Photoluminescence in amorphous TiO2-PbO systems

Photoluminescence (PL) at room temperature has been achieved in amorphous thin films and powders of the TiO2-PbO system. They were prepared by the polymeric precursor method with [PbO]/[TiO2] molar ratios ranging from 0.0 to 1.0. The energy position of maximum PL emission and the PL intensity showed dependence on Pb concentration. The Pb addition suggests an increase in the number of nonbridging oxygens (NBO) in the amorphous TiO2 network. These results support the relationship between photoluminescence and structure in TiO2-based amorphous materials.

Effect of atmosphere on the electrical properties of TiO2-SnO2 varistor systems

This work illustrates the advancement of research on TiO2-based electroceramics. In this work will be presented that the addition of different dopants, as well as thermal treatments at oxidizing and inert atmosphere, influences of the densification, the mean grain size and the electrical properties of the TiO2-based varistor ceramics. Dopants like Ta2O5, Nb2O5, and Cr2O3 have an especial role in the barrier formation at the grain boundary in the TiO2 varistors, increasing the nonlinear coefficient and decreasing the breakdown electric field. The influence of Cr'(Ti) is to increase the O' and O'(2) adsorption at the grain boundary interface and to promote a decrease in the conductivity by donating electrons to O-2 adsorbed at the grain boundary. In this paper, TiO2 and (Sn,Ti)O-2-based studies of polycrystalline ceramics, which show a non-linear I-V electrical response typical of low voltage varistor systems are also presented. All these systems are potentially promising for varistor applications. (C) 2004 Kluwer Academic Publishers.

Density functional theory study on the structural and electronic properties of low index rutile surfaces for TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 composite systems

The present study is concerned with the structural and electronic properties of the TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 composite systems. Periodic quantum mechanical method with density functional theory at the B3LYP level has been carried out. Relaxed surface energies, structural characteristics and electronic properties of the (I 10), (0 10), (10 1) and (00) low-index rutile surfaces for TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 models are studied. For, comparison purposes, the bare rutile TiO2 and SnO2 structures are also analyzed and compared with previous theoretical and experimental data. The calculated surface energy for both rutile TiO2 and SnO2 surfaces follows the sequence (110) < (010) < (101) < (001) and the energy increases as (010) < (101) < (110) < (001) and (010) approximate to (110) < (101) < (001) for SnO2/TiO2/SnO2 and TiO2/SnO2/TiO2 composite systems, respectively. SnO2/TiO2/SnO2 presents larger values of surface energy than the individual SnO2 and TiO2 metal oxides and the TiO2/SnO2/TiO2 system renders surface energy values of the same order that the TiO2 and lower than the SnO2. An analysis of the electronic structure of the TiO2/SnO2/TiO2 and SnO2/TiO2/SnO2 systems shows that the main characteristics of the upper part of the valence bands for all the studied surfaces are dominated by the external layers, i.e., by the TiO2 and the SnO2, respectively, and the topology of the lower part of the conduction bands looks like the core layers. There is an energy stabilization of both valence band top and conduction band bottom for (110) and (010) surfaces of the SnO2/TiO2/SnO2 composite system in relation to their core TiO2, whereas an opposite trend is found for the same surfaces of the TiO2/SnO2/TiO2 composite system in relation to the bare SnO2. The present theoretical results may explain the growth of TiO2@SnO2 bimorph composite nanotape.

Reconfiguration of distribution systems by a modified genetic algorithm

In this paper a genetic algorithm based reconfiguration method is proposed to minimize the real power losses of distribution systems. The main innovation of this research work is that new types of crossover and mutation operators are proposed, such that the best possible results are obtained, with an acceptable computational effort. The crossover and mutation operators were developed so as to take advantage of the particular characteristics of distribution systems (as the radial topology). Simulation results indicate that the proposed method is very efficient, being able to find excellent configurations, with low computational effort, especially for larger systems. ©2007 IEEE.

Minimal levels of ultraviolet light enhance the toxicity of TiO2 nanoparticles to two representative organisms of aquatic systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Properties of one modified composite resin by TiO2 nanoparticles

The purpose of this study was to evaluate the compressive strength and color changes of one composite resin modified by TiO2 nanoparticles and their distribution by SEM.

Adsorção-fotodegradação do herbicida paraquate em água pela argila Na-Bentonita e por novos materiais TiO2-Bentonita, TiO2/ZnOBentonita, Al/Fe-Bentonita e Al/Fe.Cu-Bentonita

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

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

Loss minimization by the predictor-corrector modified barrier approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Optimal reactive power flow via the modified barrier Lagrangian function approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.

Stability and convergence analysis of a neural model applied in nonlinear systems optimization

A neural model for solving nonlinear optimization problems is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The network is shown to be completely stable and globally convergent to the solutions of nonlinear optimization problems. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are presented to validate the developed methodology.

A novel approach for solving constrained nonlinear optimization problems using neurofuzzy systems

A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are completed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Parameterized fast decoupled power flow methods for obtaining the maximum loading point of power systems. Part I. Mathematical modeling

The conventional Newton and fast decoupled power flow (FDPF) methods have been considered inadequate to obtain the maximum loading point of power systems due to ill-conditioning problems at and near this critical point. It is well known that the PV and Q-theta decoupling assumptions of the fast decoupled power flow formulation no longer hold in the vicinity of the critical point. Moreover, the Jacobian matrix of the Newton method becomes singular at this point. However, the maximum loading point can be efficiently computed through parameterization techniques of continuation methods. In this paper it is shown that by using either theta or V as a parameter, the new fast decoupled power flow versions (XB and BX) become adequate for the computation of the maximum loading point only with a few small modifications. The possible use of reactive power injection in a selected PV bus (Q(PV)) as continuation parameter (mu) for the computation of the maximum loading point is also shown. A trivial secant predictor, the modified zero-order polynomial which uses the current solution and a fixed increment in the parameter (V, theta, or mu) as an estimate for the next solution, is used in predictor step. These new versions are compared to each other with the purpose of pointing out their features, as well as the influence of reactive power and transformer tap limits. The results obtained with the new approach for the IEEE test systems (14, 30, 57 and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are enhanced and the region of convergence around the singular solution is enlarged. In addition, it is shown that parameters can be switched during the tracing process in order to efficiently determine all the PV curve points with few iterations. (C) 2003 Elsevier B.V. All rights reserved.