Data fusion is crucial in catalysis for several reasons:
Enhanced Accuracy: Combining data from different sources can reduce uncertainties and improve the reliability of the results. Comprehensive Insights: Data fusion provides a holistic view of catalytic systems, integrating insights from kinetic studies, spectroscopy, microscopy, and computational chemistry. Efficient Resource Use: By combining data, researchers can make better use of available resources, minimizing the need for redundant experiments. Improved Prediction: Integrated data can enhance the predictive power of models, leading to better catalyst design and optimization.
