Evidence map›Paper›PMID 41681194›Full record

ArticleMaterials (Basel, Switzerland)2026

Enhancing Plant Fibre-Reinforced Polymer Composites for Biomedical Applications Using Atmospheric Pressure Plasma Treatment.

Cho-Sin Nicole Chan, Wing-Yu Chan, Sun-Pui Ng, Chi-Wai Kan, Wang-Kin Chiu, Cheuk-Him Ng

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Cho-Sin Nicole ChanSchool of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong.
Wing-Yu ChanSchool of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong.
Sun-Pui NgSchool of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong.
Chi-Wai KanSchool of Fashion & Textiles, The Hong Kong Polytechnic University, Hong Kong.ORCID 0000-0002-7668-2410
Wang-Kin ChiuSchool of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong.ORCID 0000-0003-4341-0926
Cheuk-Him NgSchool of Professional Education and Executive Development, The Hong Kong Polytechnic University, Hong Kong.

Funding

Research Grants Council (RGC) of the Hong Kong Special Administrative Region, China Project No.: UGC/FDS24/E07/20
6 · The paper itself

Abstract

This research investigates the effects of corona plasma treatment on the mechanical properties of jute/epoxy-reinforced composites, particularly within biomedical application contexts. Plant Fibre Composites (PFCs) are attractive for medical devices and scaffolds due to their environmental friendliness, renewability, cost-effectiveness, low density, and high specific strength. However, their applications are often constrained by inferior mechanical performance arising from poor bonding between the plant fibre used as the reinforcement and the synthetic resin or polymer serving as the matrix. This study addresses the challenge of improving the weak interfacial bonding between plant fibre and synthetic resin in a 2/2 twill-weave-woven jute/epoxy composite material. The surface of the jute fibre is modified for better adhesion with the epoxy resin through plasma treatment, which exposes the jute fibre to controlled plasma energy and utilises dry air (plasma only), argon (Ar) (argon gas with plasma), and nitrogen (N

Indexed as

biomedical applicationcomposite materialepoxyinterlaminar shear strengthjute fibreplasma treatmentSEMtensile properties

Identifiers

PMID41681194
PMCPMC12898020

What OpenQuestion holds

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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.