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We demonstrate a recognition and feature visualization method that uses a deep convolutional neural network for Raman spectrum analysis. The visualization is achieved by calculating important regions in the spectra from weights in pooling and fully-connected layers. The method is first examined for simple Lorentzian spectra, then applied to the spectra of pharmaceutical compounds and numerically mixed amino acids. We investigate the effects of the size and number of convolution filters on the extracted regions for Raman-peak signals using the Lorentzian spectra. It is confirmed that the Raman peak contributes to the recognition by visualizing the extracted features. A near-zero weight value is obtained at the background level region, which appears to be used for baseline correction. Common component extraction is confirmed by an evaluation of numerically mixed amino acid spectra. High weight values at the common peaks and negative values at the distinctive peaks appear, even though the model is given one-hot vectors as the training labels (without a mix ratio). This proposed method is potentially suitable for applications such as the validation of trained models, ensuring the reliability of common component extraction from compound samples for spectral analysis. Image 1 • A recognition and trained feature visualization that uses a CNN are demonstrated. • Raman peak extraction and near-zero feature value at background region are obtained. • Common component and extraordinary peak extraction from mixed spectra are confirmed. [ABSTRACT FROM AUTHOR]

Generative adversarial linear discriminant analysis (GALDA) is formulated as a broadly applicable tool for increasing classification accuracy and reducing overfitting in spectrochemical analysis. Although inspired by the successes of generative adversarial neural networks (GANs) for minimizing overfitting artifacts in artificial neural networks, GALDA was built around an independent linear algebra framework distinct from those in GANs. In contrast to feature extraction and data reduction approaches for minimizing overfitting, GALDA performs data augmentation by identifying and adversarially excluding the regions in spectral space in which genuine data do not reside. Relative to non-adversarial analogs, loading plots for dimension reduction showed significant smoothing and more prominent features aligned with spectral peaks following generative adversarial optimization. Classification accuracy was evaluated for GALDA together with other commonly available supervised and unsupervised methods for dimension reduction in simulated spectra generated using an open-source Raman database (Romanian Database of Raman Spectroscopy, RDRS). Spectral analysis was then performed for microscopy measurements of microsphereroids of the blood thinner clopidogrel bisulfate and in THz Raman imaging of common constituents in aspirin tablets. From these collective results, the potential scope of use for GALDA is critically evaluated relative to alternative established spectral dimension reduction and classification methods. [Display omitted] • Generative adversarial linear discriminant analysis (GALDA) was developed for spectral classification. • A theoretical foundation for implementing GALDA for spectral dimension reduction and classification was derived. • Simulations with known ground truth spectral classes supported the assessment of GALDA. • Application of GALDA improved classification accuracy in polymorph discrimination by conventional Raman spectroscopy. • Pixel-wise application of GALDA produced composition maps in good agreement with manual assignments for model system. [ABSTRACT FROM AUTHOR]

Many chemometric tools are invaluable and have proven effective in data mining and substantial dimensionality reduction of highly multivariate data. This becomes vital for interpreting various physicochemical data due to rapid development of advanced analytical techniques, delivering much information in a single measurement run. This concerns especially spectra, which are frequently used as the subject of comparative analysis in e.g. forensic sciences. In the presented study the microtraces collected from the scenarios of hit-and-run accidents were analysed. Plastic containers and automotive plastics (e.g. bumpers, headlamp lenses) were subjected to Fourier transform infrared spectrometry and car paints were analysed using Raman spectroscopy. In the forensic context analytical results must be interpreted and reported according to the standards of the interpretation schemes acknowledged in forensic sciences using the likelihood ratio approach. However, for proper construction of LR models for highly multivariate data, such as spectra, chemometric tools must be employed for substantial data compression. Conversion from classical feature representation to distance representation was proposed for revealing hidden data peculiarities and linear discriminant analysis was further applied for minimising the within-sample variability while maximising the between-sample variability. Both techniques enabled substantial reduction of data dimensionality. Univariate and multivariate likelihood ratio models were proposed for such data. It was shown that the combination of chemometric tools and the likelihood ratio approach is capable of solving the comparison problem of highly multivariate and correlated data after proper extraction of the most relevant features and variance information hidden in the data structure. [ABSTRACT FROM AUTHOR]

