Ultrasensitive Electrochemiluminescence Platform Based on Self-Photocatalysis-Induced Continuous Generation of H 2 O 2 for Synchronous Monitoring and Degradation of Enrofloxacin

化学 电化学发光 检出限 鲁米诺 降级(电信) 线性范围 恩诺沙星 化学发光 水溶液 分解 光催化 纳米颗粒 可见光谱 信号(编程语言) 持续监测 适体 化学工程 纳米技术 污染 分析化学(期刊)
作者
Jia Wang,Xiaoman Qin,Xianzhen Song,Lu Zhao,Caifeng Ding
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:98 (15): 11330-11339
标识
DOI:10.1021/acs.analchem.6c00145
摘要

Luminol, as a classic electrochemiluminescence (ECL) emitter, often suffers from signal instability due to the rapid decomposition of its common coreactant H 2 O 2 . In this study, a self-photocatalysis strategy was developed to generate the coreactant in situ for luminol and enhance the stability of its ECL stability, and the underlying mechanism was systematically investigated. The proposed sensor enabled the sensitive and accurate detection of enrofloxacin (ENR) in natural water samples. Specifically, the photocatalyst NH 2 -MIL-125 (TiM) was incorporated into the sensing platform. The light energy emitted by luminol ( hv = 2.89 eV) exceeded the bandgap energy of TiM (E bg = 2.50 eV), thereby activating TiM to catalyze the production of H 2 O 2, which ensured a continuous supply of the coreactant and significantly improved the ECL signal stability. Furthermore, a stable and antifouling sensing interface was constructed by the codeposition of a zwitterionic polymer and in situ reduction of silver nanoparticles (Ag NPs), which ensures reliable sensing performance in complex aqueous environments and supports the practical applicability of the proposed dual-function platform. In the presence of ENR, H 2 O 2 was consumed through a degradation process that converted ENR into nontoxic and harmless small molecules, resulting in a corresponding decrease of the luminol ECL signal. This dual-function strategy enabled the simultaneous detection and degradation of the antibiotic. The sensor exhibits a wide linear range (100 fM-1 μM) and a low detection limit (42.8 fM, S / N = 3), demonstrating great potential for rapid and accurate monitoring of antibiotic contaminants in environmental water.
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