Google DeepMind AI Breakthrough Could Help Battery and Chip Development

Researchers at Google DeepMind have used artificial intelligence to predict the structures of more than 2 million new materials, in a breakthrough that could have wide-reaching benefits in sectors such as renewable energy and computing. DeepMind published 381,000 of the 2.2 million crystal structures that it predicts to be most stable. The breakthrough increases the number of known stable materials by a factor of ten. Although the materials will still need to be synthesized and tested, steps which can take months or even years, the latest development is expected to accelerate the discovery of new materials, which will be required for applications such as energy storage, solar cells, and superconductor chips. "While materials play a very critical role in almost any technology, we as humanity know only about a few tens of thousands of stable materials," says Ekin Dogus Cubuk, a Staff Research Scientist at Google Brain, who worked on the DeepMind AI tool, known as Graph Networks for Materials Exploration (GNoME).