Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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A Study on CFD Result Analysis of Mist-CVD using Artificial Intelligence Method

인공지능기법을 이용한 초음파분무화학기상증착의 유동해석 결과분석에 관한 연구

  • Joohwan Ha (Advanced Electronic Materials Laboratory, Advanced Institute of Convergence Technology, Seoul National University) ;
  • Seokyoon Shin (Advanced Electronic Materials Laboratory, Advanced Institute of Convergence Technology, Seoul National University) ;
  • Junyoung Kim (Department of Smart Factory, Gwangju Campus, Korea Polytechnics) ;
  • Changwoo Byun (Advanced Electronic Materials Laboratory, Advanced Institute of Convergence Technology, Seoul National University)
  • 하주환 (서울대학교 차세대융합기술연구원 차세대전자재료연구실) ;
  • 신석윤 (서울대학교 차세대융합기술연구원 차세대전자재료연구실) ;
  • 김준영 (한국폴리텍대학 광주캠퍼스 스마트팩토리과) ;
  • 변창우 (서울대학교 차세대융합기술연구원 차세대전자재료연구실)
  • Received : 2023.03.20
  • Accepted : 2023.03.22
  • Published : 2023.03.31
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Abstract

This study focuses on the analysis of the results of computational fluid dynamics simulations of mist-chemical vapor deposition for the growth of an epitaxial wafer in power semiconductor technology using artificial intelligence techniques. The conventional approach of predicting the uniformity of the deposited layer using computational fluid dynamics and design of experimental takes considerable time. To overcome this, artificial intelligence method, which is widely used for optimization, automation, and prediction in various fields, was utilized to analyze the computational fluid dynamics simulation results. The computational fluid dynamics simulation results were analyzed using a supervised deep neural network model for regression analysis. The predicted results were evaluated quantitatively using Euclidean distance calculations. And the Bayesian optimization was used to derive the optimal condition, which results obtained through deep neural network training showed a discrepancy of approximately 4% when compared to the results obtained through computational fluid dynamics analysis. resulted in an increase of 146.2% compared to the previous computational fluid dynamics simulation results. These results are expected to have practical applications in various fields.

Keywords

References

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