972 resultados para Near infrared spectral(NIRS)
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The influence of the presence of hydrogen on Pt/TiO2 catalysts submitted to reduction treatment has been studied by FT-IR at room temperature. After submitting to LTR treatment, the hydrogen spillover has been detected and the presence of hydrogen at the bulk is shown to produce a strong absorption in the infrared spectral region. After HTR treatment, the hydrogen is strongly chemissorbed.
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Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special characteristics for model complex systems. The basic principles of two types of neural networks, the multi-layer perceptrons and radial basis functions, are introduced, as well as, a pruning approach to architecture optimization. Two analytical applications based on near infrared spectroscopy are presented, the first one for determination of nitrogen content in wheat leaves using multi-layer perceptrons networks and second one for determination of BRIX in sugar cane juices using radial basis functions networks.
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In this dissertation, Active Galactic Nuclei (AGN) and their host galaxies are discussed. Together with transitional events, such as supernovae and gamma-ray bursts, AGN are the most energetic phenomena in the Universe. The dominant fraction of their luminosity originates from the center of a galaxy, where accreting gas falls into a supermassive black hole, converting gravitational energy to radiation. AGN have a wide range of observed properties: e.g. in their emission lines, radio emission, and variability. Most likely, these properties depend significantly on their orientation to our line-of-sight, and to unify AGN into physical classes it is crucial to observe their orientation-independent properties, such as the host galaxies. Furthermore, host galaxy studies are essential to understand the formation and co-evolution of galactic bulges and supermassive black holes. In this thesis, the main focus is on observationally characterizing AGN host galaxies using optical and near-infrared imaging and spectroscopy. BL Lac objects are a class of AGN characterized by rapidly variable and polarized continuum emission across the electromagnetic spectrum, and coredominated radio emission. The near-infrared properties of intermediate redshift BL Lac host galaxies are studied in Paper I. They are found to be large elliptical galaxies that are more luminous than their low redshift counterparts suggesting a strong luminosity evolution, and a contribution from a recent star formation episode. To analyze the stellar content of galaxies in more detail multicolor data, especially observations at blue wavelengths, are essential. In Paper III, optical - near-infrared colors and color gradients are derived for low redshift BL Lac host galaxies. They show bluer colors and steeper color gradients than inactive ellipticals which, most likely, are caused by a relatively young stellar population indicating a different evolutionary stage between AGN hosts and inactive ellipticals. In Paper II, near-infrared imaging of intermediate redshift radio-quiet quasar hosts is used to study their luminosity evolution. The hosts are large elliptical galaxies, but they are systematically fainter than the hosts of radio-loud quasars at similar redshifts, suggesting a link between the luminosity of the host galaxies and the radio properties of AGN. In Paper IV, the characteristics of near-infrared stellar absorption features of low redshift radio galaxies are compared with those of inactive early-type galaxies. The comparison suggests that early-type galaxies with AGN are in a different evolutionary stage than their inactive counterparts. Moreover, radio galaxies are found to contain stellar populations containing both old and intermediate age components.
