Evidence map›Paper›PMID 37177307›Full record

ReviewPolymers2023

Flame Retardancy of Nylon 6 Fibers: A Review.

Xiaocheng Guo, Linjing Liu, Haisheng Feng, Dinghua Li, Zhonghua Xia, Rongjie Yang

Abstract readReview
In one paragraph

Review in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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.

Xiaocheng GuoNational Engineering Research Center of Flame Retardant Materials, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.
Linjing LiuNational Engineering Research Center of Flame Retardant Materials, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.
Haisheng FengNational Engineering Research Center of Flame Retardant Materials, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.
Dinghua LiNational Engineering Research Center of Flame Retardant Materials, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.
Zhonghua XiaNational Engineering Research Center of Flame Retardant Materials, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.ORCID 0000-0001-5737-831X
Rongjie YangNational Engineering Research Center of Flame Retardant Materials, School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As synthetic fibers with superior performances, nylon 6 fibers are widely used in many fields. Due to the potential fire hazard caused by flammability, the study of the flame retardancy of nylon 6 fibers has been attracting more and more attention. The review has summarized the present research status of flame-retarded nylon 6 fibers from three aspects: intrinsic flame-retarded nylon 6, nylon 6 composites, and surface strategies of nylon 6 fibers/fabrics. The current main focus is still how to balance the application performances, flame retardancy, and production cost. Moreover, melt dripping during combustion remains a key challenge for nylon 6 fibers, and the further developing trend is to study novel flame retardants and new flame-retardancy technologies for nylon 6 fibers.

Indexed as

compositefiberflame retardancynylon 6surface strategy

Identifiers

PMID37177307
PMCPMC10181247

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.