반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

인공지능기법을 이용한 초음파분무화학기상증착의 유동해석 결과분석에 관한 연구

A Study on CFD Result Analysis of Mist-CVD using Artificial Intelligence Method

  • 하주환 (서울대학교 차세대융합기술연구원 차세대전자재료연구실) ;
  • 신석윤 (서울대학교 차세대융합기술연구원 차세대전자재료연구실) ;
  • 김준영 (한국폴리텍대학 광주캠퍼스 스마트팩토리과) ;
  • 변창우 (서울대학교 차세대융합기술연구원 차세대전자재료연구실)
  • 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)
  • 투고 : 2023.03.20
  • 심사 : 2023.03.22
  • 발행 : 2023.03.31
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초록

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.

키워드

참고문헌

  1. Seok, Ogyun, "Power semiconductor technology trends for electric vehicles." The Korean Institute of Electrical Engineers 71(12), 9-15, 2022.
  2. Chun H W and Yang I S, "Market and Technology Development Trends of Power IC." Electronics and Telecommunications Trends, pp. 206-216, 2013. https://doi.org/10.22648/ETRI.2013.J.280620
  3. Choe Hyo-Sang and Jeong In-Seong. " Electric vehicle (EV) technology development status and trend." The Korean Institute of Electrical Engineer 66.9, pp. 35-40. 2017.
  4. Hyunwoo Kim and Hyungjun Kim. "Epitaxial Growth of Silicon Carbide (SiC) Using Chemical Vapor Deposition (CVD)." the Korean institute of electrical and electronic material engineers, Vol. 30, No. 6, pp. 29- 39, 2017.
  5. Ey Goo Kang. " Ga2O3 Epi Growth by HVPE for Application of Power Semiconductor." Journal of IKEEE, Vol. 22, No. 2, pp. 427-431, 2018 https://doi.org/10.7471/IKEEE.2018.22.2.427
  6. Minhtan Ha, et al., "Leidenfrost Motion of Water Microdroplets on Surface Substrate: Epitaxy of Gallium Oxide via Mist Chemical Vapor Deposition." Advanced Materials Interfaces, Vol 8, No. 6, pp. 2001895, 2021.
  7. Kyoungho Kim, et al., "Growth of 2-inch α-Ga2O3 epilayers via rear-flow-controlled mist chemical vapor deposition." ECS Journal of Solid State Science and Technology 8.7, pp. Q3165-Q3170, 2019. https://doi.org/10.1149/2.0301907jss
  8. Minhtan Ha, et al., "Understanding Thickness Uniformity of Ga2O3 Thin Films Grown by Mist Chemical Vapor Deposition." ECS Journal of Solid State Science and Technology 8.7, pp. Q3106-Q3212, 2019. https://doi.org/10.1149/2.0381907jss
  9. Giang T. Dang et al. "Electronic devices fabricated on mist-CVD-grown oxide semiconductors and their applications." Japanese Journal of Applied Physics 58, pp. 090606, 2019.
  10. Yuya Matamura, et al. " Mist CVD of vanadium dioxide thin films with excellent thermochromic properties using a water-based precursor solution." Solar Energy Materials and Solar Cells 230, pp. 111287, 2021.
  11. Yeon-Ho Jang, Dong Kuk Ko and Ik-Tae Im, "Numerical Study on Flow and Heat Transfer in a CVD Reactor with Multiple Wafers." Journal of the Semiconductor & Display Technology, Vol. 17, No.4, pp. 91-96, 2018.
  12. SunKue Kim, et al. " Analysis of electric property in silicon thin film by using Design of Experiment (DOE)." Korean Society for New and Renewable Energy Spring Conference, pp. 66.2, 2010.
  13. Sang wook Park. "AI technology and market trends." The magazine of KIICE, Vol. 19, No. 2 pp. 11-22, 2018.
  14. Sujeong Yoo, "The 4th Industrial Revolution and Artificial Intelligence", Journal of the Korean Multimedia Society, Vol. 21, No. 4, pp. 1-8, 2017.
  15. Joohwan Ha, et al., "Uniformity Prediction of Mist-CVD Ga2O3 Thin Film using Particle Tracking Methodology." Journal of the Semiconductor & Display Technology, Vol. 21, No. 3, pp. 101-104, 2022.
  16. Joohwan Ha, et al., "Computational Fluid Dynamics for Enhanced Uniformity of Mist-CVD Ga2O3 Thin Film." Journal of the Semiconductor & Display Technology, Vol. 21, No. 4, pp. 81-85, 2022.