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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
Che, F.
, University of Massachusetts Lowell
Co-Chairs
Xin, H.
, Virginia Tech
Senftle, T.
Presentations
08:00 AM
(661a) Data Science & Machine Learning Approaches to Catalysis
Kitchin, J.
08:36 AM
(661b) Competition between Mononuclear and Binuclear Copper Sites across Different Zeolite Topologies
Wijerathne, A.
,
Daya, R.
,
Sawyer, A.
,
Paolucci, C.
08:54 AM
(661c) Developing Physically Meaningful and Accurate Machine Learning Interatomic Potentials for Catalysis
Szilvasi, T.
,
Maxson, T.
,
Soyemi, A.
09:12 AM
(661d) Using Neural Networks to Interpret Transient Kinetic Data
Medford, A.
,
Gusmão, G.
,
Nai, D.
09:48 AM
(661e) Modeling Supported Sub-Nanometer Cluster Catalysts Via Multiscale Computations and Machine Learning
Khan, S. A.
,
Caratzoulas, S.
,
Vlachos, D.
10:06 AM
(661f) Towards Domain-Informed Machine Learned Models from High Throughput Experimental Data
Takac, M.
,
Rangarajan, S.
,
Ziu, K.