Evidence map›Paper›PMID 40653890›Full record

ReviewAdvanced materials (Deerfield Beach, Fla.)2025

Mechanism-Guided Thermoelectric Strategies for Smart Fire Prevention.

Boyou Hou, Yong Guo, Qingshan Yang, Long-Cheng Tang, Yongqian Shi, Jiefeng Gao, Ye-Tang Pan, Min Hong, Toan Dinh, Hao Wang and 2 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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

12 authors.

Boyou HouSchool of Agriculture and Environmental Science, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.
Yong GuoSchool of Engineering, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.
Qingshan YangSchool of Engineering, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.
Long-Cheng TangKey Laboratory of Organosilicon Chemistry and Material Technology of MoE, College of Material, Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou, 311121, People's Republic of China.
Yongqian ShiCollege of Environment and Safety Engineering, Fuzhou University, Fuzhou, 350116, People's Republic of China.
Jiefeng GaoSchool of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, 225002, People's Republic of China.
Ye-Tang PanNational Engineering Research Center of Flame Retardant Materials, School of Materials Science & Engineering, Beijing Institute of Technology, Beijing, 100081, P. R. China.
Min HongSchool of Engineering, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.ORCID https://orcid.org/0000-0002-6469-9194
Toan DinhSchool of Engineering, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.
Hao WangSchool of Engineering, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.
Zhi-Gang ChenSchool of Chemistry and Physics, ARC Research Hub in Zero-emission Power Generation for Carbon Neutrality, and Centre for Materials Science, Queensland University of Technology, Brisbane, Queensland, 4000, Australia.ORCID https://orcid.org/0000-0002-9309-7993
Pingan SongSchool of Agriculture and Environmental Science, Centre for Future Materials, University of Southern Queensland, Springfield, Queensland, 4300, Australia.ORCID https://orcid.org/0000-0003-1082-652X

Funding

Australian Research Council DP240102628Australian Research Council DP240102728Australian Research Council FT230100316Australian Research Council IH200100035Australian Research Council LP220100278
6 · The paper itself

Abstract

Fire prevention and early warning systems are essential to minimize fire risks. Thermoelectric (TE) materials that convert temperature gradients into electrical signals offer a promising pathway for designing self-powered fire-warning technologies and devices; however, their practical applications are often impeded by their low output power, inefficient charge transport, and poor interfacial compatibility. Despite several relevant reviews focusing on material types, it has remained underexplored from a mechanism-driven perspective to enhance the fire prevention performance of TE strategies to date. To fill this knowledge gap, this work aims to systematically review TE materials and design strategies, e.g., structural design, energy filtering, ion doping, ionic thermoelectric effects, and interfacial engineering. This work highlights typical applications of TE-driven fire prevention systems, such as wearable sensors, distributed forest fire monitoring networks, and intelligent building safety systems. Finally, future directions are discussed, which include multifunctional integration, durability under harsh conditions, and AI-driven fire prediction, paving the way for developing intelligent, self-powered fire safety technologies. This work underpins how mechanism-oriented material design advances next-generation fire warning systems with enhanced sensitivity, environmental adaptability, and autonomous operation, thereby expediting the creation of next-generation fire-prevention system and platform.

Indexed as

design strategiesenergy filtering effectionic thermoelectric effectsmart fire protectionthermoelectric materials

Identifiers

PMID40653890
PMCPMC12506613

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.