The process typically involves the following steps:
Library Design: A diverse library of potential catalysts is created by systematically varying the components and synthesis conditions. This library can include different metal combinations, supports, and promoters. High-Throughput Screening: Automated systems are used to test the catalyst library under various reaction conditions. This step generates a large amount of data on the performance of each catalyst. Data Analysis: Advanced data analysis techniques, often involving machine learning, are employed to identify trends and correlations in the data, pinpointing the most promising catalysts. Optimization: The identified catalysts are further optimized and validated through additional experiments to ensure their effectiveness and stability.
