Evidence map›Paper›PMID 42076363›Full record

ArticlePolymers2026

Optimizing PVA/Chitosan Films with Acid-Functionalized MWCNTs: A Multifaceted Study on Performance Enhancement.

Mukaddes Karataş, Buket Erzen, Şermin Deniz, Ercan Aydoğmuş, Ramazan Orhan

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mukaddes KarataşFaculty of Engineering, Department of Chemical Engineering, Fırat University, 23200 Elazığ, Türkiye.ORCID 0000-0001-5803-6821
Buket ErzenFaculty of Engineering, Department of Chemical Engineering, Fırat University, 23200 Elazığ, Türkiye.
Şermin DenizFaculty of Engineering, Department of Chemical Engineering, Fırat University, 23200 Elazığ, Türkiye.
Ercan AydoğmuşFaculty of Engineering, Department of Chemical Engineering, Fırat University, 23200 Elazığ, Türkiye.ORCID 0000-0002-1643-2487
Ramazan OrhanFaculty of Engineering, Department of Chemical Engineering, Fırat University, 23200 Elazığ, Türkiye.ORCID 0000-0003-2287-4238

Funding

FIRAT UNIVERSITY SCIENTIFIC RESEARCH PROJECTS UNIT MF.25.144
6 · The paper itself

Abstract

Poly(vinyl alcohol)/chitosan (PVA/CS) biodegradable films reinforced with acid-functionalized multi-walled carbon nanotubes (f-MWCNTs) were fabricated via solution casting to investigate the effects of nanotube incorporation on structural, mechanical, thermal, dielectric, and physicochemical properties. Unlike conventional CNT-reinforced systems, this study focuses on the role of acid functionalization in improving nanotube dispersion and interfacial interactions, enabling simultaneous enhancement of multiple performance characteristics. Fourier transform infrared spectroscopy (FTIR) analysis confirmed strong intermolecular interactions between PVA/CS functional groups and carboxyl groups on f-MWCNTs, while scanning electron microscopy (SEM) revealed homogeneous nanotube dispersion at low loadings and partial aggregation at higher contents. X-ray diffraction (XRD) indicated that crystallinity was modified in a non-monotonic manner with increasing nanotube concentration due to competing nucleation and chain-restriction effects, while dielectric measurements showed an increase in dielectric constant from 3.78 to 4.27 as a result of enhanced interfacial polarization. The thermal conductivity improved from 0.195 to 0.247 W·m

Indexed as

acid-functionalized MWCNTmechanical propertiesnanocomposite filmsPVA/chitosan filmsswelling behavior

Identifiers

PMID42076363
PMCPMC13120311

What OpenQuestion holds

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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.