Speaker: Fang Ren, SSRL
Program Description
Metallic glasses (MGs) are a class of material that combines properties of metals and amorphous ceramics. While efforts over the last several decades have fabricated some MGs, most of which contain expensive metals and not industrially feasible. The fabrication of MGs in the past has relied mainly on empirical rules. Because of MG’s multi-element nature, it requires extensive experimental efforts to search MGs. In this talk, I will present my research on combining machine learning with high throughput experimentation to discover new MGs faster. The experimental design is aligned with the Materials Genome Initiative’s goal of “integrating experiments, computation, and theory”.