How Does Machine Learning Aid in Catalyst Discovery?
In traditional catalyst discovery, researchers rely on trial-and-error methods, which are often time-consuming and resource-intensive. Machine learning platforms can expedite this process by analyzing large datasets to identify patterns and predict the performance of new catalysts. These platforms use algorithms to process experimental data, computational simulations, and even literature information to recommend promising candidates for experimental validation.
