Evidence map›Paper›PMID 31460024›Full record

ArticleACS omega2019

Engineering of Durable Antifog Thin Coatings on Plastic Films by UV-Curing of Proteinoid Prepolymers with PEG-Diacrylate Monomers.

Elisheva Sason, Michal Kolitz-Domb, Jordan H Chill, Shlomo Margel

Abstract read
In one paragraph

Article in ACS omega, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

4 authors.

Elisheva SasonDepartment of Chemistry, Institute of Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.
Michal Kolitz-DombDepartment of Chemistry, Institute of Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.
Jordan H ChillDepartment of Chemistry, Institute of Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.
Shlomo MargelDepartment of Chemistry, Institute of Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 5290002, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fog formation on transparent surfaces constitutes a major challenge in several optical applications, such as plastic packaging, lenses, mirrors, and windshields. To overcome this problem, we prepared and characterized durable antifog thin coatings on plastic films such as polyethylene terephthalate (PET). Proteinoids are biocompatible random polymers made of α-amino acids by thermal step-growth polymerization. Proteinoid prepolymers were prepared by adding activated double bonds to proteinoids via the Michael addition reaction. A series of thin antifog cross-linked coatings were prepared by spreading on PET films with a Mayer rod various mixtures of the proteinoid prepolymers, polyethylene glycol diacrylate, and a photoinitiator, followed by UV-curing of the dried coatings. The antifog properties of the coatings were determined by the contact angle, roughness, haze, and gloss measurements, as well as hot and cold fog tests, to examine the optical properties of the films under fog formation conditions. Mechanical properties such as adhesion, robustness, and abrasion resistance of the antifog coatings were examined by tape, knife-scratch, and sandpaper abrasion tests. The effect of coating composition, wettability, and roughness on the antifog properties of the coated PET films was elucidated. The formula was optimized, and the corresponding UV-cured antifog cross-linked thin coating exhibited transparency with good adhesion and excellent durable antifog performance.

Identifiers

PMID31460024
PMCPMC6648281

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.