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Multicolor Fluorescence Detection for Droplet Microfluidics Using Optical Fibers
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Fiber-optics based fluorescence detection. Part I: Basic concepts.

Bong Lee1, Luca Ceresa1, Danh Pham1

  • 1Department of Physics and Astronomy, Texas Christian University, Fort Worth, TX, 76109, United States of America.

Methods and Applications in Fluorescence
|July 2, 2024
PubMed
Summary
This summary is machine-generated.

Fiber optics enable compact in situ detection, but signal distortions hinder accurate analysis. This study models light collection efficiency to correct spectral data for improved accuracy in diverse applications.

Keywords:
absorptionfiber opticfluorescenceinner filter effectspectroscopy

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Area of Science:

  • Analytical Chemistry
  • Biomedical Optics
  • Optical Engineering

Background:

  • Fiber optics are crucial for compact, in situ chemical and biological analysis in industrial and biomedical settings.
  • Current understanding of light collection efficiency and detection sensitivity in fiber-optic systems is limited.
  • Challenges exist in comparing samples with varying optical properties and correcting for signal artifacts like inner-filter effects and scattering.

Purpose of the Study:

  • To investigate factors causing signal and spectral distortions in fiber-optic detection.
  • To develop a generic model for excitation profile and emission collection efficiency.
  • To provide a framework for correcting measured spectra and recovering true emission profiles.

Main Methods:

  • Analysis of signal detection in bare and lens-coupled flat-tipped fiber optic configurations.
  • Development and experimental verification of a generic model for light collection.
  • Evaluation of parameters influencing signal/spectral distortions.

Main Results:

  • Identified key factors contributing to signal and spectral distortions in fiber-optic measurements.
  • Presented a validated model accurately describing excitation profiles and emission collection efficiency.
  • Demonstrated the model's utility in understanding and potentially correcting spectral artifacts.

Conclusions:

  • A fundamental understanding of fiber-optic signal collection is essential for accurate quantitative analysis.
  • The developed model offers a rational basis for correcting spectral data, particularly for optically dense samples.
  • Improved spectral correction will enhance the reliability and comparability of results across different experimental setups.