化学
光电流
Mercury(编程语言)
氧气
检出限
离子
水溶液中的金属离子
吸附
分析化学(期刊)
光电子学
环境化学
电极
物理化学
材料科学
有机化学
计算机科学
程序设计语言
色谱法
作者
Xiang Ren,Na Song,Jingui Chen,Gao Min,Huan Wang,Zhong Feng Gao,Huangxian Ju,Jinxiu Zhao,Qin Wei
出处
期刊:Talanta
[Elsevier]
日期:2024-02-01
卷期号:: 125780-125780
被引量:6
标识
DOI:10.1016/j.talanta.2024.125780
摘要
Mercury ion (Hg2+) poses a serious threat to human health due to its high toxicity. In this study, a smartphone-based photoelectrochemical sensor based on oxygen vacancies (OVs) driven signal enhancement for mercury ion detection was designed. BiVO4-x/Bi2S3/AuNPs were combined with T−Hg2+−T recognition mode to construct a multi-sandwich photoelectrochemical sensor. On the one hand, the OVs can increase the adsorption of light by the materials and enhance the photocurrent response as well as the superconductivity of Au NPs to accelerate the charge transfer at the electrode interface. On the other hand, the multi-sandwich structure was exploited to increase the binding site of Hg2+, as well as the T−Hg2+−T structure for sensitive recognition of Hg2+ and signal amplification. The sensor showed good linearity for Hg2+ concentration in the range of 0.1 nM–1.0 μM with a detection limit of 4.8 pM (S/N = 3). Eventually the smartphone-based real-time detection sensor is expected to contribute to the future analysis of heavy metal ions.
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