Evidence map›Paper›PMID 40404731›Full record

ArticleScientific reports2025

Topological edge state resonance as gamma dosimeter using poly nanocomposite in symmetrical periodic structure.

Zaky A Zaky, Mohammed Sallah, V D Zhaketov, Arafa H Aly

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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.

Zaky A ZakyTH-PPM Group, Physics Department, Faculty of Sciences, Beni-Suef University, Beni Suef, 62514, Egypt. zaky.a.zaky@science.bsu.edu.eg.ORCID http://orcid.org/0000-0002-8300-7755
Mohammed SallahDepartment of Physics, College of Sciences, University of Bisha, P.O. Box 344, 61922, Bisha, Saudi Arabia.ORCID https://orcid.org/0000-0003-2063-8979
V D ZhaketovFrank Laboratory of Neutron Physics, Joint Institute for Nuclear Research, Dubna, Russia, 141980.
Arafa H AlyTH-PPM Group, Physics Department, Faculty of Sciences, Beni-Suef University, Beni Suef, 62514, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Topological edge state resonance based sensor, including photonic crystal, is proposed for gamma radiation detection. This article initiates by showing the fundamental principles of photonic crystal, topological edge state, and gamma dosimeter, highlighting their benefits and performance over conventional detectors. This study discusses the possibility of exciting a topological edge state resonance using two symmetrical photonic crystals composed of silicon doped with poly(ethylene oxide) nanocomposite as a gamma detector. The simulation results using the transfer matrix method recorded a sensitivity of 1.24 nm/Gy for gamma doses from 0 to 100 Gy and 0.34 nm/Gy for gamma doses from 100 to 200 Gy when the proposed structure is composed of silicon doped with poly(ethylene oxide) nanocomposite as an active material. It is found that the maximum figure of merit and quality factor of the detector are [Formula: see text] [Formula: see text] and [Formula: see text], respectively. Thus, this innovative topological edge state resonance-based detector is extremely promising for radiation detection. According to these investigations, topological edge state gamma sensors have distinct advantages over traditional dosimeters in terms of increased sensitivity, robustness against disorder, and simplified structure, which makes them appropriate for use in environmental radiation monitoring and medical imaging.

Indexed as

DosimeterGamma radiationPeriodic structurePolymer nanocompositeTopological edge state

Identifiers

PMID40404731
PMCPMC12098784

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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.