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Artificial intelligence for search and discovery of quantum materials

Published

Author(s)

A. Gilad Kusne, Ichiro Takeuchi, Valentin Stanev, Johnpierre Paglione

Abstract

Artificial intelligence and machine learning are becoming indispensable tools in many areas of physics, including astrophysics, particle physics, and climate science. In the arena of quantum materials, the rise of new experimental and computational techniques has increased the volume and the speed with which data are collected, and artificial intelligence is poised to impact the exploration of new materials such as superconductors, spin liquids, and topological insulators. This review outlines how the use of data-driven approaches is changing the landscape of quantum materials research. From rapid construction and analysis of computational and experimental databases to implementing physical models as pathfinding guidelines for autonomous experiments, we show that artificial intelligence is already well on its way to becoming the lynchpin in the search and discovery of quantum materials.
Citation
Nature Communications Materials

Keywords

machine learning, quantum materials

Citation

Kusne, A. , Takeuchi, I. , Stanev, V. and Paglione, J. (2021), Artificial intelligence for search and discovery of quantum materials, Nature Communications Materials (Accessed May 27, 2024)

Issues

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Created October 13, 2021, Updated October 26, 2022