Development of a Heteroleptic Palladium Catalyst for the Fluorination of Arylboronic Acids using Data Science Tools

We report the development of a rare example of metal-catalyzed arylboronic acid fluorination that utilizes heteroleptic palladium complexes─catalysts that utilize two distinct ligands to achieve effective catalysis. Reaction optimization was achieved using high-throughput experimentation (HTE) for data collection, accelerated using multiobjective Bayesian optimization (EDBO+) for selection of experiments. Substrate scope was selected employing data science tools, and evaluation of these substrates revealed excellent functional group tolerance. Extensive mechanistic studies suggest that the two ligand types play unique roles in promoting the reaction wherein the Pd-terpyridine complex promotes facile transmetalation with the aryl boronic acid, while the addition of a second bidentate ligand is required for effective oxidation of this intermediate to form a high-valent Pd-F species that undergoes reductive elimination. This data science-driven workflow presents an illustrative example of exploiting heteroleptic catalysts to advance new fluorination reactions.