1. Data-Driven Catalyst Design: AI can analyze vast amounts of experimental and computational data to suggest novel catalytic materials with desired properties. 2. Reaction Optimization: Machine learning algorithms optimize reaction conditions such as temperature, pressure, and reactant concentrations to maximize yield and efficiency. 3. Mechanistic Understanding: AI helps in elucidating complex reaction mechanisms by analyzing kinetic and spectroscopic data, providing deeper insights into catalytic processes. 4. Predictive Modelling: By predicting the behavior of catalysts under different conditions, AI enables the rapid screening of large chemical spaces.
