Automatic TCAD Model Parameter Calibration using Autoencoder
Publication Date
1-1-2023
Document Type
Conference Proceeding
Publication Title
International Conference on Simulation of Semiconductor Processes and Devices, SISPAD
DOI
10.23919/SISPAD57422.2023.10319530
First Page
277
Last Page
280
Abstract
Modified autoencoders (AEs) have been used to capture the latent space physics of a given electrical characteristic curve (e.g. IV or CV). Therefore, it is expected that they can also be used to calibrate TCAD model parameters of novel materials such as Ga2O3 which is an emerging ultra-wide-bandgap (UWBG) material. In this paper, we demonstrate the use of an AE to perform automatic TCAD parameter calibration (Philips Unified Mobility model (PhuMob)) in Ga2O3 with 6 parameters. We also discuss a noise technique to improve calibration accuracy and an efficient training data generation method using Latin Hypercube Sampling (LHS). The machine is validated with unseen noisy curves to mimic experimental data. The PhuMob parameters extracted from the unseen curves are used in TCAD simulation and can reproduce the original curves with high accuracy (thus the calibration is successful).
Funding Number
2046220
Funding Sponsor
National Science Foundation
Keywords
Calibration, Machine Learning, Manifold Learning, Technology Computer-Aided Design (TCAD)
Department
Electrical Engineering
Recommended Citation
Matthew Eng and Hiu Yung Wong. "Automatic TCAD Model Parameter Calibration using Autoencoder" International Conference on Simulation of Semiconductor Processes and Devices, SISPAD (2023): 277-280. https://doi.org/10.23919/SISPAD57422.2023.10319530
