Taking Advantage of Electrostatic Interactions To Grow Langmuir-Blodgett Films Containing Multilayers of the Phospholipid Dipalmitoylphosphatidylglycerol

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Natural Polysaccharides as Active Biomaterials in Nanostructured Films for Sensing

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effect of Gamma Irradiation on Caprolactam Migration from Multi layer Polyamide 6 Films into Food Simulants: Development and Validation of a Gas Chromatographic Method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

Artificial neural networks for load flow and external equivalents studies

In this paper an artificial neural network (ANN) based methodology is proposed for (a) solving the basic load flow, (b) solving the load flow considering the reactive power limits of generation (PV) buses, (c) determining a good quality load flow starting point for ill-conditioned systems, and (d) computing static external equivalent circuits. An analysis of the input data required as well as the ANN architecture is presented. A multilayer perceptron trained with the Levenberg-Marquardt second order method is used. The proposed methodology was tested with the IEEE 30- and 57-bus, and an ill-conditioned 11-bus system. Normal operating conditions (base case) and several contingency situations including different load and generation scenarios have been considered. Simulation results show the excellent performance of the ANN for solving problems (a)-(d). (C) 2010 Elsevier B.V. All rights reserved.

Analysis of Acid Alizarin Violet N Dye Removal Using Sugarcane Bagasse as Adsorbent

With the development of the textile industry, there has been a demand for dye removal from contaminated effluents. In recent years, attention has been directed toward various natural solid materials that are capable of removing pollutants from contaminated water at low cost. One such material is sugarcane bagasse. The aim of the present study was to evaluate adsorption of the dye Acid Violet Alizarin N with different concentrations of sugarcane bagasse and granulometry in agitated systems at different pH. The most promising data (achieved with pH 2.5) was analyzed with both Freundlich and Langmuir isotherms equations. The model that better fits dye adsorption interaction into sugarcane bagasse is Freundlich equation, and thus the multilayer model. Moreover, a smaller bagasse granulometry led to greater dye adsorption. The best treatment was achieved with a granulometry value lower than 0.21 mm at pH 2.50, in which the total removal was estimated at a concentration of 16.25 mg mL(-1). Hence, sugarcane bagasse proves to be very attractive for dye removal from textile effluents.

Quartz Crystal Microbalance monitoring the real-time binding of lectin with carbohydrate with high and low molecular mass

Quartz Crystal Microbalance (QCM) was used to monitor the mass changes on a quartz crystal surface containing immobilized lectins that interacted with carbohydrates. The strategy for lectin immobilization was developed on the basis of a multilayer system composed of Au-cystamine-glutaraldehyde-lectin. Each step of the immobilization procedure was confirmed by FTIR analysis. The system was used to study the interactions of Concanavalin A (ConA) with maltose and Jacalin with Fetuin. The real-time binding of different concentrations of carbohydrate to the immobilized lectin was monitored by means of QCM measurements and the data obtained allowed for the construction of Langmuir isotherm curves. The association constants determined for the specific interactions analyzed here were (6.4 +/- 0.2) X 10(4) M-1 for Jacalin-Fetuin and (4.5 +/- 0.1) x 10(2) M-1 for ConA-maltose. These results indicate that the QCM constitutes a suitable method for the analysis of lectin-carbohydrate interactions, even when assaying low molecular mass ligands such as disaccharides. Published by Elsevier B.V.

Erbium-activated silica-zirconia planar waveguides prepared by sol-gel route

Er(3+) doped (100-x)SiO(2)-xZrO(2) planar waveguides were prepared by the sol-gel route, with x ranging from 10 up to 30 mol%. Multilayer films doped with 0.3 mol% Er(3+) ions were deposited on fused quartz substrates by the dip-coating technique. The thickness and refractive index were measured by m-line spectroscopy at different wavelengths. The fabrication protocol was optimized in order to confine one propagating mode at 1.5 mu m. Photoluminescence in the near and visible region indicated a crystalline local environment for the Er(3+) ion. (c) 2007 Elsevier B.V. All rights reserved.

