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Label-free Single Molecule Detection Using Microtoroid Optical Resonators
Published on: December 29, 2015
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Label-Free Optical Resonator-Based Biosensors.
Donggee Rho1, Caitlyn Breaux1, Seunghyun Kim1
1Electrical and Computer Engineering Department, Baylor University, One Bear Place #97356, Waco, TX 76798, USA.
Sensors (Basel, Switzerland)
|October 22, 2020
Summary
Optical resonator biosensors offer sensitive, label-free detection for diagnostics. This review covers recent advances in Fabry-Perot interferometer and whispering gallery mode biosensor technologies.
Area of Science:
- Biomedical Engineering
- Optics
- Nanotechnology
Background:
- Biosensor technology demand is rising for disease diagnosis, drug development, and environmental monitoring.
- Optical resonator biosensors provide sensitive, rapid, label-free detection of biological analytes.
- Microfluidics and micro/nanofabrication enable miniaturized, multi-analyte detection in small volumes.
Purpose of the Study:
- To review recent advancements in label-free optical resonator-based biosensors.
- To categorize biosensors into Fabry-Perot interferometer-based and whispering gallery mode-based types.
- To discuss progress in configurations, materials, test setups, and light confinement.
Main Methods:
- Literature review focusing on publications from the last 5 years.
- Categorization based on optical resonator principles: Fabry-Perot interferometers and whispering gallery modes.
- Analysis of recent developments in biosensor design and application.
Main Results:
- Optical resonator biosensors are crucial for medical diagnostics and point-of-care applications.
- Recent progress has been made in enhancing sensitivity, speed, and miniaturization.
- Both Fabry-Perot interferometer and whispering gallery mode biosensors show significant development.
Conclusions:
- Optical resonator biosensors represent a promising platform for advanced diagnostics.
- Continued research in materials and fabrication will further enhance biosensor capabilities.
- Future work should address current challenges to optimize performance and expand applications.

