АI-орtimized angled multimode interference splitter with buried sin waveguide for highperformance O-band photonic networks
Traditional 1 × 2 multimode interference (MMI) splitters often encounter challenges such as high back reflections and limited output flexibility, which typically require additional structures like tapers or S-bends. These constraints limit their performance in advanced photonic networks. To overcome these issues, we propose an AI-optimized angled multimode interference (AMMI) splitter featuring a buried silicon nitride (SiN) core with silica cladding. By employing an angled propagation path, the device minimizes reflections to the source and allows greater adaptability for waveguide interconnections in dense photonic circuits. The design optimization was performed using a combination of artificial intelligence (AI) algorithms integrated with full-vectorial beam propagation method (FV-BPM) and finite-difference time-domain (FDTD) simulations. AI-driven parameter scanning enabled efficient exploration of the design space, improving device performance and robustness compared to manual optimization. The proposed AMMI splitter achieves an excess loss of 0.22 dB and an output imbalance of 0.001 dB at 1.31 μm, with total device length of 101 μm and thickness of 0.4 μm. Over the full O-band (1260–1360 nm), performance remains stable, with excess loss below 1.57 dB and imbalance below 0.05 dB, while maintaining back reflections as low as –40 dB. The compact CMOS-compatible design demonstrates high tolerance to fabrication deviations, making it highly suitable for large-scale integration. With its AI-enhanced optimization process, the proposed splitter supports high-speed, low-loss transmission for O-band photonic networks and data-center interconnects, offering scalability and reliability for next-generation optical systems.