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Quantitative and Sensitive SERS Platform with Analyte Enrichment and Filtration Function.

Qianqian Ding1, Jing Wang2, Xueyan Chen1

  • 1Institute for Composites Science Innovation, School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China.

Nano Letters
|September 1, 2020
PubMed
Summary
This summary is machine-generated.

This study presents a novel Surface-Enhanced Raman Scattering (SERS) platform that enhances quantification and analyte identification in complex samples. It achieves this by controlling SERS site formation and incorporating analyte enrichment and filtration for sensitive detection.

Keywords:
analyte enrichmentquantitative detectionsensorsslippery surfacessurface-enhanced Raman scattering

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Area of Science:

  • Analytical Chemistry
  • Materials Science
  • Spectroscopy

Background:

  • Surface-Enhanced Raman Scattering (SERS) offers inherent analyte identification but faces a trade-off between sensitivity and quantification.
  • Existing SERS methods often struggle to provide accurate quantification in complex sample matrices due to uncontrolled signal enhancement.

Purpose of the Study:

  • To develop an integrated SERS platform that overcomes the mutual exclusivity of sensitivity and quantification.
  • To enhance analyte identification capabilities in complex environments through controlled SERS and selective analyte enrichment/filtration.

Main Methods:

  • Fabrication of gold (Au) nanorods encapsulated within thick metal-organic framework (MOF) shells to prevent ultrasensitive SERS site formation.
  • Implementation of a slippery surface for analyte enrichment, compensating for reduced SERS sensitivity.
  • Utilizing the porous MOF shell as a size-selective filter for analyte approach to Au nanorods.

Main Results:

  • Achieved high quantification capability by suppressing ultrasensitive SERS hotspots through MOF shell separation of Au nanorods.
  • Demonstrated compensation for sensitivity loss via analyte enrichment, maintaining sensitive detection.
  • Showcased enhanced analyte identification in complex samples due to size-selective filtration by the MOF shell.

Conclusions:

  • The developed SERS platform successfully integrates analyte enrichment and filtration functions.
  • This approach enables sensitive, quantitative, and size-selective analyte identification in complex environments.
  • The study provides a new strategy for designing advanced SERS sensors with improved performance metrics.