Catalytic CO2 conversion to energy carriers and intermediates is of utmost importance to energy and environmental goals. However, the lack of fundamental understanding of the reaction mechanism renders designing a selective catalyst inefficient. We performed operando FTIR/SSITKA experiments to understand the correlation between the kinetics of product formation and that of surface species conversion during CO2 reduction over Pd/Al2O3 catalysts. We found that the rate-determining step for CO formation is the conversion of adsorbed formate, while that for CH4 formation is the hydrogenation of adsorbed carbonyl. The balance of the hydrogenation kinetics between adsorbed formates and carbonyls governs the selectivities to CH4 and CO. As a result, we demonstrated how this knowledge can be used to design catalysts to achieve high selectivities to desired products.
@article{osti_1406770,
author = {Wang, Xiang and Shi, Hui and Szanyi, Janos},
title = {Controlling selectivities in CO<sub>2</sub> reduction through mechanistic understanding},
annote = {Catalytic CO2 conversion to energy carriers and intermediates is of utmost importance to energy and environmental goals. However, the lack of fundamental understanding of the reaction mechanism renders designing a selective catalyst inefficient. We performed operando FTIR/SSITKA experiments to understand the correlation between the kinetics of product formation and that of surface species conversion during CO2 reduction over Pd/Al2O3 catalysts. We found that the rate-determining step for CO formation is the conversion of adsorbed formate, while that for CH4 formation is the hydrogenation of adsorbed carbonyl. The balance of the hydrogenation kinetics between adsorbed formates and carbonyls governs the selectivities to CH4 and CO. As a result, we demonstrated how this knowledge can be used to design catalysts to achieve high selectivities to desired products.},
doi = {10.1038/s41467-017-00558-9},
url = {https://www.osti.gov/biblio/1406770},
journal = {Nature Communications},
issn = {ISSN 2041-1723},
number = {1},
volume = {8},
place = {United States},
publisher = {Nature Publishing Group},
year = {2017},
month = {09}}