| Title |
Optimization and Analysis of Doping Concentration in Insulated-Gate Bipolar Transistor using Machine-Learning Method |
| DOI |
https://doi.org/10.5370/KIEE.2020.69.11.1703 |
| Keywords |
Insulated gated bipolar transistor; doping optimization; machine learning; TCAD simulation |
| Abstract |
In this study, machine-learning and technology computer-aided design (TCAD) simulation are collaborated for optimizing and analyzing the doping concentration in insulated gate bipolar transistor (IGBT). Stochastic current-voltage data is extracted from TCAD simulation. Theses results are trained in XGBoost algorithms of machine-learing method. From the trained results, targeting the performance of IGBT without additional experiment or numerical simulation is being easy and fast. Therefore, the collaboration of TCAD simulation and machine-learning is effective and useful to save time and cost in the development of semiconductor. |