Evidence map›Paper›PMID 41517884›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Dual-Responsive Yarn-Based Artificial Muscles for Adaptive Thermal Management.

Mengjiao Pan, Xiaohui Zhang, Jinhao Xu, Ziqi Li, Junjie Wang, Qirui Zhang, Yi Liu, Hongfei Yang, Kinor Jiang, Albert Chan and 2 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mengjiao PanFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Xiaohui ZhangFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Jinhao XuFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Ziqi LiFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Junjie WangFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Qirui ZhangFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Yi LiuFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Hongfei YangFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Kinor JiangResearch Centre of Textiles for Future Fashion, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Albert ChanResearch Centre of Textiles for Future Fashion, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Yucan PengDepartment of Energy and Resources Engineering, College of Engineering, Peking University, Beijing, P. R. China.
Dahua ShouFuture Intelligent Wear Centre, School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0003-3896-7885

Funding

Green Tech Fund GTF202220106Innovation and Technology Fund HKRITAInnovation and Technology Fund ITP/047/25TINational Natural Science Foundation of China 22475007PolyU Awarding Fund Scheme BBFRPolyU Endowed Young Scholars Scheme 84CCResearch Grants Council of the Hong Kong Special Administrative Region, China PolyU152157/24E
6 · The paper itself

Abstract

In the face of global extreme weather and a changing climate, the development of adaptive textiles that provide thermoregulation by altering their structure has become increasingly critical. Such textiles require artificial muscles capable of fast, reliable motion to effectively respond to fluctuating environmental conditions. However, moisture-responsive yarn-based muscles, while promising candidates, are hindered by slow and uncontrollable actuation, limiting their practical application. Inspired by the conscious movement of skeletal muscle, we present a hybrid yarn-based artificial muscle (HYAM) that couples moisture actuation with electrothermal recovery. This design achieves a 128% increase in actuation stroke and a 136% increase in speed compared with pristine yarn-based muscles. Electrothermal recovery controllably shortens recovery and full-cycle times by 91% and 83%, respectively. Inspired by spindle-driven gates, HYAM flips dual-mode radiative curtains to switch between warming and cooling, showing promise for intelligent personalized thermal management.

Indexed as

Artificial OrgansBody Temperature RegulationMuscle, SkeletalTextilesHumansadaptive textileartificial muscledual responsivenessthermal management

Identifiers

PMID41517884
PMCPMC13042714

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.