| 학회 | 한국재료학회 |
| 학술대회 | 2021년 봄 (05/12 ~ 05/14, 광주 김대중컨벤션센터) |
| 권호 | 27권 1호 |
| 발표분야 | 특별심포지엄 1. 에너지용 기능성 재료 특별심포지엄-오거나이저: 신병하(KAIST) |
| 제목 | Reducing Time to Material's Discovery: M3I3 |
| 초록 | Renaissance established the scientific method, a system by which both observation and reason are employed in order to test the proposed mechanisms for planetary motion. Descartes promoted science by first questioning everything and then building up a theory based on sound observational evidence. Materials science is no exception in the sense that visualization of order parameters or materials properties provides the solid ground on which materials theory and design can flourish. Recently, KAIST announced 10 flagship research fields, which include KAIST Materials Revolution: Materials and Molecular Modeling, Imaging, Informatics and Integration (M3I3). M3I3 initiative aims at reducing the time for discovery, design and development of new materials based on multiscale processing-structure-property relationship and materials hierarchy, which will be quantified and understood through combination of machine learning and scientific insight. In this presentation, I will present the role of materials imaging combined with machine learning in realizing our vision of M3I3. |
| 저자 | 홍승범 |
| 소속 | 한국과학기술원 |
| 키워드 | M3I3; Materials Imaging; Machine Learning; Data Mining; Battery Materials |
