In this paper, two methodologies are used to speed up the maximization of the breakdown volt-age (BV) of a vertical GaN diode that has a theoretical maximum BV of ~2100V. 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 (>1400V) 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 1887V (89% of the ideal case) compared to ~1100V designed with human domain expertise.
Cite
@article{arxiv.2208.01142,
title = {Vertical GaN Diode BV Maximization through Rapid TCAD Simulation and ML-enabled Surrogate Model},
author = {Albert Lu and Jordan Marshall and Yifan Wang and Ming Xiao and Yuhao Zhang and Hiu Yung Wong},
journal= {arXiv preprint arXiv:2208.01142},
year = {2022}
}