893 resultados para chemometric technique


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In this work, using the EPR spectroscopy, we analysed the thermal stability of some organic-mineral compounds found in a Gleysoil from Rio Janeiro. It was observed a complete disappearance of the EPR signal around 600 °C for the < 2 µm fraction and a residual EPR signal of semiquinone free radical for the 2-20 µm and 20-53 µm fractions at the same temperature. Also, the experiments showed that the 2-20 µm fraction had a larger concentration of semiquinone free radical per g of carbon and a smaller line width indicated a larger humification of this fraction. This is an evidence that the soil organic matter of this fraction (2-20 µm) is more stable than the other ones.

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The design and use of a novel apparatus for a variant of vacuum distillation is described. Relative to a conventional device, the apparatus/technique described permits superior recovery of multigram quantities of moderately volatile liquids from vacuum distillations.

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We report the use of an optical fiber sensor to measure the soybean oil concentration in samples obtained from the mixture of pure biodiesel and commercial soybean oil. The operation of the device is based on the long-period grating sensitivity to the surrounding medium refractive index, which leads to measurable modifications in the grating transmission spectrum. The proposed analysis method results in errors in the oil concentration of 0.4% and 2.6% for pure biodiesel and commercial soybean oil, respectively. Techniques of total glycerol, dynamic viscosity, density, and hydrogen nuclear magnetic resonance spectroscopy were also employed to validate the proposed method.

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Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

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Two spectrophotometric methods are described for the simultaneous determination of ezetimibe (EZE) and simvastatin (SIM) in pharmaceutical preparations. The obtained data was evaluated by using two different chemometric techniques, Principal Component Regression (PCR) and Partial Least-Squares (PLS-1). In these techniques, the concentration data matrix was prepared by using the mixtures containing these drugs in methanol. The absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbances in the range of 240 - 300 nm in the intervals with Δλ = 1 nm at 61 wavelengths in their zero order spectra, then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of EZE and SIM in their mixture. The procedure did not require any separation step. The linear range was found to be 5 - 20 µg mL-1 for EZE and SIM in both methods. The accuracy and precision of the methods were assessed. These methods were successfully applied to a pharmaceutical preparation, tablet; and the results were compared with each other.

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Signal processing methods based on the combined use of the continuous wavelet transform (CWT) and zero-crossing technique were applied to the simultaneous spectrophotometric determination of perindopril (PER) and indapamide (IND) in tablets. These signal processing methods do not require any priory separation step. Initially, various wavelet families were tested to identify the optimum signal processing giving the best recovery results. From this procedure, the Haar and Biorthogonal1.5 continuous wavelet transform (HAAR-CWT and BIOR1.5-CWT, respectively) were found suitable for the analysis of the related compounds. After transformation of the absorbance vectors by using HAAR-CWT and BIOR1.5-CWT, the CWT-coefficients were drawn as a graph versus wavelength and then the HAAR-CWT and BIOR1.5-CWT spectra were obtained. Calibration graphs for PER and IND were obtained by measuring the CWT amplitudes at 231.1 and 291.0 nm in the HAAR-CWT spectra and at 228.5 and 246.8 nm in BIOR1.5-CWT spectra, respectively. In order to compare the performance of HAAR-CWT and BIOR1.5-CWT approaches, derivative spectrophotometric (DS) method and HPLC as comparison methods, were applied to the PER-IND samples. In this DS method, first derivative absorbance values at 221.6 for PER and 282.7 nm for IND were used to obtain the calibration graphs. The validation of the CWT and DS signal processing methods was carried out by using the recovery study and standard addition technique. In the following step, these methods were successfully applied to the commercial tablets containing PER and IND compounds and good accuracy and precision were reported for the experimental results obtained by all proposed signal processing methods.

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Antimony is a common catalyst in the synthesis of polyethylene terephthalate used for food-grade bottles manufacturing. However, antimony residues in final products are transferred to juices, soft drinks or water. The literature reports mentions of toxicity associated to antimony. In this work, a green, fast and direct method to quantify antimony, sulfur, iron and copper, in PET bottles by X-ray fluorescence spectrometry is presented. 2.4 to 11 mg Sb kg-1 were found in 20 samples analyzed. The coupling of the multielemental technique to chemometric treatment provided also the possibility to classify PET samples between bottle-grade PET/recycled PET blends by Fe content.

