近日，北京大学的胡小永&及其研究小组与浙江大学的狄大卫等人合作并取得一项新进展。经过不懈努力，他们实现异质集成的钙钛矿/氮化硅芯片上光子系统。相关研究成果已于2025年1月2日在国际知名学术期刊《自然—光子学》上发表。
本文提出并实验实现了一种基于钙钛矿/氮化硅光子平台的近红外单片集成光子系统，开发了纳米异质集成技术，将高效发光二极管、高性能处理器和灵敏光电探测器集成在一起。研究人员实现了光子神经网络，用于执行光子模拟和计算机视觉任务。该网络能够高效预测二维无序Su-Schrieffer-Heeger模型中的拓扑不变量，并以87%的平均保真度模拟非线性拓扑模型。
此外，使用扩展架构，研究人员在边缘检测任务中实现了超过85%的测试准确率，在CIFAR-10数据集上实现了56%的准确率。这项工作解决了将多种纳米光子组件集成到同一芯片上的挑战，为芯片集成多功能光子信息处理提供了一种有前景的解决方案。
据悉，集成光子芯片在光通信、计算、激光雷达、传感和成像等领域具有巨大潜力，能够提供卓越的数据吞吐量和低功耗。一个关键目标是构建一个单片集成光子系统，将光源、处理器和光电探测器集成在同一芯片上。然而，由于材料工程、芯片集成技术和设计方法的限制，这一目标仍然面临挑战。钙钛矿材料具有制备简单、对晶格失配容差高、带隙可调性强和成本低等优点，使其成为与硅光子学异质集成的有前景的选择。
附：英文原文
Title: Hetero-integrated perovskite/Si3N4 on-chip photonic system
Author: Liao, Kun, Lian, Yaxiao, Yu, Maotao, Du, Zhuochen, Dai, Tianxiang, Wang, Yaxin, Yan, Haoming, Wang, Shufang, Lu, Cuicui, Chan, C. T., Zhu, Rui, Di, Dawei, Hu, Xiaoyong, Gong, Qihuang
Issue&Volume: 2025-01-02
Abstract: Integrated photonic chips hold substantial potential in optical communications, computing, light detection and ranging, sensing, and imaging, offering exceptional data throughput and low power consumption. A key objective is to build a monolithic on-chip photonic system that integrates light sources, processors and photodetectors on a single chip. However, this remains challenging due to limitations in materials engineering, chip integration techniques and design methods. Perovskites offer simple fabrication, tolerance to lattice mismatch, flexible bandgap tunability and low cost, making them promising for hetero-integration with silicon photonics. Here we propose and experimentally realize a near-infrared monolithic on-chip photonic system based on a perovskite/silicon nitride photonic platform, developing nano-hetero-integration technology to integrate efficient light-emitting diodes, high-performance processors and sensitive photodetectors. Photonic neural networks are implemented to perform photonic simulations and computer vision tasks. Our network efficiently predicts the topological invariant in a two-dimensional disordered Su–Schrieffer–Heeger model and simulates nonlinear topological models with an average fidelity of 87%. In addition, we achieve a test accuracy of over 85% in edge detection and 56% on the CIFAR-10 dataset using a scaled-up architecture. This work addresses the challenge of integrating diverse nanophotonic components on a chip, offering a promising solution for chip-integrated multifunctional photonic information processing.
DOI: 10.1038/s41566-024-01603-y
Source: https://www.nature.com/articles/s41566-024-01603-y