Machine learning (ML) plays a pivotal role in optimizing algorithms for catalysis. ML algorithms can analyze large datasets to identify patterns and relationships that might not be evident through traditional methods. For instance, ML can predict the catalytic activity and selectivity of various materials, guiding researchers towards the most promising candidates. Techniques such as neural networks, support vector machines, and random forests are commonly employed.
