2022 Annual Meeting

Session: New Developments in Computational Catalysis: Efficiency and Automation

Chair

Matthew Montemore, Tulane University

Co-Chair

Presentations

08:00 AM

(684a) Towards Catalysis Informatics: How the Particularities of Catalytic Data Impact Machine Learning
Pedro Mendes, Florence Vermeire, Thibaut Van Haute, Joris Thybaut

08:18 AM

(684b) Predicting the Morphology of Metal Nanoparticles Decorated with p-Block Promoters on-the-Fly
Asmee Prabhu, Tej Choksi

08:36 AM

(684c) Machine Learning Screening of Alloy Surfaces for Catalytic Stability in Reaction Conditions
Gloria Sulley, Matthew Montemore, Jihun Hamm

08:54 AM

(684d) Towards Swift Predictions of Metal Ad-Atom Diffusion Barriers and Surface Energies for Enhanced Understanding of Sintering and Catalysts Durability
Shyam Deo, Joakim Halldin Stenlid, Frank Abild-Pedersen

09:12 AM

(684e) Developing a Theoretical Model to Unravel the Importance of Adsorbate Effects in Chemisorption on Surface Alloys
Shikha Saini, Joakim Halldin Stenlid, Frank Abild-Pedersen

09:30 AM

(684f) Theory-Infused Neural Network for Interpretable Reactivity Prediction
Shih-Han Wang, Hemanth Pillai, Siwen Wang, Luke E. K. Achenie, Hongliang Xin

09:48 AM

(684g) Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery
Adeesh Kolluru, Muhammed Shuaibi, Aini Palizhati, Abhishek Das, Brandon Wood, C. Lawrence Zitnick, John Kitchin, Zachary Ulissi, Nima Shoghi

10:06 AM

(684h) A Computational Workflow for Intermetallic Catalyst Discovery for Selective Hydrogenation Reactions
Michael Janik, Angela Nguyen, Unnatti Sharma, Zachary Ulissi