Abstract: Both near-infrared (NIR) and Raman spectroscopy have been studied for the quantitative measurement of components (H3PO4, HNO3, and CH3COOH) in an etchant solution and the corresponding prediction robustness has been evaluated. Both measurements were accomplished by illuminating radiation directly through a Teflon tube. Raman spectral features of each component were much clearer and more selective than those observed in the NIR spectrum. Especially, NIR spectral variation pertinent to H3PO4 and HNO3 were mostly based on the displacement and perturbation of water bands rather than due solely to NIR absorption. Therefore, the resulting spectral variations were not highly specific. When the validation set contained minor spectral variations resulting from a slight instrumental change, NIR prediction performance for all three components degraded substantially by showing obvious prediction bias. However, the accuracies of Raman predictions were maintained. Since partial least squares (PLS) models for each component were built using NIR spectra of poor specificity with broadly overlapping features, even minor spectral differences introduced by instrumental variations sensitively influenced the prediction performance of the NIR models. Overall, the selectivity (specificity) of a targeting spectroscopic method should be considered critically to secure prediction robustness for monitoring components in an etchant solution. [Copyright &y& Elsevier]

Abstract: Knowledge and control of the polymorphic phases of chemical compounds are important aspects of drug development in the pharmaceutical industry. Salmeterol xinafoate, a long acting β-adrenergic receptor agonist, exists in two polymorphic Forms, I and II. Raman and near infrared spectra were obtained of these polymorphs at selected wavelengths in the range of 488–1064nm; significant differences in the Raman and near-infrared spectra were apparent and key spectral marker bands have been identified for the vibrational spectroscopic characterisation of the individual polymorphs which were also characterised with X ray diffractometry. The solid-state transition of salmeterol xinafoate polymorphs was studied using simultaneous in situ portable Raman spectroscopy and differential scanning calorimetry isothermally between transitions. This method assisted in the unambiguous characterisation of the two polymorphic forms by providing a simultaneous probe of both the thermal and vibrational data. The study demonstrates the value of a rapid in situ analysis of a drug polymorph which can be of potential value for at-line in-process control. [Copyright &y& Elsevier]

Abstract: A ball lens hollow-fiber Raman probe (BHRP) is a powerful tool for in vivo nondestructive subsurface analysis of biomedical tissues in a living body. It has confocal-like optical properties, but its collection volume is rather large in comparison with that of a conventional confocal Raman system. Therefore, the obtained Raman spectra have contributions from the upper and lower layers at different rates depending on the thickness of the upper layer when the measurement point is close to the boundary surface of the two layers. In the present study, we describe a methodology to extract quantitative information about the thickness of the subsurface layer structure by using a BHRP combined with the partial least-square regression (PLSR) analysis. The simulation study indicates that distribution of the collection efficiency in the collection volume of the BHRP is similar to a Gaussian distribution. The empirical study suggests that the PLSR model built with only a principal component (PC) 1 based on the linearized depth data gives good prediction. [Copyright &y& Elsevier]

Abstract: Tear fluid is a complex aqueous solution containing proteins, metabolites, electrolytes and lipids. This study uses Raman spectroscopy to analyse the composition of human tear fluid from three healthy volunteers. Two different methods are used to obtain Raman spectra from the 3μL tear samples: (i) solution-phase Raman spectroscopy, and (ii) drop coating deposition Raman spectroscopy (DCDRS). Tear samples were either basal fluid, or yawn reflex secreted fluid. Calibration of the solution technique with standard protein solutions (5–15mgmL−1) showed that this method could predict the protein concentration (cross-validation) with an error of less than 1mgmL−1. The Raman signals from the tear fluid were very weak but signals due to protein and urea were clearly observable in all samples. The drop coating deposition technique was shown to produce very high signal-to-noise spectra for relatively short acquisition times, and small sample volumes. Raman point mapping combined with principal components analysis showed that the protein, urea, bicarbonate and lipid could all be detected in the tear samples and that the distribution of these components was inhomogeneous. Their position within the drying pattern was shown to depend on their relative solubilities. The results of this study suggest that solution Raman measurements may be calibrated to give the total tear protein concentration and DCDRS could be used to give a fingerprint of the tear protein (and lipid) composition. [Copyright &y& Elsevier]

