Data-driven workflows to guide experiments and understand ligand effects in catalysis
Traditionally, discovery in catalysis is an empirical process that is mostly reliant on human knowledge and intuition and often involves extensive, iterative trial-and-error screening rather than quantitative predictions. This is a consequence of the very large and highly multidimensional search space where even minor changes in the catalyst structures canā¦