How is Machine Learning Used to Optimize Reaction Conditions?
Optimizing reaction conditions is a critical aspect of catalysis research. ML models can analyze the effects of various factors such as temperature, pressure, and reactant concentrations on catalytic performance. Optimization algorithms such as genetic algorithms and Bayesian optimization can be used to find the optimal set of conditions that maximize catalytic efficiency. This reduces the need for extensive experimental trials and accelerates the development of efficient catalytic processes.