| 학회 | 한국재료학회 |
| 학술대회 | 2018년 봄 (05/16 ~ 05/18, 삼척 쏠비치 호텔&리조트) |
| 권호 | 24권 1호 |
| 발표분야 | C. 에너지 재료 분과 |
| 제목 | Machine Learning Driven Computationa Design of Electrocatalysts for PEM Fuel Cells |
| 초록 | Using first-principles calculations big data is establised for electrocatalysts in PEM fuel cells, which are in turn, analyzed on the basis of materials informatics such as neural network and machine learning. Combined the computations and the analysis enables us to identify new candidates with catalytic activity comparable to conventional Pt catalyst. Furthermore, the approach can propose an innovative design principles for optimizing the properties on the aspect of electrochemical stability in acidic mediaum. We suggest that such a automated artificial intelligence is a promising new research paradigm for over coming challenging issues for developing key energy materials. |
| 저자 | 한병찬 |
| 소속 | 연세대 |
| 키워드 | <P>Machine Learning; Computation; Electrocatalyst; Fuel Cell; </P> |
