How Does Machine Learning Enhance Catalysis Research?
Machine learning models can be trained on experimental and simulation data to predict the performance of new catalysts. These models help in identifying structure-property relationships, optimizing reaction conditions, and even suggesting new catalyst designs. For instance, random forest algorithms can be used to classify catalysts based on their activity levels, while regression models can predict reaction outcomes under different conditions.
