Improving the accuracy of computational methods in catalysis involves several strategies. One approach is the development of better exchange-correlation functionals for DFT, tailored specifically for catalytic systems. Another strategy is the use of machine learning techniques to develop more accurate force fields for MD simulations. Additionally, multi-scale modeling approaches that combine different levels of theory can help capture the essential physics of catalytic processes more accurately.
