Graphene Field-effect Transistor Modeling Based on Artificial Neural Network

Abstract

Simulations and verifications on graphene electronic devices are foundations for application of graphene in integrated circuits. Modeling on graphene metal-oxide-semiconductor field-effect transistor is implemented with artificial neural network. The proposed model has high accuracy and high efficiency. The computational time for the MOSFET model is decreased significantly. More importantly, the novel model for graphene MOSFET is realized in HSPICE software as a subcircuit, which may obviously increase the efficiency of simulations on graphene large scale integrated circuits. Keywords-graphene; field-effect transistors; modeling; artificial neural network; HSPICE