Issue 1, 2023

Efficient interlayer confined nitrate reduction reaction and oxygen generation enabled by interlayer expansion

Abstract

Electrochemically converting nitrate ions back to ammonia can not only eliminate water pollution but also obtain valuable ammonia without a serious carbon footprint, and is thus deemed as an efficient supplement to the traditional Haber–Bosch process. Currently reported catalysts can achieve a single electrode reaction in the electrochemical nitrate reduction reaction. However, the bifunctionality of a single catalyst for both cathodic and anodic reactions has not yet been reported. Herein, we report Fe-doped layered α-Ni(OH)2 with expanded interlayer spacing as an efficient bifunctional catalyst for the nitrate reduction reaction and oxygen evolution reaction. The expanded interlayer spacing facilitates in situ electrochemical potassium ion intercalation between layers. In situ Raman spectroscopy characterization confirms that both the nitrate reduction reaction and oxygen evolution reaction are confined between layers and are triggered by the accumulation of potassium ions. The obtained α-Ni0.881Fe0.119(OH)2 nanosheets deliver an ammonia yield rate of 8.1 mol gcat.−1 h−1 with a NO3-to-NH3 faradaic efficiency of 97.5% at the cathode. The overpotential of oxygen generation at 10 mA cm−2 is reduced to 254 mV at the anode. As a bifunctional catalyst in overall electrolysis, the current density of α-Ni0.881Fe0.119(OH)2 reaches 24.8 mA cm−2 at a voltage of 2.0 V and performs continuously for 50 h with a current retention of 80.2%.

Graphical abstract: Efficient interlayer confined nitrate reduction reaction and oxygen generation enabled by interlayer expansion

Supplementary files

Article information

Article type
Paper
Submitted
11 Sep 2022
Accepted
24 Nov 2022
First published
25 Nov 2022

Nanoscale, 2023,15, 204-214

Efficient interlayer confined nitrate reduction reaction and oxygen generation enabled by interlayer expansion

Y. Zhang, M. Xu, X. Xu, X. Li, G. Zhu, G. Jia, B. Yang, R. Yin, P. Gao and W. Ye, Nanoscale, 2023, 15, 204 DOI: 10.1039/D2NR05001C

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