Artificial intelligence for search and discovery of quantum materials

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. Quantum materials host many exotic properties, which might be utilized for new electronic devices. Here, artificial intelligence for the discovery of quantum materials is discussed, covering both materials and property prediction, and high-throughput synthesis.

Automated summary

Artificial intelligence and machine learning are essential tools in various areas of physics, particularly in the research of quantum materials. Through data-driven approaches, artificial intelligence has become a key player in the discovery of quantum materials. Quantum materials possess unique properties that could be utilized for the development of new electronic devices.