新闻动态
·科研动态
·综合新闻
·学术活动
·媒体聚焦
·通知公告
您现在的位置:首页 > 新闻动态 > 学术活动
3.29】Speaker:Prof. Hongbin Zhang
Topic:Inverse Design of Functional Materials
 
2024-03-19 | 文章来源:材料设计与计算研究部        【 】【打印】【关闭

题目:Inverse Design of Functional Materials 

报告人:张洪彬 教授

时间:2024年3月29日(周五) 14:30

地点:师昌绪楼408室


报告摘要:Machine learning has been widely applied to obtain statistical understanding and rational design of advanced materials by mapping out the processing - (micro)structure - property – performance relationships. In this work,I am going to demonstrate the concept of inverse design and to showcase how it can be carried out in three different flavours,i.e.,high-throughput combinatorial computation,Bayesian optimization,and generative deep learning. Taking magnetic materials as an example,I have implemented an automatized high-throughput workflow,which has been applied to screen for promising candidate materials as permanent magnets and magnetocaloric,as well as spintronic materials [1]. After identifying the essential benchmarking properties,our workflow can be straightforwardly generalized to screening for other functional materials,as demonstrated for thermal management [2] and photovoltaic [3] materials. Furthermore,in order to explore the vast chemical space more efficiently,forward modelling of the Curie temperatures for ferromagnetic materials has been carried out [4]. This provides the basis for multi-objective optimization,which will be illustrated by figuring out the two-dimensional Pareto front of magnetization and critical temperature. Interestingly,such a generic approach based on Bayesian statistics can be directly integrated with experiments,leading to adaptive design of high-entropy alloys [5]. Last but not least,I am going to give an overview on how generative deep learning can be applied to predict novel crystal structures and microstructures based on our recent implementation using the generative adversarial network [6].

Refs:

[1] H. Zhang,Electronic structure,3,(2021) 033001

[2] S. Lin,C. Shen,and H. Zhang,Materials Today Physics,32,(2023) 100998

[3] C. Shen,et al.,JACS,145,(2023) 21925 

[4] T. Long,et al.,Mat. Res. Lett.,9,(2021) 169 

[5] Z. Rao,et al.,Science,378,(2022) 78 

[6] T. Long,et al.,Acta Mat.,231,(2022) 117898 

个人简介:Hongbin Zhang has completed his PhD from Technical University of Dresden and Postdoctoral Studies from Jülich Research Center (Germany) and Rutgers University (USA). He is a professor leading the division Theory of Magnetic Materials at Technical University of Darmstadt. He has published more than 100 papers in peer-reviewed journals and has been serving as an editorial board member of repute.

文档附件

相关信息
联系我们 | 友情链接
地址: 沈阳市沈河区文化路72号 邮编: 110016
中国科学院金属研究所 版权所有 辽ICP备05005387号-1

官方微博

官方微信