895 resultados para koritnigite, mineral, hydrogen-arsenate, Raman spectroscopy, molecular water, hydrogen bonds
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High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).
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In the last three decades, there has been a broad academic and industrial interest in conjugated polymers as semiconducting materials for organic electronics. Their applications in polymer light-emitting diodes (PLEDs), polymer solar cells (PSCs), and organic field-effect transistors (OFETs) offer opportunities for the resolution of energy issues as well as the development of display and information technologies1. Conjugated polymers provide several advantages including low cost, light weight, good flexibility, as well as solubility which make them readily processed and easily printed, removing the conventional photolithography for patterning2. A large library of polymer semiconductors have been synthesized and investigated with different building blocks, such as acenes or thiophene and derivatives, which have been employed to design new materials according to individual demands for specific applications. To design ideal conjugated polymers for specific applications, some general principles should be taken into account, including (i) side chains (ii) molecular weights, (iii) band gap and HOMO and LUMO energy levels, and (iv) suited morphology.3-6 The aim of this study is to elucidate the impact that substitution exerts on the molecular and electronic structure of π-conjugated polymers with outstanding performances in organic electronic devices. Different configurations of the π-conjugated backbones are analyzed: (i) donor-acceptor configuration, (ii) 1D lineal or 2D branched conjugated backbones, and (iii) encapsulated polymers (see Figure 1). Our combined vibrational spectroscopy and DFT study shows that small changes in the substitution pattern and in the molecular configuration have a strong impact on the electronic characteristics of these polymers. We hope this study can advance useful structure-property relationships of conjugated polymers and guide the design of new materials for organic electronic applications.
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In archaeometry, the advantages of a combined use of Raman spectroscopy and X-ray fluorescence spectroscopy are extensively discussed for applications such as the analysis of paintings, manuscripts, pottery, etc. Here, we demonstrate for the first time the advantage of using both techniques for analysing glyptics. These engraved gemstones or glass materials were originally used as stamps, to identify the owner, for instance on letters, but also on wine vessels. For this research, a set of 64 glyptics (42 Roman glass specimens and 22 modern ones), belonging to the collection of the museum ‘Quinta das Cruzes’ in Funchal (Madeira, Portugal), was analysed with portable Raman spectroscopy and handheld X-ray fluorescence (hXRF). These techniques were also used to confirm the gemological identification of these precious objects and can give extra information about the glass composition. Raman spectroscopy identifies the molecular composition as well as on the crystalline phases present. On the other hand, hXRF results show that the antique Roman glass samples are characterised with low Pb and Sn levels and that the modern specimens can be discriminated in two groups: lead-based and non-lead-based ones.
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Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.
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This paper presents the study of photochemical behavior of polycyclic aromatic hydrocarbons (PAHs), potential pollutants in secondary reactions in aerosols, through Raman spectroscopy compared with its electrochemical behavior. The PAHs studied include pyrene, anthracene, phenanthrene and fluorene. These were adsorbed onto TiO2 and irradiated with ultraviolet light (254 nm). Their electrochemical oxidation was studied by in situ Surface-enhanced Raman Scattering (SERS) and led to the formation of carbonyl-containing products. Oxidized intermediates bearing the C=O group were also formed during photodegradation. The joint analysis of the photodegradation data with those produced by electrochemical means - using spectroscopic techniques for the identification and characterization of the products - revealed the formation of identical products for anthracene, but not for pyrene. A reasonable explanation for this difference in results is that photochemical and electrochemical oxidation reactions proceed via different mechanisms. While photocatalytic degradation over TiO2 is initiated by hydroxyl radicals, electrochemical oxidation is initiated by the direct electron transfer from adsorbed PAH to the electrode, generating PAH cation radicals that undergo subsequent reactions.
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Single-point diamond turning of monocrystalline semiconductors is an important field of research within brittle materials machining. Monocrystalline silicon samples with a (100) orientation have been diamond turned under different cutting conditions (feed rate and depth of cut). Micro-Raman spectroscopy and atomic force microscopy have been used to assess structural alterations and surface finish of the samples diamond turned under ductile and brittle modes. It was found that silicon undergoes a phase transformation when machined in the ductile mode. This phase transformation is evidenced by the creation of an amorphous surface layer after machining which has been probed by Raman scattering. Compressive residual stresses are estimated for the machined surface and it is observed that they decrease with an increase in the feed rate and depth of cut. This behaviour has been attributed to the formation of subsurface cracks when the feed rate is higher than or equal to 2.5 mu m/rev. The surface roughness was observed to vary with the feed rate and the depth of cut. An increase in the surface roughness was influenced by microcrack formation when the feed rate reached 5.0 mu m/rev. Furthermore, a high-pressure phase transformation induced by the tool/material interaction and responsible for the ductile response of this typical brittle material is discussed based upon the presented Raman spectra. The application of this machining technology finds use for a wide range of high quality components, for example the creation of a micrometre-range channel for microfluidic devices as well as microlenses used in the infrared spectrum range.
