195 resultados para Espectroscopia de infravermelhos

em Universidade Federal do Rio Grande do Norte(UFRN)


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Plasma process like ionic nitriding and cathodic cage plasma nitriding are utilized in order to become hard surface of steels. The ionic nitriding is already accepted in the industry while cathodic cage plasma nitriding process is in industrial implementation stage. Those process depend of plasma parameters like electronic and ionic temperature (Te, Ti), species density (ne, ni) and of distribution function of these species. In the present work, the plasma used to those two processes has been observed through Optical Emission Spectroscopy OES technique in order to identify presents species in the treatment ambient and relatively quantify them. So plasma of typical mixtures like N2 H2 has been monitored through in order to study evolution of those species during the process. Moreover, it has been realized a systematic study about leaks, also thought OES, that accomplish the evolution of contaminant species arising because there is flux of atmosphere to inside nitriding chamber and in what conditions the species are sufficiently reduced. Finally, to describe the physic mechanism that acts on both coating techniques ionic nitriding and cathodic cage plasma nitriding

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Many applications require that the plasma discharge is produced apart from the surface to be processed, thus preventing damage caused by bombardment and/or plasma radiation. In the post-discharge regime in various applications thermally sensitive materials can be used. In this work, active species produced by discharge and post-discharge hollow cathode were diagnosed by optical emission spectroscopy and mass spectrometry. The discharge was produced with the gases Ar and Ar - N2 gas flow ranging from 1 to 6 cm3/min and electric current between 150 to 600 mA. It was estimated that the ion density inside the hollow cathode, with 2 mm diameter ranged between 7.71 and 14.1 x 1015 cm-3. It was observed that the gas flow and the electric current changes the emission intensity of Ar and N2 species. The major ionic species detected by quadrupole mass spectrometry were Ar+ and N2+. The ratio of optical emission intensities of N2(1 +)/Ar(811 nm) was related to the partial pressure of N2 after the hollow cathode discharge at low pressure

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A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes

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This work deals with the application of X-Ray Absorption Spectroscopy on the study of the behavior of Cu2+ ions in inverse micelles. The formation of copper nanoparticles in water-in-oil microemulsions in pseudo-ternary systems of cetyl trimethylammonium Bromide (CTAB) surfactant, butanol co-surfactant, heptane as oil phase and aqueous solutions of CuSO4.5H2O, and NaBH4. The microemulsions were prepared with a fixed percentage (60 %) of oil phase and a variable water to tensoative proportion. It was observed an increase on Cu2+ reduction by the sodium borohydride in microemulsions with 13 % of aqueous phase, independent of the reaction time. For the microemulsions in which the aqueous phase is composed only by the CuSO4 solution, it was observed that the color of the solution depends on the water to surfactant ratio. These changes in color were attributed to a competition for the hidratation water between the polar head of the tensoative and Cu2+ ions with the eventual substitution of oxygen by bromine atoms in the first coordination shell of Cu2+ ions

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In this work calibration models were constructed to determine the content of total lipids and moisture in powdered milk samples. For this, used the near-infrared spectroscopy by diffuse reflectance, combined with multivariate calibration. Initially, the spectral data were submitted to correction of multiplicative light scattering (MSC) and Savitzsky-Golay smoothing. Then, the samples were divided into subgroups by application of hierarchical clustering analysis of the classes (HCA) and Ward Linkage criterion. Thus, it became possible to build regression models by partial least squares (PLS) that allowed the calibration and prediction of the content total lipid and moisture, based on the values obtained by the reference methods of Soxhlet and 105 ° C, respectively . Therefore, conclude that the NIR had a good performance for the quantification of samples of powdered milk, mainly by minimizing the analysis time, not destruction of the samples and not waste. Prediction models for determination of total lipids correlated (R) of 0.9955, RMSEP of 0.8952, therefore the average error between the Soxhlet and NIR was ± 0.70%, while the model prediction to content moisture correlated (R) of 0.9184, RMSEP, 0.3778 and error of ± 0.76%

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This work is combined with the potential of the technique of near infrared spectroscopy - NIR and chemometrics order to determine the content of diclofenac tablets, without destruction of the sample, to which was used as the reference method, ultraviolet spectroscopy, which is one of the official methods. In the construction of multivariate calibration models has been studied several types of pre-processing of NIR spectral data, such as scatter correction, first derivative. The regression method used in the construction of calibration models is the PLS (partial least squares) using NIR spectroscopic data of a set of 90 tablets were divided into two sets (calibration and prediction). 54 were used in the calibration samples and the prediction was used 36, since the calibration method used was crossvalidation method (full cross-validation) that eliminates the need for a validation set. The evaluation of the models was done by observing the values of correlation coefficient R 2 and RMSEC mean square error (calibration error) and RMSEP (forecast error). As the forecast values estimated for the remaining 36 samples, which the results were consistent with the values obtained by UV spectroscopy

