Evidence map›Paper›PMID 41709003›Full record

ArticleNature materials2026

Multiscale-structured miniaturized 3D force sensors.

Guolin Yun, Zesheng Chen, Zhuo Chen, Jinrui Chen, Binghan Zhou, Mingfei Xiao, Michael Stevens, Manish Chhowalla, Tawfique Hasan

Abstract read
In one paragraph

Article in Nature materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

9 authors.

Guolin YunCambridge Graphene Centre, University of Cambridge, Cambridge, UK. ygl@ustc.edu.cn.ORCID http://orcid.org/0000-0001-5457-3777
Zesheng ChenCambridge Graphene Centre, University of Cambridge, Cambridge, UK.
Zhuo ChenCambridge Graphene Centre, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-4199-725X
Jinrui ChenCambridge Graphene Centre, University of Cambridge, Cambridge, UK.
Binghan ZhouCambridge Graphene Centre, University of Cambridge, Cambridge, UK.
Mingfei XiaoCambridge Graphene Centre, University of Cambridge, Cambridge, UK.
Michael StevensCambridge Graphene Centre, University of Cambridge, Cambridge, UK.
Manish ChhowallaDepartment of Materials Science and Metallurgy, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-8183-4044
Tawfique HasanCambridge Graphene Centre, University of Cambridge, Cambridge, UK. th270@cam.ac.uk.ORCID http://orcid.org/0000-0002-6250-7582

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/T014601/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/W024284/1Royal Society NIF\R1\211458
6 · The paper itself

Abstract

Flexible tactile sensors are pivotal for advancing neuroprosthetics, human-machine interactions and intelligent robotics. However, achieving highly sensitive tactile sensing to differentiate normal and tangential forces, particularly in mimicking the high-resolution multidimensional haptics of human fingers, remains a challenge. Here we propose a triaxial force microsensor array made from graphene-liquid-metal composites. Using anisotropic particle networks in microporous composites with pyramid geometries, we achieve normal-tangential force decoupling through multiscale structuring. Our approach offers exceptional sensitivity of 110 kPa

Identifiers

PMID41709003
PMCPMC13236590

What OpenQuestion holds

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LicenceCC BY
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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.