Deep learning models, particularly neural networks, are utilized to predict the properties and activities of catalysts. These models can handle high-dimensional data, making it possible to explore a wide range of potential catalytic materials and reaction conditions. Applications include the design of new catalysts, optimization of reaction conditions, and the discovery of unknown catalytic mechanisms.
