How can computational methods aid in optimization?
Computational methods, including density functional theory (DFT) and molecular dynamics (MD), can play a significant role in the optimization of synthesis methods. These methods allow for the prediction of the atomic structure and properties of catalysts, helping to identify optimal synthesis conditions. Additionally, machine learning algorithms can analyze large datasets to uncover patterns and suggest optimal parameters more efficiently than traditional experimental approaches.
