| 학회 |
한국화학공학회 |
| 학술대회 |
2021년 가을 (10/27 ~ 10/29, 광주 김대중컨벤션센터) |
| 권호 |
27권 2호, p.1474 |
| 발표분야 |
공정시스템 |
| 제목 |
OPERANDO SPECTROSCOPY MEASUREMENT ON THE STABILITY OF CATALYSTS FOR ELECTROCHEMICAL REDUCTION OF CO2 TO CO IMPLEMENTING DEEP LEARNING |
| 초록 |
The information on electrochemical methods is still limited to be a conceptual framework for understanding electrochemistry due to its high cost, operating conditions, and lacking long-term running stability. Herein, we have performed 5250 experiments to elucidate the mechanism of degradation and stability of different catalysts, namely silver-based and Ni-N/C supporting by anion exchange membrane and filter paper at constant potentials. We can predict dependent parameters such as FE (Faraday efficiency) of CO, H2, and total current using the signal pattern of LSV (Linear sweep voltammetry). Our robust method is applicable to any experimental conditions, despite membrane, catalyst, flow rate, and electrolyte concentrations. Furthermore, explainable artificial intelligence(XAI) has been proposed for the interpretability of inputs relating to output through our model focusing on what parts are most associated with output. Operando spectroscopy measurement is employed to verify the robustness of our model |
| 저자 |
하칸카라수1, Daeun SHIN2, Kyojin JANG3, Il MOON3, Jonggeol NA2, 이웅1
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| 소속 |
1Korea Institute of Science and Technology, 2Ewha Womans Univ., 3Yonsei Univ. |
| 키워드 |
인공지능 기반 공정기술 |
| E-Mail |
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| 원문파일 |
초록 보기 |
