2024 AIChE Annual Meeting

Session: Data Science and ML Approaches to Catalysis II: Surrogates, Bayesian Optimization, Microkinetics

Chair

Renqin Zhang, Clariant

Co-Chair

Tibor Szilvasi, University of Alabama

Presentations

12:30 PM

(306a) Virtual Pareto-Front Mapping of Transition Metal-Catalyzed Gas-Liquid Reactions
Negin Orouji, Milad Abolhasani

12:48 PM

(306b) Surrogate Optimization of Liquid Organic Hydrogen Carrier Processes
Ethan Sunshine, John Kitchin, Carl Laird, Sneha Akhade

01:06 PM

(306c) Leveraging Small Data for Faster and Better Catalysis
Daniela Blanco, Ethan Tenison

01:24 PM

(306d) Resolving Coverage Dependence By Combining Automated Quantum Chemistry Workflows with Interpretable Machine Learning
Matthew S. Johnson, David Bross, Judit Zádor

01:42 PM

(306e) Microkinetic Modeling and Design of Catalytic Materials with Fine-Tuned Machine-Learning Interatomic Potentials
Raffaele Cheula, Mie Andersen, John Kitchin

02:00 PM

(306f) Machine Learning Enhancements to Transient Kinetic Models
Kenneth Kusima, Lars Grabow

02:18 PM

(306g) Automated Discovery of the Smallest Feasible Reaction Mechanism
Miguel Angel de Carvalho Servia, Klaus Hellgardt, King Kuok (Mimi) Hii, Dongda Zhang, Antonio del Rio Chanona

02:36 PM

(306h) Discovering Equations for Acid/Base Interactions Using Symbolic Regression
Charishma Puli, Fariha Agbere, Samiha Sharlin, Kianoush Ramezani, Tyler R. Josephson