956 resultados para impedance spectra


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

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

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

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The effect of manganese on the vibrational properties of Ga(1-x)Mn(x)N (0 <= x <= 0.18) films has been investigated by Raman scattering using 488.0 and 632.8 nm photon excitations. The first-order transverse and longitudinal optical GaN vibrational bands were observed in the whole composition range using both excitations, while the corresponding overtones, as well as a prominent peak located in 1238 cm(-1) (153.5 meV) were only observed in the Mn-containing films under 488.0 nm excitation. We propose that the peak observed at 1238 cm(-1) is due to resonant Mn local vibrational modes, the excitation process being related to electronic transitions involving the Mn acceptor band.

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Injection-limited operation is identified in thin-film, alpha-NPD-based diodes. A detailed model for the impedance of the injection process is provided which considers the kinetics of filling/releasing of interface states as the key factor behind the injection mechanism. The injection model is able to simultaneously account for the steady-state, current-voltage (J-V) characteristics and impedance response. and is based on the sequential injection of holes mediated by energetically distributed surface states at the metal-organic interface. The model takes into account the vacuum level offset caused by the interface dipole, along with the partial shift of the interface level distribution with bias voltage. This approach connects the low-frequency (similar to 1 Hz) capacitance spectra, which exhibits a transition between positive to negative values, to the change in the occupancy of interface states with voltage. Simulations based on the model allow to derive the density of interface states effectively intervening in the carrier injection (similar to 5 x 10(12) cm(-2)), which exhibit a Gaussian-like distribution. A kinetically determined hole barrier is calculated at levels located similar to 0.4 eV below the contact work function. (C) 2008 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.