MXene fibers-based molecularly imprinted disposable electrochemical sensor for sensitive and selective detection of hydrocortisone.

Electrochemical sensor Hydrocortisone MXene fibers Molecularly imprinted polymer

Journal

Talanta
ISSN: 1873-3573
Titre abrégé: Talanta
Pays: Netherlands
ID NLM: 2984816R

Informations de publication

Date de publication:
01 Jan 2024
Historique:
received: 29 04 2023
revised: 31 07 2023
accepted: 18 08 2023
medline: 24 8 2023
pubmed: 24 8 2023
entrez: 23 8 2023
Statut: ppublish

Résumé

A molecularly imprinted electrochemical sensor based on MXene fibers was proposed in this work. Firstly, the wet spinning technique prepared MXene fibers with a large aspect ratio, which can make the sheet-like MXene uniformly arranged, avoiding the agglomeration of MXene and improving the electrical conductivity. Afterwards, molecularly imprinted polymers (MIPs) with specific recognition sites were synthesized on the surface of MXene fibers using the electro-polymerization method. The electrochemical sensor utilized the advantages of MXene fibers and molecular imprinting techniques to gain superior selectivity and sensitivity of hydrocortisone (HC). Electrochemical tests with different concentrations of HC (0.5 nM-10.0 μM) under optimal measurement conditions exhibited excellent linearity and a limit of detection (LOD) of 0.17 nM. Furthermore, the electrochemical sensor displayed excellent selectivity, interference resistance, reproducibility, stability and outstanding application performance in serum. This work has promising applications in trace analysis in real sample.

Identifiants

pubmed: 37611366
pii: S0039-9140(23)00851-2
doi: 10.1016/j.talanta.2023.125100
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

125100

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Zhuo Shi (Z)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Zifeng Wang (Z)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Kaiwen Li (K)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Yuwei Wang (Y)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Zhanhong Li (Z)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.

Zhigang Zhu (Z)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China. Electronic address: zhigang_zhu259@163.com.

Classifications MeSH