Evidence map›Paper›PMID 36616539›Full record

ArticlePolymers2022

Microstructure and Self-Healing Capability of Artificial Skin Composites Using Biomimetic Fibers Containing a Healing Agent.

Qian Sun, Xu Gao, Sai Wang, Rong-Yue Shao, Xin-Yu Wang, Jun-Feng Su

Abstract read
In one paragraph

Article in Polymers, 2022. 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. Review
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

6 authors.

Qian SunSchool of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China.
Xu GaoSchool of Material Science and Engineering, Tiangong University, Tianjin 300387, China.
Sai WangSchool of Material Science and Engineering, Tiangong University, Tianjin 300387, China.
Rong-Yue ShaoSchool of Material Science and Engineering, Tiangong University, Tianjin 300387, China.
Xin-Yu WangSchool of Mechanical Engineering, Tianjin University of Commerce, Tianjin 300134, China.
Jun-Feng SuSchool of Material Science and Engineering, Tiangong University, Tianjin 300387, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aging and damage of artificial skin materials for artificial intelligence robots are technical problems that need to be solved urgently in their application. In this work, poly (vinylidene fluoride) (PVDF) fibers containing a liquid agent were fabricated directly as biomimetic microvasculars, which were mixed in a glycol-polyvinyl alcohol-gelatin network gel to form biomimetic self-healing artificial skin composites. The self-healing agent was a uniform-viscous buffer solution composed of phosphoric acid, acetic acid, and sodium carboxymethyl cellulose (CMC-Na), which was mixed under 40 °C. Microstructure analysis showed that the fiber surface was smooth and the diameter was uniform. SEM images of the fiber cross-sections showed that there were uniformly distributed voids. With the extension of time, there was no phenomenon of interface separation after the liquid agent diffused into the matrix through the fiber cavity. The entire process of self-healing was observed and determined including fiber breakage and the agent diffusion steps. XRD and FT-IR results indicated that the self-healing agent could enter the matrix material through fiber damage or release and it chemically reacted with the matrix material, thereby changing the chemical structure of the damaged matrix. Self-healing behavior analysis of the artificial skin indicated that its self-healing efficiency increased to an impressive 97.0% with the increase in temperature to 45 °C.

Indexed as

artificial skin compositefiberhealing agentself-healing

Identifiers

PMID36616539
PMCPMC9824380

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.