Harnessing Heterogeneous Interface and Oxygen Vacancy in Cu/Cu 2 O for Efficient Electrocatalytic Nitrate Reduction to Ammonia

Yaxuan Li, Ling Fang () and Yuanjuan Bai ()
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Yaxuan Li: Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, College of Material Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China
Ling Fang: Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
Yuanjuan Bai: Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, College of Material Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China

Energies, 2024, vol. 17, issue 17, 1-11

Abstract: In recent years, the electrocatalytic reduction of nitrate to ammonia (NRA) has garnered significant research attention. However, the complex multi-step proton–electron transfer process often results in various by-products, limiting NH 3 production. Therefore, designing and developing highly active and selective electrocatalysts for efficient NRA is crucial. This study proposes a method to construct Cu/Cu 2 O nanosheet arrays with heterogeneous interfaces and oxygen vacancies on copper foam surfaces through electrochemical reduction. The interface coupling between Cu and Cu 2 O significantly optimizes the catalyst’s surface electronic structure, providing sufficient active sites. In addition, the presence of oxygen vacancies in Cu/Cu 2 O can optimize the adsorption kinetics of intermediates in the NRA process and effectively inhibit the formation of by-products. The results show that Cu/CuO 2 nanosheet arrays are superior NRA catalysts, achieving a Faradaic efficiency of up to 91.1%, a nitrate conversion of 96.25%, and an NH 3 yield rate of 6.11 mg h −1 cm −2 .

Keywords: electrocatalytic reduction of nitrate to ammonia; Cu/Cu 2 O; interfaces; oxygen vacancies (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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