Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 178

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Visible-Light-Induced Photocatalyst Based on Cobalt-Doped Zinc Ferrite Nanocrystals

Fan, Guoli, Tong, Ji, Li, Feng·2012·Industrial & Engineering Chemistry Research

Abstract

The present work reported the synthesis of visible-light-induced cobalt-doped zinc ferrite (Zn 1- x Co x Fe 2 O 4 ) photocatalysts via a facile reduction–oxidation route, which involved rapid reduction of Fe 3+ and Co 2+ cations in colloid mill reactor, followed by oxidation of iron and cobalt nuclei and structural transformation under hydrothermal conditions. The structural and optical properties of materials were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and UV–vis diffuse reflectance spectra. The results indicated that metallic Co and Fe nuclei could be obtained by reduction in the colloid mill, and Zn 1- x Co x Fe 2 O 4 nanocrystals with uniform size were successfully achieved. Furthermore, compared to ZnFe 2 O 4, Zn 1- x Co x Fe 2 O 4 samples ( x = 0.03, 0.1, 0.2) exhibited enhanced photocatalytic activity in the degradation of methylene blue under visible light irradiation. Especially, the Zn 0.8 Co 0.2 Fe 2 O 4 sample had the highest photocatalytic activity, which was mainly attributable to its smaller band edge. Since as-synthesized Zn–Co ferrites nanocrystals have the advantages of intrinsic chemical stability and magnetic property, it can be expected that they may have potential application in the field of industrial photodegradation of organic pollutants.

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 · 10.1021/ie201933g

Cites

1 of 1 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

Cited by

See all 178

Metadata

Authors
Fan, G., Tong, J., & Li, F.
Venue
Industrial & Engineering Chemistry Research
Published
2012-10-11
Volume
51
Issue
42
Pages
13639-13647
ISSN
  • 0888-5885 (ISSN-L)
  • 1520-5045
OpenAlex
W2321664459
Cited by
178
References
1
FWCI
2.19
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

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.