Uncovering the effects of interface-induced ordering of liquid on crystal growth using machine learning

Abstract

Crystallization is a challenging process to model quantitatively. Here the authors use machine learning and atomistic simulations together to uncover the role of the liquid structure on the process of crystallization and derive a predictive kinetic model of crystal growth.