Evidence map›Paper›PMID 41786784›Full record

ArticleNature communications2026

A rubber-based sensor with over 100 million-level ultra-sensitivity (0-10% strain range) via 3D super-interface.

Xinghuo Wang, Yaru Huang, Hui Wang, Shiheng Yin, Chuanhui Xu, Zuankai Wang, Yukun Chen

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Xinghuo WangLab of Advanced Elastomer, South China University of Technology, Tianhe District, Guangzhou, PR China.
Yaru HuangLab of Advanced Elastomer, South China University of Technology, Tianhe District, Guangzhou, PR China.
Hui WangSchool of Materials and Energy, Guangdong University of Technology, Guangzhou, PR China. wanghui@gdut.edu.cn.ORCID http://orcid.org/0009-0007-1530-4700
Shiheng YinLab of Advanced Elastomer, South China University of Technology, Tianhe District, Guangzhou, PR China.
Chuanhui XuSchool of Chemistry and Chemical Engineering, Guangxi University, Nanning, PR China. xuhuiyee@gxu.edu.cn.ORCID http://orcid.org/0000-0002-1212-3636
Zuankai WangDepartment of Mechanical Engineering, Hong Kong Polytechnic University, Hong Kong, PR China. zk.wang@polyu.edu.hk.ORCID http://orcid.org/0000-0002-3510-1122
Yukun ChenLab of Advanced Elastomer, South China University of Technology, Tianhe District, Guangzhou, PR China. cyk@scut.edu.cn.ORCID http://orcid.org/0000-0001-5523-3942

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Constrained by materials, structures, and interface, achieving high sensitivity, wide strain range, and linearity simultaneously remains an impossible triangle for flexible sensors. Herein, we propose 3D super-interface strategy based on patterned rubber substrate-conductive crack layer, successfully developing a microcrack super-interface flexible sensor (MSFS) with ultra-sensitivity (0-10% strain, GF 1.1 × 10⁸ and linearity 0.98). The 3D super-interface relies on the synergistic micro/nano level physical anchoring, and hydrogen bonding interfacial interactions between the rubber matrix and conductive crack layer, achieving strong interlayer bonding. During the sensing process, the crack structure endows the sensor ultra-sensitivity within 0-10% strain range; while the 3D super-interface ensures continuous electrical conductivity under >50% strain conditions. MSFS holds potential application value in monitoring expansion in silicon anode batteries. When the battery expansion reaches 2%, its resistance change can be as high as 22-fold. This approach enables the customized design of flexible sensors for ultra-sensitivity applications.

Identifiers

PMID41786784
PMCPMC13087276

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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.