The Discrimination of Colored Acrylic, Cotton, and Wool Textile Fibers Using Micro-Raman Spectroscopy. Part 1 : In Situ Detection and Characterization of Dyes

Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

Evaluation de spectromètres portables Raman, Infrarouge et Proche Infrarouge pour la détection de contrefaçons de médicaments

La contrefaçon de médicaments est un délit qui n'a cessé d'augmenter ces dernières années. Diff érents spectromètres portables ont été proposés sur le marché afi n de permettre une détection rapide des contrefaçons sur le terrain. Les spectroscopies Raman, Infrarouge et Proche Infrarouge présentent des caractéristiques intéressantes pour l'analyse de médicaments douteux, propriétés qui sont exposées dans cet article. Une comparaison des diff érents instruments portables permet de présenter l'intérêt d'utiliser ces spectromètres pour la détection de contrefaçons.

L'apport d'une approche criminalistique pour lutter contre la contrefaçon de médicaments

Dans le domaine de l'analyse et la détection de produits pharmaceutiques contrefaits, différentes techniques analytiques ont été appliquées afin de discriminer les produits authentiques des contrefaçons. Parmi celles-ci, les spectroscopies proche infrarouge (NIR) et Raman ont fourni des résultats prometteurs. L'objectif de cette étude était de développer une méthodologie, basée sur l'établissement de liens chimiques entre les saisies de produits contrefaits, permettant de fournir des informations utiles pour les acteurs impliqués dans la lutte à la prolifération de ces produits. Une banque de données de spectres NIR et Raman a été créée et différents algorithmes de classification non-supervisée (i.e., analyse en composantes principales (ACP) et analyse factorielle discriminante (AFD) - elus ter onolysis) ont été utilisées afin d'identifier les différents groupes de produits présents. Ces classes ont été comparées aux profils chimiques mis en évidence par la spectroscopie infrarouge à transformée de Fourier (FT-IR) et par la chromatographie gazeuse couplée à la spectrométrie de masse (GC -MS). La stratégie de classification proposée, fondée sur les classes identifiées par spectroscopie NIR et Raman, utilise un algorithme de classification basé sur des mesures de distance et des courbes Receiver Operating Characteristics (ROC). Le modèle est capable de comparer le spectre d'une nouvelle contrefaçon à ceux des saisies précédemment analysées afin de déterminer si le nouveau spécimen appartient à l'une des classes existantes, permettant ainsi de le lier à d'autres saisies dans la base de données.

Applications of a transportable Raman spectrometer for the in situ detection of controlled substances at border controls

A transportable Raman spectrometer was tested for the detection of illicit drugs seized during border controls. In a first step, the analysis methodology was optimized using reference substances such as diacetylmorphine (heroin), cocaine and amphetamine (as powder or liquid forms). Adequate focalisation distance and times of analysis, influence of daylight and artificial light sources, repeatability and limits of detection were studied. In a second step the applications and limitations of the technique to detect the illicit substances in different mixtures and containers was evaluated. Transportable Raman spectroscopy was found to be adequate for a rapid screen of liquids and powders for the detection and identification of controlled substances. Additionally, it had the advantage over other portable techniques, such as ion mobility spectrometry, of being non-destructive and capable of rapid analysis of large quantities of substances through containers such as plastic bags and glass bottles.

Identification of pharmaceutical tablets by Raman spectroscopy and chemometrics

Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.

Detection, Determination of Chemical Composition and Chemical Profiling of Counterfeit Medicines by Raman Spectroscopy.

Raman spectroscopy has become a widespread technique for the analysis ofpharmaceutical solid forms. The application proposed here is the investigationof counterfeit medicines. This serious global issue requires quick and accurateidentification methods to fight against this phenomenon. Thanks to its chemicalselectivity, rapidity of analysis and potential of generating repeatable spectralprofiles, Raman spectroscopy presents distinct advantages for the analysis ofcounterfeits. Combined with chemometric tools, the technique enablesthe detection, the determination of chemical composition and the profiling ofmedicine counterfeits.

