What are High-Throughput Screening and Machine Learning?
High-throughput screening involves rapidly testing a large number of materials for catalytic activity. This approach is often combined with machine learning algorithms that can analyze the data to identify patterns and predict the performance of new materials. By learning from existing data, these algorithms can suggest promising candidates for synthesis and testing, thereby accelerating the discovery process.
