Why is Data Driven Research Important in Catalysis?
Traditional approaches in catalysis research can be time-consuming and costly. Data driven methodologies offer several advantages:
1. Efficiency: By analyzing large datasets, researchers can quickly identify promising catalysts and reaction conditions without extensive trial-and-error experimentation. 2. Predictive Power: Machine learning models can predict catalytic activity and selectivity, guiding experimental efforts towards the most promising candidates. 3. Discovery: Hidden patterns and correlations in data can lead to the discovery of new catalytic materials and mechanisms that might not be apparent through conventional methods.
