Publication Date
12-1-2022
Document Type
Conference Proceeding
Publication Title
Solid-State Electronics
Volume
198
Issue
SI: LETTERS from the International Conference on Simulation of Semiconductor Processes and Devices 2022
DOI
10.1016/j.sse.2022.108468
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.
Funding Number
ECCS-2134374
Funding Sponsor
National Science Foundation
Keywords
Breakdown voltage, Differential evolution, Diode, Gallium nitride (GaN), Machine learning, Power device, Power electronics, Technology Computer-Aided Design (TCAD), Diode
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Electrical Engineering
Recommended Citation
Albert Lu, Jordan Marshall, Yifan Wang, Ming Xiao, Yuhao Zhang, and Hiu Yung Wong. "Vertical GaN diode BV maximization through rapid TCAD simulation and ML-enabled surrogate model" Solid-State Electronics (2022). https://doi.org/10.1016/j.sse.2022.108468
