What Are the Challenges of Using Machine Learning in Catalysis?
Despite its potential, there are several challenges in applying ML to catalysis. One major challenge is the need for large, high-quality datasets, which can be difficult to obtain. Additionally, the complex nature of catalytic systems can make it challenging to develop accurate models. Model interpretability is another issue, as it can be difficult to understand how ML models arrive at their predictions. Finally, integrating ML models with experimental workflows requires careful planning and coordination.
