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Reflectivity enhanced refractive index sensor based on a fiber-integrated Fabry-Perot microresonator
Optics Express
|November 18, 2014
Summary
This study presents a fiber-integrated refractive index sensor with enhanced detection performance using focused-ion beam milling. Coating resonator walls significantly boosted mirror reflectivity, optimizing it as a Fabry-Perot resonator for improved sensing capabilities.
Area of Science:
- Photonics and Optical Sensing
- Materials Science and Engineering
- Nanotechnology
Background:
- Refractive index sensors are crucial for various applications, including chemical detection and biomedical diagnostics.
- Existing fiber-integrated sensors often face limitations in sensitivity and detection performance.
- Fabry-Perot resonators offer a promising platform for high-performance optical sensing.
Purpose of the Study:
- To develop and characterize a fiber-integrated refractive index sensor with significantly improved detection performance.
- To investigate the impact of resonator wall coating on sensor performance.
- To provide design rules and mathematical analysis for optimizing such sensors.
Main Methods:
- Implementation of a resonator using focused-ion beam milling of a step index fiber.
- Coating of resonator walls to enhance mirror reflectivity.
- Mathematical analysis and derivation of design rules for sensor optimization.
Main Results:
- Achieved a sensitivity of approximately 1.15 µm/RIU for the refractive index sensor.
- Demonstrated a significant improvement in mirror reflectivity by a factor of approximately 26 through resonator wall coating.
- Confirmed the sensor operates as an optimized Fabry-Perot resonator.
Conclusions:
- The developed fiber-integrated sensor exhibits strongly improved detection performance.
- Coating resonator walls is an effective strategy for enhancing mirror reflectivity and overall sensor performance.
- The performance of Fabry-Perot sensors is fundamentally limited by the detection limit function, influenced by cavity finesse and measurement capabilities.