Abstract: In pH 4.2–4.8 HAc–NaAc buffer solution, folic acid (FA) could react with uranium (VI) to form a 2:1 anionic chelate which further reacted with some basic triphenylmethane dyes (BTPMD) such as Ethyl Violet (EV), Methyl Violet (MV) and Crystal Violet (CV) to form 1:2 ion-association complexes. As a result, not only the absorption spectra were changed, but also the intensities of resonance Rayleigh scattering (RRS) were enhanced greatly and the new RRS spectra were observed. The maximum RRS wavelengths were located at 328nm for EV system, 325nm for MV system and 328nm for CV system. The fading degree (ΔA) and RRS intensities (ΔI) of three systems were different. Under given conditions, the ΔA and ΔI were all directly proportional to the concentration of FA. The linear ranges and the detection limits of RRS methods were 0.0039–5.0μgmL−1 and 1.2ngmL−1 for EV system, 0.0073–4.0μgmL−1 and 2.2ngmL−1 for MV system, 0.014–3.5μgmL−1 and 4.7ngmL−1 for CV system. The RRS methods exhibited higher sensitivity, so they are more suitable for the determination of trace FA. The optimum conditions, the influencing factors and the effects of coexisting substances on the reaction were investigated. The method can be applied to the determination of FA in serum and urine samples with satisfactory results. The structure of the ternary ion-association complex and the reaction mechanism were discussed in this work. [Copyright &y& Elsevier]

Abstract: Imaging in Raman spectroscopy is a valuable tool for analytical chemistry. Although molecular characterization at micron level is achieved for many applications, it usually fails producing chemical images of micron size samples as expected in chemical, environmental and biological analysis. The aim of the work is to introduce the potential of super-resolution in vibrational spectroscopic imaging. This original chemometrics approach uses several low resolution images of the same sample in order to retrieve a higher resolution chemical image. It is thus possible to overcome in a certain way some physical and instrumentals limitations. To illustrate the methodology, sub-micronic details of a Si/Au sample are retrieved from low resolution images with different super-resolution algorithms. The better results are obtained with Iterative L2/Bilateral Total Variation regularization method. The use of a regularization procedure gives also better results since its first property is to preserve edges during the reconstruction of the super-resolved image. This concept of chemical image data processing should open new analytical opportunities. [Copyright &y& Elsevier]

Abstract: We demonstrate the potential of Raman spectroscopy to detect cocaine concealed inside transparent glass bottles containing alcoholic beverages. A clear Raman signature of cocaine with good signal-to-noise was obtained from a ∼300g solution of adulterated cocaine (purity 75%) in a 0.7L authentic brown bottle of rum with 1s acquisition time. The detection limit was estimated to be of the order of 9g of pure cocaine per 0.7L (∼0.04molesL−1) with 1s acquisition time. The technique holds great promise for the fast, non-invasive, detection of concealed illicit compounds inside beverages using portable Raman instruments, thus permitting drug trafficking to be combated more effectively. [Copyright &y& Elsevier]

Abstract: In this paper we explore the possibilities of Raman spectroscopy in order to deduce information on the fatty acid composition of bacterial cells. Therefore, representative strains of two bacterial taxa were each cultured in different conditions and in parallel analyzed by Raman spectroscopy and gaschromatographic FAME analysis. Raman spectra of pure fatty acids were recorded and used as reference spectra. The culturing conditions for each strain could be easily distinguished by the fatty acid information retrieved from bacterial Raman spectra. Chemometric techniques such as EMSC and PCA allowed to extract information about groups of fatty acids, that was consistent with the results from FAME analysis. Although the information retrieved from Raman spectroscopy is not as refined as that from FAME analysis, the presented methods could be useful to obtain basic information on the fatty acid present in bacteria when performing Raman spectroscopic analysis for fast whole cell profiling, which provides information for different types of cell components (fatty acids, amino acids, primary metabolites, etc.). [Copyright &y& Elsevier]

