Evidence map›Paper›PMID 36146059›Full record

ArticlePolymers2022

Alkaline Treatment Variables to Characterize Poly(Vinyl Alcohol)/Poly(Vinyl Butyral/Vinyl Alcohol) Blend Films.

Seong Baek Yang, Mohammad Rezaul Karim, Jungeon Lee, Jeong Hyun Yeum, Sabina Yeasmin

Abstract read
In one paragraph

Article in Polymers, 2022. 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
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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

5 authors.

Seong Baek YangDepartment of Biofibers and Biomaterials Science, Kyungpook National University, Daegu 41566, Korea.ORCID 0000-0003-3806-4539
Mohammad Rezaul KarimCenter of Excellence for Research in Engineering Materials, Deanship of Scientific Research, King Saud University, Riyadh 11421, Saudi Arabia.ORCID 0000-0002-4567-6069
Jungeon LeeDepartment of Biofibers and Biomaterials Science, Kyungpook National University, Daegu 41566, Korea.
Jeong Hyun YeumDepartment of Biofibers and Biomaterials Science, Kyungpook National University, Daegu 41566, Korea.
Sabina YeasminDepartment of Biofibers and Biomaterials Science, Kyungpook National University, Daegu 41566, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel poly(vinyl alcohol) (PVA)/poly(vinyl butyral-vinyl alcohol) (P(VB-VA)) films with improved hydrophobicity were prepared from poly(vinyl acetate) (PVAc)/poly(vinyl butyral) (PVB) blend films with various mass ratios by saponification in a heterogeneous medium. The successful conversion of PVAc to PVA and PVAc/PVB to PVA/P(VB-VA) films was confirmed by Fourier transform infrared spectrometry, X-ray diffraction, and proton nuclear magnetic resonance analysis. This study also shows that the degree of saponification (DS) depends on the saponification time. The maximum DS of 99.99% was obtained at 96 h of saponification for all films, and the presence of PVB did not affect the DS at saponification times of 48-96 h. The effects of the PVAc/PVB blend ratio before and after saponification were determined by contact angle measurement, and the hydrophobicity was found to increase in both cases with increasing PVB content. Additionally, all the films exhibited improved mechanical properties after saponification, and the treated films possessed an unusual porous and uneven surface, in contrast with the untreated films. The prepared films with improved hydrophobicity can be used for various applications, such as biomaterials, filters, and medical devices.

Indexed as

blend filmheterogeneous saponificationpoly(vinyl alcohol)poly(vinyl butyral)

Identifiers

PMID36146059
PMCPMC9505735

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.