Evidence map›Paper›PMID 40625910›Full record

ArticleSmart molecules : open access2024

Highly tough, crack-resistant and self-healable piezo-ionic skin enabled by dynamic hard domains with mechanosensitive ionic channel.

XueBin Wang, Tong Liu, FuYao Sun, Jingyi Zhang, BoWen Yao, JianHua Xu, JiaJun Fu

Abstract read
In one paragraph

Article in Smart molecules : open access, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. An Underwater Self-Healing Polysulfide Elastomer with In-Situ Curing and Adhesion.Polymer science & technology (Washington, D.C.) · 2025
    Article
  7. Article
  8. 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.

XueBin WangSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.
Tong LiuSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.
FuYao SunSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.
Jingyi ZhangSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.
BoWen YaoSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.
JianHua XuSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.ORCID https://orcid.org/0000-0001-8814-6108
JiaJun FuSchool of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing China.ORCID https://orcid.org/0000-0002-8542-9556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robust and reliable piezo-ionic materials that are both crack resistant and self-healable like biological skin hold great promise for applications inflexible electronics and intelligent systems with prolonged service lives. However, such a combination of high toughness, superior crack resistance, autonomous self-healing and effective control of ion dynamics is rarely seen in artificial iontronic skin because these features are seemingly incompatible in materials design. Here, we resolve this perennial mismatch through a molecularly engineered strategy of implanting carboxyl-functionalized groups into the dynamic hard domain structure of synthesized poly(urethane-urea). This design provides an ultra-high fracture energy of 211.27 kJ m

Indexed as

crack resistancepiezo‐ionic dynamicsself‐healing

Identifiers

PMID40625910
PMCPMC12118253

What OpenQuestion holds

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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.