Aplicação de redes neurais na estimação da temperatura interna de transformadores de distribuição imersos em óleo

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação de painéis produzidos a partir de resíduos sólidos para aplicação na arquitetura

O presente trabalho tem por objetivo o reaproveitamento de resíduos sólidos na preparação de painéis para uso na arquitetura. Para atingir as metas propostas, painéis foram preparados a partir de resíduos provenientes de embalagens cartonadas e plásticas, utilizando-se como elemento de reforço, resíduos lignocelulósicos (casca de amendoim e de arroz). A concentração e a natureza dos resíduos utilizados como matriz e como carga foram variadas gerando doze condições experimentais diferentes. As propriedades avaliadas dos painéis foram o módulo de ruptura, módulo de elasticidade, tração perpendicular à superfície, inchamento em espessura, absorção de água e densidade. Todos os ensaios foram realizados segundo as normas ASTM D1037 e EN 317, referente à chapa de partículas. Os resultados foram analisados segundo a norma ANSI A208.1 que especifica as propriedades de desempenho requeridas para as chapas de partículas. Os painéis foram classificados como de baixa densidade, podendo ser utilizados como forros, divisórias, revestimento decorativos e demais aplicações que requerem as mesmas propriedades físicas e mecânicas. Os painéis a base de embalagem plástica reforçados com casca de arroz apresentaram propriedades superiores do que os demais painéis produzidos. O elemento arquitetônico desenvolvido neste estudo representa um novo mercado potencial, podendo ser empregado no ambiente urbano e rural, atendendo ao conceito de produto ecoeficiente.

Photo-induced transformations in chalcogenide nanocomposite layers

Investigations of photo-induced structural transformations (PST) and related changes of optical parameters in amorphous chalcogenide layers were further developed towards the establishment of their dependence on the compositional modulation of the material at nanoscale-dimensions (similar to3-10 nm) and possible improvement of optical recording parameters as well. Besides the known amorphous-amorphous PST, photo-stimulated interdiffusion and crystallization in multilayer structures were found as a useful method for amplitude-phase optical relief formation. The last two types of PST were influenced by size restrictions and efficiently operated by the composition and by the modulation period of the layered nanocomposite. Experimental evidences were obtained in Se-, AsSe-, Se0.4Te0.6-containing layered or quasi zero-dimensional structures based on As2S3 or SiOx and MgF2 matrix. Comparison was made with As2S3- and GeS2-based multicomponent layers, containing Se, Te and Ga. (C) 2004 Elsevier B.V. All rights reserved.

An application of neural network technique to correct the dome temperature effects on pyrgeometer measurements

This work describes an application of a multilayer perceptron neural network technique to correct dome emission effects on longwave atmospheric radiation measurements carried out using an Eppley Precision Infrared Radiometer (PIR) pyrgeometer. It is shown that approximately 7-month-long measurements of dome and case temperatures and meteorological variables available in regular surface stations (global solar radiation, air temperature, and air relative humidity) are enough to train the neural network algorithm and correct the observed longwave radiation for dome temperature effects in surface stations with climates similar to that of the city of São Paulo, Brazil. The network was trained using data from 15 October 2003 to 7 January 2004 and verified using data, not present during the network-training period, from 8 January to 30 April 2004. The longwave radiation values generated by the neural network technique were very similar to the values obtained by Fairall et al., assumed here as the reference approach to correct dome emission effects in PIR pyrgeometers. Compared to the empirical approach the neural network technique is less limited to sensor type and time of day (allows nighttime corrections).

Electroactive layer-by-layer films of iron tetrasulfonated phthalocyanine

Electroactive films of iron tetrasulfonated phthalocyanine (FeTsPc) were assembled via the electrostatic layer-by-layer technique (LBL), in which FeTsPc layers were alternated with the polycationic poly(allylamine hydrochloride) (PAN). The multilayer formation was monitored via UV-Vis spectroscopy by measuring the increase in the Q Band of FeTsPc at 676 nm. Film thickness was estimated by profilometry as ca. 10 Angstrom per bilayer. Fourier transform infrared and UV-Vis absorption spectroscopy suggested specific interactions between FeTsPc and PAR Cyclic voltammograms showed reproducible pairs of oxidation-reduction peaks at 0.92 mV and 0.70 mV, respectively, for a 50-bilayer PAH/FeTsPc film at 50 mV/s (vs Ag/AgNO3).

Microstructure and dielectric properties of (Ba,Sr)TiO3 thin film produced by the polymeric precursor method

BaxSr1-xTiO3 (x = 0.6) (BST) thin films were successfully prepared on a Pt(111)/TiO2/SiO2/Si(100) substrate by spin coating, using the polymeric precursor method. BST films with a perovskite single phase were obtained after heat treatment at 700 degrees C. The multilayer BST thin films had a granular structure will a grain size of approximately 60 nm. A 480-nm-thick film was obtained by carrying out five cycles of the spin-coating/heating process. Scanning electron microscopy and atomic force microscopy analyses showed that the thin films had a smooth, dense, crack-free surface with low surface roughness (3.6 nm). At room temperature and at a frequency of 100 kHz, the dielectric constant and the dissipation factor were, respectively, 748 and 0.042. The high dielectric constant value was due to the high microstructural quality and chemical homogeneity of the thin films obtained by the polymeric precursor method.