Abstract: The active pharmaceutical ingredient (ambroxol) in an intact capsule formulation has been non-destructively quantified using Raman spectroscopy. To improve the problem of insufficient representive sampling inherent in Raman measurements, we have employed a wide area illumination (WAI) scheme that enables much improved sample coverage through a circular excitation laser spot with a 6mm diameter. One of the anticipated sources of variation for this measurement was variation in the capsule shells. However, the WAI scheme significantly decreased the spectral variation among empty capsules compared to a measurement with a traditional small-spot excitation. Therefore, measurement variations emanating from the capsule shell did not significantly influence the accuracy of the determination of ambroxol concentrations. The resulting standard error of prediction (SEP) using the WAI scheme was comparable to that from previous Raman measurements which used a conventional small-spot excitation and employed a sampling scheme that involved rotation of an ambroxol pellet. It is further noteworthy that the SEP was also similar to that obtained from the use of transmission NIR spectroscopy, which was achieved by collection of spectra of the powdered capsule contents removed from the shell. The proposed Raman measurement using the WAI scheme in this case was sufficient to achieve the quantitative measurement of the active pharmaceutical ingredient (API) content of capsules non-destructively. [Copyright &y& Elsevier]

The Raman spectra of several pairs of alkenyl methyl ethers of general structure R1R2C = C(R3R4)OCH3 and R1R2C(OCH3)C(R5) = R4 (R1, R2, R3, R4, R5 = H or CnH2n+1, n =1–3) are reported and discussed, with a view to establishing whether Raman spectroscopy offers a viable means of distinguishing between these isomeric unsaturated species. Key bands associated with the ν(sp2C-H) and ν(C=C) stretching modes are found to be particularly useful in this connection: R1R2C = CHCH2OCH3 and R1R2C(OCH3)CH = CH2 ethers (R1, R2 =CH3, C2H5) are easily distinguished on this basis. Differentiation of their lower homologues, R1CH = CH2OCH3 and R1CH(OCH3)CH = CH2 (R1 = CH3, C2H5, C3H7), by similar means is also quite straightforward, even in cases where cis and trans isomers are possible. Pairs of isomeric ethers, such as CH3CH = C(CH3)CH2OCH3 and CH3CH(OCH3)C(CH3) = CH2, in which the structural differences are more subtle, may also be distinguished with care. Deductions based on bands ascribed to the stretching vibrations are usually confirmed by consideration of the signals associated with the corresponding δ(sp2C-H) deformation vibrations. Even C2H5CH = CHCH(C3H7)OCH3 and C3H7CH = CHCH(C2H5)OCH3 are found to have distinctive Raman spectra, but differentiation of these closely related isomers requires additional consideration of the low wavenumber region. [Copyright &y& Elsevier]

Abstract: A multi-method approach has been developed for the characterisation of the proteinaceous binding media, drying oils and pigments present in samples from the panel paintings of the Church of the Assumption in Cephalonia (Ionian Islands, Greece). The analytical protocol involved the use of scanning electron microscopy/energy dispersive X-ray analysis (SEM/EDX), Raman spectroscopy and gas chromatography. The identification of the pigments was achieved by SEM/EDX and Raman spectroscopy. The latter technique was also used for the detection of the binding media, while their characterisation was achieved by gas chromatographic analysis of ethyl chloroformate derivatives. The aim of this multi-method protocol was to obtain as much information as possible from the panel paintings of the Church of the Assumption, through non-destructive methods, before proceeding to gas chromatography. Little scientific information is available for the understanding of the construction technique and the materials used by the post-Byzantine artists and whatever is available comes mainly from artists’ manuals. One of the aims of this paper is to provide a scientific background to the technology of the Ionian post-Byzantine icons. [Copyright &y& Elsevier]

Abstract: An alternative fast and non-destructive validated Raman spectroscopic analytical procedure, requiring no sample preparation, was compared with the industrially applied HPLC reference method (Pfizer Manufacturing Belgium) for the quantitative determination of medroxyprogesterone acetate (MPA) in DepoProvera® suspensions (150mgmL−1, Pfizer). The Raman calibration model was developed by plotting the peak intensity of the baseline-corrected and normalized spectral band (corrected by external standard measurements) between 1595 and 1620cm−1 against known MPA concentrations in standards. At this band, no spectral interferences from the suspension medium are observed. The most suitable model for the calibration data (straight line or higher order polynomial) was determined by evaluating the fit and predictive properties of the models. In a second step, the developed Raman spectroscopic analytical method was validated by calculating the accuracy profile on the basis of the analysis results of validation samples. Furthermore, based on the data of the accuracy profile, the measurement uncertainty was determined. Finally, as the aim of the alternative method is to replace the destructive, time-consuming HPLC method, requiring sample preparation, it needs to be demonstrated that the new Raman method performs at least as good as the HPLC method. Therefore, the performance (precision and bias) of both methods was compared. A second order polynomial calibration curve through the calibration data supplies the best predictive properties and gives an acceptable fit. From the accuracy profile, it was concluded that at the target concentration (150mgmL−1), 95 out 100 future routine measurements will be included within the acceptance limits (5%). Comparison of the alternative method with the reference method at the target concentration indicates that the Raman method performs at least as good as the HPLC method for precision (repeatability and intermediate precision) and bias. The fast and non-destructive Raman method hence provides an alternative for the destructive and time-consuming HPLC procedure. [Copyright &y& Elsevier]

