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Fluorescent Lateral Flow Immunoassay Based on Quantum Dots Nanobeads
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Data detection algorithms for multiplexed quantum dot encoding.

Kelly C Goss1, Geoff G Messier, Mike E Potter

  • 1Department of Electrical and Computer Engineering, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada. kcgoss@ucalgary.ca

Optics Express
|March 16, 2012
PubMed
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Multiplexed quantum dots (MxQDs) offer unique spectral codes for identification. Novel algorithms achieve 99.7% accuracy in reading these quantum dot barcodes, enabling over 46,000 unique spectral codes.

Area of Science:

  • Quantum optics and photonics
  • Spectroscopy and optical sensing
  • Information theory and communications

Background:

  • Quantum dots (QDs) can be engineered for unique spectral emissions via size (wavelength) and quantity (intensity).
  • This multiplexing capability has potential applications in biological tagging and object identification.

Purpose of the Study:

  • To develop a communications system model for multiplexed quantum dots (MxQDs).
  • To analyze signal-to-noise ratio (SNR) considering interference and detector noise.
  • To propose data detection algorithms for enhanced readability of QD tags.

Main Methods:

  • Analytical modeling of SNR for a Charge-Coupled Device (CCD) spectrometer.
  • Experimental validation of the analytical SNR model.

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  • Development and application of data detection algorithms for MxQD systems.

    • Main Results:

    • The SNR model was analytically derived and experimentally confirmed.
    • Proposed data detection algorithms significantly improve the readability of QD tags.
    • Achieved 99.7% accuracy in reading multiplexed quantum dot barcodes with 6 colors and 6 intensity levels.

    Conclusions:

    • MxQDs provide a robust platform for generating a large number of unique spectral codes (46,655 demonstrated).
    • The developed communications system model and detection algorithms enhance the practical application of QD-based identification systems.