Evidence map›Paper›PMID 30970687›Full record

ArticlePolymers2017

Preparation and Characterization of Highly Aligned Carbon Nanotubes/Polyacrylonitrile Composite Nanofibers.

Yanhua Song, Zhaoyang Sun, Lan Xu, Zhongbiao Shao

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
26.7field-weighted citation impact, top 1% of its field
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

16 citing papers in PubMed, 366 citations in OpenAlex.

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  13. Engineering of oriented carbon nanotubes in composite materials.Beilstein journal of nanotechnology · 2018
    Review
  14. Article
  15. Article
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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 at 1 institution in 1 country.

Yanhua SongNational Engineering Laboratory for Modern Silk, College of Textile and Engineering, Soochow University, 199 Ren-ai Road, Suzhou 215123, China. syanhua2015@163.com.
Zhaoyang SunNational Engineering Laboratory for Modern Silk, College of Textile and Engineering, Soochow University, 199 Ren-ai Road, Suzhou 215123, China. zhaoyangsun1991@163.com.
Lan XuNational Engineering Laboratory for Modern Silk, College of Textile and Engineering, Soochow University, 199 Ren-ai Road, Suzhou 215123, China. lanxu@suda.edu.cn.ORCID 0000-0003-2185-4104
Zhongbiao ShaoNational Engineering Laboratory for Modern Silk, College of Textile and Engineering, Soochow University, 199 Ren-ai Road, Suzhou 215123, China. sdszb2015@163.com.
Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the electrospinning process, a modified parallel electrode method (MPEM), conducted by placing a positively charged ring between the needle and the parallel electrode collector, was used to fabricate highly aligned carbon nanotubes/polyacrylonitrile (CNTs/PAN) composite nanofibers. Characterizations of the samples-such as morphology, the degree of alignment, and mechanical and conductive properties-were investigated by a combination of scanning electron microscopy (SEM), transmission electron microscopy (TEM), universal testing machine, high-resistance meter, and other methods. The results showed the MPEM could improve the alignment and uniformity of electrospun CNTs/PAN composite nanofibers, and enhance their mechanical and conductive properties. This meant the successful preparation of highly aligned CNT-reinforced PAN nanofibers with enhanced physical properties, suggesting their potential application in appliances and communication areas.

Indexed as

carbon nanotubescomposite nanofiberselectrospinninghighly aligned

Identifiers

PMID30970687
PMCPMC6432014
OpenAlexW2562168949

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.