光学
宽带
分光计
材料科学
光纤布拉格光栅
磷
波导管
衍射光栅
光电子学
衍射
光纤
物理
光纤传感器
保偏光纤
作者
Xinyang Chen,Xin Kang,Gan Yuan,Xiaotong Zhang,Ning Wang,Yong Zhu,Jie Zhang,Xuetao Gan
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2025-07-31
卷期号:33 (17): 35385-35385
被引量:7
摘要
On-chip spectrometers offer advantages such as compact footprint, lightweight, and low complexity, making them widely applicable in scientific research, medical diagnostics, airborne remote sensing, and related fields. To simultaneously achieve high spectral resolution and broadband detection, we innovatively proposed an on-chip filter spectrometer based on a silicon-on-insulator (SOI) waveguide platform. The spectrometer is constructed with four thermo-optically tunable multimode waveguide Bragg gratings (MM-WBGs) with slightly different periods, and the spectral reconstruction is completed using the reflection spectra of the fundamental modes. We analyzed the mechanism through which the incident spectrum of the fundamental mode is converted into the reflection spectra of multi-order even modes through the MM-WBG. By reducing the proportion of the fundamental-mode field distribution at the grating edges, we achieved a narrow-linewidth reflection spectrum. Meanwhile, the reflection spectra of the fundamental mode and higher-order modes exhibit significant center-wavelength spacing, which supports broadband operation. The performance of the on-chip spectrometer was characterized via thermo-optic modulation, with heating electrodes integrated on top of a single-order four-channel MM-WBG filter array. Spectral reconstruction experiments demonstrated a stable resolution better than 150 pm within a 35 nm operational bandwidth. Furthermore, we successfully explored a spiral-MM-WBG to improve spatial utilization efficiency on the waveguide platform and a narrow linewidth MM-WBG (∼40 pm) to enhance spectral resolution. This work presents an innovative approach for developing integrated spectral analysis chips with high resolution, broadband operation, and low complexity.
科研通智能强力驱动
Strongly Powered by AbleSci AI