Navigating the “Kessel Run” of digital materials acceleration

Abstract

Computational methods such as machine learning, artificial intelligence, and big data in physical sciences, particularly materials science, have been exponentially growing in terms of progress, method development, and number of studies and related publications. This aggregate momentum of the community is palpable, and many exciting discoveries are likely on the horizon. But, like all endeavors, some thought should be given to the current trajectory of the field, ensuring the full potential of the new digital space.