Mint Explainer: The implications of AI creating new materials in seconds

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Materials Project and other groups have helped develop 28,000 new materials till date. But this is an expensive and time-consuming process, and researchers may find it difficult to develop radically different structures since they mostly work with existing materials. Recently, though, Google unit DeepMind Technologies’ AI tool, called Graph Networks for Materials Exploration (GNoME), helped create 2.2 million crystals, of which 380,000 are stable materials.

This is significant progress, as it could help researchers develop greener technologies such as more efficient batteries for electric cars, photovoltaics, superconductors, and more efficient computing. GNoME is a deep-learning tool that predicts the stability of new materials, thus increasing the speed and efficiency of discovery and allowing researchers to create materials faster and at scale. Google says its new discovery is “equivalent to nearly 800 years’ worth of knowledge".

GNoME’s predictions are accessible to scientists around the world. A team of researchers at the Lawrence Berkeley National Laboratory, in partnership with DeepMind, has published a paper revealing how AI predictions can be leveraged for autonomous material synthesis. The lab uses machine-learning and robotic arms to create new materials.

Other researchers have independently created 736 of GNoME’s new materials in their labs, according to Google. The AI tool has identified 52,000 new layered compounds similar to graphene, which can be used instead of silicon to make superconductors. Previously, about 1,000 such materials had been identified.