Catalyst search shows how computing can take the guesswork out of chemistry

A team of researchers at Osaka University utilized machine learning to streamline the discovery of new catalysts. They used a computational library of both synthesized and theoretical molecules to identify the best candidates for catalyzing specific reactions. This approach allowed them to efficiently find a triarylborane-based catalyst that functions effectively, producing only water as waste. Their method promises to improve catalyst selection while minimizing environmental impact. Learn more here: