An improved analog electrical performance of submicron Dual-Material gate (DM) GaAs-MESFETs using multi-objective computation

In this paper, new modeling and optimization approaches are proposed to improve the electrical behavior of the submicron Dual-Material-gate (DM) Gallium Arsenide (GaAs)-MESFETs for analog circuit applications. The electrical properties such as current-voltage characteristics, transconductance, output conductance and drain to source resistance of the device have been ascertained and mathematical models have been developed. The proposed mathematical models are used to formulate the objective functions, which are the pre-requisite of genetic algorithm. The problem is then presented as a multi-objective optimization one, where the electrical parameters are considered simultaneously. Analog electrical parameters are also built for the three points sampled from the different locations of the Pareto front, and a discussion is presented for the Pareto relation between the small signal performances (analog behavior) and the design parameters. Therefore, the proposed technique is used to search for optimal electrical and dimensional parameters to obtain better electrical performance of the device for analog circuit applications. The proposed models have been validated by comparison with 2-D numerical simulations (SILVACO); the observed agreement with numerical simulations is quite good.