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Quantitative surface-enhanced Raman measurements with embedded internal reference.

Yan Zhou1, Rui Ding1, Padmanabh Joshi1

  • 1Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, United States.

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|April 26, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for accurate quantitative analysis using Surface-Enhanced Raman Spectroscopy (SERS). By incorporating an internal reference, this technique significantly improves the reliability of SERS measurements for various analytes.

Keywords:
AminothiophenolCore–shell nanostructureInternal referenceMelamineQuantitative surface-enhanced Raman measurement

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Area of Science:

  • Analytical Chemistry
  • Materials Science
  • Spectroscopy

Background:

  • Quantitative analysis using Surface-Enhanced Raman Spectroscopy (SERS) faces challenges in achieving reliable results.
  • Existing SERS methods often lean towards qualitative assessments due to difficulties in precise signal measurement.

Purpose of the Study:

  • To develop a novel strategy for accurate quantitative SERS measurements.
  • To enhance the precision and reliability of SERS analysis through the incorporation of an internal reference standard.

Main Methods:

  • Utilized gold-core/silver-shell nanoparticles with embedded 4-aminothiophenol as an internal reference.
  • Applied the developed SERS strategy for the detection of Toluidine Blue O in aqueous solution and melamine in milk.

Main Results:

  • Achieved a detection limit of 0.1 μM for Toluidine Blue O.
  • Demonstrated a detection limit of approximately 5 μM for melamine in milk.
  • Showcased significant improvement in linear fitting, indicating enhanced accuracy in quantitative SERS measurements.

Conclusions:

  • The developed SERS strategy with an internal reference effectively improves the accuracy of quantitative measurements.
  • The method demonstrates versatility, successfully detecting diverse analytes like dyes and contaminants in complex matrices such as milk.
  • This approach offers a robust solution for reliable quantitative SERS analysis in various applications.