[SY-I11] Symposium I-11

[SY-I11] A Machine Learning Exploration of Grain Boundary Mobility Mechanisms

Invited

Leila Khalili¹, Eric R Homer², ^○Srikanth Patala¹ (1.North Carolina State University, United States of America, 2.Brigham Young University, United States of America)

The mobility of grain boundaries plays an important role in governing the kinetics of microstructural evolution in every class of polycrystalline materials. Of particular interest is the role of bicrystallography, characterized by the macroscopic crystallographic degrees of freedom, on the underlying atomistic mechanisms governing grain boundary mobility. In this talk, I will present an algorithm to automatically identify such mechanisms that give rise to mobility of an interface. We use machine-learning methods, inspired by recent work in disordered solids, to correlate local structure with the susceptibility for rearrangement of grain boundary atoms. We show that it is possible to automatically identify mobility mechanisms of grain boundaries with a diverse range of crystallographic character.