Identifying the selectivity of carbon dioxide electrochemical reduction over copper-based alloys through ab initio simulations

This thesis addresses the urgent need for sustainable energy solutions by exploring carbon dioxide utilization technologies, particularly the electrochemical reduction of CO₂ to valuable fuels and alcohols. Copper, for its unique ability to reduce CO₂ to various products, emerges as pivotal to this research. Designing effective catalysts for such complex electrochemical reactions requires an accurate knowledge of the interactions between reaction intermediates, electrodes, and the surrounding environment at an atomic level, which can be modelled using first-principle calculations. The study focuses on three bare metal surfaces, Cu(111), Ti(0001), and Sn(111), and two Cu-based single-atom alloys, Ti@Cu and Sn@Cu, analyzed in the computational hydrogen electrode framework. These surfaces were selected for a collaboration with experimental researchers from the Nanomaterials for Renewable Energy Conversion and Storage group at the University of Bologna. The adsorption simulations of key intermediates, as well as thermodynamic analysis of the CO₂ reduction reaction, yield results consistent with existing literature. Our results showed that Cu(111) can catalyze the CO₂ reduction to carbon monoxide, while the bare Ti surface was prone to poisoning. Sn(111) and Ti@Cu(111) showed selectivity towards producing formate ions, while Sn@Cu(111) displayed similar properties to the bare Cu surfaces. The formation of the HCO ion was identified as a critical intermediate step for methane production, and a linear scaling relationship for HCO and COOH binding energies was proposed. This work aims to define a workflow for studying electroreduction mechanisms that could be implemented in high-throughput codes to design efficient catalysts, aiding experimentalists in identifying the most effective catalysts based on activity and selectivity before conducting experiments, potentially replacing the current trial-and-error process.