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Confined interface engineering of self-supported Cu@N-doped graphene for electrocatalytic CO2 reduction with enhanced selectivity towards ethanol

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Abstract

Electroreduction of greenhouse gas CO2 into value-added fuels and chemicals provides a promising pathway to address the issues of energy crisis and environmental change. However, the regulations of the selectivity towards C2 product and the competing hydrogen evolution reaction (HER) are major challenges for CO2 reduction reaction (CO2RR). Here, we develop an interface-enhanced strategy by depositing a thin layer of nitrogen-doped graphene (N-G) on a Cu foam surface (Cu-N-G) to selectively promote the ethanol pathway in CO2RR. Compared to the undetectable ethanol selectivity of pure Cu and Cu@graphene (Cu-G), Cu-N-G has boosted the ethanol selectivity to 33.1% in total Faradic efficiency (FE) at −0.8 V vs. reversible hydrogen electrode (RHE). The experimental and density functional theory (DFT) results verify that the interconnected graphene coating can not only serve as the fast charge transport channel but also provide confined nanospace for mass transfer. The N doping can not only trigger the intrinsic interaction between N in N-G and CO2 molecule for enriching the local concentration of reactants but also promote the average valence state of Cu for C-C coupling pathways. The confinement effect at the interface of Cu-N-G can not only provide high adsorbed hydrogen (Had) coverage but also stabilize the key ⋆HCCHOH intermediate towards ethanol pathway. The provided interface-enhanced strategy herein is expected to inspire the design of Cu-based CO2RR electrocatalysts towards multi-carbon products.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Nos. 21907043 and 21801153) and Shandong Provincial Natural Science Foundation (No. ZR2019BB025).

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Correspondence to Dejin Zang or Haiqing Wang.

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12274_2022_4698_MOESM1_ESM.pdf

Confined interface engineering of self-supported Cu@N-doped graphene for electrocatalytic CO2 reduction with enhanced selectivity towards ethanol

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Zang, D., Gao, X.J., Li, L. et al. Confined interface engineering of self-supported Cu@N-doped graphene for electrocatalytic CO2 reduction with enhanced selectivity towards ethanol. Nano Res. 15, 8872–8879 (2022). https://doi.org/10.1007/s12274-022-4698-3

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