What is it about?
Machine Learning is a useful tool for chemical reaction optimization and catalyst discovery, however, its prediction can be misleading. In this work, the authors showed how machine learning can be guided by theoretical knowledge so that machine learning prediction strictly follows chemical principles.
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Why is it important?
The authors developed a method to integrate theoretical knowledge into a machine learning model for predicting the performance of catalysts in a chemical reaction.
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This page is a summary of: Theory‐guided machine learning to predict the performance of noble metal catalysts in the water‐gas shift reaction, ChemCatChem, May 2022, Wiley, DOI: 10.1002/cctc.202200355.
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