Exploring effective ways to detect intermediates during the electrochemical CO reduction reaction (CORR) process is pivotal for understanding reaction pathways and underlying mechanisms. Recently, two-dimensional FeN-embedded graphene has received increasing attention as a promising catalyst for CORR. Here, by means of density functional theory computations combined with the non-equilibrium Green's function (NEGF) method, we proposed a detection device to evaluate the performance of FeN-embedded graphene in intermediates detection during the CORR process. Our results reveal that the four key intermediates, including *COOH, *OCHO, *CHO, and *COH, can be chemisorbed on FeN-embedded graphene with high adsorption energies and appropriate charge transfer. The computed current-voltage (-) characteristics and transmission spectra suggest that the adsorption of these intermediates induces significant type-dependent changes in currents and transmission coefficients of FeN-embedded graphene. Remarkably, the FeN-embedded graphene is more sensitive to *COOH and *COH than to *OCHO and *CHO within the entire bias window. Consequently, our theoretical study indicates that the FeN-embedded graphene can effectively detect the key intermediates during the CORR process, providing a practical scheme for identifying catalytic reaction pathways and elucidating underlying reaction mechanisms.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11270574 | PMC |
http://dx.doi.org/10.1021/acsomega.4c04465 | DOI Listing |
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