Peking University Nature Photonics: Heterogeneous integrated perovskite/silicon nitride on-chip photonic system

2025/8/30 8:54:12 admin 阅读 181【次】

Zhu Rui & Hu Xiaoyong from Peking University, Di David from Zhejiang University, and Chen Ziting from the Hong Kong University of Science and Technology published a research paper titled "Hetero-integrated perovskite/Si3N4 on-chip photonic system" in the journal Nature Photonics. Liao Kun is the first author, and Zhu Rui, Hu Xiaoyong, Di David, and Chen Ziting are co-corresponding authors.

Key Highlights: This paper reports an on-chip photonic system based on a heterogeneously integrated metal halide perovskite/silicon nitride (Si3N4) photonic platform, demonstrating its versatility. The network can effectively predict topological invariants in a two-dimensional disordered Su-Schrieffer-Heeger model and simulate nonlinear topological models with an average fidelity of 87%. Furthermore, using an extended architecture, a test accuracy exceeding 85% was achieved in edge detection, and 56% on the CIFAR-10 dataset.

Integrated photonic chips hold great potential in optical communications, computing, light detection and ranging, sensing, and imaging, offering excellent data throughput and low power consumption. A key goal is to build a monolithic on-chip photonic system that integrates a light source, processor, and photodetector on a single chip. However, this remains challenging due to limitations in materials engineering, chip integration technology, and design methods. Perovskites offer promise for heterogeneous integration with silicon photonics due to their simple fabrication, tolerance to lattice mismatch, flexible bandgap tunability, and low cost.

In light of this, a team led by Zhu Rui, Hu Xiaoyong of Peking University, Di Dawei of Zhejiang University, and Chen Ziting of the Hong Kong University of Science and Technology proposed and experimentally realized a near-infrared monolithic on-chip photonic system based on a perovskite/silicon nitride photonic platform. They developed a nanoscale heterogeneous integration technique to integrate a high-efficiency light-emitting diode, a high-performance processor, and a sensitive photodetector. A photonic neural network was used to perform photonic simulation and computer vision tasks. The network effectively predicts topological invariants in a two-dimensional disordered Su-Schrieffer-Heeger model and simulates nonlinear topological models with an average fidelity of 87%. Furthermore, using an extended architecture, they achieved a test accuracy exceeding 85% in edge detection and 56% on the CIFAR-10 dataset.

This research addresses the challenges of integrating various nanophotonic components on a chip, providing a promising solution for chip-integrated multifunctional photonic information processing.

Source：https://doi.org/10.1038/s41566-024-01603-y

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Peking University Nature Photonics: Heterogeneous integrated perovskite/silicon nitride on-chip photonic system

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