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The hydroalcoholic extracts prepared from standard leaves of Maytenus ilicifolia and commercial samples of espinheira-santa were evaluated qualitatively (fingerprinting) and quantitatively. In this paper, fingerprinting chromatogram coupled with Principal Component Analysis (PCA) is described for the metabolomic analysis of standard and commercial espinheira-santa samples. The epicatechin standard was used as an external standard for the development and validation of a quantitative method for the analysis in herbal medicines using a photo diode array detector. This method has been applied for quantification of epicatechin in commercialized herbal medicines sold as espinheira-santa in Brazil and in the standard sample of M. ilicifolia.

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The importance of medicinal plants and their use in industrial applications is increasing worldwide, especially in Brazil. Phyllanthus species, popularly known as "quebra-pedras" in Brazil, are used in folk medicine for treating urinary infections and renal calculus. This paper reports an authenticity study, based on herbal drugs from Phyllanthus species, involving commercial and authentic samples using spectroscopic techniques: FT-IR, ¹H HR-MAS NMR and ¹H NMR in solution, combined with chemometric analysis. The spectroscopic techniques evaluated, coupled with chemometric methods, have great potential in the investigation of complex matrices. Furthermore, several metabolites were identified by the NMR techniques.

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We developed a simple, rapid, and solventless method for analyzing trihalomethanes in beer samples using headspace solid-phase microextraction. The effects of varying experimental parameters, such as extraction temperature and time, addition of sodium chloride, and agitation speed, on extraction yield were studied using a univariate experimental design. Limits of detection between 0.22 and 0.46 µg L- 1 and wide linear ranges were achieved for trihalomethanes. We measured the trihalomethane recoveries and precision (as the standard deviation of repeat measurements) and demonstrated the applicability of the proposed method by analyzing 32 beer samples.

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To choose among the variety of oleaginous plants for biodiesel production, the oil content of several matrices was determined through different low-field ¹H nuclear magnetic resonance (NMR) experiments with varied pulse sequences, namely single-pulse, spin-echo, CPMG, and CWFP. The experiments that involved the first three sequences showed high correlation with each other and with the solvent extraction method. The quality of the vegetable oils was also evaluated on the basis of the existing correlation between the T2 values of the oils and their properties, such as viscosity, iodine index, and cetane index. These analyses were performed using HCA and PCA chemometric tools. The results were sufficiently significant to allow separation of the oleaginous matrices according to their quality. Thus, the low-field ¹H NMR technique was confirmed as an important tool to aid in the selection of oleaginous matrices for biodiesel production.

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A statistical mixture-design technique was used to study the effects of different solvents and their mixtures on the yield, total polyphenol content, and antioxidant capacity of the crude extracts from the bark of Schinus terebinthifolius Raddi (Anacardiaceae). The experimental results and their response-surface models showed that ternary mixtures with equal portions of all the three solvents (water, ethanol and acetone) were better than the binary mixtures in generating crude extracts with the highest yield (22.04 ± 0.48%), total polyphenol content (29.39 ± 0.39%), and antioxidant capacity (6.38 ± 0.21). An analytical method was developed and validated for the determination of total polyphenols in the extracts. Optimal conditions for the various parameters in this analytical method, namely, the time for the chromophoric reaction to stabilize, wavelength of the absorption maxima to be monitored, the reference standard and the concentration of sodium carbonate were determined to be 5 min, 780 nm, pyrogallol, and 14.06% w v-1, respectively. UV-Vis spectrophotometric monitoring of the reaction under these conditions proved the method to be linear, specific, precise, accurate, reproducible, robust, and easy to perform.

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We propose an analytical method based on fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectroscopy to detect the adulteration of petrodiesel and petrodiesel/palm biodiesel blends with African crude palm oil. The infrared spectral fingerprints from the sample analysis were used to perform principal components analysis (PCA) and to construct a prediction model using partial least squares (PLS) regression. The PCA results separated the samples into three groups, allowing identification of those subjected to adulteration with palm oil. The obtained model shows a good predictive capacity for determining the concentration of palm oil in petrodiesel/biodiesel blends. Advantages of the proposed method include cost-effectiveness and speed; it is also environmentally friendly.