In the field of catalysis, scikit-learn can be used to analyze large datasets to identify patterns and predict catalytic activity. This can significantly speed up the process of discovering new catalysts and optimizing existing ones. By using machine learning models, researchers can predict the performance of catalysts under different conditions, thus reducing the need for extensive experimental trials.
