Studying the Outcomes and Mechanisms of Carbocationic Rearrangements Using Algorithm‐Augmented Experimentation

Carbocationic rearrangements are fundamental to both biosynthetic and synthetic chemistries, yet their high reactivity and mechanistic complexity often defy intuitive prediction of outcomes. Herein, HopCat, a hybrid algorithmic platform combining rule‐based transformation logic with quantum‐mechanically informed kinetics, is applied to explore the rearrangement networks of acid‐catalyzed terpenoid transformations. Using a series of terpenoid substrates, an array of structurally diverse and unprecedented products is obtained. It is narated how HopCat can work synergistically with a human chemist to guide product assignment, downselect product candidates based on NMR cues, and reconstruct plausible, multistep mechanistic pathways, including those involving unanticipated intermediates.