Achieving high predictive accuracy involves several strategies:
Computational Modeling: Techniques such as Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations are widely used to predict catalytic behavior at the molecular level. Machine Learning: Data-driven approaches can analyze large datasets to identify patterns and make predictions about catalyst performance. Experimental Validation: Combining computational predictions with experimental data to validate and refine models.