Abstract: In this study, we explore Raman spectra of bacteria for their biochemical information. Therefore, a database of biomolecules was used and several approaches were applied such as the study of difference spectra, the calculation dot products, the usage of coefficients obtained from an EMSC procedure and the application of 2D correlation spectroscopy. These methods were applied on a dataset containing Raman spectra of Cupriavidus metallidurans LMG 1195 in five stages of its growth, aiming to extract information about the evolution of cell components during growth. EMSC coefficients seemed to be most promising for tracking metabolic products and the results were often confirmed by difference spectra or by 2D correlation spectroscopy. [Copyright &y& Elsevier]

Abstract: The compatibility Teflon-AF 2400 liquid core optical fibre with resonance Raman spectroscopy (RRS-LCOF) was used to detect aqueous biomolecules. The maximum sensitivity enhancement factor for concentrations greater than the detection limit in a conventional cell was 10, and detection limit reduction of about 1000-fold have been achieved for the measurement of aqueous absorbing sample using Teflon-AF 2400 fibre Raman cell compared to the conventional cell. We were able to collect spectra of 2.5×10−9 and 2.5×10−10 M aqueous β-carotene using 16.2mW of laser power and 10s integration time. This volume of a 2.5×10−10 M aqueous solution corresponds to only 1.5fmol or 830fg of β-carotene. The results of this preliminary study indicate that RRS-LCOF has potential in bioanalytical and biomedical applications. [Copyright &y& Elsevier]

Abstract: The Raman and mass spectra of 1,4-diphenylbuta-1,3-diene and several of its monomethyl and dimethyl homologues are reported and discussed, with a view to developing a spectroscopic protocol for detecting the presence and position of a methyl group in these compounds. Raman spectroscopy and mass spectrometry are shown to provide complementary information, by which the four available monomethyl homologues may be readily distinguished from each other and 1,4-diphenylbuta-1,3-diene itself. The utility of these 1,4-diarylbutadienes as model compounds for carotenoids and related materials, which may serve as indicators of extinct or extant extraterrestrial life, is considered. [Copyright &y& Elsevier]

Abstract: A novel and reliable Raman collection system for the non-destructive analysis of pharmaceutical tablets has been proposed. The main idea was to develop and utilize the wide area illumination (WAI) scheme for Raman collection to cover a large surface area (coverage area: 28.3mm2) of solid tablet to dramatically improve the reliability in sample representation and the reproducibility of sampling due to less sensitivity of sample placement with regard to the focal plane. Simultaneously, the effective and synchronous standard configuration using isobutyric anhydride was harmonized with the WAI scheme to correct the problematic variation of Raman intensity from the change of laser power. To verify the quantitative performance of the proposed scheme, the compositional analysis of active ingredient in naproxen tablet has been performed. The average sample composition was successfully represented by using the WAI scheme compared to the conventional scheme with a much smaller illumination area. After the intensity correction using the non-overlapping peak of isobutyric anhydride standard and area normalization, a partial least squares (PLS) model was developed using an optimized spectral range and the concentrations of naproxen in tablets were accurately predicted. The prediction accuracy was not sensitive to changes in laser power or tablet position within ±2mm. Additionally, the prediction accuracy was repeatable without systematic drift or need for re-calibration. [Copyright &y& Elsevier]

