Evidence map›Paper›PMID 42140922›Full record

ArticleNature communications2026

A self healable dielectric elastomer artificial muscle.

Jie Mao, Jiahao Li, Xiaorong Dou, Huiyao Zhao, Peiyao Zhong, Li-Juan Yin, Yingwu Luo, Qibing Pei, Zhi-Min Dang

Abstract read
In one paragraph

Article in Nature communications, 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

9 authors.

Jie Mao *School of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, China. maojie@nxu.edu.cn.ORCID http://orcid.org/0000-0002-6635-4886
Jiahao Li *School of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, China.ORCID http://orcid.org/0009-0003-2889-0965
Xiaorong DouSchool of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, China.
Huiyao ZhaoSchool of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, China.
Peiyao ZhongSchool of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, China.
Li-Juan YinState Key Laboratory of Power System Operation and Control, Tsinghua University, Beijing, China.
Yingwu LuoState Key Laboratory of Chemical Engineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0000-0003-2487-5226
Qibing PeiDepartment of Materials Science and Engineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, CA, USA. qpei@seas.ucla.edu.ORCID http://orcid.org/0000-0003-1669-1734
Zhi-Min DangState Key Laboratory of Power System Operation and Control, Tsinghua University, Beijing, China. dangzm@tsinghua.edu.cn.ORCID http://orcid.org/0000-0001-5961-9033

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52437002National Natural Science Foundation of China (National Science Foundation of China) 52503005
6 · The paper itself

Abstract

Dielectric elastomers are soft electroactive polymers capable of large-strain actuation with the moniker artificial muscle. However, current dielectric elastomers exhibit limited operational stability when operated at strain and energy density in the neighborhood of natural muscles, due to mechanical fatigue or electrical breakdown. In this work, we design a dielectric elastomer comprising a bimodal network structure and zwitterionic side groups to overcome electro-mechanical instability and enable self-healing. The resulting material demonstrates a stably operable strain of 125% at a field of 25 MV m

Identifiers

PMID42140922
PMCPMC13282402

What OpenQuestion holds

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Registered trials

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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.