Bringing Atomistic Deep Learning to Prime Time

TL;DR

This paper discusses the challenges and opportunities in integrating atomistic deep learning with molecular science and high-performance computing to advance material and molecule design.

Contribution

It identifies four key barriers to applying atomistic deep learning in materials science and proposes focused research efforts to overcome them.

Findings

Four barriers to atomistic deep learning integration identified

Opportunities for advancements in materials and molecular design outlined

Research directions proposed to address current challenges

Abstract

Artificial intelligence has not yet revolutionized the design of materials and molecules. In this perspective, we identify four barriers preventing the integration of atomistic deep learning, molecular science, and high-performance computing. We outline focused research efforts to address the opportunities presented by these challenges.