2022 Annual Meeting

Session: Data Science & Machine Learning Approaches to Catalysis III: Applications of Machine Learning to Heterogeneous Catalysis: From Porous Materials to Cluster Catalysis

Chair

Xin, H., Virginia Tech

Co-Chair

Alexopoulos, K., University of Delaware

Presentations

08:00 AM

(582a) Crystal Engineering of a Zeolite Using Machine Learning
Li, X., Han, H., Evangelou, N., Wichrowski, N. J., Lu, P., Xu, W., Hwang, S. J., Zhao, W., Song, C., Guo, X., Bhan, A., Kevrekidis, I. G., Tsapatsis, M.

08:36 AM

(582c) Electronic Environment-Based Correction Scheme Using DFT and Wft-Level Energies to Accurately Predict Energetics of Catalytic Interfaces
Sahoo, S. J., Lei, X., Medford, A.

08:54 AM

(582d) Computational Design of Metal Oxide Nanoclusters for Selective Partial Oxidation of Hydrocarbons
Wang, X., Snurr, R.

09:12 AM

(582e) Predicting Thermochemical Properties of Hydrocarbon Adsorbates on Metal Surfaces Using Machine Learning
Nam, J., Celik, F., Ramasamy, C., Raser, D., Barbosa Couto, G.

09:30 AM

(582f) A Data-Driven Approach Towards Assessing the Stability and Activity of Nanoparticles Containing on Order of Thousand Atoms: A Case Study Using the Oxygen Reduction Reaction
Yam, K. M., Prabhu, A., Lee, M. L., Chan, W. C., Choksi, T.

09:48 AM

(582g) Modeling the Distribution of Supported Sub-Nanometer Cluster Catalysts
Khan, S. A., Caratzoulas, S., Vlachos, D.

10:06 AM

(582h) Site Geometry Driven Selective Hydrogenation on Intermetallic Catalysts
Ulissi, Z., Nguyen, A., Janik, M., Sharma, U.