Vertical GaN diode BV maximization through rapid TCAD simulation and ML-enabled surrogate model
Albert Lu, Jordan M. Marshall, Yifan Wang, Ming Xiao, Yuhao Zhang, Hiu Yung Wong
Abstract
In this paper, two methodologies are used to speed up the maximization of the breakdown voltage (BV) of a vertical GaN diode that has a theoretical maximum BV of ∼ 2100 V. Firstly, we demonstrated a 5X faster accurate simulation method in Technology Computer-Aided-Design (TCAD). This allows us to find 50 % more numbers of high BV (>1400 V) designs at a given simulation time. Secondly, a machine learning (ML) model is developed using TCAD-generated data and used as a surrogate model for differential evolution optimization. It can inversely design an out-of-the-training-range structure with BV as high as 1887 V (89 % of the ideal case) compared to ∼ 1100 V designed with human domain expertise.