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

Hongliang Xin, Virginia Tech

Co-Chair

Konstantinos Alexopoulos, University of Delaware

Presentations

08:00 AM

(582a) Crystal Engineering of a Zeolite Using Machine Learning
Xinyu Li, He Han, Nikolas Evangelou, Noah J. Wichrowski, Peng Lu, Wenqian Xu, Son-Jong Hwang, Wenyang Zhao, Chunshan Song, Xinwen Guo, Aditya Bhan, Ioannis G. Kevrekidis, Michael Tsapatsis

08:36 AM

(582c) Electronic Environment-Based Correction Scheme Using DFT and Wft-Level Energies to Accurately Predict Energetics of Catalytic Interfaces
Sushree Jagriti Sahoo, Xiangyun Lei, Andrew Medford

08:54 AM

(582d) Computational Design of Metal Oxide Nanoclusters for Selective Partial Oxidation of Hydrocarbons
Xijun Wang, Randall Snurr

09:12 AM

(582e) Predicting Thermochemical Properties of Hydrocarbon Adsorbates on Metal Surfaces Using Machine Learning
Jinwoong Nam, Fuat Celik, Charanyadevi Ramasamy, Daniel Raser, Gustavo Barbosa Couto

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
Kah Meng Yam, Asmee Prabhu, Mun Ling Lee, Wern Chin Chan, Tej Choksi

09:48 AM

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

10:06 AM

(582h) Site Geometry Driven Selective Hydrogenation on Intermetallic Catalysts
Zachary Ulissi, Angela Nguyen, Michael Janik, Unnatti Sharma