How Does Computational Catalysis Contribute to Catalyst Design?
Computational catalysis has become an indispensable tool in the design and optimization of catalysts. Techniques such as Density Functional Theory (DFT) allow researchers to model the electronic structure of catalysts and predict their reactivity. These computational methods help in identifying active sites and understanding reaction mechanisms at the atomic level. By employing Machine Learning algorithms, large datasets generated from experiments and simulations can be analyzed to discover patterns and correlations, thus accelerating the discovery of new catalysts.
