A carbon nanotube field effect transistor (CNTFET) with Schottky contacts for the drain and the source has been investigated. It is shown that the saturation region of the transistor output characteristics is small. This limits the application of the transistor. To impr More
A carbon nanotube field effect transistor (CNTFET) with Schottky contacts for the drain and the source has been investigated. It is shown that the saturation region of the transistor output characteristics is small. This limits the application of the transistor. To improve the saturation range in the output characteristics, new structures are proposed, and the simulation results are compared. The proposed structures have supperior output characteristics.
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In this paper an efficient method for modeling semiconductor devices using the drift-diffusion (DD) model and neural network is presented. Unlike HD model which is complicated, time consuming with high processing cost, the proposed method has lower complexity and higher More
In this paper an efficient method for modeling semiconductor devices using the drift-diffusion (DD) model and neural network is presented. Unlike HD model which is complicated, time consuming with high processing cost, the proposed method has lower complexity and higher simulate speed. In our method, a RBF neural network is used to modify DD parameters. The modified DD model can generate simulate results of accurate HD model. The proposed method is first applied to a silicon n-i-n diode in one dimension, and then to a silicon thin-film MOSFET in two dimensions, both for interpolation and extrapolation. The obtained results for basic variables, i.e., electron and potential distribution for different voltages, confirm the high efficiency of the proposed method.
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