Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 167

The DOI matches its Crossref record.

Efficient anoxic pollutant removal with oxygen functionalized graphitic carbon nitride under visible light

Dong, Guohui, Ai, Zhihui, Zhang, Lizhi·2014·RSC Advances

Abstract

Photocatalytic oxidation of organic pollutants is often carried out oxically because molecular oxygen plays important roles like capturing photogenerated electrons to habilitate electron–hole pair recombination and produce reactive oxygen species during photocatalysis. It would be very attractive to extend the application of photocatalytic oxidation technology to the anoxic removal of organic pollutants existing in some oxygen-free spaces, but still a challenge. In this study, we demonstrate that oxygen functionalization endows g-C3N4 with anoxic photocatalytic organic pollutant oxidation ability. The oxygen functionalization could increase the anoxic photocatalytic pollutant degradation and mineralization constants by about 18 and 7 times under visible light, respectively. After systematically investigating the relationship between oxygen functional groups and anoxic photo-oxidation properties of g-C3N4, we attribute the anoxic photocatalytic oxidation ability of g-C3N4 to the holes that remained after photogenerated electron trapping by oxygen functional groups for hydrogen evolution. The anoxic photo-oxidation activity of oxygen functionalized g-C3N4 did not significantly decrease after four cycles, suggesting its high stability. This study provides some new insight into the correlation between oxygen functionalization and semiconductor photocatalysis as well as the design and fabrication of anoxic photocatalysts.

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 · 10.1039/c3ra46068a

Cites

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

Metadata

Authors
Dong, G., Ai, Z., & Zhang, L.
Venue
RSC Advances
Published
2014
Volume
4
Issue
11
Pages
5553
ISSN
2046-2069 (ISSN-L)
OpenAlex
W2067368805
Cited by
167
References
0
FWCI
3.25
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: Efficient anoxic pollutant removal with oxygen functionalized graphitic carbon nitride under visible light. https://app.cochat.ai/papers/10.1039/c3ra46068a
The paper
Dong, G., Ai, Z., & Zhang, L. (2014). Efficient anoxic pollutant removal with oxygen functionalized graphitic carbon nitride under visible light. RSC Advances. https://doi.org/10.1039/c3ra46068a

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.