Evidence map›Paper›PMID 41385509›Full record

ArticlePloS one2025

A terahertz graphene-metamaterial sensor for highly sensitive detection of trace pesticide metaldehyde.

Dazhi Zhang, Xinlei Ruan, Maosheng Yang, Honglai Liu, Xiaobing Li, Peipei Li

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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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

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Dazhi ZhangSchool of Chemical Engineering & Technology, China University of Mining and Technology, Xuzhou, Jiangsu, P. R. China.ORCID https://orcid.org/0000-0002-2234-4811
Xinlei RuanCollege of Materials and Chemical Engineering, West Anhui University, Luan, Anhui, P. R. China.
Maosheng YangCollege of Materials and Chemical Engineering, West Anhui University, Luan, Anhui, P. R. China.
Honglai LiuSchool of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, P. R. China.
Xiaobing LiSchool of Chemical Engineering & Technology, China University of Mining and Technology, Xuzhou, Jiangsu, P. R. China.
Peipei LiCollege of Materials and Chemical Engineering, West Anhui University, Luan, Anhui, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To address the demand for rapid detection of trace metaldehyde pesticide residues in agricultural products such as Dendrobium officinale Kimura et Migo (D. officinale), this paper proposes and validates a high-sensitivity metal-graphene hybrid metamaterial sensor, which exhibits significant advantages in the field of pesticide residue detection. The sensor consists of a quartz substrate, periodic gold array, polyimide (PI) spacer layer, and few-layer graphene, and is fabricated using standard micro-nano processing technologies. Utilizing a terahertz time-domain spectroscopy (THz-TDS) system, the reflection spectra of the sensor in response to metaldehyde solutions with different concentrations (0-2400 pg mL-1) were measured in the 0.6-1.5 THz frequency band. The results indicate that compared with the bare metamaterial, the introduction of graphene significantly enhances the sensor's sensitivity, and its resonance intensity decreases noticeably with the increase in metaldehyde concentration. Simulation analyses reveal the existence of the toroidal dipole resonance mode and the mechanism by which the graphene layer induces a resonant red shift by increasing the effective capacitance, while confirming that the regulation of graphene's Fermi energy level can dynamically modulate the resonance intensity. Experimental measurements show that the hybrid metamaterial sensor achieves a minimum detection limit of 100 pg mL-1 for metaldehyde, with a rapid response in the low concentration range (0-200 pg mL-1). This high sensitivity is primarily attributed to the effective modulation of the dielectric environment on the graphene surface by the monolayer adsorption of analytes at low concentrations. The sensor developed in this study exhibits excellent performance, providing an effective technical solution for the rapid screening of pesticide residues in the safety inspection of agricultural products such as D. officinale.

Indexed as

AcetaldehydeGraphitePesticide ResiduesTerahertz SpectroscopyCrop ProductionDendrobiumDrug ContaminationDrugs, Chinese HerbalLimit of DetectionPlants, MedicinalPlant StemsAcetaldehydeDrugs, Chinese HerbalGraphitemetaldehydePesticide Residues

Identifiers

PMID41385509
PMCPMC12700456

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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.