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Optimization and Analysis of Doping Concentration in Insulated-Gate Bipolar Transistor using Machine-Learning Method
- Authors
- Kim, J.
- Issue Date
- 2020
- Publisher
- Korean Institute of Electrical Engineers
- Keywords
- Doping optimization; Insulated gated bipolar transistor; Machine learning. tcad simulation
- Citation
- Transactions of the Korean Institute of Electrical Engineers, v.69, no.11, pp.1703 - 1706
- Indexed
- SCOPUS
KCI
- Volume
- 69
- Number
- 11
- Start Page
- 1703
- End Page
- 1706
- ISSN
- 1975-8359
- 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 TC'AD 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. ? 2020 Korean Institute of Electrical Engineers. All rights reserved.
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