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

08:36 AM

(582c) Electronic Environment-Based Correction Scheme Using DFT and Wft-Level Energies to Accurately Predict Energetics of Catalytic Interfaces

08:54 AM

(582d) Computational Design of Metal Oxide Nanoclusters for Selective Partial Oxidation of Hydrocarbons

09:12 AM

(582e) Predicting Thermochemical Properties of Hydrocarbon Adsorbates on Metal Surfaces Using Machine Learning

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

09:48 AM

(582g) Modeling the Distribution of Supported Sub-Nanometer Cluster Catalysts

10:06 AM

(582h) Site Geometry Driven Selective Hydrogenation on Intermetallic Catalysts