Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 304

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Electrocatalytic nitrate/nitrite reduction to ammonia synthesis using metal nanocatalysts and bio-inspired metalloenzymes

Open access
Wang, Jing, Feng, Tao, Chen, Jiaxin, Ramalingam, Vinoth, Li, Zhongxiao, Kabtamu, Daniel Manaye, He, Jr-Hau, Fang, Xiaosheng·2021·Nano Energy

Abstract

Abstract Ammonia (NH3) is attracted as a potential carbon free energy carrier and as important feedstock for most of the fertilizers, chemicals, pharmaceutical related products. NH3 is industrially produced by conventional Haber–Bosch process under harsh experimental conditions (high temperature and high pressure), and this process requires high-energy consumption and produces large amount of CO2 emissions into the atmosphere. Therefore, there is an urgent need to develop an alternative and sustainable route for NH3 production under ambient conditions. Recently, electrocatalytic N2 reduction to NH3 production has attracted as a potential approach, but achieving high NH3 yield and Faradaic efficiency, and avoiding competitive hydrogen-evolution reaction (HER) are still challenging. Nitrate/nitrite (NO3−/NO2−) is the widely reported contaminant for eutrophication and carcinogens, which can be utilized as a nitrogen resource for electrocatalytic NO3−/NO2− reduction to NH3 (NRA) via eight/six-electron transfer process. Unfortunately, electrocatalytic NRA using metal nanomaterials are rarely investigated. In this review, we discuss the electrocatalytic NRA performance containing reactivity, selectivity, Faradaic efficiency and cycling stability of metal nanocatalysts, bio-inspired metalloenzymes and bioelectrochemical system. After this overview, we investigate the key factors, rate-determining step and the reaction mechanism that controlling the NRA performance. Finally, we summarize the challenges and future pathways guiding the design of effective nanomaterials and reaction systems to promote the industrial application of electrocatalytic NRA.

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 · 10.1016/j.nanoen.2021.106088

Cites

3 of 3 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 3 references

Cited by

See all 304

Metadata

Authors
Wang, J., Feng, T., Chen, J., Ramalingam, V., Li, Z., Kabtamu, D. M., He, J.-H., & Fang, X.
Venue
Nano Energy
Publisher
Elsevier BV
Published
2021-08
Volume
86
Pages
106088
ISSN
2211-2855 (ISSN-L)
OpenAlex
W3157908711
Cited by
304
References
3
FWCI
8.88
Type
journal article
Language
en
Open access
green

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: Electrocatalytic nitrate/nitrite reduction to ammonia synthesis using metal nanocatalysts and bio-inspired metalloenzymes. https://app.cochat.ai/papers/10.1016/j.nanoen.2021.106088
The paper
Wang, J., Feng, T., Chen, J., Ramalingam, V., Li, Z., Kabtamu, D. M., He, J.-H., & Fang, X. (2021). Electrocatalytic nitrate/nitrite reduction to ammonia synthesis using metal nanocatalysts and bio-inspired metalloenzymes. Nano Energy. https://doi.org/10.1016/j.nanoen.2021.106088

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.