1. Efficiency: AI models can rapidly screen large libraries of catalysts, significantly reducing the time and cost associated with experimental testing. 2. Optimization: They help in optimizing reaction conditions such as temperature, pressure, and reactant concentrations for maximum efficiency. 3. Discovery: AI can identify new [catalytic materials]() with desired properties by predicting their performance before they are synthesized. 4. Data Utilization: These models make effective use of available data, providing insights that might be missed by traditional methods.
