Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 993

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Transparent air filter for high-efficiency PM2.5 capture

Open access
Liu, Chong, Hsu, Po-Chun, Lee, Hyun-Wook, Ye, Meng, Zheng, Guangyuan, Liu, Nian, Li, Weiyang, Cui, Yi·2015·Nature Communications

Abstract

Particulate matter (PM) pollution has raised serious concerns for public health. Although outdoor individual protection could be achieved by facial masks, indoor air usually relies on expensive and energy-intensive air-filtering devices. Here, we introduce a transparent air filter for indoor air protection through windows that uses natural passive ventilation to effectively protect the indoor air quality. By controlling the surface chemistry to enable strong PM adhesion and also the microstructure of the air filters to increase the capture possibilities, we achieve transparent, high air flow and highly effective air filters of ~90% transparency with >95.00% removal of PM2.5 under extreme hazardous air-quality conditions (PM2.5 mass concentration >250 μg m−3). A field test in Beijing shows that the polyacrylonitrile transparent air filter has the best PM2.5 removal efficiency of 98.69% at high transmittance of ~77% during haze occurrence. Particulate matter pollution is a public health concern in industrialized and urban areas. Here, the authors control the surface chemistry and microstructure of filtration materials to fabricate effective and transparent air filters for the capture of PM2.5pollutants.

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 · 10.1038/ncomms7205

Cites

2 of 2 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 2 references

Cited by

See all 993

Metadata

Authors
Liu, C., Hsu, P.-C., Lee, H.-W., Ye, M., Zheng, G., Liu, N., Li, W., & Cui, Y.
Venue
Nature Communications
Published
2015-02-16
Volume
6
Issue
1
Pages
6205-6205
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2049661780
Cited by
993
References
2
FWCI
32.56
Type
journal article
Language
en
Open access
gold

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: Transparent air filter for high-efficiency PM2.5 capture. https://app.cochat.ai/papers/10.1038/ncomms7205
The paper
Liu, C., Hsu, P.-C., Lee, H.-W., Ye, M., Zheng, G., Liu, N., Li, W., & Cui, Y. (2015). Transparent air filter for high-efficiency PM2.5 capture. Nature Communications. https://doi.org/10.1038/ncomms7205

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.