FeN-Embedded Graphene as a Highly Sensitive and Selective Single-Atom Sensor for Reaction Intermediates of Electrochemical CO Reduction.

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.