Evidence map›Paper›PMID 41397849›Full record

ArticleACS sensors2026

Accurate Methane Detection in Combustible Gas Mixtures by Using SnO

Mingzhi Jiao, Haojie Dong, Yuting Qiao, Ruqi Guo, Chu Manh Hung, Nguyen Van Duy, Nguyen Duc Hoa, Chenyu Wen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS sensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mingzhi JiaoNational and Local Joint Engineering Laboratory of Internet Application Technology on Mine, China University of Mining and Technology, Xuzhou 221116, China.
Haojie DongNational and Local Joint Engineering Laboratory of Internet Application Technology on Mine, China University of Mining and Technology, Xuzhou 221116, China.
Yuting QiaoNational and Local Joint Engineering Laboratory of Internet Application Technology on Mine, China University of Mining and Technology, Xuzhou 221116, China.
Ruqi GuoNational and Local Joint Engineering Laboratory of Internet Application Technology on Mine, China University of Mining and Technology, Xuzhou 221116, China.
Chu Manh HungInternational Training Institute of Materials Science, Hanoi University of Science and Technology, Hanoi 100000, Vietnam.
Nguyen Van DuyInternational Training Institute of Materials Science, Hanoi University of Science and Technology, Hanoi 100000, Vietnam.
Nguyen Duc HoaInternational Training Institute of Materials Science, Hanoi University of Science and Technology, Hanoi 100000, Vietnam.
Chenyu WenDivision of Solid-State Electronics, Department of Electrical Engineering, Ångströmlaboratoriet, Uppsala University, Lägerhyddsvägen 1, Uppsala 75237, Sweden.ORCID 0000-0003-4395-7905

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient monitoring of methane is crucial for avoiding gas explosions in industrial processes. Metal oxide methane sensors exhibit promising gas detection performance, which has been well studied recently. However, conventional metal oxide sensors suffer from high operating temperatures, limited selectivity in multigas interference scenarios, and insufficient compatibility between hardware efficiency and algorithmic complexity for real-life applications. Here, we developed methane sensors based on SnO

Indexed as

GasesMethaneSilverTin CompoundsZinc OxideGasesMethaneSilverstannic oxideTin CompoundsZinc Oxidegas classificationheterostructuremethane sensorSnO2 compositeSqueezeNet

Identifiers

PMID41397849
PMCPMC12836351

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.