Machine learning and artificial intelligence are transforming catalysis by enabling the rapid screening of catalyst properties and predicting their performance. These tools can analyze vast datasets to identify patterns and trends, significantly speeding up the discovery of new catalysts. For example, machine learning algorithms can predict the activity and stability of metal-organic frameworks (MOFs) and other complex materials, thereby reducing the time and cost associated with experimental testing.
