How do computational methods aid in the development of new catalysts?
Computational methods, such as density functional theory (DFT) and machine learning, play a crucial role in the development of new catalysts. These methods allow researchers to model and predict the behavior of catalytic materials at the atomic level, accelerating the discovery and optimization of new catalysts. By understanding the structure-activity relationships, scientists can design catalysts with tailored properties for specific reactions.
