Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 194

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

Efficient removal of arsenate by versatile magnetic graphene oxide composites

Sheng, Guodong, Li, Yimin, Yang, Xin, Ren, Xuemei, Yang, Shitong, Hu, Jun, Wang, Xiangke·2012·RSC Advances

Abstract

The magnetic graphene oxide (MGO) composites were prepared by coprecipitation of FeCl3·6H2O and FeCl2·4H2O on graphene oxide (GO) nanosheets and characterized in detail. The Fe3O4 was uniformly deposited on the surface of GO. The synthesized MGO composites were used as a versatile adsorbent for As(V) removal from aqueous solutions. The results showed that the adsorption of As(V) on MGO is an endothermic process and the adsorption kinetic fitted the pseudo-second-order model well. The MGO composites had a good adsorption capability for As(V) removal and the adsorption isotherms were described by the Langmuir model better than by the Freundlich model. The adsorption of As(V) on MGO decreased with ascending pH due to the electrostatic interaction. In addition, the adsorption of As(V) on MGO was greatly affected by the nature and concentration of coexisting cations and anions. The presence of coexisting anions showed an inhibiting effect on As(V) adsorption, which was more efficient at low pH, whereas the presence of coexisting cations showed an enhancing effect on As(V) adsorption, which was more efficient at high pH. The results of this work indicated that the combination of the excellent adsorption capacity of GO and the magnetic properties of Fe3O4 nanoparticles is very important in drinking water treatment due to the easy magnetic separation of MGO from aqueous solutions.

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/c2ra21623j

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 194

Metadata

Authors
Sheng, G., Li, Y., Yang, X., Ren, X., Yang, S., Hu, J., & Wang, X.
Venue
RSC Advances
Published
2012
Volume
2
Issue
32
Pages
12400
ISSN
2046-2069 (ISSN-L)
OpenAlex
W2036973967
Cited by
194
References
3
FWCI
9.66
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 removal of arsenate by versatile magnetic graphene oxide composites. https://app.cochat.ai/papers/10.1039/c2ra21623j
The paper
Sheng, G., Li, Y., Yang, X., Ren, X., Yang, S., Hu, J., & Wang, X. (2012). Efficient removal of arsenate by versatile magnetic graphene oxide composites. RSC Advances. https://doi.org/10.1039/c2ra21623j

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.