Issue 14, 2021

Triple-signaling amplification strategy based electrochemical sensor design: boosting synergistic catalysis in metal–metalloporphyrin–covalent organic frameworks for sensitive bisphenol A detection

Abstract

A covalent organic framework (COF) is a promising type of porous material with customizable surface characteristics. Confining multiple catalytic units within a mesoporous COF can generate abundant active sites and improve the catalytic performance. In this work, a COF with both metalloporphyrin and a metal nanoparticle complex denoted as hemin/TAPB-DMTP-COF/AuNPs (TAPB: 1,3,5-tris(4-amino-phenyl)benzene, DMTP: 2,5-dimethoxyterephaldehyde, AuNPs: Au nanoparticles) has been successfully fabricated through a hierarchical encapsulation method. The as-synthesized composite was then employed to construct an electrochemical sensing platform for the efficient detection of bisphenol A (BPA). Under the optimal conditions, the hemin/TAPB-DMTP-COF/AuNP sensor presented a linear range of 0.01–3 μmol L−1 and a low detection limit of 3.5 nmol L−1. The satisfactory signal amplification is based on a triple-signaling amplification strategy due to the abundant Fe3+ sites of Fe-porphyrin, high conductivity of AuNPs and a large specific surface area of the TAPB-DMTP-COF. The proposed method was used to measure the content of BPA in different water samples with a satisfactory recovery from 95.5 to 104.0%, suggesting the great potential of the sensor in practical applications.

Graphical abstract: Triple-signaling amplification strategy based electrochemical sensor design: boosting synergistic catalysis in metal–metalloporphyrin–covalent organic frameworks for sensitive bisphenol A detection

Article information

Article type
Paper
Submitted
17 Apr 2021
Accepted
26 May 2021
First published
22 Jun 2021

Analyst, 2021,146, 4585-4594

Triple-signaling amplification strategy based electrochemical sensor design: boosting synergistic catalysis in metal–metalloporphyrin–covalent organic frameworks for sensitive bisphenol A detection

Y. Xie, N. Wang, X. Sun, H. Chu, Y. Wang and X. Hu, Analyst, 2021, 146, 4585 DOI: 10.1039/D1AN00665G

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