2022 Annual Meeting

Session: New Developments in Computational Catalysis: Efficiency and Automation

Chair

Montemore, M., Tulane University

Co-Chair

Presentations

08:00 AM

(684a) Towards Catalysis Informatics: How the Particularities of Catalytic Data Impact Machine Learning
Mendes, P., Vermeire, F., Van Haute, T., Thybaut, J.

08:18 AM

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

08:36 AM

(684c) Machine Learning Screening of Alloy Surfaces for Catalytic Stability in Reaction Conditions
Sulley, G., Montemore, M., Hamm, J.

08:54 AM

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

09:12 AM

(684e) Developing a Theoretical Model to Unravel the Importance of Adsorbate Effects in Chemisorption on Surface Alloys
Saini, S., Halldin Stenlid, J., Abild-Pedersen, F.

09:30 AM

(684f) Theory-Infused Neural Network for Interpretable Reactivity Prediction
Wang, S. H., Pillai, H., Wang, S., Achenie, L. E. K., Xin, H.

09:48 AM

(684g) Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery
Kolluru, A., Shuaibi, M., Palizhati, A., Das, A., Wood, B., Zitnick, C. L., Kitchin, J., Ulissi, Z., Shoghi, N.

10:06 AM

(684h) A Computational Workflow for Intermetallic Catalyst Discovery for Selective Hydrogenation Reactions
Janik, M., Nguyen, A., Sharma, U., Ulissi, Z.