What role does machine learning play in catalysis and computational chemistry?
Machine learning is increasingly being integrated with computational chemistry to accelerate catalyst discovery and optimization. Machine learning algorithms can analyze vast amounts of data from simulations and experiments to identify trends and correlations that might not be apparent through traditional methods. This approach can lead to the discovery of new catalysts and the optimization of existing ones more quickly than conventional trial-and-error methods. Furthermore, machine learning models can predict the performance of catalysts under different conditions, aiding in the design of robust catalytic systems.
