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Proceedings
2023 AIChE Annual Meeting
Catalysis and Reaction Engineering Division
Data Science and Machine Learning Approaches to Catalysis I: Data-enhanced Multiscale Simulations
2023 AIChE Annual Meeting
Session: Data Science and Machine Learning Approaches to Catalysis I: Data-enhanced Multiscale Simulations
Chair
Fanglin Che
, University of Massachusetts Lowell
Co-Chairs
Hongliang Xin
, Virginia Tech
Thomas Senftle
Presentations
08:00 AM
(661a) Data Science & Machine Learning Approaches to Catalysis
John Kitchin
08:36 AM
(661b) Competition between Mononuclear and Binuclear Copper Sites across Different Zeolite Topologies
Asanka Wijerathne, Rohil Daya, Allison Sawyer, Christopher Paolucci
08:54 AM
(661c) Developing Physically Meaningful and Accurate Machine Learning Interatomic Potentials for Catalysis
Tibor Szilvasi, Tristan Maxson, Ademola Soyemi
09:12 AM
(661d) Using Neural Networks to Interpret Transient Kinetic Data
Andrew Medford, Gabriel Gusmão, Dingqi Nai
09:48 AM
(661e) Modeling Supported Sub-Nanometer Cluster Catalysts Via Multiscale Computations and Machine Learning
Salman A. Khan, Stavros Caratzoulas, Dionisios Vlachos
10:06 AM
(661f) Towards Domain-Informed Machine Learned Models from High Throughput Experimental Data
Martin Takac, Srinivas Rangarajan, Klea Ziu
