2020 Virtual AIChE Annual Meeting

Session: Applications of Data Science in Catalysis and Reaction Engineering II

Chair

Zachary Ulissi, Carnegie Mellon University

Co-Chairs

Presentations

08:00 AM

(106a) Molecular Design Blueprints: Catalysts and Principles from New Simulation and Machine Learning Tools
Heather Kulik, Aditya Nandy, Daniel Harper, Michael Taylor, Chenru Duan, Fang Liu, Naveen Arunachalam, Jon Paul Janet

08:15 AM

(106b) Machine Learning Quantum Tunneling in the Kinetics of Chemical Reactions
Stephanie Valleau

08:30 AM

(106c) Improved Catalyst Design and Performance through Application of Machine Learning Algorithms
Foster Agblevor, Luke Achenie

08:45 AM

(106d) Improving the Reusability of Machine Learning Models for Materials
Matthew Montemore, Gbolade Kayode, Chukwudi Nwaokorie

09:00 AM

(106e) The Open Catalyst Project Dataset
Zachary Ulissi, Junwoong Yoon, Kevin Tran, Muhammed Shuaibi, Aini Palizhati, Javier Heras-Domingo, Abhishek Das, Devi Parikh, Lowik Chanussot, Siddharth Goyal, Caleb Ho, Thibaut Lavril, Morgane Riviere, C. Lawrence Zitnick

09:15 AM

(106f) Active-Learning Framework for the Discovery of Novel Materials for Catalysis
Kirsten T. Winther, Raul Flores, Ankit Jain, Michal Bajdich, Thomas Bligaard

09:30 AM

(106g) Identifying Interaction Trends between Single Metal Atoms and Modified MgO(100) Supports with Statistical Learning
Chun-Yen Liu, Shijia Zhang, Daniel Martinez, Meng Li, Thomas Senftle

09:45 AM

(106h) How to Fix Some of Our Errors Via Data Science
Dionisios Vlachos