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Proceedings
2020 Virtual AIChE Annual Meeting
Topical Conference: Applications of Data Science to Molecules and Materials
Applications of Data Science in Catalysis and Reaction Engineering I
2020 Virtual AIChE Annual Meeting
Session: Applications of Data Science in Catalysis and Reaction Engineering I
Chair
Zachary Ulissi
, Carnegie Mellon University
Co-Chairs
Bryan Goldsmith
Thomas Senftle
Presentations
08:00 AM
(45a) Discovery of Light-Driven Hydrogen Evolution Catalysts Using High Throughput Simulation, Experiments and Machine Learning
John Kitchin, Zachary Ulissi, Jill E. Millstone, Stefan Bernhard
08:15 AM
(45b) High Throughput Screening of Alloy Structures for Propane Dehydrogenation Reaction
Ranga Rohit Seemakurthi, Siddharth Deshpande, Yinan Xu, Fabio H. Ribeiro, Jeffrey T. Miller, Jeffrey Greeley
08:30 AM
(45c) Theory-Guided, Interpretable Machine Learning Finds Predictive Geometric Structure-Property Relationships for Chemisorption on Alloys
Jacques Esterhuizen, Bryan Goldsmith, Suljo Linic
08:45 AM
(45d) Trends in Catalyst Stability and Reactivity: Extracting Physical Insights Using Simple Data-Driven Approaches
Tej Choksi, Jeffrey Greeley, Paulami Majumdar, Verena Streibel, Frank Abild-Pedersen, Lavie Rekhi
09:00 AM
(45e) Orienteering in an Uncharted Chemical Space: Searching for an Optimal Bimetallic Nanocatalyst
James Dean, Giannis Mpourmpakis
09:15 AM
(45f) Physics Informed Machine Learning of Chemisorption at Metal Surfaces
Shih-Han Wang, Hongliang Xin, Siwen Wang, Noushin Omidvar, Luke Achenie
09:30 AM
(45g) Improved Catalyst Predictions with Machine Learning Coupled Alchemical Perturbation Density Functional Theory
Karthikeyan Saravanan, Charles Griego, Lingyan Zhao, John Keith