Data mining in catalysis is the process of extracting useful information and patterns from large datasets related to catalytic processes. This involves the use of advanced computational techniques to analyze data collected from experiments, simulations, and literature. The goal is to uncover hidden relationships, predict outcomes, and optimize catalytic processes.
