Two-dimensional modeling the static parameters for a submicron field-effect transistor

A comparison of two different models for simulation of submicron GaAs MESFETs static characteristics has been made. A new two-dimensional numerical model is presented to investigate the submicron field-effect transistor characteristics, the influence of the geometry of the component, like the inter-electrode distance, on the capacities. All simulation revealed the existence of a high contact electric field near the gate, which creates a depopulated zone around the gate, but the preceding studies have neglected the edge effects, which are very significant for the submicron MESFETs

Artificial intelligence to predict inhibition performance of pitting corrosion

This work aims to compare several algorithms for predicting the inhibition performance of localized corrosion. For this more than 400 electrochemical experiments were carried out in a corrosive solution containing an inorganic inhibitor. Pitting potential is used to indicate the performance of the inhibitor/oxidant mixture to prevent pitting corrosion. At the end of the electrochemical program a file containing all the experimental results has been prepared and submitted to several algorithms. Through a training phase each algorithm uses a set of experimental results to adjust its parameters and another set to predict the pitting potential starting from the properties and the chemical composition of the solution. The prediction performance of an algorithm is estimated by the  difference between experimental pitting potential and the calculated one. The order of performance of the algorithms is: GA-ANN > LS-SVM > PSO-ANN > ANN >ANFIS > KNN > RT > KBP > LDA.Key words: Pitting potential, Corrosion inhibitor, Performance prediction, Artificial intelligence

Active layer – semi-insulating substrate interface effect on GaAs MESFET components

This paper describes the polarization effect of the substrate on the electric characteristics of the GaAs Metal Semiconductor Field Effect Transistor (GaAs MESFET). An analysis based on the existence of a double space charge at the interface active layer – semi-insulating substrate is applied to determine the active layer and interface parameters. The properties of the drain current and the output admittance characteristics as well as the physical phenomena inherent to this interface are assigned to the dynamic response of the double space charge region

An improved contribution to optimize Si and GaAs solar cell performances

In resent years a considerable effort (experience, numerical simulation and theoretical prediction models) has been devoted to the study of photovoltaic devices characterised by high efficiency and low cost. The present study comes in way to contribute in the optimisation of the performance of Si an GaAs based (N/P) solar cells by the determination of physical and technological parameters giving the best photovoltaic conversion efficiency and a good spectral response. The four principal parameters that influence the operation of a solar cell are emitter and base doping, junction depth and base thickness. We have also taken into account the recent technique of elaboration of these structures. This study concerns the use of novel optimised values of electronic properties of GaAs and Si materials such as recombination velocity at surface (front and back). All enhancements recently reached: BSF, BSR layers, ARC anti reflection layer with textured surface, surfaces passivation, improved ohmic contacts are taken into account. I-V, P-V, EQE-λ characteristics obtained by PC1D similator on two different cells (Si and GaAs) under the global spectra AM1.5 have allowed us to get optimal cells. The comparison of the cells shows the advantage of given GaAs cells. The effect of solar concentration (1-100 suns) on cell operation has been studied. The later has contributed to the enhancement of the energetic efficiency. The effects different standard spetra such as AM1, AM1, 5G, and AM1.5D have been studied. The optimal values of physical parameters giving the best currents of short-circuit and voltages of open circuit as well as high conversion efficiency have been obtained for these two solar materials

OPTIMIZATION OF LEARNING ALGORITHMS IN THE PREDICTION OF PITTING CORROSION

This work is part of a scientific research program whose objective is to prevent pitting corrosion of an open cooling circuit of a nuclear installation. Various corrosion inhibitors have been studied. The performances of pitting corrosion inhibition were discussed and compared on the basis of several criteria. The experimental data were collected in a large table and subjected to algorithms in order to construct models for predicting corrosion inhibition performance. We used four algorithms: Genetic Algorithm-Artificial Neural Network (GAANN); Least Squares-Support Vector Machine (LS-SVM), K Nearest Neighbors (KNN) and Regression Tree (RT). We optimized the data fraction reserved for learning and we sought to optimize the parameters specific to each algorithm. The efficiency of pitting inhibition increases in the following order: HCO3- < H2PO4- < CO32- < PO4-2 < PO4 3- < SiO3 2- < MoO4 2- < WO4 2-. Our results showed that the order of performance of the algorithms is: RT < KNN < LS-SVM < GA-ANN

Accurate numerical modelling the GaAs MESFET current-voltage characteristics

In this paper, we present a computing model of the current-voltage (I-V) characteristics of a gallium arsenide Schottky barrier field effect transistor called GaAs MESFET. This physical model is based on the two-dimensional analysis of the Poisson equation in the active region under the gate. In this frame, we elaborated a simulation software based on analysis of expressions that we have previously set up [1-3], the obtained theoretical results are discussed and compared to the experimental ones

Influence of physical and geometrical parameters on electrical properties of short gate GaAs MESFETs

In the information sciences such as computer science, telecommunications, the treatment of signal or image transmission, the field effect components play an important role. In the frame of our work, we are interested in the study of the gallium arsenide short gate field effect transistor called GaAs MESFET. After analytical studying the component static characteristics, according to different operation regimes, a numerical simulation was worked out. The influence of technological dimensions (L, Z, a, and Nd) was studied. The obtained results allow us to determine optimal parameters of the devices from the viewpoint of their applications and specific use

Modélisation des Caractéristiques du GaAs MESFET

A NEW MODELING OF THE CHARACTERISTICS OF GaAs MESFET'S: A new approach for I-V standard model is proposed. This approach allowed to conceive applicable model for MESFET's operating in the turn-one or pinch-off region, and valid for the short-channel and the long-channel MESFET's, in which the two-dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional 1D approximation. The drain current is decomposed into two components; the first is due to the conduction current flowing through the conduction channel, and the second component is a result of the current flowing through the space charge region resulting from the injection of the channel electrons into this last region. Moreover, comparison between the proposed analytical model and the experimental data are made and good agreement is obtained. In the end, this model is applied to estimate the cut-off frequency of the MESFET-GaAs from these static characteristics. This estimation is based on the theoretical calculation of the transconductance and the gate capacitance of the device