Traditional methods of studying and optimizing catalytic processes can be time-consuming and costly. Machine learning offers a powerful alternative by enabling the analysis of large datasets to discover patterns and predict outcomes more efficiently. This reduces the need for extensive experimental work and accelerates the development of new catalysts.
