Fritz Haber Institute of the Max Planck Society

报告摘要:

Artificial intelligence (AI) may capture the properties and functions of materials better than previous theoretical/computational methods because it targets correlations and does not assume a specific underlying physical model. Thus, it addresses the full intricacy of the numerous processes that govern the function of materials. However, the statistical analysis and interpretation of AI models require careful attention.
    In this talk I will discuss recently developed, explainable AI methods and applications that combine detailed, consistent experimental data (called “clean data”) with theoretical data for the identification of “rules” that determine the properties and functions of materials. These “rules” depend on descriptive parameters, called “materials genes”. In analogy to genes in biology they are correlated with a certain material property or function. Thus, these materials genes help the identification of materials that are, for example, better electrical conductors or better heat insulators or better catalysts.

报告人简介：

Matthias Scheffler is a theoretical condensed-matter physicist, working at the Fritz Haber Institute (FHI) of the Max Planck Society since 1988 (founding the FHI Theory Department). He is also honorary professor at all three Berlin universities, and distinguished visiting professor at the University of California Santa Barbara and at Hokkaido University in Sapporo. Scheffler has been working on fundamental aspects of the chemical and physical properties of surfaces, interfaces, clusters and nanostructures since the beginning of his career. He is particularly known for his contributions to and developments of electronic-structure theory, thermodynamics, and statistical mechanics for materials science. Current research activities include heterogeneous catalysis, thermal and electrical conductivity, thermoelectric materials, defects in semiconductors, and biophysics. Since 2000 he is also developing artificial intelligence methods and getting more and more active in open science and data science activities. Scheffler has been coordinator of the European Center of Excellence NOMAD (Novel Materials Discovery) since 2015. 

联系人：胡江平 研究员         （8264 9818）

　　　　任新国 特聘研究员（8264 9603）