Traditional methods of optimizing catalytic processes often involve trial-and-error experiments, which can be time-consuming and costly. Data driven approaches can significantly reduce the time and resources required by providing precise predictions and insights. This leads to faster development cycles, lower costs, and potentially more innovative solutions in fields such as chemical manufacturing, energy production, and environmental protection.
