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., VTH, I-D-V-G, hysteresis, breakdown characteristics, and timedependent 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 multi-dimensional parameters, further assisting in the optimization for GaN-based devices towards the targeted performance.