@article{30576, keywords = {Mechanism, Electrocatalysis, Density functional theory, Transport model, CO2 reduction}, author = {Meenesh R Singh and Jason D Goodpaster and Adam Z Weber and Martin Head-Gordon and Alexis T Bell}, title = {Mechanistic insights into electrochemical reduction of CO2 over Ag using density functional theory and transport models}, abstract = {

Electrochemical reduction of CO2 using renewable sources of electrical energy holds promise for converting CO2 to fuels and chemicals. Since this process is complex and involves a large number of species and physical phenomena, a comprehensive understanding of the factors controlling product distribution is required. While the most plausible reaction pathway is usually identified from quantum-chemical calculation of the lowest free-energy pathway, this approach can be misleading when coverages of adsorbed species determined for alternative mechanism differ significantly, since elementary reaction rates depend on the product of the rate coefficient and the coverage of species involved in the reaction. Moreover, cathode polarization can influence the kinetics of CO2 reduction. Here, we present a multiscale framework for ab initio simulation of the electrochemical reduction of CO2 over an Ag(110) surface. A continuum model for species transport is combined with a microkinetic model for the cathode reaction dynamics. Free energies of activation for all elementary reactions are determined from density functional theory calculations. Using this approach, three alternative mechanisms for CO2 reduction were examined. The rate-limiting step in each mechanism is **COOH formation at higher negative potentials. However, only via the multiscale simulation was it possible to identify the mechanism that leads to a dependence of the rate of CO formation on the partial pressure of CO2 that is consistent with experiments. Simulations based on this mechanism also describe the dependence of the H2 and CO current densities on cathode voltage that are in strikingly good agreement with experimental observation.

}, year = {2017}, journal = {Proceedings of the National Academy of Sciences}, volume = {114}, pages = {E8812 - E8821}, month = {10/2017}, issn = {0027-8424}, doi = {10.1073/pnas.1713164114}, language = {eng}, }