Abstract: Wax sculptures contain several materials from both organic and inorganic nature. These works of art are particularly fragile. Determining their chemical composition is thus of prime importance for their preservation. The identification of the recipes of waxy pastes used through time also provides valuable information in the field of art history. The aim of the present research was to develop a convenient analytical strategy, as non-invasive as possible, that allows to identify the wide range of materials involved in wax sculptures. A multi-step analytical methodology, based on the use of complementary techniques, either non- or micro-destructive, was elaborated. X-ray fluorescence and micro-Raman spectroscopy were used in a non-invasive way to identify inorganic pigments, opacifiers and extenders. The combination of structural and separative techniques, namely infrared spectroscopy, direct inlet electron ionisation mass spectrometry and high temperature gas chromatography, was shown to be appropriate for unravelling the precise composition of the organic substances. A micro-chemical test was also performed for the detection of starch. From this study it has been possible to elucidate the composition of the waxy pastes used by three different sculptors at the end of the 19th century. Complex and elaborated recipes, in which a large range of natural substances were combined, were highlighted. [Copyright &y& Elsevier]

Abstract: Raman spectroscopy has been evaluated for characterisation of the degree of fatty acid unsaturation (iodine value) of salmon (Salmo salar). The Norwegian Quality Cuts from 50 salmon samples were obtained, and the samples provided an iodine value range of 147.8–170.0gI2/100gfat, reflecting a normal variation of farmed salmon. Raman measurements were performed both on different spots of the intact salmon muscle, on ground salmon samples as well as on oil extracts, and partial least squares regression (PLSR) was utilised for calibration. The oil spectra provided better iodine value predictions than the other data sets, and a correlation coefficient of 0.87 with a root mean square error of cross-validation of 2.5gI2/100gfat was achieved using only one PLSR component. The ground samples provided comparable results, but at least two PLSR components were needed. Higher prediction errors were obtained from Raman spectra of intact salmon muscle, and this may partly be explained by sampling uncertainties in the relation between Raman measurements and reference analysis. All PLSR models obtained were based on chemically sound regression coefficients, and thus information regarding fatty acid unsaturation is readily available from Raman spectra even in systems with high contents of protein and water. The accuracy, the robustness and the low complexity of the PLSR models obtained suggest Raman spectroscopy as a promising method for rapid in-process control of the degree of unsaturation in salmon samples. [Copyright &y& Elsevier]

Abstract: This article presents the “in situ” and totally non destructive investigation of a wall painting in Santa María de Lemoniz (Biscay, Basque Country, Spain) by Raman microprobe spectroscopy 14 years after its restoration. Although no sample was allowed to be taken, it has been possible to determine the original pigments in the artwork (vermilion, red iron oxide, yellow iron oxide, carbon black, lead white), as well as some degradation products (calcium oxalate dihydrate, anhydrite). For the first time, the mechanism for the transformation of malachite into copper basic sulphates has been ascertained by the integration of Raman data with thermodynamic speciation studies. Moreover, some remarks regarding the unsuitability of the past intervention procedure with regard to the chemical stability of the artwork are made. [Copyright &y& Elsevier]

Abstract: FT-Raman spectroscopy has been used successfully for the non-destructive identification of modern ivories and is evaluated here for the identification of osseous materials from archaeological sites. Results on archaeological ivories are reported and the problems faced in matching FT-Raman spectra to standards for the validation of these materials are highlighted. Archaeological specimens of different dates, provenance and taphonomic history, including both conserved and unconserved items, have been analysed. [Copyright &y& Elsevier]

Abstract: We propose a new mid-level data-fusion system to process, as a unique signal, the Raman and X-ray fluorescence (XRF) spectra obtained from the first micro-Raman–XRF instrument. The system is based on the main advantage of the wavelet transform, which is multiresolution. First, each spectrum set is split into blocks according to their frequency. The blocks which contains background and noise signals are removed and variable selection is performed on the remaining blocks to extract those variables with the most power of classification. These variables are concatenated and form a Raman–XRF meta-signal ensemble. Finally, dual-domain signal ensembles from references and samples are classified using partial least squares discriminant analysis (PLS-DA). Our results show that this system is suitable for rapidly and automatically classifying ancient pigments using the complementary information provided by both techniques. Classification with different levels of difficulty can be handled and no prior knowledge of the sample composition is required. This system has been applied to real spectra of ancient pigments and can also be applied to combinations of other spectral signals. [Copyright &y& Elsevier]

