AI-driven tools improve catalyst design by utilizing machine learning models to predict the performance of potential catalysts. By analyzing historical data and identifying patterns, these models can propose new catalyst structures with optimized properties. Additionally, AI can simulate various reaction conditions, allowing researchers to test numerous hypotheses quickly and cost-effectively.
