Evidence map›Paper›PMID 38985378›Full record

ArticleNano-micro letters2024

Ultrafast Response and Threshold Adjustable Intelligent Thermoelectric Systems for Next-Generation Self-Powered Remote IoT Fire Warning.

Zhaofu Ding, Gang Li, Yejun Wang, Chunyu Du, Zhenqiang Ye, Lirong Liang, Long-Cheng Tang, Guangming Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nano-micro letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Mechanism-Guided Thermoelectric Strategies for Smart Fire Prevention.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  6. Review
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.

Zhaofu DingCollege of Materials Science and Engineering & College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518055, People's Republic of China.
Gang LiCollege of Materials Science and Engineering & College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518055, People's Republic of China.
Yejun WangCollege of Material, Chemistry and Chemical Engineering, Key Laboratory of Organosilicon Chemistry and Material Technology of MoE, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.
Chunyu DuCollege of Materials Science and Engineering & College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518055, People's Republic of China.
Zhenqiang YeCollege of Materials Science and Engineering & College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518055, People's Republic of China.
Lirong LiangCollege of Materials Science and Engineering & College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518055, People's Republic of China. lianglirong@szu.edu.cn.
Long-Cheng TangCollege of Material, Chemistry and Chemical Engineering, Key Laboratory of Organosilicon Chemistry and Material Technology of MoE, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China. lctang@hznu.edu.cn.
Guangming ChenCollege of Materials Science and Engineering & College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518055, People's Republic of China. chengm@szu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fire warning is vital to human life, economy and ecology. However, the development of effective warning systems faces great challenges of fast response, adjustable threshold and remote detecting. Here, we propose an intelligent self-powered remote IoT fire warning system, by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films. The flexible films, prepared by a convenient solution mixing, display p-type characteristic with excellent high-temperature stability, flame retardancy and TE (power factor of 239.7 ± 15.8 μW m

Indexed as

IoT fire warningSelf-poweredThermoelectricThreshold adjustableUltrafast response

Identifiers

PMID38985378
PMCPMC11236834

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.