Enhancing Microkinetic Modeling for CO₂Reduction Reaction: Integrating Electrolyte Effects

In the current landscape of escalating global environmental challenges, the development of sustainable energy solutions has become increasingly critical. A pivotal area in this endeavor is the carbon dioxide reduction reaction (CO 2 RR) technology, which holds the promise of converting CO 2 , a major greenhouse gas, into valuable chemicals and fuels. The intricate nature of CO 2 RR, characterized by complex reaction pathways and a plethora of intermediates, presents significant scientific and engineering challenges. Key to surmounting these challenges is the accurate and comprehensive modeling of CO2RR processes. However, traditional computational models often overlook a crucial aspect – the influence of electrolyte interactions with CO 2 RR intermediates. This omission leads to models that inadequately capture the true dynamics of the electrochemical environment, resulting in less accurate predictions. In this work, we introduce CatEnergy, a Python module that enhances our existing microkinetic modeling tool, CatMAP[1], focusing on CO 2 RR. CatEnergy specifically addresses the complexity of CO 2 RR by integrating electrolyte interaction data. This integration enables a more accurate representation of the electrochemical environment, improving the predictive power and efficacy of CO 2 RR models. By generating essential electrolyte interaction data for microkinetic modeling, it facilitates more effective catalyst design and optimization of reaction conditions. This development is key in advancing the accuracy of microkinetic modeling for CO 2 RR and underscores our commitment to sophisticated tool development in sustainable energy research. [1] Medford, A. J. et al. CatMAP: A Software Package for Descriptor-Based Microkinetic Mapping of Catalytic Trends. Catal. Lett. 145 , 794–807 (2015).