Compact Modeling of N- and P-Type GAA NS FETs Using Physical-Based Artificial Neural Networks with Temperature Dependence

We propose a compact model that utilizes physical-based artificial neural networks (ANNs) to model the effect of temperature on n- and p-type gate-all-around nanosheet FETs. Our compact model comprises two independent ANNs, where the first ANN is designed to output parameters related to temperature and the second ANN is utilized for the device physical parameters. All outputs of ANNs are integrated into a physical equation of drain current to form the entire compact model. Compared with the BSIM-CMG model in circuit simulations, our results are highly consistent in transfer characteristics and timing dynamics.