Supra-Quantum Dot Assemblies to Maximize Color-Based Multiplexed Fluorescence Detection with a Smartphone Camera.

Area of Science:

• Nanotechnology
• Biophotonics
• Analytical Chemistry

Background:

• Smartphone-based photoluminescence (PL) imaging is gaining traction for point-of-care diagnostics.
• Current color multiplexing in this field is limited, with its full potential unexplored.
• Quantum dots (QDs) offer tunable optical properties for multiplexed bioanalysis.

Purpose of the Study:

• To evaluate and advance color multiplexing capabilities for smartphone-based PL imaging.
• To develop supra-nanoparticle assemblies of quantum dots (supra-QDs) for tailored color generation.
• To assess the accuracy and scalability of multi-color classification using these supra-QDs.

Main Methods:

• Coassembled R-, G-, and B-emitting QDs on silica nanoparticle scaffolds to create supra-QDs with composite colors.
• Characterized supra-QDs and used them to label cell-sized objects for flow measurements.
• Employed smartphone-based PL imaging and support vector machine (SVM) models for color classification.

Main Results:

• Achieved ≥87% classification accuracy for 10-color multiplexing, improving to ≥94% with optimized RGB color space analysis.
• Demonstrated that accuracy is signal-dependent, with misclassification reduced by establishing nonclassifiable zones.
• Simulations suggest ≥14-color multiplexing with ≥90% accuracy is feasible with optimized supra-QD sets.

Conclusions:

• Supra-QDs provide a robust platform for advanced RGB color-based multiplexing in smartphone PL imaging.
• This approach significantly enhances the potential for multiplexed bioanalysis and diagnostics using ubiquitous smartphone technology.
• The study lays the groundwork for future development of highly multiplexed imaging systems based on color image sensors.