Traditional methods of catalyst discovery are often time-consuming and expensive. AI and ML, however, can significantly accelerate this process. By leveraging machine learning algorithms, researchers can predict the properties of new catalysts before they are synthesized. These algorithms can analyze large datasets from previous experiments to identify potential new catalysts with desired properties. This predictive capability reduces the need for trial-and-error approaches, saving both time and resources.
