(348b) Implications of Surface Reconstructions Impacting Py-Catalyzed CO2 Reduction on Semiconductor Photoelectrodes
AIChE Annual Meeting
2016 AIChE Annual Meeting
Catalysis and Reaction Engineering Division
Electrocatalysis and Photoelectrocatalysis V: Electrolysis and Solar Fuels
Tuesday, November 15, 2016 - 12:50pm to 1:10pm
The (photo)electro-catalytic reduction of CO2 to useful fuels via energy from sunlight has received significant attention as a promising route for generating carbon-neutral fuels and value-added chemicals. Experimental evidence demonstrates that pyridine (Py) is an effective co-catalyst during CO2 reduction over GaP, CdTe, and CuInS2 semiconductor electrodes. Identifying the role of Py during catalytic reduction is essential for optimizing the design of such photocatalytic processes. Recent studies suggest that the semiconductor surfaces themselves can facilitate a heterogeneous reduction mechanism, and for this reason a detailed understanding of the interaction between Py and the various surfaces is required. Surface reconstructions occurring during operation alter the nature of adsorption sites available for interaction with the solution, therefore impacting the performance of the electrode. To address this issue, we employ density functional theory to assess the stability of reconstructed GaP, CdTe, and CuInS2 surfaces, as well as to identify adsorption trends of Py-derived intermediates across sites created by such reconstructions. We also use many-body Greenâ??s function theory combined with calculations of work functions to determine band edge positions of the explicitly solvated, reconstructed surfaces, which we compare to calculated reduction potentials involved in proposed elementary steps in the overall CO2 reduction mechanism. This allows us to determine which reduction steps are thermodynamically feasible based on the energy of a photo-excited electron from the conduction band of the semiconductor. These results identify stable intermediate species along the CO2 reaction path over reconstructed surfaces, thus lending insight into the Py-catalyzed reaction mechanism.