Active learning enabled reactor characterization for mass transfer in aerobic oxidation reactions

A generalizable active learning framework enables accurate prediction of mass transfer coefficients ( k L a ), and iterative design of experiments to efficiently characterize new reactor configurations with minimal experimental trials.