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Rosin is a natural product from pine forests and it is used as a raw material in resinate syntheses. Resinates are polyvalent metal salts of rosin acids and especially Ca- and Ca/Mg- resinates find wide application in the printing ink industry. In this thesis, analytical methods were applied to increase general knowledge of resinate chemistry and the reaction kinetics was studied in order to model the non linear solution viscosity increase during resinate syntheses by the fusion method. Solution viscosity in toluene is an important quality factor for resinates to be used in printing inks. The concept of critical resinate concentration, c crit, was introduced to define an abrupt change in viscosity dependence on resinate concentration in the solution. The concept was then used to explain the non-inear solution viscosity increase during resinate syntheses. A semi empirical model with two estimated parameters was derived for the viscosity increase on the basis of apparent reaction kinetics. The model was used to control the viscosity and to predict the total reaction time of the resinate process. The kinetic data from the complex reaction media was obtained by acid value titration and by FTIR spectroscopic analyses using a conventional calibration method to measure the resinate concentration and the concentration of free rosin acids. A multivariate calibration method was successfully applied to make partial least square (PLS) models for monitoring acid value and solution viscosity in both mid-infrared (MIR) and near infrared (NIR) regions during the syntheses. The calibration models can be used for on line resinate process monitoring. In kinetic studies, two main reaction steps were observed during the syntheses. First a fast irreversible resination reaction occurs at 235 °C and then a slow thermal decarboxylation of rosin acids starts to take place at 265 °C. Rosin oil is formed during the decarboxylation reaction step causing significant mass loss as the rosin oil evaporates from the system while the viscosity increases to the target level. The mass balance of the syntheses was determined based on the resinate concentration increase during the decarboxylation reaction step. A mechanistic study of the decarboxylation reaction was based on the observation that resinate molecules are partly solvated by rosin acids during the syntheses. Different decarboxylation mechanisms were proposed for the free and solvating rosin acids. The deduced kinetic model supported the analytical data of the syntheses in a wide resinate concentration region, over a wide range of viscosity values and at different reaction temperatures. In addition, the application of the kinetic model to the modified resinate syntheses gave a good fit. A novel synthesis method with the addition of decarboxylated rosin (i.e. rosin oil) to the reaction mixture was introduced. The conversion of rosin acid to resinate was increased to the level necessary to obtain the target viscosity for the product at 235 °C. Due to a lower reaction temperature than in traditional fusion synthesis at 265 °C, thermal decarboxylation is avoided. As a consequence, the mass yield of the resinate syntheses can be increased from ca. 70% to almost 100% by recycling the added rosin oil.
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A new method has been developed for determining the content of mixtures of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), the HMX/RDX ratio, in explosive compositions by Fourier transform infrared spectroscopy (FT-IR), in the regions MIR (mid infrared) and NIR (near infrared) with reference values obtained by chromatographic analysis (HPLC). Plots of relative MIR (A917 / A783) or NIR absorbance values (A4412 / A4317) versus HMX/RDX ratio determined by HPLC analysis revealed good linear relationships.
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A short duration burst reminiscent of a soft gamma-ray repeater/anomalous X-ray pulsar behaviour was detected in the direction of LS I +61 303 by the Swift satellite. While the association with this well known gamma-ray binary is likely, a different origin cannot be excluded. Aims. We explore the error box of this unexpected flaring event and establish the radio, near-infrared and X-ray sources in our search for any peculiar alternative counterpart. Methods. We carried out a combined analysis of archive Very Large Array radio data of LS I +61 303 sensitive to both compact and extended emission. We also reanalysed previous near infrared observations with the 3.5 m telescope of the Centro Astronómico Hispano Alemán and X-ray observations with the Chandra satellite. Results. Our deep radio maps of the LS I +61 303 environment represent a significant advancement on previous work and 16 compact radio sources in the LS I +61 303 vicinity are detected. For some detections, we also identify near infrared and X-ray counterparts. Extended emission features in the field are also detected and confirmed. The possible connection of some of these sources with the observed flaring event is considered. Based on these data, we are unable to claim a clear association between the Swift-BAT flare and any of the sources reported here. However, this study represents the most sophisticated attempt to determine possible alternative counterparts other than LS I +61 303.
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In this work a fast method for the determination of the total sugar levels in samples of raw coffee was developed using the near infrared spectroscopy technique and multivariate regression. The sugar levels were initially obtained using gravimety as the reference method. Later on, the regression models were built from the near infrared spectra of the coffee samples. The original spectra were pre-treated according to the Kubelka-Munk transformation and multiplicative signal correction. The proposed analytical method made possible the direct determination of the total sugar levels in the samples with an error lower by 8% with respect to the conventional methodology.
