journal article·2025-08Open access

* H Species Regulation of Heterostructured Cu 2 O/NiO Nanoflowers Boosting Tandem Nitrite Reduction for High‐Efficiency Ammonia Production

Yi Feng, Xianwei Lv, Haoyu Wang, Hao Wang, Fengxiao Yan, Lei Wang, Huiying Wang, Jin‐Tao Ren, Zhong‐Yong Yuan

Advanced Functional Materials· Volume 35· Issue 34

Abstract

Abstract Ambient electrocatalytic reduction of NO 2 − to NH 3 (NO 2 RR) provides a reliable route for migrating NO 2 − pollutants and simultaneously generating valuable NH 3. However, the NO 2 RR involves multistep electron transfer and complex intermediates, rendering the achievement of high NH 3 selectivity a major challenge. In this contribution, heterostructured Cu 2 O/NiO nanoflowers are explored for incorporating the advantages of dual active sites as a highly active and selective NO 2 RR catalyst. Combined theoretical calculations and in situ FTIR/EPR spectroscopy analysis, it is revealed the synergistic effect of Cu 2 O and NiO to promote the NO 2 RR energetics of Cu 2 O/NiO heterostructure electrocatalyst through a tandem catalysis pathway, where Cu 2 O activates the initial absorption and deoxygenation of NO 2 − for boosting * NO formation, while the generated * NO on Cu 2 O is then transferred on NiO substrate with abundant active hydrogen for NH 3 conversion. Moreover, the heterostructure formation enhances * H retention capacity, promoting * H consumed in NO 2 RR and inhibiting inter‐ * H species binding. As a result, Cu 2 O/NiO equipped in a flow cell displays a superior NH 3 yield rate of 128.2 mg h −1 cm −2 and Faradaic efficiency of 97.1% at a high current density of −1.25 A cm −2 . Further, this designed tandem system is proven to be adaptable for other electrochemical NH 3 production reactions including NO 3 − reduction.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Ammonia Synthesis and Nitrogen Reduction · Advanced Photocatalysis Techniques · Caching and Content Delivery

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Materials Science and Engineering Smart Sensing Interdisciplinary Science Center Nankai University Tianjin 300350 China

School of Material Science and Engineering Tiangong University Tianjin 300387 China

Funding

National Natural Science Foundation of China

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