Researchers employ a variety of strategies to discover new catalysts. High-throughput screening techniques allow scientists to rapidly test a large number of potential catalysts, identifying promising candidates for further study. Computational modeling and machine learning are increasingly used to predict the properties of new catalysts, guiding experimental efforts. Additionally, insights from nature-inspired design and biomimicry can lead to the development of catalysts that mimic the functionality of enzymes.
