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Ultra-compact silicon mode-order converters based on dielectric slots
Optics Letters
|July 8, 2020
Summary
Researchers developed ultra-compact dielectric slot mode converters on silicon-on-insulator. These devices efficiently convert optical modes with minimal insertion loss, offering scalability for advanced photonic integrated circuits.
Area of Science:
- Photonics
- Integrated Optics
- Materials Science
Background:
- Mode-order converters are crucial components in photonic integrated circuits for manipulating optical signals.
- Existing converters often suffer from large footprints and high insertion losses, limiting their practical application.
Purpose of the Study:
- To demonstrate ultra-compact mode-order converters utilizing dielectric slots on a silicon-on-insulator (SOI) platform.
- To achieve efficient conversion between different transverse electric (TE) modes with minimal signal loss.
Main Methods:
- Fabrication of mode converters on an SOI platform featuring precisely engineered dielectric slots.
- Characterization of device performance, including insertion loss and operational bandwidth, across a specific wavelength range (1520-1570 nm).
- Optimization of the converter structure to minimize footprint and insertion loss for TE0 to TE1 and TE0 to TE2 mode conversion.
Main Results:
- Demonstration of an ultra-compact TE0 to TE1 mode converter with a footprint of 0.8×1.2 µm² and insertion loss < 1.2 dB.
- Optimized converters achieved insertion losses < 0.5 dB for TE0 to TE1 and TE0 to TE2 modes, with footprints of 0.88×2.3 µm² and 1.4×2.4 µm², respectively.
- The proposed devices exhibit cascadability and scalability for higher-order mode conversion.
Conclusions:
- Ultra-compact and low-loss mode-order converters are achievable using dielectric slot structures on SOI.
- The demonstrated devices offer significant advantages in terms of size and performance for integrated photonic applications.
- The scalability and cascadability of these converters pave the way for complex photonic systems and advanced signal processing.
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