AI significantly accelerates the traditionally time-consuming and resource-intensive process of catalyst discovery. By leveraging large datasets, AI algorithms can identify patterns and relationships that may not be apparent through conventional methods. For instance, machine learning models can predict the activity, selectivity, and stability of potential catalysts before they are synthesized, thus reducing the number of experimental trials needed.
