Evidence map›Paper›PMID 38989248›Full record

ArticleRSC advances2024

Computational modelling of graphene/aluminum nitride (GP/AlN) hybrid materials for the detection of 2,4 dichlorophenoxyacetic acid (DCP) pollutant.

Chioma G Apebende, Ismail O Amodu, Miracle N Ogbogu, Ubua P Unimuyi, Monsurat Alarape Raimi, Godwin O Igomah

Abstract read
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Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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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

6 authors.

Chioma G ApebendeDepartment of Pure and Applied Chemistry, University of Calabar Calabar Nigeria gloriaapebende@gmail.com.ORCID https://orcid.org/0000-0003-1003-4717
Ismail O AmoduDepartment of Mathematics and Statistics, University of Calabar Calabar Nigeria.
Miracle N OgboguDepartment of Genetics and Biotechnology, University of Calabar Calabar Nigeria.
Ubua P UnimuyiDepartment of Pure and Applied Chemistry, University of Calabar Calabar Nigeria gloriaapebende@gmail.com.
Monsurat Alarape RaimiDepartment of Chemistry, University of Ilorin Ilorin Nigeria.
Godwin O IgomahDepartment of Physics, University of Calabar Calabar Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite their efficacy in eliminating undesired crops and increasing yield, a range of environmental issues and chronic ailments arise when hazardous chemicals are highly concentrated in wastewater and then deposited into rivers, lakes or the air. Hence, the detection of these chemicals has become a cause of concern for researchers and scientists because they contribute largely to serious health problems. Herein, the potential of newly tailored nanomaterials for the detection of 2,4 dichlorophenoxyacetic acid (DCP) in humans was examined. The theoretical approach adopted in this work is within the framework of density functional theory (DFT) using the DFT/B3LYP-D3/def2SVP computational method. The reduction in the energy gap upon adsorption is indicative of good adsorbing properties. A chemisorption phenomenon was observed for DCP-GP/AlN. However, in most cases, physisorption occurs. Interestingly, the noncovalent nature of the interactions was observed in all the cases, indicating that the material was good. The green colour of the 3D RDG maps implies a significant intermolecular interaction. Sensor mechanisms confirmed that the nanocomposite materials exhibit excellent detection potential for DCP through greater charge transfer, better sensitivity, conductivity, and enhanced adsorption capacity. The potential of nanocomposite materials as stable and promising detectors for DCP pollutants was confirmed in this study. Hence, the studied GP/AlN nanocomposite material can be used in the engineering of future sensor devices for detecting DCP.

Identifiers

PMID38989248
PMCPMC11234257

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