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Updated: May 6, 2026

Surface Enhanced Raman Spectroscopy Detection of Biomolecules Using EBL Fabricated Nanostructured Substrates
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Trends in surface plasmon resonance biosensing: materials, methods, and machine learning.

Daniel D Stuart1, Westley Van Zant1, Santino Valiulis1

  • 1Department of Chemistry, University of California, Riverside, CA, 92521, USA.

Analytical and Bioanalytical Chemistry
|June 5, 2024
PubMed
Summary
This summary is machine-generated.

Surface plasmon resonance (SPR) advancements enhance label-free biosensing. Novel materials, signal transduction, and machine learning integration improve biomolecular interaction studies for human health research.

Keywords:
BiosensingMachine learningPlasmonic materialsSurface plasmon resonanceThe Kretschmann configuration

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Area of Science:

  • Optoelectronics and Photonics
  • Biotechnology and Biosensing
  • Materials Science

Background:

  • Surface plasmon resonance (SPR) is a key label-free detection technique for biomolecular interactions.
  • The Kretschmann configuration is a foundational platform for SPR-based biosensors.
  • Current SPR methods face limitations in sensitivity and data analysis complexity.

Purpose of the Study:

  • To review recent advancements in Surface Plasmon Resonance (SPR) technology.
  • To highlight key developments enhancing SPR capabilities for biosensing.
  • To explore the impact of these advancements on biomolecular interaction studies and human health research.

Main Methods:

  • Exploration of novel plasmonic materials for improved SPR performance.
  • Discussion of innovative signal transduction and collection methods using traditional and alternative materials.
  • Review of advanced data analysis techniques, including machine learning integration for complex SPR datasets.

Main Results:

  • Novel plasmonic materials significantly shape SPR performance.
  • Advanced signal transduction and collection enhance detection capabilities.
  • Machine learning algorithms improve the analysis of complex SPR data, enabling new biosensing functions.

Conclusions:

  • Recent developments in SPR, including new materials, signal processing, and AI, significantly boost biosensing performance.
  • These enhancements enable new applications in biomolecular interaction studies.
  • The progress in SPR technology opens new avenues for its role in human health research.