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In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

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The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums

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Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

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This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification

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In this work, the structures of LaCoO3, La0,8Ba0,2CoO3 and La0,8Ca0,2CoO3 perovskites were characterized as a function of temperature (LaCoO3 structure being analyzed only at room temperature). The characterization of these materials were made by X-Ray Absorption Spectroscopy (XAS), in the cobalt K-edge, taking into account the correlated Einstein model X-ray absorption fine structure (EXAFS). The first part of the absorption spectrum corresponded the X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS). These materials were prepared by the combustion method. The combustion products were calcinated at 900 0C, for 6 hours in air. Noted that the sample LaCoO3 at room temperature and samples doped with Calcium and Barium in the temperature range of 50 K to 298 K showed greater distortion to monoclinic symmetry with space group I2/a. However, the sample doped with barium at the temperatures 50 K, 220 K, and 260 K showed a slight distortion to rhombohedral symmetry with space group R-3c. The La0,8Ca0, 2CoO3 structure was few sensitive to temperature variation, showing a higher local distortion in the octahedron and a higher local thermal disorder. These interpretations were in agreement with the information electronic structural on the XANES region and geometric in the EXAFS region

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This work was developed with the objective of proposing a simple, fast and versatile methodological routine using near-infrared spectroscopy (NIR) combined with multivariate analysis for the determination of ash content, moisture, protein and total lipids present in the gray shrimp (Litopenaeus vannamei ) which is conventionally performed gravimetrically after ashing at 550 ° C gravimetrically after drying at 105 ° C for the determination of moisture gravimetrically after a Soxhlet extraction using volumetric and after digestion and distillation Kjedhal respectively. Was first collected the spectra of 63 samples processed boiled shrimp Litopenaeus vannamei species. Then, the determinations by conventional standard methods were carried out. The spectra centered average underwent multiplicative scattering correction of light, smoothing Saviztky-Golay 15 points and first derivative, eliminated the noisy region, the working range was from 1100,36 to 2502,37 nm. Thus, the PLS models for predicting ash showed R 0,9471; 0,1017 and RMSEP RMSEC 0,1548; Moisture R was 0,9241; 2,5483 and RMSEP RMSEC 4,1979; R protein to 0,9201; 1,9391 and RMSEP RMSEC 2,7066; for lipids R 0,8801; 0,2827 and RMSEP RMSEC 0,2329 So that the results showed that the relative errors found between the reference method and the NIR were small and satisfactory. These results are an excellent indication that you can use the NIR to these analyzes, which is quite advantageous, since conventional techniques are time consuming, they spend a lot of reagents and involve a number of professionals, which requires a reasonable runtime while after the validation of the methodology execution using NIR reduces all this time to a few minutes, saving reagents, time and without waste generation, and that this is a non-destructive technique.

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Plasma process like ionic nitriding and cathodic cage plasma nitriding are utilized in order to become hard surface of steels. The ionic nitriding is already accepted in the industry while cathodic cage plasma nitriding process is in industrial implementation stage. Those process depend of plasma parameters like electronic and ionic temperature (Te, Ti), species density (ne, ni) and of distribution function of these species. In the present work, the plasma used to those two processes has been observed through Optical Emission Spectroscopy OES technique in order to identify presents species in the treatment ambient and relatively quantify them. So plasma of typical mixtures like N2 H2 has been monitored through in order to study evolution of those species during the process. Moreover, it has been realized a systematic study about leaks, also thought OES, that accomplish the evolution of contaminant species arising because there is flux of atmosphere to inside nitriding chamber and in what conditions the species are sufficiently reduced. Finally, to describe the physic mechanism that acts on both coating techniques ionic nitriding and cathodic cage plasma nitriding

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ALVES, Ana paula Melo. Vermiculitas tratadas quimicamente na obtenção de sólidos microporosos como precursores para híbridos inorgânico-orgânicos com aplicações adsortivas. 2009. 124 f. Tese (Doutorado em Quimica) - Centro de Ciências Exatas e da Natureza, Universidade Federal da Paraíba, João Pessoa, PB, 2009.

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MELO, D. M. A. et al. Synthesis and charactezarion of lanthanum and yttrium doped Fe2O3 pigments. Cerâmica, São Paulo, v. 53, p. 79-82, 2007.