Machine learning algorithms can process vast amounts of experimental and theoretical data to predict the behavior of catalysts under various conditions. These algorithms can identify patterns and correlations that may not be apparent through traditional methods. For instance, machine learning can be used to predict the optimal reaction conditions or to design new catalysts with desired properties.
