Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 285

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

Nanosheet-Assembled ZnFe2O4 Hollow Microspheres for High-Sensitive Acetone Sensor

Zhou, Xin, Li, Xiaowei, Sun, Hongbin, Sun, Peng, Liang, Xishuang, Liu, Fengmin, Hu, Xiaolong, Lu, Geyu·2015·ACS Applied Materials & Interfaces

Abstract

Semiconductor oxides with hierarchically hollow architecture can provide significant advantages as sensing materials for gas sensors by facilitating the diffusion of target gases. Herein, we develop a facile template-free solvothermal strategy combined with the subsequent thermal treatment process toward the successful synthesis of novel ZnFe2O4 hollow flower-like microspheres. The images of electron microscopy unambiguously indicated that the ZnFe2O4 nanosheets with thickness of around 20 nm assembled hierarchically to form the unique flower-like architecture. As a proof-of-concept demonstration of the function, the as-prepared product was utilized as sensing material for gas sensor. Significantly, in virtue of the porous shell structure, hollow interior, and large surface area, ZnFe2O4 hierarchical microspheres exhibited high response, excellent cyclability, and long-term stability to acetone at the operating temperature of 215 °C.

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/acsami.5b03537

Cites

43 of 43 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 43 references

Cited by

See all 285

Metadata

Authors
Zhou, X., Li, X., Sun, H., Sun, P., Liang, X., Liu, F., Hu, X., & Lu, G.
Venue
ACS Applied Materials & Interfaces
Published
2015-07-07
Volume
7
Issue
28
Pages
15414-15421
ISSN
  • 1944-8244 (ISSN-L)
  • 1944-8252
OpenAlex
W2340381581
Cited by
285
References
43
FWCI
14.92
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: Nanosheet-Assembled ZnFe2O4 Hollow Microspheres for High-Sensitive Acetone Sensor. https://app.cochat.ai/papers/10.1021/acsami.5b03537
The paper
Zhou, X., Li, X., Sun, H., Sun, P., Liang, X., Liu, F., Hu, X., & Lu, G. (2015). Nanosheet-Assembled ZnFe2O4 Hollow Microspheres for High-Sensitive Acetone Sensor. ACS Applied Materials & Interfaces. https://doi.org/10.1021/acsami.5b03537

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.