Abstract: Diesel properties determined by ASTM reference methods as cetane index, density, viscosity, distillation temperatures at 50% (T50) and 85% (T85) recovery, and the total sulfur content (%, w/w) were modeled by FTIR-ATR, FTNIR, and FT-Raman spectroscopy using partial last square regression (PLS) and artificial neural network (ANN) spectral analysis. In the PLS models, 45 diesel samples were used in the training group and the other 45 samples were used in the validation. In the ANN analysis a modular feedforward network was used. Sixty diesel samples were used in the neural network training and other 30 samples were used in the validation. Two different ATR configurations were compared in the FTIR, a conventional (ATR1) and an immersion (ATR2) cell. The ATR1 cell presented the best results, with smaller prediction errors (root mean square error of prediction, RMSEP). The comparison of the three PLS models (FTIR-ATR1, FTNIR, and FT-Raman) shows that reasonable values of R 2 and RMSEP were obtained by the FTIR-ATR1 and FTNIR models in the evaluation of density, viscosity, and T50. The PLS/FT-Raman models presented reasonable results only for the T50 property. None of the techniques was able to generate suitable PLS calibration models for the determination of sulfur content. The ANN/FT-Raman models presented the best performances, with all models presenting R 2-values above 85% some of them with RMSEP values significantly smaller than those obtained with FTIR-ATR and FTNIR. The ANN/FT-Raman and ANN/FTIR-ATR1 models were able to estimate the total sulfur content of diesel with 0.01% (w/w) accuracy. [Copyright &y& Elsevier]

Abstract: This work presents the archaeometric characterisation of a group of ancient pottery remains discovered during the restoring of the Novalesa Abbey (Susa Valley, Turin, Italy) performed in 2000. The characterisation focuses on the achievement of information about provenance and production process of the samples. Firstly, the data concerning the multi-element characterisation of the samples by inductively coupled plasma–mass spectrometry (ICP–MS) were analysed by chemometric tools (principal component analysis and cluster analysis) in order to obtain information about their similarity and clustering. These information, integrated with the results of micro-Raman spectroscopy analysis of the inclusions shed light on differences in the production process of the samples. [Copyright &y& Elsevier]

Abstract: The Raman spectrum of guarana, an important product of the Amazonian rain forest, has been investigated; the therapeutic properties of guarana and it''s extracts have been realised for some time and have been attributed to guaranine, which could be a complex of caffeine and tannins or to a new xanthine natural product. The purpose of this study is two-fold: firstly, to provide molecular structural information about guarana seeds and their extracts and, secondly, to test the viability of using the technique as a method of verification of genuine guarana extracts from synthetic composites. Raman spectroscopy shows that the composition of the guarana is very similar for the whole seed and for the outer and inner portions of the dissected seed, which are closely similar also to the ground commercial powders produced in the Amazon for the distributors. The results indicate that Fourier-transform Raman spectroscopy could be used for the monitoring of quality control of guarana products in the phytopharmaceutical industry. [Copyright &y& Elsevier]

In column liquid chromatography (LC) coupled to conventional Raman spectroscopy (RS) removal of the spectral background of the eluent is often demanding, because of the strong signals of the organic modifier. A new chemometrical method is proposed, called the eluent background subtraction (EBS) method, which can correct for small shape and intensity differences of the eluent spectra. The variations in the eluent spectra are modelled using principal component analysis (PCA). The PCA loading vectors are subsequently used for eluent background correction of the elution spectra of the analyte. The loading vectors are fitted under these spectra by an asymmetric least-squares method. This method was successfully applied under various experimental conditions and performed much better than conventional background correction methods. Analyte detectability was improved by (weighted) averaging of all elution spectra and smoothing via a p-spline function. [Copyright &y& Elsevier]

Evidence for the existence of primitive life forms such as lichens and fungi can be based upon the formation of oxalates which are most readily detected using Raman spectroscopy. A comparative study of a suite of natural oxalates including weddellite, whewellite, moolooite, humboldtine, glushinskite, natroxalate and oxammite has been undertaken using Raman spectroscopy. The minerals are characterised by the wavenumber of the CO stretching vibration which is cation sensitive. The band is observed at 1468 cm-1 for weddellite, 1489 cm-1 for moolooite, 1471 cm-1 for glushinskite and 1456 cm-1 for natroxalate. Except for oxammite, the infrared and Raman spectra are mutually exclusive indicating that the minerals are bidentate. Differences are also observed in the wavenumber of the water OH stretching bands of the minerals. The significance of this work rests with the ability of Raman spectroscopy to identify oxalates which often occur as films on host rocks. [Copyright &y& Elsevier]