Evidence map›Paper›PMID 40649506›Full record

ArticleMaterials (Basel, Switzerland)2025

Direct Measurement of Transverse Compressive Properties of Polyacrylonitrile-Based Single Carbon Fibers.

Jin Yan, Hongyi Ma, Xueming Wang, Hongyun Li, Biao Li, Qi Wei, Zhenghua Cao

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jin YanComposite Testing Technology Center, AVIC Composite Co., Ltd., Beijing 101300, China.ORCID 0000-0002-6693-3394
Hongyi MaComposite Testing Technology Center, AVIC Composite Co., Ltd., Beijing 101300, China.
Xueming WangComposite Testing Technology Center, AVIC Composite Co., Ltd., Beijing 101300, China.
Hongyun LiComposite Testing Technology Center, AVIC Composite Co., Ltd., Beijing 101300, China.
Biao LiSchool of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China.
Qi WeiAviation Key Laboratory of Science and Technology on Advanced Surface Engineering, AVIC Manufacturing Technology Institute, Beijing 100024, China.ORCID 0000-0002-4711-4668
Zhenghua CaoAVIC Composite Technology Center, AVIC Manufacturing Technology Institute, Beijing 101300, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evaluating the properties of single carbon fibers is crucial, as it provides parameters not only for optimizing carbon fiber production processes but also for enhancing composite material properties. In recent years, significant advancement have been made in the evaluations of the transverse compressive properties of single fibers. However, compressive testing methods for fibers in the fine size range remain limited at the commercial scale. The direct measurement of the transverse compressive properties of three domestic high-strength polyacrylonitrile-based single carbon fibers (T300 grade, T700 grade, and T800 grade) with diameters of ~5.5~6.5 μm was made possible through the use of a micro-compression tester. Transverse compressive moduli of 5.19 GPa (0.050), 5.42 GPa (0.104), and 6.63 GPa (0.120) were obtained for domestic T300-, T700- and T800-grade carbon fibers, respectively. In addition, transverse compressive strengths of 2.35 GPa (0.033), 2.65 GPa (0.041), and 2.82 GPa (0.121) were obtained for domestic T300-, T700- and T800-grade carbon fibers, respectively. It is noted that minor deviations in fiber geometry from an ideal circular cross-section may influence absolute modulus and strength values. These fibers exhibit strong anisotropy in the longitudinal and transverse directions from the fiber axis. A correlation between the transverse compressive modulus and strength was found for these fibers. These results provide critical parameters for the optimization of carbon fiber-reinforced composite designs (e.g., enhancing impact resistance in aerospace structures), offering substantial practical value to the field of materials science.

Indexed as

anisotropycarbon fibermechanical propertiestransverse compression

Identifiers

PMID40649506
PMCPMC12251188

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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.