Electrochemical C–N coupling represents a potential means to produce value-added nitrogen-containing chemicals with carbon-reduction capability by utilizing carbon-containing (e.g., CO2/CO/HCOOH) and nitrogen-containing reactants (e.g., NO3–/NO2–). Urea is the most reported coupling product from the electrochemical C–N coupling, while the value of urea remains limited. In contrast, other coupling products, such as formamide, usually have low yield rates and selectivities. In this work, we utilized constant potential computations to reveal that the difference in the hydrogenated atom type (e.g., C, N, and O) is critical for tuning the C–N coupling product selectivity of urea versus formaldehyde. In addition, the protonation of *CO to *CHO and the coupling between *CHO and *NH are found to be viable pathways to form formamide, and two descriptors, (ΔEads(*NH) and ΔEads(*CHO) – ΔEads(*CO)/ΔEads(*CO)), are established. Accordingly, we conducted machine-learning methods to screen ∼60 types of different catalysts and selected Cr-doped Cu as the most effective catalyst for the electrochemical C–N coupling to produce formamide, which was confirmed by experiments with a high formamide yield rate of 35.0 mmol h–1 g–1 and inhibition of urea production, suggesting the potential of theoretically guided electrocatalyst designs toward unconventional product selectivity.
Xue et al. (Mon,) studied this question.