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Optimized ARROW-Based MMI Waveguides for High Fidelity Excitation Patterns for Optofluidic Multiplexing
Matthew A Stott1, Vahid Ganjalizadeh2, Maclain Olsen1
1Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT 84602 USA.
This study optimizes multimode interference (MMI) rib anti-resonant reflecting optical waveguides (ARROWs) for multiplexed fluorescence biosensors. Precise design of excitation waveguides and tapers enhances high-fidelity spot patterns for sensitive biomarker detection.
Area of Science:
- Optics and Photonics
- Biomedical Engineering
- Materials Science
Background:
- Multimode interference (MMI) waveguides enable optical signal multiplexing and de-multiplexing.
- High-fidelity, wavelength-dependent spot patterns are crucial for multiplexed fluorescence optofluidic biosensors.
- Accurate identification of multiple targets requires precise optical signal manipulation.
Purpose of the Study:
- To explore design parameters for MMI rib anti-resonant reflecting optical waveguides (ARROWs).
- To achieve high-fidelity spot patterns for biomarker excitation in optofluidic biosensors.
- To optimize waveguide geometry for enhanced optical throughput and mode matching.
Main Methods:
- Experimental fabrication and characterization of MMI rib ARROW waveguides.
- Optical simulations to analyze waveguide performance and spot pattern generation.
- Systematic investigation of waveguide width and etch depth parameters.
Main Results:
- Identified critical design parameters, including excitation waveguide width and etch depth.
- Demonstrated the impact of these parameters on input optical mode size and output spot fidelity.
- Showcased the effectiveness of waveguide tapers for improving optical throughput via mode matching.
Conclusions:
- Optimized MMI rib ARROW waveguide designs produce high-fidelity spot patterns.
- Precise control over waveguide geometry is essential for sensitive multiplexed biosensing.
- The findings facilitate the development of advanced optofluidic biosensor platforms.
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