Vertical GaN diode BV maximization through rapid TCAD simulation and ML-enabled surrogate model

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.