Artificial Intelligence Comes to Battery Design

DOE/Argonne National Laboratory researchers have turned to the power of machine learning and artificial intelligence to dramatically accelerate battery discovery. The press release likens designing new batteries with the best molecular building blocks for battery components to trying to create a recipe for a new kind of cake, when you have billions of potential ingredients. The challenge involves determining which ingredients work best together – or, more simply, produce an edible (or, in the case of batteries, a safe) product. But even with state-of-the-art supercomputers, scientists cannot precisely model the chemical characteristics of every molecule that could prove to be the basis of a next-generation battery material. As described in two new papers, the Argonne researchers first created a highly accurate database of roughly 133,000 small organic molecules that could form the basis of battery electrolytes.