L'application de la spectroscopie Raman en criminalistique pour l'analyse du colorant des fibres textiles en acrylique, coton et laine

RESUME La méthode de la spectroscopie Raman est une technique d'analyse chimique basée sur l'exploitation du phénomène de diffusion de la lumière (light scattering). Ce phénomène fut observé pour la première fois en 1928 par Raman et Krishnan. Ces observations permirent à Raman d'obtenir le Prix Nobel en physique en 1930. L'application de la spectroscopie Raman a été entreprise pour l'analyse du colorant de fibres textiles en acrylique, en coton et en laine de couleurs bleue, rouge et noire. Nous avons ainsi pu confirmer que la technique est adaptée pour l'analyse in situ de traces de taille microscopique. De plus, elle peut être qualifiée de rapide, non destructive et ne nécessite aucune préparation particulière des échantillons. Cependant, le phénomène de la fluorescence s'est révélé être l'inconvénient le plus important. Lors de l'analyse des fibres, différentes conditions analytiques ont été testées et il est apparu qu'elles dépendaient surtout du laser choisi. Son potentiel pour la détection et l'identification des colorants imprégnés dans les fibres a été confirmé dans cette étude. Une banque de données spectrale comprenant soixante colorants de référence a été réalisée dans le but d'identifier le colorant principal imprégné dans les fibres collectées. De plus, l'analyse de différents blocs de couleur, caractérisés par des échantillons d'origine inconnue demandés à diverses personnes, a permis de diviser ces derniers en plusieurs groupes et d'évaluer la rareté des configurations des spectres Raman obtenus. La capacité de la technique Raman à différencier ces échantillons a été évaluée et comparée à celle des méthodes conventionnelles pour l'analyse des fibres textiles, à savoir la micro spectrophotométrie UV-Vis (MSP) et la chromatographie sur couche mince (CCM). La technique Raman s'est révélée être moins discriminatoire que la MSP pour tous les blocs de couleurs considérés. C'est pourquoi dans le cadre d'une séquence analytique nous recommandons l'utilisation du Raman après celle de la méthode d'analyse de la couleur, à partir d'un nombre de sources lasers le plus élevé possible. Finalement, la possibilité de disposer d'instruments équipés avec plusieurs longueurs d'onde d'excitation, outre leur pouvoir de réduire la fluorescence, permet l'exploitation d'un plus grand nombre d'échantillons. ABSTRACT Raman spectroscopy allows for the measurement of the inelastic scattering of light due to the vibrational modes of a molecule when irradiated by an intense monochromatic source such as a laser. Such a phenomenon was observed for the first time by Raman and Krishnan in 1928. For this observation, Raman was awarded with the Nobel Prize in Physics in 1930. The application of Raman spectroscopy has been undertaken for the dye analysis of textile fibers. Blue, black and red acrylics, cottons and wools were examined. The Raman technique presents advantages such as non-destructive nature, fast analysis time, and the possibility of performing microscopic in situ analyses. However, the problem of fluorescence was often encountered. Several aspects were investigated according to the best analytical conditions for every type/color fiber combination. The potential of the technique for the detection and identification of dyes was confirmed. A spectral database of 60 reference dyes was built to detect the main dyes used for the coloration of fiber samples. Particular attention was placed on the discriminating power of the technique. Based on the results from the Raman analysis for the different blocs of color submitted to analyses, it was possible to obtain different classes of fibers according to the general shape of spectra. The ability of Raman spectroscopy to differentiate samples was compared to the one of the conventional techniques used for the analysis of textile fibers, like UV-Vis Microspectrophotometry (UV-Vis MSP) and thin layer chromatography (TLC). The Raman technique resulted to be less discriminative than MSP for every bloc of color considered in this study. Thus, it is recommended to use Raman spectroscopy after MSP and light microscopy to be considered for an analytical sequence. It was shown that using several laser wavelengths allowed for the reduction of fluorescence and for the exploitation of a higher number of samples.

Profiling of counterfeit medicines by vibrational spectroscopy

Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

Spontaneous Atopic Dermatitis-Like Symptoms in a/a ma ft/ma ft/J Flaky Tail Mice Appear Early after Birth.

Loss-of-function mutations in human profilaggrin gene have been identified as the cause of ichthyosis vulgaris (IV), and as a major predisposition factor for atopic dermatitis (AD). Similarly, flaky tail (a/a ma ft/ma ft/J) mice were described as a model for IV, and shown to be predisposed to eczema. The aim of this study was to correlate the flaky tail mouse phenotype with human IV and AD, in order to dissect early molecular events leading to atopic dermatitis in mice and men, suffering from filaggrin deficiency. Thus, 5-days old flaky tail pups were analyzed histologically, expression of cytokines was measured in skin and signaling pathways were investigated by protein analysis. Human biopsies of IV and AD patients were analyzed histologically and by real time PCR assays. Our data show acanthosis and hyperproliferation in flaky tail epidermis, associated with increased IL1β and thymic stromal lymphopoietin (TSLP) expression, and Th2-polarization. Consequently, NFκB and Stat pathways were activated, and IL6 mRNA levels were increased. Further, quantitative analysis of late epidermal differentiation markers revealed increased Small proline-rich protein 2A (Sprr2a) synthesis. Th2-polarization and Sprr2a increase may result from high TSLP expression, as shown after analysis of 5-days old K14-TSLP tg mouse skin biopsies. Our findings in the flaky tail mouse correlate with data obtained from patient biopsies of AD, but not IV. We propose that proinflammatory cytokines are responsible for acanthosis in flaky tail epidermis, and together with the Th2-derived cytokines lead to morphological changes. Accordingly, the a/a ma ft/ma ft/J mouse model can be used as an appropriate model to study early AD onset associated with profilaggrin deficiency.

