In catalysis, Bayesian inference can be employed to optimize catalyst design, understand reaction mechanisms, and predict the outcomes of catalytic processes. By integrating experimental data with theoretical models, researchers can refine their hypotheses and improve the efficiency and selectivity of catalytic reactions.
