Evidence map›Paper›PMID 35808684›Full record

ArticlePolymers2022

Microstructure Analysis of Drawing Effect and Mechanical Properties of Polyacrylonitrile Precursor Fiber According to Molecular Weight.

Hyunchul Ahn, Hyeon Jung Gwak, Yong Min Kim, Woong-Ryeol Yu, Won Jun Lee, Sang Young Yeo

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Hyunchul AhnAdvanced Textile R&D Department, Korea Institute of Industrial Technology, Ansan-si 15588, Korea.
Hyeon Jung GwakAdvanced Textile R&D Department, Korea Institute of Industrial Technology, Ansan-si 15588, Korea.
Yong Min KimDepartment of Materials Science and Engineering (MSE) and Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul 08826, Korea.
Woong-Ryeol YuDepartment of Materials Science and Engineering (MSE) and Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul 08826, Korea.
Won Jun LeeDepartment of Fiber System Engineering, Dankook University, Yongin 16890, Korea.
Sang Young YeoAdvanced Textile R&D Department, Korea Institute of Industrial Technology, Ansan-si 15588, Korea.ORCID 0000-0002-5907-718X

Funding

Ministry of Trade, Industry and Energy 20010219
6 · The paper itself

Abstract

Polyacrylonitrile (PAN) fiber is the most widely used carbon fiber precursor, and methyl acrylate (MA) copolymer is widely used for research and commercial purposes. The properties of P (AN-MA) fibers improve increasingly as the molecular weight increases, but high-molecular-weight materials have some limitations with respect to the manufacturing process. In this study, P (AN-MA) precursor fibers of different molecular weights were prepared and analyzed to identify an efficient carbon fiber precursor manufacturing process. The effects of the molecular weight of P (AN-MA) on its crystallinity and void structure were examined, and precursor fiber content and process optimizations with respect to molecular weight were conducted. The mechanical properties of high-molecular-weight P (AN-MA) were good, but the internal structure of the high-molecular-weight material was not the best because of differences in molecular entanglement and mobility. The structural advantages of a relatively low molecular weight were confirmed. The findings of this study can help in the manufacturing of precursor fibers and carbon fibers with improved properties.

Indexed as

drawingmicrostructuremolecular weightpolyacrylonitrileprecursor

Identifiers

PMID35808684
PMCPMC9268880

What OpenQuestion holds

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LicenceCC BY
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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.