Magnetoelectricity in the ferrimagnetic Cu2OSeO3: symmetry analysis and Raman scattering study

sublattices ferrimagnet Cu2OSeO3 with a cubic symmetry and a linear magnetoelectric effect. There is no spectroscopic evidence for structural lattice distortions below T-C=60 K, which are expected due to magnetoelectric coupling. Using symmetry arguments we explain this observation by considering a special type of ferrimagnetic ground state which does not generate a spontaneous electric polarization. Interestingly, Raman scattering shows a strong increase of electric polarization of media through a dynamic magnetoelectric effect as a remarkable enhancement of the scattering intensity below T-C. New lines of purely magnetic origin have been detected in the magnetically ordered state. A part of them are attributed as scattering on exchange magnons. Using this observation and further symmetry considerations we argue for strong Dzyaloshinskii-Moriya interaction existing in the Cu2OSeO3. (c) 2010 American Institute of Physics. [doi:10.1063/1.3455808]

A re-evaluation of Raman as a tool for the determination of 12C and 13C in geological fluid inclusions

Raman spectroscopy has been used by fluid inclusionists to: 1) identify and quantitatively determine the relative abundances of gaseous species within fluid inclusions; 2) identify solid phases precipitating from, or accidentally trapped, within fluid inclusions; and 3) determine the detection limits of the C-13/C-12 ratio in the CO2 bearing phase of fluid inclusions.

A reassessment of models for hydrocarbon generation in the Khibiny nepheline syenite complex, Kola Peninsula, Russia

Although hydrocarbon-bearing fluids have been known from the alkaline igneous rocks of the Khibiny intrusion for many years, their origin remains enigmatic. A recently proposed model of post-magmatic hydrocarbon (HC) generation through Fischer-Tropsch (FT) type reactions suggests the hydration of Fe-bearing phases and release of H-2 which reacts with magmatically derived CO2 to form CH4 and higher HCs. However, new petrographic, microthermometric, laser Raman, bulk gas and isotope data are presented and discussed in the context of previously published work in order to reassess models of HC generation. The gas phase is dominated by CH4 with only minor proportions of higher hydrocarbons. No remnants of the proposed primary CO2-rich fluid are found in the complex. The majority of the fluid inclusions are of secondary nature and trapped in healed microfractures. This indicates a high fluid flux after magma crystallisation. Entrapment conditions for fluid inclusions are 450-550 degrees C at 2.8-4.5 kbar. These temperatures are too high for hydrocarbon gas generation through the FT reaction. Chemical analyses of rims of Fe-rich phases suggest that they are not the result of alteration but instead represent changes in magma composition during crystallisation. Furthermore, there is no clear relationship between the presence of Fe-rich minerals and the abundance of fluid inclusion planes (FIPs) as reported elsewhere. delta C-13 values for methane range from -22.4% to -5.4%, confirming a largely abiogenic origin for the gas. The presence of primary CH4-dominated fluid inclusions and melt inclusions, which contain a methane-rich gas phase, indicates a magmatic origin of the HCs. An increase in methane content, together with a decrease in delta C-13 isotope values towards the intrusion margin suggests that magmatically derived abiogenic hydrocarbons may have mixed with biogenic hydrocarbons derived from the surrounding country rocks. (C) 2006 Elsevier BV. All rights reserved.

Raman analysis of multilayer automotive paints in forensic science: measurement variability and depth profile?

The aim of this work is to study the influence of several analytical parameters on the variability of Raman spectra of paint samples. In the present study, microtome thin section and direct (no preparation) analysis are considered as sample preparation. In order to evaluate their influence on the measures, an experimental design such as 'fractional full factorial' with seven factors (including the sampling process) is applied, for a total of 32 experiments representing 160 measures. Once the influence of sample preparation highlighted, a depth profile of a paint sample is carried out by changing the focusing plane in order to measure the colored layer under a clearcoat. This is undertaken in order to avoid sample preparation such a microtome sectioning. Finally, chemometric treatments such as principal component analysis are applied to the resulting spectra. The findings of this study indicate the importance of sample preparation, or more specifically, the surface roughness, on the variability of the measurements on a same sample. Moreover, the depth profile experiment highlights the influence of the refractive index of the upper layer (clearcoat) when measuring through a transparent layer.