Evidence map›Paper›PMID 36188249›Full record

ArticleACS omega2022

Synthesis, Characterization, and Performance of Pyridomethene-BF2 Fluorescence Dye-Doped PVA Thin Film and PVP Nanofibers as Low γ-ray Dosimeters.

Sadeq M Al-Hazmy, Yassine El-Ghoul, Jameelah Al-Harby, Haja Tar, Fahad M Alminderej

Abstract read
In one paragraph

Article in ACS omega, 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.

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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.

Sadeq M Al-HazmyDepartment of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia.
Yassine El-GhoulDepartment of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia.ORCID https://orcid.org/0000-0001-9520-1793
Jameelah Al-HarbyDepartment of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia.
Haja TarDepartment of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia.
Fahad M AlminderejDepartment of Chemistry, College of Science, Qassim University, Buraidah 51452, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, particular attention is paid to public health related to the field of γ-ray dosimetry, which is becoming increasingly important in medical diagnostic processes. Incorporating sensitive dyes as radiation dose sensors in different material hosts has shown promising radiation dosimetry application routes. In this perspective, the current study proposes a new fluorescent dye based on boron difluoride complex, the pyridomethene-BF2 named 2-(1-(difluoroboraneyl)-1,2-dihydroquinolin-2-yl)-2-(1-methylquinoxalin-2-ylidene) acetonitrile (DBDMA) as an indicator for low γ-ray doses. The different optical and quantum chemical parameters and the spectral behavior of the selected fluorescent dye were first studied. Then, PVP/DBDMA electrospun nanofibers and PVA/DBDMA thin films were prepared. The different UV-vis spectrophotometric and fluorescence studies revealed a clear change after exposure to different γ-ray doses. Thermogravimetric analysis exhibited excellent thermal stability of the prepared nanocomposite films, showing altered thermal behavior after γ-ray treatment. Furthermore, the SEM evaluation displayed a significant modification in the surface morphology of the two designed nanomaterials with increased radiation dose intensity. These novel forms of dosimeter designed in nanoscale composites could therefore constitute a promising and efficient alternative for rapid and accurate detection of low doses of γ-rays in various medical applications.

Identifiers

PMID36188249
PMCPMC9520551

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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.