Virtual experimentations by deep learning on tangible materials

Abstract

Artificial intelligence may significantly accelerate the discovery of new materials but is not easily applicable to non-periodic structures. Here, a deep learning framework is proposed to predict properties of tangible carbon nanotubes by generating virtual structures at different scales and compositions.