Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures
One of the ultimate goals of computational modeling in condensed matter is to be able to
accurately compute materials properties with minimal empirical information. First-principles …
accurately compute materials properties with minimal empirical information. First-principles …
Application of machine learning methods for predicting new superhard materials
Superhard materials are of great interest in various practical applications, and an increasing
number of research efforts are focused on their development. In this article, we demonstrate …
number of research efforts are focused on their development. In this article, we demonstrate …