate calibration task. The results showed that the tea quality could be accurately and rapidly determined via the Yb‐based internal standard NIR spectroscopy combined with BLS‐SVR method. Moreover, the introduction of boosting drastically enhanced the performance of individual LS‐SVR, and BLS‐SVR compared favorably with partial least‐squares regression. Copyright © 2013 John Wiley & Sons, Ltd.     

Highly near‐infrared photoluminescence from aza‐borondipyrromethene‐based conjugated polymers

Near‐infrared (NIR) emissive conjugated polymers were prepared by palladium‐catalyzed Sonogashira polymerization of diiodobenzene‐functionalized aza‐borondipyrromethene (Aza‐BODIPY) monomers, which were substituted at 3 and 5 or 1 and 7 positions on the Aza‐BODIPY core, with 1,4‐diethynyl‐2,5‐dihexadecyloxybenzene or 3,3′‐didodecyl‐2,2′‐diethynyl‐5,5′‐bithiophene. The structures of the polymers were confirmed by ¹H NMR, ¹³C NMR, ¹¹B NMR, Fourier transform infrared (FT‐IR) spectroscopies, and size exclusion chromatography (SEC). The optical properties were then characterized by UV–vis absorption and photoluminescence (PL) spectroscopies, and theoretical calculation using density‐functional theory (DFT) method. The polymers were fusible and soluble in common organic solvents including tetrahydrofuran (THF), o‐xylene, toluene, CHCl₃, and CH₂Cl₂, etc. The UV–vis absorption and PL spectra of the polymers shifted to long wavelength region in comparison with simple Aza‐BODIPY as the counterpart because of extended π‐conjugation of the polymers. The polymers efficiently emitted NIR light with narrow emission bands at 713～777 nm on excitation at each absorption maximum. Especially, the polymer attached 1,4‐diethynyl‐2,5‐dihexadecyloxybenzene to 3,5‐position on the core revealed intense quantum yields (?_F = 24%) in this NIR region (753 nm). © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2010     

Detection of malathion in food peels by surface-enhanced Raman imaging spectroscopy and multivariate curve resolution

An analytical methodology was developed for detection of malathion in the peels of tomatoes and Damson plums by surface-enhanced Raman imaging spectroscopy and multivariate curve resolution. To recover the pure spectra and the distribution mapping of the analyzed surfaces, non-negative matrix factorization (NMF), multivariate curve calibration methods with alternating least squares (MCR-ALS) and MCR with weighted alternating least square (MCR-WALS) were utilized. Error covariance matrices were estimated to evaluate the structure of the error over all the data. For the tomato data, NMF-ALS and MCR-ALS presented excellent spectral recovery even in the absence of initial knowledge of the pesticide spectrum. For the Damson plum data, owing to heteroscedastic noise, MCR-WALS produced better results. This methodology enabled detection below to the maximum residue limit permitted for this pesticide. This approach can be implemented for in situ monitoring because it is fast and does not require extensive manipulation of samples, making its use feasible for other fruits and pesticides as well.     

Semiconducting polymer dots as near‐infrared fluorescent probes for bioimaging and sensing

In recent years, semiconducting polymer dots (Pdots) have emerged as a new type of ultrabright fluorescent probes, which have been proved to be very useful for biomedical imaging. Pdots possess several exceptional advantages including high fluorescence brightness, fast radiative rate, excellent photostability, and negligible cytotoxicity. Among these new types of Pdots, the near‐infrared (NIR) fluorescent Pdots appear to be the most urgent and important owing to their promising deep‐tissue imaging in the clinic. This mini‐review highlights the recent progress in the design of NIR‐emitting Pdots and their biomedical applications both in vitro and in vivo.     

Matrix merging arrangements for the study protein dynamics by time-resolved step-scan Fourier transform infrared spectroscopy and multivariate curve resolution

In this paper, we propose the construction of merging arrangements for combining the information from various runs as a powerful approach to improve the resolution. The bacteriorhodopsin (bR) photocycle has been chosen in this study as an example dealing with the protein dynamics monitored by means of time-resolved step-scan FT-IR spectroscopy. The possibilities of matrix merging are evaluated and results are compared with those from the analysis of individual and augmented matrices. As a conclusion, this strategy provides excellent results for the analysis of this type of time-resolved FT-IR data.     

Combining convolutional neural networks and in‐line near‐infrared spectroscopy for real‐time monitoring of the chromatographic elution process in commercial production of notoginseng total saponins

The chromatographic elution process is a key step in the production of notoginseng total saponins. Due to quality variability of loading samples and resin capacity decreasing over cycle time, saponins, especially the five main saponins of notoginseng total saponins, need to be monitored in real time during the elution process. In this study, convolutional neural networks, one of the most popular deep learning methods, were used to develop quantitative calibration models based on in‐line near‐infrared spectroscopy for notoginsenoside R₁, ginsenosides Rg₁, Re, Rb₁ and Rd, and their sum concentration, with root mean square error of prediction values of 0.87, 2.76, 0.60, 1.57, 0.28, and 4.99 mg/mL, respectively. Partial least squares calibration models were also developed for model performance comparison. Results show predicted concentration profiles outputted by both the convolutional neural network models and partial least squares models show agreements with the real trends defined by reference measurements, and can be used for elution process monitoring and endpoint determination. To the best of our knowledge, this is the first reported case study of combining convolutional neural networks and in‐line near‐infrared spectroscopy for monitoring of the chromatographic elution process in commercial production of botanical drug products.     

