2020 Virtual AIChE Annual Meeting

Session: Applications of Data Science in Catalysis and Reaction Engineering I

Chair

Zachary Ulissi, Carnegie Mellon University

Co-Chairs

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