Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 336

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

Enhancing Electrochemical Nitrate Reduction to Ammonia over Cu Nanosheets via Facet Tandem Catalysis

Fu, Yunfan, Wang, Shuo, Wang, Yi, Wei, Pengfei, Shao, Jiaqi, Liu, Tianfu, Wang, Guoxiong, Bao, Xinhe·2023·Angewandte Chemie International Edition

Abstract

Electrochemical conversion of nitrate (NO 3−) into ammonia (NH 3) represents a potential way for achieving carbon‐free NH 3 production while balancing the nitrogen cycle. Herein we report a high‐performance Cu nanosheets catalyst which delivers a NH 3 partial current density of 665 mA cm−2 and NH 3 yield rate of 1.41 mmol h−1 cm−2 in a flow cell at −0.59 V vs. reversible hydrogen electrode. The catalyst showed a high stability for 700 h with NH 3 Faradaic efficiency of ≈88 % at 365 mA cm−2. In situ spectroscopy results verify that Cu nanosheets are in situ derived from the as‐prepared CuO nanosheets under electrochemical NO 3− reduction reaction conditions. Electrochemical measurements and density functional theory calculations indicate that the high performance is attributed to the tandem interaction of Cu(100) and Cu(111) facets. The NO 2− generated on the Cu(100) facets is subsequently hydrogenated on the Cu(111) facets, thus the tandem catalysis promotes the crucial hydrogenation of *NO to *NOH for NH 3 production.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/anie.202303327

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 52 references

Metadata

Authors
Fu, Y., Wang, S., Wang, Y., Wei, P., Shao, J., Liu, T., Wang, G., & Bao, X.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2023-05-15
Volume
62
Issue
26
Pages
e202303327-e202303327
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W4367369483
Cited by
336
References
52
FWCI
15.61
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Enhancing Electrochemical Nitrate Reduction to Ammonia over Cu Nanosheets via Facet Tandem Catalysis. https://app.cochat.ai/papers/10.1002/anie.202303327
The paper
Fu, Y., Wang, S., Wang, Y., Wei, P., Shao, J., Liu, T., Wang, G., & Bao, X. (2023). Enhancing Electrochemical Nitrate Reduction to Ammonia over Cu Nanosheets via Facet Tandem Catalysis. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.202303327

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.