Trends in surface plasmon resonance biosensing: materials, methods, and machine learning.

Journal: Analytical and bioanalytical chemistry
Published Date: Jun 6, 2024

Abstract

Surface plasmon resonance (SPR) proves to be one of the most effective methods of label-free detection and has been integral for the study of biomolecular interactions and the development of biosensors. This trend delves into the latest SPR research and progress built upon the Kretschmann configuration, a pivotal platform, and highlights three key developments that have enhanced the capabilities of the technique. We will first cover a range of explorations of novel plasmonic materials that have shaped SPR performance. Innovative signal transduction and collection, which leverages traditional materials and emerging alternatives, will then be discussed. Finally, the evolving landscape of data analysis, including the integration of machine learning algorithms to navigate complex SPR datasets, will be reviewed. We will also discuss the implementation of these improvements that have enabled new biosensing functions. These advancements not only pave the way for enhanced biosensing in general but also open new avenues for the technique to play a more significant role in research concerning human health.

Authors

  • Daniel D Stuart
    Department of Chemistry, University of California, Riverside, CA, 92521, USA.
  • Westley Van Zant
    Department of Chemistry, University of California, Riverside, CA, 92521, USA.
  • Santino Valiulis
    Department of Chemistry, University of California, Riverside, CA, 92521, USA.
  • Alexander S Malinick
    Department of Chemistry, University of California, Riverside, CA, 92521, USA.
  • Victor Hanson
    Department of Chemistry, University of California, Riverside, CA, 92521, USA.
  • Quan Cheng
    Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.

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