6-7. ALKEMIE: artificial learning and knowledge enhanced materials informatics engineering

Zhimei Sun^1,2

1. School of Materials Science and Engineering, Beihang University, Beijing, 100191, China

2. Center for Integrated Computational Materials Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing, 100191, China

Abstract: It is nearly mission impossible to develop new materials with target functions through the traditional time-consuming trial-and-error ways, where the relation between chemical compositions and performances of candidate materials is unknown. Nowadays, with the rapid development of high-performance clusters and computing software, it is possible to “synthesize” desired candidate materials from computers by high-throughput calculations and big-data analysis. Supported by the National Key Research and Development Program of China, to accelerate the discovery of new materials, we have independently developed a standardized platform named ALKEMIE that is the initials of Artificial Learning and Knowledge Enhanced Materials Informatics Engineering. ALKEMIE can realize complete automatic and high-throughput processes from model constructions and calculations to data analysis without manual interventions, which hence improves efficiency of theoretical works and prevents personal errors. This talk will present a short introduction to the ALKEMIE platform.