Evidence map›Paper›PMID 40647731›Full record

ArticlePolymers2025

Effects of Void Characteristics on the Mechanical Properties of Carbon Fiber Reinforced Polyetheretherketone Composites: Micromechanical Modeling and Analysis.

Yong Zhang, Yibo Li, Xi Luan, Bin Meng, Jinsong Liu, Yan Lu

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Yong ZhangCollege of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.
Yibo LiCollege of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.ORCID 0000-0002-2408-9148
Xi LuanJiangsu Automation Research Institute (Shanghai), Shanghai 222006, China.
Bin MengLight Alloy Research Institute, Central South University, Changsha 410083, China.
Jinsong LiuLight Alloy Research Institute, Central South University, Changsha 410083, China.
Yan LuCollege of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.

Funding

the National Natural Science Foundation of China 52475417the National Natural Science Foundation of China U21A20132
6 · The paper itself

Abstract

This study proposes a novel algorithm for generating representative volume elements which mitigate microstructural inhomogeneities in fiber-reinforced composites. The algorithm integrates void characteristics obtained from micro-computed tomography to more accurate microstructure models. Based on these models, the effects of void content, spatial distribution, and void diameter on the mechanical behavior of CF/PEEK composites are systematically evaluated using finite element analysis and experimental validation. The results reveal that void content significantly reduces transverse tensile strength and ductility, while void size further accelerates failure and enhances brittleness. In contrast, void distribution has minimal influence on the transverse mechanical response. These findings not only offer qualitative insights into void-induced damage mechanisms but also provide a theoretical basis for optimizing microstructures to enhance the mechanical performance of CF/PEEK and similar composite systems. Finally, the limitations of this study have been discussed, and directions for future research are proposed.

Indexed as

composite materialsfinite element analysis (FEA)mechanical propertiesrepresentative volume element (RVE)void characteristics

Identifiers

PMID40647731
PMCPMC12252172

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.