Bay‐annulated indigo based near‐infrared sensitive polymer for organic solar cells

A new conjugated polymer (PBAIIDTT) based on bay‐annulated indigo and indacenodithieno[3,2‐b]thiophene was designed, synthesized, and characterized. PBAIIDTT shows strong absorption in 400–500 and 600–800 nm, and its HOMO and LUMO energy levels are −5.45 eV and −3.65 eV, respectively. In organic field‐effect transistors, the polymer exhibits a relatively high hole mobility of 0.39 cm² V⁻¹ s⁻¹. PBAIIDTT was added to poly(3‐hexylthiophene) (P3HT) and phenyl‐C₆₁‐butyric acid methyl ester (PC₆₁BM) based organic solar cells. Ternary blend solar cells with 10% PBAIIDTT show an increased short circuit current density due to the broadened photocurrent generated in the near‐infrared region, and a power conversion efficiency of 3.78%, which is higher than that of the P3HT:PC₆₁BM binary control devices (3.33%). © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018 , 56, 213–220     

Highly near‐infrared emissive boron di(iso)indomethene‐based polymer: Drastic change from deep‐red to near‐infrared emission via quantitative polymer reaction

It is challenging to realize the near‐infrared (NIR) emission with large brightness and sharp spectra from the conjugated polymers. In this study, we demonstrate the strategy for receiving strong and pure NIR emission from polymeric materials using organoboron complexes and the modification after polymerization. A series of NIR emissive conjugated polymers with boron di(iso)indomethenes (BODINs) and fluorene or bithiophene were synthesized by Suzuki–Miyaura coupling reaction. The obtained polymers exhibited high emissions in the range from deep‐red to NIR region (quantum yields: ?_PL = 0.40–0.79, full width at half maximum height: Δλ_1/2 = 660–940 cm^?1, emission maxima: λ_PL = 686–714 nm). Next, the demethylation of the BODIN‐based polymer with o‐methoxyphenyl groups was carried out. The transformation of the polymer structure quantitatively proceeded via efficient intramolecular crosslinking through the intermediary of the boron atom. Finally, the resulting polymer showed both drastically larger red‐shifted and sharper photoluminescence spectrum than that of the parent polymer with deep‐red emission (?_PL = 0.37, Δλ_1/2 = 460 cm^?1, λ_PL = 758 nm). © 2013 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2013     

Estimation of rotation ambiguity in multivariate curve resolution with charged particle swarm optimization (cPSO‐MCR)

Rotation ambiguity (RA) in multivariate curve resolution (MCR) is an undesirable case, when the physicochemical constraints are not sufficiently strong to provide a unique resolution of the data matrix of the mixtures into spectra and concentration profiles of individual chemical components. RA is often met in MCR of overlapped chromatographic peaks, kinetic and equilibrium data, and fluorescence two‐dimensional spectra. In case of RA, a single candidate solution has little practical value. So, the whole set of feasible solutions should be characterized somehow. It is a quite intricate task in a general case. In the present paper, a method was proposed to estimate RA with charged particle swarm optimization (cPSO), a population‐based algorithm. The criteria for updating the particles were modified, so that the swarm converged to the steady state, which spanned the set of feasible solutions. The performance of cPSO‐MCR was demonstrated on test functions, simulated datasets, and real‐world data. Good accordance of the cPSO‐MCR results with the analytical solutions (Borgen plots) was observed. cPSO‐MCR was also shown to be capable of estimating the strength of the constraints and of revealing RA in noisy data. As compared with analytical methods, cPSO‐MCR is simpler to implement, expands to more than three chemical compounds, is immune to noise, and can be easily adapted to virtually all types of constraints and objective functions (constraint based or residue based). cPSO‐MCR also provides natural visual information about the level of RA in spectra and concentration profiles, similar to the methods of two extreme solutions (e.g., MCR‐BANDS). Copyright © 2014 John Wiley & Sons, Ltd.     

Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution

This paper presents the quantification of Penicillin V and phenoxyacetic acid, a precursor, inline during Pencillium chrysogenum fermentations by FTIR spectroscopy and partial least squares (PLS) regression and multivariate curve resolution – alternating least squares (MCR-ALS). First, the applicability of an attenuated total reflection FTIR fiber optic probe was assessed offline by measuring standards of the analytes of interest and investigating matrix effects of the fermentation broth. Then measurements were performed inline during four fed-batch fermentations with online HPLC for the determination of Penicillin V and phenoxyacetic acid as reference analysis. PLS and MCR-ALS models were built using these data and validated by comparison of single analyte spectra with the selectivity ratio of the PLS models and the extracted spectral traces of the MCR-ALS models, respectively. The achieved root mean square errors of cross-validation for the PLS regressions were 0.22 g L⁻¹ for Penicillin V and 0.32 g L⁻¹ for phenoxyacetic acid and the root mean square errors of prediction for MCR-ALS were 0.23 g L⁻¹ for Penicillin V and 0.15 g L⁻¹ for phenoxyacetic acid. A general work-flow for building and assessing chemometric regression models for the quantification of multiple analytes in bioprocesses by FTIR spectroscopy is given.     

A new near‐infrared switchable electrochromic polymer and its device application

A new near‐infrared switchable electrochromic polymer containing carbazole pendant (poly‐SNSC), synthesized by electrochemical polymerization of 2,5‐bis‐dithienyl‐1H‐pyrrole (SNS) main chain, has been prepared. The electrochemical and optical properties of SNSC monomer and its polymer have been investigated. Because of having two different electro‐donor moieties; that is, carbazole and SNS, SNSC gave two separate electrochemical oxidation and also light brown color of the film in the neutral state turn into gray on oxidation. An electrochromic device, contructed in the sandwich configuration [indium tin oxide (ITO)‐coated glass/anodically coloring polymer (poly‐SNSC)//gel electrolyte//cathodically coloring polymer (PEDOT)/ITO‐coated glass] and exhibited a high coloration efficiency (1216 cm² C^–1), a very short response time (about 0.3 s), low driving voltage, and a high redox stability. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2010     

Multivariate control charts based on NAS and mid‐infrared spectroscopy for quality control of B5 blends of methyl soybean biodiesel in diesel

In this work, mid‐infrared spectroscopy and multivariate control charts based on net analyte signal were applied for quality control of B5 blends of biodiesel/diesel (5% biodiesel/95% diesel). Control charts were constructed using instrumental signal decomposition, generating three charts: the net analyte signal chart for monitoring the analyte of interest (methyl soybean biodiesel); the interference chart, which corresponds to the contribution of all other compounds in the diesel sample (diesel); and the residual chart, which corresponds to non‐systematic variations. Statistical limits were established for each developed chart, using samples inside quality specifications (normal operation conditions). To validate multivariate control charts, new samples were analyzed. The new samples represented samples in‐control and samples out‐of‐control in relation to the content of biodiesel, adulterated biodiesel with severe vegetable oils and adulterated diesel with residual automotive lubricant oil, kerosene, and gasoline. The results obtained show an excellent distinction between the samples inside and out of the quality specifications, with 91% and 100% correctly classified, respectively, which demonstrates that the methodology developed is a viable alternative for quality monitoring of this type of fuel. Copyright © 2015 John Wiley & Sons, Ltd.     

In situ real-time monitoring of a diglycidyl ether of bisphenol a epoxy resin modified with poly(etherimide)/polysulphone blends by simultaneous dielectric/near-infrared spectroscopy

Simultaneous dielectric and near infrared measurements were performed in “real-time” to follow polymerisation reactions on blends of a diglycidyl ether of bisphenol A (DGEBA) epoxy resin with 4,4′-diaminodiphenylmethane (DDM) hardener and a mixture of polysulphone (PSU) and polyetherimide (PEI) as modifier. All the blends had a 10 wt% of PSU/PEI mixture. The effect of the PEI/PSU ratio in the mixture was studied. Monitoring of the α-relaxation (related to vitrification) was performed by dielectric measurements, while epoxy conversion was followed by near infrared spectroscopy. The effect of the PEI/PSU ratio on this behaviour was studied, as well as that of the curing temperature. Obtained results were compared with that of the blends with neat PSU and PEI as modifiers.     

Resolution and identification of co‐eluting alkylphenols in comprehensive two‐dimensional gas chromatography–mass spectrometry by multivariate curve resolution‐alternating least squares

The interest in the analysis of alkylphenols (APs) has widely increased in the last decades because of the endocrine disrupting features of these phenol derivatives. However, the isolation and identification of many of the multiple chemical structures of all APs is a very challenging task because of their similar physicochemical properties. In this work, the co‐elution of the isomers present in technical mixtures and using comprehensive two‐dimensional gas chromatography coupled to quadrupole mass spectrometry was resolved using multivariate curve resolution‐alternating least squares algorithm. The mass spectrum of each resolved compound was compared with the theoretical mass spectrum obtained from the literature, in order to assign the appropriate identification of each isomer. Two commercial mixtures were studied; in one of them, 34 compounds were resolved, and in the second mixture, 40 compounds were resolved. The relative abundances of the compounds were also calculated in both mixtures. Copyright © 2015 John Wiley & Sons, Ltd.