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Least-squares support vector machines (LS-SVM) were used as an alternative multivariate calibration method for the simultaneous quantification of some common adulterants found in powdered milk samples, using near-infrared spectroscopy. Excellent models were built using LS-SVM for determining R², RMSECV and RMSEP values. LS-SVMs show superior performance for quantifying starch, whey and sucrose in powdered milk samples in relation to PLSR. This study shows that it is possible to determine precisely the amount of one and two common adulterants simultaneously in powdered milk samples using LS-SVM and NIR spectra.
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Diffuse reflectance near-infrared (DR-NIR) spectroscopy associated with partial least squares (PLS) multivariate calibration is proposed for a direct, non-destructive, determination of total nitrogen in wheat leaves. The procedure was developed for an Analytical Instrumental Analysis course, carried out at the Institute of Chemistry of the State University of Campinas. The DR-NIR results are in good agreement with those obtained by the Kjeldhal standard procedure, with a relative error of less than ± 3% and the method may be used for teaching purposes as well as for routine analysis.
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Rare earth ion doped solid state materials are the most important active media of near-infrared and visible lasers and other photonic devices. In these ions, the occurrence of Excited State Absorptions (ESA), from long lived electronic levels, is commonplace. Since ESA can deeply affect the efficiencies of the rare earth emissions, evaluation of these transitions cross sections is of greatest importance in predicting the potential applications of a given material. In this paper a detailed description of the pump-probe technique for ESA measurements is presented, with a review of several examples of applications in Nd3+, Tm3+ and Er3+ doped materials.
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The main objective of the present work is represented by the characterization of the physical properties of industrial kraft paper (i.e. transversal and longitudinal tear resistance, transversal traction resistance, bursting or crack resistance, longitudinal and transversal compression resistance (SCT (Compressive Strength Tester) and compression resistance (RCT-Ring Crush Test)) by near infrared spectroscopy associated to partial least squares regression. Several multivariate models were developed, many of them with high prevision capacity. In general, low prevision errors were observed and regression coefficients that are comparable with those provided by conventional standard methodologies.
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Optical chemical sensors with detection in the near and mid infrared region are reviewed. Fundamental concepts of infrared spectroscopy and optical chemical sensors are briefly described, before presenting some aspects on optical chemical sensors, such as synthesis of NIR and IR reagents, preparation of new materials as well as application in determinations of species of biological, industrial and environmental importance.
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The aim of this manuscript was to show the basic concepts and practical application of Partial Least Squares (PLS) as a tutorial, using the Matlab computing environment for beginners, undergraduate and graduate students. As a practical example, the determination of the drug paracetamol in commercial tablets using Near-Infrared (NIR) spectroscopy and Partial Least Squares (PLS) regression was shown, an experiment that has been successfully carried out at the Chemical Institute of Campinas State University for chemistry undergraduate course students to introduce the basic concepts of multivariate calibration in a practical way.
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Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a resolution method that has been efficiently applied in many different fields, such as process analysis, environmental data and, more recently, hyperspectral image analysis. When applied to second order data (or to three-way data) arrays, recovery of the underlying basis vectors in both measurement orders (i.e. signal and concentration orders) from the data matrix can be achieved without ambiguities if the trilinear model constraint is considered during the ALS optimization. This work summarizes different protocols of MCR-ALS application, presenting a case study: near-infrared image spectroscopy.
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The objective of this work was to develop a free access exploratory data analysis software application for academic use that is easy to install and can be handled without user-level programming due to extensive use of chemometrics and its association with applications that require purchased licenses or routines. The developed software, called Chemostat, employs Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), intervals Principal Component Analysis (iPCA), as well as correction methods, data transformation and outlier detection. The data can be imported from the clipboard, text files, ASCII or FT-IR Perkin-Elmer “.sp” files. It generates a variety of charts and tables that allow the analysis of results that can be exported in several formats. The main features of the software were tested using midinfrared and near-infrared spectra in vegetable oils and digital images obtained from different types of commercial diesel. In order to validate the software results, the same sets of data were analyzed using Matlab© and the results in both applications matched in various combinations. In addition to the desktop version, the reuse of algorithms allowed an online version to be provided that offers a unique experience on the web. Both applications are available in English.