(514c) Automated Reaction Model Generation for Electrocatalytic Reduction of Carbon Dioxide | AIChE

(514c) Automated Reaction Model Generation for Electrocatalytic Reduction of Carbon Dioxide

Authors 

Sun, S. - Presenter, Texas A&M University
Farina, D. Jr., Northeastern University
Johnson, M. S., Sandia National Laboratories
West, R., Northeastern University
The urgent need for climate change mitigation has spurred intense research into carbon dioxide (CO2) conversion processes. One of the potential pathways is electrocatalytic CO2 reduction, converting renewable electrical energy into chemical energy and producing carbon-neutral chemical feedstocks and fuel sources. However, the design and optimization of catalysts and reactor parameters require comprehensive understanding of reaction mechanisms. Enumerating these mechanisms manually is a laborious process because a comprehensive model could involve hundreds of species and thousands of elementary reactions. This work presents an innovative approach to streamline mechanism development for electrocatalytic CO2 reduction using automated techniques.

The Reaction Mechanism Generator (RMG) is a widely-used open-source software package, utilizing libraries of existing thermodynamic and kinetics data, reaction family templates, parameter estimation methods, and a core-edge model for fully automated model generation. However, currently RMG lacks the necessary components for electrochemical processes. This study aims to bridge this gap with the RMG-Electrocat extension. The first challenge is RMG's inability to incorporate species with net charges; therefore, new atom types and charge transfer actions were implemented to represent proton-electron interactions during the proton-coupled electron transfer (PCET) process while not violating the zero net-charge restriction. Furthermore, new reaction family templates were created to enumerate possible surface PCET reactions. The computational hydrogen electrode model was utilized for estimating reaction free energies and a potential-dependent surface Arrhenius kinetics model was implemented to calculate kinetics parameters. Finally, a new reactor model was developed to simulate the electrode-electrolyte interface, where both liquid- and surface-phase reactions could occur.

By incorporating these developments into RMG, we constructed a reaction mechanism for electrocatalytic CO2 reduction which produces various value-added C1-C3 species. This advancement not only enhances RMG's utility in the field of sustainable energy, but also lays the foundation for its application in broader electrochemical systems such as battery and fuel-cells.