Data is the backbone of AI-driven catalysis. Large datasets containing information about various catalytic reactions, their conditions, and outcomes are essential for training machine learning models. High-quality and diverse data enable AI systems to make accurate predictions and uncover hidden insights, driving the discovery of more efficient and selective catalysts.
