| 报告题目 | Structure by Design towards Materials Discovery |
| 报告人 | 马琰铭 教授 |
| 报告人单位 | State Key Lab of Superhard Materials, Jilin University |
| 报告时间 | 2015-12-03 |
| 报告地点 | 合肥微尺度物质科学国家实验室一楼科技展厅 |
| 主办单位 | 合肥微尺度物质科学国家实验室、国际功能材料量子设计中心（ICQD） |
| 报告介绍 | Abstract：
Atomistic structures of materials occupy a central position, when establishing a correspondence between materials performance and chemical compositions. Theoretical prediction of atomistic structures becomes the key for the purpose of materials design. We have developed a swarm-intelligence based CALYPSO approach for structure prediction by taking the advantage of structures smart learning (See more information at http://www.calypso.cn). The method is widely used to design multi-dimensional structures ranging from bulk crystals and nanoclusters to layers and surfaces, etc. Functionality-driven design of materials becomes feasible and aids to accelerate materials discovery.
Biosketch:
Dr. Yanming Ma (http://mym.calypso.cn) received his Ph.D degree from Jilin University, China, in 2001. He then spent several years in National research council of Canada, ETH of Zurich, RIKEN of Japan, Hongkong University for long-term postdoctoral or short-term collaboration researches. He is currently a full Professor in Jilin University. His research interests mainly focus on development of simulation methods on structure prediction and exploration of new physics of condensed matters under high pressure. He and his team have developed an efficient CALYPSO method and its same-name code for structure prediction based on swarm intelligence algorithm. More than 1000 users in 40 different countries have conducted their researches using the CALYPSO method and code. The resultant research papers are now beyond 210. |
