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基于凹形金纳米箭头的苹果汁中福美胂的SERS检测

赵丽娜 沈烨 商显文 陈智扬 石吉勇 郑开逸 孙正东 张孟

分析测试学报2025,Vol.44Issue(7):1346-1354,9.
分析测试学报2025,Vol.44Issue(7):1346-1354,9.DOI:10.12452/j.fxcsxb.241129563

基于凹形金纳米箭头的苹果汁中福美胂的SERS检测

Detection of Asomate in Apple Juice Based on Surface Enhanced Raman Scattering Combined with AuCNAs

赵丽娜 1沈烨 1商显文 1陈智扬 1石吉勇 1郑开逸 1孙正东 2张孟2

作者信息

  • 1. 江苏大学 食品与生物工程学院,江苏 镇江 212013
  • 2. 华东理工大学 物理学院,上海 200237
  • 折叠

摘要

Abstract

Surface enhanced Raman spectroscopy(SERS)is an analysis technique that improves Ra-man signals through rough metal nanoparticles,with the advantages of high sensitivity,strong speci-ficity and simple operation.Therefore,this paper proposed a method to rapidly detect the residue of asomate in apple juice using concave Au nano-arrows(AuCNAs)as SERS substrate.The Au nanorods(AuNRs)were prepared based on seed-mediated growth strategy,and then used for the synthesis of AuCNAs.After that,the synthesized AuCNAs were analyzed to show good stability,homogeneity and repeatability.Meanwhile,the AuCNAs achieved high enhancement factor(1.10×106).Com-pared to other nanospheres and nanorods,AuCNAs had significantly better SERS enhancement prop-erties.The locations of SERS peaks can be attributed to the vibrations of chemical bonds through mo-lecular simulation.The intensity at the Raman peak of 1 382 cm-1 was used to establish a correction curve with the residual concentrations of asomate in apple juices,and the limit of detection(LOD)of asomate was 8.93 nmol/L.The recovery experiments showed that the average recoveries of asomate in apple juice was 96.2%-109%with relative standard deviations ranging of 4.2%-8.8%.The results in-dicated that AuCNAs can be used as SERS enhanced substrates to detect asomate in apple juice.

关键词

福美胂/表面增强拉曼光谱/凹形金纳米箭头/农药残留/苹果汁

Key words

asomate/surface enhanced Raman spectroscopy/AuCNAs/pesticide residue/ap-ple juice

分类

化学化工

引用本文复制引用

赵丽娜,沈烨,商显文,陈智扬,石吉勇,郑开逸,孙正东,张孟..基于凹形金纳米箭头的苹果汁中福美胂的SERS检测[J].分析测试学报,2025,44(7):1346-1354,9.

基金项目

国家重点研发计划项目(2017YFD0400102) (2017YFD0400102)

国家自然科学基金项目(31972153) (31972153)

国家博士后资助项目(2019M661758) (2019M661758)

江苏省博士后资助项目(2019K014) (2019K014)

江苏大学基金项目(19JDG010) (19JDG010)

分析测试学报

OA北大核心

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