Evidence map›Paper›PMID 38201741›Full record

ArticlePolymers2023

Utilization of Waste Natural Fibers Mixed with Polylactic Acid (PLA) Bicomponent Fiber: Incorporating Kapok and Cattail Fibers for Nonwoven Medical Textile Applications.

Tanyalak Srisuk, Khanittha Charoenlarp, Piyaporn Kampeerapappun

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2023. 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
1.0field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  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

3 authors at 1 institution in 1 country.

Tanyalak SrisukFaculty of Textile Industries, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand.
Khanittha CharoenlarpFaculty of Textile Industries, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand.
Piyaporn KampeerapappunFaculty of Textile Industries, Rajamangala University of Technology Krungthep, Bangkok 10120, Thailand.ORCID 0000-0002-3368-5849
Rajamangala University of Technology Krungthep · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disposable surgical gowns are usually made from petroleum-based synthetic fibers that do not naturally decompose, impacting the environment. A promising approach to diminish the environmental impact of disposable gowns involves utilizing natural fibers and/or bio-based synthetic fibers. In this study, composite webs from polylactic acid (PLA) bicomponent fiber and natural fibers, cattail and kapok fibers, were prepared using the hot press method. Only the sheath region of the PLA bicomponent fiber melted, acting as an adhesive that enhanced the strength and reduced the thickness of the composite web compared with its state before hot pressing. The mechanical and physical properties of these composite webs were evaluated. Composite webs created from kapok fibers displayed a creamy yellowish-white color, while those made from cattail fibers showed a light yellowish-brown color. Additionally, the addition of natural fibers endowed the composite webs with hydrophobic properties. The maximum natural fiber content, at a ratio of 30:70 (natural fiber to PLA fiber), can be incorporated while maintaining proper water vapor permeability and mechanical properties. This nonwoven material presents an alternative with the potential to replace petroleum-based surgical gowns.

Indexed as

bicomponent fiberbiocompositehot pressmedical textilesustainable

Identifiers

PMID38201741
PMCPMC10780681
OpenAlexW4390268289

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.