How is Computational Catalysis Transforming the Field?
Computational catalysis utilizes powerful algorithms and computational models to predict the behavior of catalysts, optimizing their performance before experimental validation. This approach reduces the time and cost associated with traditional trial-and-error methods. Techniques such as density functional theory (DFT) and machine learning are pivotal in predicting catalyst activity and stability, allowing for the design of more effective catalytic systems.
