Evidence map›Paper›PMID 39459767›Full record

ArticleMaterials (Basel, Switzerland)2024

A Group-Enriched Viscoelastic Model for High-Damping Vitrimers with Many Dangling Chains.

Yan Li, Haibo Feng, Jing Xiong, Li Li

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2024. 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

4 authors.

Yan LiState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Haibo FengState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Jing XiongState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Li LiState Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID 0000-0002-9805-3957

Funding

National Natural Science Foundation of China 52175095
6 · The paper itself

Abstract

Classical viscoelastic models usually only consider the motion of chain segments and the motion of the entire molecular chain; therefore, they will cause inevitable errors when modeling self-healing vitrimer materials with many group movements. In this paper, a group-enriched viscoelastic model is proposed for self-healing vitrimers where the group effect cannot be neglected. We synthesize a specific damping vitrimer with many dangling chains, surpassing the limited loss modulus of conventional engineering materials. Due to the dangling chains, the damping capability can be improved and the group effect cannot be neglected in the synthesized damping vitrimer. The group-enriched viscoelastic model accurately captures the experimental damping behavior of the synthesized damping vitrimer. Our results indicate that the group-enriched viscoelastic model can improve the accuracy of classical viscoelastic models. It is shown that the group effect can be ignored at low frequencies since the chain segments have sufficient time for extensive realignment; however, the group effect can become significant in the case of high frequency or low temperature.

Indexed as

damping materialgroup effectloss modulusviscoelastic modelvitrimer

Identifiers

PMID39459767
PMCPMC11509541

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.