Chemistry model transfers predictions from simple to more complex molecules

Yokohama National University reports via Phys.org that researchers combined reaction-rate experiments with molecular electronic information to train a machine-learning model on simple ketones. It predicted reaction sites and selectivity in more complex molecules in the study. Broader use in synthesis and drug discovery remains a research goal.