Computational design of highlly functionalized CO2 electroreduction catalyst with useful faradic efficiencies towards C3+ products
Project Abstract:
The electrocatalytic CO2 reduction (eCO2R) reaction powered by renewable electricity offers a sustainable route for producing multi-carbon chemicals and fuels. Copper-based metal alloy (Cu-MA) catalysts can efficiently generate C₂ products such as ethylene and ethanol; however, the formation of C3+ products-particularly propylene-remains elusive. This project aims to advance fundamental understanding and rational design of Cu-MA catalysts for selective conversion of CO2 into C3+ products. Using an innovative integration of high-throughput density functional theory (DFT) and machine learning (ML) techniques, a rigorous five-step screening strategy will be applied to identify stable and active Cu-MA catalysts.
The approach, based on the DFT-Computational Hydrogen Electrode (DFT-CHE) framework, explicitly includes *OH reduction-an often-neglected parameter-enhancing predictive accuracy and catalyst discovery. Machine learning models incorporating thermodynamic, electronic, and geometric features will be developed to extract key activity descriptors. Solvent and ion effects will be explored using ab initio molecular dynamics (AIMD) simulation, while the influence of pH and temperature will be assessed via microkinetic modeling. This multiscale methodology enables correlation between energy landscapes and catalytic selectivity, facilitating direct comparison with experimental observations. Using this integrated strategy, the expected outcome is the identification of highly fragmented Cu-MA structures that bring C1 and C2 binding sites together, promoting their coupling into C3+ products with high Faradaic efficiency.
The project will deliver fundamental insights for the rational design of selective pathways toward C3+ products via eCO2R, advance the fundamental understanding of catalytic mechanisms for renewable fuel generation, and contribute to the EU’s strategic goals in sustainable fuel production, CO2 utilization, and green industrial transformation.