What are the Key Techniques in Data Driven Catalysis?
Several techniques are pivotal in data driven catalysis research:
1. Machine Learning: Algorithms such as neural networks, support vector machines, and decision trees are used to predict catalytic performance and optimize reaction conditions. 2. Data Mining: Techniques like clustering and association rule learning help identify patterns and correlations in large datasets. 3. High-Throughput Screening: Automated experimental setups enable the rapid testing of thousands of catalyst candidates under various conditions. 4. Computational Chemistry: Quantum mechanical calculations and molecular simulations provide detailed insights into the electronic and structural properties of catalysts.
