Quantum mechanical methods, such as Density Functional Theory (DFT), provide detailed insights into the electronic structure of catalysts and reaction intermediates. These methods can predict reaction pathways, activation energies, and other critical properties. When combined with machine learning, quantum mechanics enhances the accuracy and scope of predictive models.