How are Computational Methods Aiding Catalyst Discovery?
Computational methods, including density functional theory (DFT) and machine learning, are revolutionizing catalyst discovery by:
- Predicting Properties: Simulations can predict the catalytic activity and stability of novel materials before experimental testing. - High-Throughput Screening: Algorithms can rapidly screen large libraries of materials to identify promising candidates. - Mechanistic Insights: Computational studies can provide detailed insights into reaction mechanisms, guiding the design of more efficient catalysts.
