2024 AIChE Annual Meeting

Session: Data Science and ML Approaches to Catalysis III: Electrochemical, Plasma-Enhanced, and Other Catalytic Systems

Chair

Co-Chair

Matthew Montemore, Tulane University

Presentations

03:30 PM

(389a) Understanding the Structure of the Electric Double Layer Using Machine-Learning Interatomic Potential Simulations
Ademola Soyemi, Tibor Szilvasi

03:48 PM

(389b) Neural Networks Provide in-Depth Insights into Cation and Coverage Effects at (electro)Catalytic Interfaces
Nitish Govindarajan

04:06 PM

(389c) Extending Wherewulff with Electric Field Effects
Rohan Sanspeur, John Kitchin, Jay Bender, Joaquin Resasco

04:24 PM

(389d) Electrocatalytic Biomass Valorization: Efficient Strategies for Understanding Surface Coverage Effects
Deep M. Patel, Luke T. Roling

04:42 PM

(389e) Machine Learning of NO3- Reduction Reaction Steps Via Neat Surface D-Band Properties
Daniel Rivera, Christopher Muhich

05:00 PM

(389f) Advancing Non-Thermal Plasma Catalytic Material Design through Multiscale Simulation and Interpretable Machine Learning Integration
Saleh Ahmat Ibrahim, Shengyan Meng, Charles Milhans, Magda Barecka, Juan Trelles, Yanhui Yi, Fanglin Che

05:18 PM

(389g) Hierarchical Screening Aided By Machine Learning and Genetic Algorithm to Optimize Catalysts for Plasma-Assisted NH3 Synthesis
Tsung Wei Liu, Diego Gomez Gualdron

05:36 PM

(389h) Data Science Shows That Entropy Accelerates Zeolite Crystallization
Seungbo Hong, Scott M. Auerbach