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用于食品样品表面增强拉曼光谱分析的基于UiO-66金属有机框架/金纳米粒子的基底

UiO-66 metal-organic frameworks/gold nanoparticles based substrates for SERS analysis of food samples.

作者信息

Fu Jingtai, Lai Huasheng, Zhang Zhuomin, Li Gongke

机构信息

School of Chemistry, Sun Yat-sen University, Guangzhou, 510275, China.

School of Chemistry, Sun Yat-sen University, Guangzhou, 510275, China.

出版信息

Anal Chim Acta. 2021 May 29;1161:338464. doi: 10.1016/j.aca.2021.338464. Epub 2021 Mar 28.

DOI:10.1016/j.aca.2021.338464
PMID:33896560
Abstract

Recently, metal-organic frameworks (MOFs) based substrates have shown great potential for the quantitative analysis of food samples by surface-enhanced Raman scattering (SERS) due to their unique properties. Herein, we developed two UiO-66 MOFs/gold nanoparticles (AuNPs) based substrates by self-assembly, including UiO-66/AuNPs suspension substrate and UiO-66(NH)/AuNPs/Nylon-66 flexible membrane substrate, for quantitative analysis of complex food samples by SERS. UiO-66/AuNPs suspension substrate was prepared for SERS-based determination of a carcinogenic heterocyclic amine in barbecue meat. UiO-66(NH)/AuNPs/Nylon-66 membrane substrate was fabricated for the simultaneous separation, enrichment, and in situ analysis of Sudan Red 7B in chilli products. The heterocyclic amine and Sudan dye in real samples could be detected and quantified with the recoveries of 82.3-110% and 84.5-114% and relative standard deviations (RSDs) of 3.1-11.0% and 1.9-5.6% (n = 3) by use of these two substrates, respectively. These two UiO-66/AuNPs based substrates combined molecular enrichment and SERS activity, achieving excellent analytical accuracy and widening SERS application in practical food safety analysis.

摘要

最近,基于金属有机框架(MOFs)的基底由于其独特的性质,在通过表面增强拉曼散射(SERS)对食品样品进行定量分析方面显示出巨大潜力。在此,我们通过自组装开发了两种基于UiO-66金属有机框架/金纳米粒子(AuNPs)的基底,包括UiO-66/AuNPs悬浮液基底和UiO-66(NH)/AuNPs/尼龙-66柔性膜基底,用于通过SERS对复杂食品样品进行定量分析。制备UiO-66/AuNPs悬浮液基底用于基于SERS测定烤肉中的致癌杂环胺。制备UiO-66(NH)/AuNPs/尼龙-66膜基底用于同时分离、富集和原位分析辣椒制品中的苏丹红7B。使用这两种基底分别对实际样品中的杂环胺和苏丹染料进行检测和定量,回收率分别为82.3 - 110%和84.5 - 114%,相对标准偏差(RSDs)分别为3.1 - 11.0%和1.9 - 5.6%(n = 3)。这两种基于UiO-66/AuNPs的基底结合了分子富集和SERS活性,在实际食品安全分析中实现了优异的分析准确性并拓宽了SERS的应用范围。

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