2020 Virtual AIChE Annual Meeting

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

Chair

Ulissi, Z., 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
Kitchin, J., Ulissi, Z., Millstone, J. E., Bernhard, S.

08:15 AM

(45b) High Throughput Screening of Alloy Structures for Propane Dehydrogenation Reaction
Seemakurthi, R. R., Deshpande, S., Xu, Y., Ribeiro, F. H., Miller, J. T., Greeley, J.

08:30 AM

(45c) Theory-Guided, Interpretable Machine Learning Finds Predictive Geometric Structure-Property Relationships for Chemisorption on Alloys
Esterhuizen, J., Goldsmith, B., Linic, S.

08:45 AM

(45d) Trends in Catalyst Stability and Reactivity: Extracting Physical Insights Using Simple Data-Driven Approaches
Choksi, T., Greeley, J., Majumdar, P., Streibel, V., Abild-Pedersen, F., Rekhi, L.

09:00 AM

(45e) Orienteering in an Uncharted Chemical Space: Searching for an Optimal Bimetallic Nanocatalyst
Dean, J., Mpourmpakis, G.

09:15 AM

(45f) Physics Informed Machine Learning of Chemisorption at Metal Surfaces
Wang, S. H., Xin, H., Wang, S., Omidvar, N., Achenie, L.

09:30 AM

(45g) Improved Catalyst Predictions with Machine Learning Coupled Alchemical Perturbation Density Functional Theory
Saravanan, K., Griego, C., Zhao, L., Keith, J.