The Device Compact Model Based on Multi-gradient Neural Network and Its Application on MoS2 Field Effect Transistors
Guodong Qi, Qihang Yang, Xinyu Chen, Zengxing Zhang, Peng Zhou, Wenzhong Bao, Ye Lu · 2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM) · 2022
Transistor compact model (TCM) is the key bridge between process technology and chip design. A TCM based on multi-gradient neural network (MNN) is developed to capture the nonlinear device electronic characteristics and their high order derivatives in high precision. The typical MNN model creation time of a single transistor is95% (error2FET, and the created model is characterized and implemented for the simulations of logic circuits such as ring oscillator (RO) and various standard cells. Simulation results agree well with experimental data.