Artificial Neural Network-Based (ANN) Approach for Characteristics Modeling and Prediction in GaN-on-Si Power Devices

This paper reports on the demonstration of the characteristics modeling and prediction in GaN-on-Si power devices (MIS-HEMTs and p-GaN HEMTs) using the artificial neural network (ANN)-based approach. A multi-layer ANN is developed to model the electrical characteristics, e.g., V$_{TH}, {I}_{D} V_{G}$, hysteresis, breakdown characteristics, and time-dependent dielectric breakdown (TDDB), etc. Furthermore, an autoencoder with two ANNs is also developed to reconstruct the device designs based on the specific characteristics. We show that the ANN-based approach is promising for modeling and prediction with multidimensional parameters, further assisting in the optimization for GaN-based devices towards the targeted performance.