How does Machine Learning assist in Catalyst Design?
Machine learning accelerates the discovery of novel catalysts by predicting the performance of various catalyst candidates. Traditional methods rely heavily on trial and error, which can be time-consuming and costly. By using ML techniques, researchers can train models on existing data to predict the efficiency, stability, and selectivity of potential catalysts. This reduces the number of experiments needed, saving both time and resources.
