Membrana de alumina anódica: comportamento da microestrutura e estudo das propriedades ópticas após tratamento térmico

Thin commercial aluminum electrolytic and passed through reactions was obtained with anodic alumina membranes nanopores. These materials have applications in areas recognized electronic, biomedical, chemical and biological weapons, especially in obtaining nanostructures using these membranes as a substrate or template for processing nanowires, nanodots and nanofibers for applications noble. Previous studies showed that the membranes that have undergone heat treatment temperature to 1300° C underwent changes in morphology, crystal structure and optical properties. This aim, this thesis, a study of the heat treatment of porous anodic alumina membranes, in order to obtain and to characterize the behavior changes structures during the crystallization process of the membranes, at temperatures ranging between 300 and 1700° C. It was therefore necessary to mount a system formed by a tubular furnace resistive alumina tube and controlled environment, applying flux with special blend of Ag-87% and 13% N2, in which argon had the role of carrying out the oxygen nitrogen system and induce the closing of the pores during the densification of the membrane. The duration of heat treatment ranged from 60 to 15 minutes, at temperatures from 300 to 1700° C respectively. With the heat treatment occurred: a drastic reduction of porosity, grain growth and increased translucency of the membrane. For the characterization of the membranes were analyzed properties: Physical - thermogravimetric, X-ray diffraction, BET surface area; morphological - SEM, EDS through compositional and, optical absorbance, and transmittance in the UV-VIS, and FTIR. The results using the SEM showed that crystallization has occurred, densification and significant changes in membrane structure, as well as obtaining microtube, the BET analysis showed a decrease in specific surface area of the membranes has to 44.381 m2.g-1 to less than 1.8 m2.g-1 and in the analysis of transmittance and absorbance was found a value of 16.5% in the range of 800 nm, characteristic of the near infrared and FTIR have confirmed the molecular groups of the material. Thus, one can say that the membranes were mixed characteristics and properties which qualify for use in gas filtration system, as well as applications in the range of optical wavelength of the infra-red, and as a substrate of nanomaterials. This requires the continuation and deepening of additional study

Dispersões sólidas de sinvastatina: preparação, caracterização, no estado sólido utilizando técnicas emergentes e estudo de estabilidade

This thesis aimed to assess the increase in solubility of simvastatin (SINV) with solid dispersions using techniques such as kneading (MA), co-solvent evaporation (ES), melting carrier (FC) and spray dryer (SD). Soluplus (SOL), PEG 6000 (PEG), PVP K-30 (PVP) e sodium lauryl sulphate (LSS) were used as carriers. The solid dispersions containing PEG [PEG-2(SD)], Soluplus [SOL-2(MA)] and sodium lauryl sulphate [LSS-2(ES)] were presented with a greater increase in solubility (5.02, 5.60 and 5.43 times respectively); analyses by ANOVA between the three groups did not present significant difference (p<0.05). In the phase solubility study, the calculation of the Gibbs free energy (ΔG) revealed that the spontaneity of solubilisation of SINV occurred in the order SOL>PEG >PVP 75%>LSS, always 80%. The phase diagrams of PEG and LSS presented solubilization stoichiometry of type 1:1 (type AL). The diagrams with PVP and SOL tend to 1:2 stoichiometry (type AL + AP). The stability coefficients (Ks) of the phase diagrams revealed that the most stable reactions occurred with LSS and PVP. The solid dispersions were characterized by Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), particle size distribution (PSD), near-infrared spectroscopy imaging (NIR-CI) and X-ray diffraction of the powder using the Topas software (PDRX-TOPAS). The solid dispersion PEG-2(SD) presented the greatest homogeneity and the lowest degree of crystallinity (18.2%). The accelerated stability study revealed that the solid dispersions are less stable than SINV, with PEG-2(SD) being the least stable, confirmed by FTIR and DSC. The analyses by PDRX-TOPAS revealed the amorphous character of the dispersions and the mechanism of increasing solubility

Monitoramento em tempo real de processos fermentativos por espectroscopia no infravermelho próximo (NIRS)

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

Morfologia em alta resolução espacial de estrelas de tipo Mira e R Corenae Borealis

Mira and R Coronae Borealis (R CrB) variable stars are evolved objects surrounded by circumstellar envelopes (CSE) composed of the ejected stellar material. We present a detailed high-spatial resolution morfological study of the CSE of three stars: IRC+10216, the closest and more studied Carbon-Rich Mira; o Ceti, the prototype of the Mira class; and RY Sagitarii (RY Sgr), the brightest R CrB variable of the south hemisphere. JHKL near-infrared adaptive optics images of IRC+10216 with high dynamic range and Vband images with high angular resolution and high depth, collected with the VLT/NACO and VLT/FORS1 instruments, were analyzed. NACO images of o Ceti were also analyzed. Interferometric observations of RY Sgr collected with the VLTI/MIDI instrument allowed us to explore its CSE innermost regions (»20 40 mas). The CSE of IRC+10216 exhibit, in near-infrared, clumps with more complex relative displacements than proposed in previous studies. In V-band, the majority of the non-concentric shells, located in the outer CSE layers, seem to be composed of thinner elongated shells. In a global view, the morphological connection between the shells and the bipolar core of the nebulae, located in the outer layers, together with the clumps, located in the innermost regions, has a difficult interpretation. In the CSE of o Ceti, preliminar results would be indicating the presence of possible clumps. In the innermost regions (.110 UA) of the CSE of RY Sgr, two clouds were detected in different epochs, embedded in a variable gaussian envelope. Based on a rigorous verification, the first cloud was located at »100 R¤ (or »30 AU) from the centre, toward the east-north-east direction (modulo 180o) and the second one was almost at a perpendicular direction, having aproximately 2£ the distance of the first cloud. This study introduces new constraints to the mass-loss history of these kind of variables and to the morphology of their innermost CSE regions

Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

Construção de modelos multivariados para determinação de lipídios totais e unidade em leite em pó comercial utilizando espectroscopia no infravermelho próximo

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%

Determinação do teor de diclofenaco sódico em comprimidos por espectroscopia no infravermelho próximo NIR com calibração multivariada PLS

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

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

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

Determinação de parâmetros (sólidos solúveis, pH e acidez titulável) em ameixas intactas usando espectroscopia no infravermelho próximo e seleção de comprimento de onda

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

Uso da espectroscopia do infravermelho próximo e técnicas multivariadas para diferenciar escherichia coli e salmonella enteritidis inoculadas em polpa de fruta (abacaxi)

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

Estudo da potencialidade da espectroscopia de infravermelho próximo na análise de cabelo utilizando ferramentas quimiométricas para diferenciar fumantes de não fumantes

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