Skip to main content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Materials Science in the AI age: high-throughput library generation, machine learning and a pathway from correlations to the underpinning physics

Published

Author(s)

Kamal Choudhary, Aaron G. Kusne, Francesca M. Tavazza, Jason R. Hattrick-Simpers, Rama K. Vasudevan, Apurva Mehta, Ryan Smith, Lukas Vlcek, Sergei V. Kalinin, Maxim Ziatdinov

Abstract

The use of advanced data analytics, statistical and machine learning approaches (‘AI’) to materials science has experienced a renaissance, driven by advances in computer sciences, availability and access of software and hardware, and a growing realization that data-driven methods can provide a new route to tackling age-old problems. In this prospective, we review some of the recent work on this topic, focusing on generation of libraries from both experiment and theoretical tools, across length scales. In each area, we highlight both the need for these libraries and the key advances facilitated by statistical and/or machine learning algorithms in providing new, previously unobtainable insights, and illustrate areas of improvement. We focus on the importance of community-driven efforts to build these libraries, and illustrate how modeling, macroscopic experiments and atomic-scale imaging can be combined to dramatically accelerate understanding and development of new material systems via a statistical physics framework. These point towards a data driven future wherein knowledge can be aggregated and used collectively, surpassing the capabilities of individual researchers, groups or institutions, and accelerating the advancement of materials science.
Citation
MRS Communications
Created July 22, 2019, Updated January 7, 2020