In process optimization, ML algorithms can identify the optimal conditions for catalytic reactions. For example, Bayesian Optimization can be used to find the best combination of parameters like temperature, pressure, and reactant concentrations. This approach not only improves the efficiency of the catalytic process but also reduces operational costs.