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A recently developed dual-beam configuration that optimizes the thermal lens technique has been used to obtain the absorption spectrum of pure water from 350 to 528 nm. Our results indicate the minimum linear absorption coefficient smaller than 2 X 10(-5) cm(-1) between 360 and 400 nm. This value is lower than previous literature data, and it is blueshifted. Absorption coefficients as small as 2 X 10(-7) cm(-1) can be measured for water using 1 W of excitation power. A detection limit of similar to 6 X 10(-9) cm(-1) (P=1 W) for CCl(4) was estimated, which represents, to the best of our knowledge, the highest sensitivity obtained in small absorption measurements in liquids. (C) 2009 Optical Society of America
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Ni-doped SnO(2) nanoparticles, promising for gas-sensing applications, have been synthesized by a polymer precursor method. X-ray diffraction (XRD) and transmission electron microscopy (TEM) data analyses indicate the exclusive formation of nanosized particles with rutile-type phase (tetragonal SnO(2)) for Ni contents below 10 mol%. The mean crystallite size shows a progressive reduction with the Ni content. Room-temperature Raman spectra of Ni-doped SnO(2) nanoparticles show the presence of Raman active modes and modes activated by size effects. From the evolution of the A(1g) mode with the Ni content, a solubility limit at similar to 2 mol% was estimated. Below that content, Raman results are consistent with the occurrence of solid solution (ss) and surface segregation (seg.) of Ni ions. Above similar to 2 mol% Ni, the redshift of A(1g) mode suggests that the surface segregation of Ni ions takes place. Disorder-activated bands were determined and their integrated intensity evolution with the Ni content suggest that the solid-solution regime favors the increase of disorder; meanwhile, that disorder becomes weaker as the Ni content is increased. Copyright (C) 2010 John Wiley & Sons, Ltd.
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The present study aims at the use of Raman spectroscopy in the quantification of unsaturated fats in fat-containing foods, compared to the information available in the Nutritional Table, to obtain a non-destructive optical quantification of unsaturation. Raman spectra of edible oil, margarine, mayonnaise, hydrogenated fat, and butter were obtained with a near-infrared Raman spectrometer (830nm). By analyzing selected bands in the regions of 1750, 1660, 1440, 1300, and 1260cm-1, the amount of total and unsaturated fat of samples of oil, margarine, and mayonnaise were correlated with the information displayed in the Nutritional Table. The amount of unsaturated trans fat in selected samples was correlated to the Raman shift of 1660cm-1. Dispersive Raman spectroscopy was shown to be effective in quantifying the unsaturated fats in oil, margarine, and mayonnaise, and trans fat in hydrogenated oils and butter.
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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.
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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.
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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.
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In this study, we present a detailed structural characterization by means of transmission electron microscopy and Raman spectroscopy of polymorphous silicon (pm-Si:H) thin films deposited using radio-frequency dust-forming plasmas of SiH4 diluted in Ar. Square-wave modulation of the plasma and gas temperature was varied to obtain films with different nanostructures. Transmission electron microscopy and electron diffraction have shown the presence of Si crystallites of around 2 nm in the pm-Si:H films, which are related to the nanoparticles formed in the plasma gas phase coming from their different growth stages, named particle nucleation and coagulation. Raman scattering has proved the role of the film nanostructure in the crystallization process induced ¿in situ¿ by laser heating.
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Podeu consultar el llibre complet a: http://hdl.handle.net/2445/32166
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Raman spectroscopy combined with chemometrics has recently become a widespread technique for the analysis of pharmaceutical solid forms. The application presented in this paper is the investigation of counterfeit medicines. This increasingly serious issue involves networks that are an integral part of industrialized organized crime. Efficient analytical tools are consequently required to fight against it. Quick and reliable authentication means are needed to allow the deployment of measures from the company and the authorities. For this purpose a method in two steps has been implemented here. The first step enables the identification of pharmaceutical tablets and capsules and the detection of their counterfeits. A nonlinear classification method, the Support Vector Machines (SVM), is computed together with a correlation with the database and the detection of Active Pharmaceutical Ingredient (API) peaks in the suspect product. If a counterfeit is detected, the second step allows its chemical profiling among former counterfeits in a forensic intelligence perspective. For this second step a classification based on Principal Component Analysis (PCA) and correlation distance measurements is applied to the Raman spectra of the counterfeits.