Data Science & Machine Learning Approaches to Catalysis I: Interpretable and Theory-Guided Machine Learning For Catalysis Design and Understanding

This Session covers all topics related to Data Science & Machine Learning Approaches to Catalysis. Topics can include but are not limited to: 1) ML-aided screening and understanding of active, selective, and stable catalytic materials. 2) Interpretable machine learning for knowledge generation in heterogeneous catalysis. 3) Accelerating structure prediction and characterization of catalysts with DS and ML. 4) New algorithms or methods or featurization schemes. 5) New datasets or databases to aid ML studies in catalysis.