Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Toward photodetection at 2 μm wavelength band: GeSn/Ge multiple-quantum-well photodetectors integrated on Si substrates

Not Accessible

Your library or personal account may give you access

Abstract

Optical detection at 2-μm wavelength spectral range has recently attracted increasing attention for many important applications. This can be done using narrow-bandgap III-V or II-VI based semiconductor photodetectors (PDs). Here, we report on group-IV based GeSn/Ge multiple-quantum-well (MQW) photoconductive photodetectors (PDs) for optical detection at the 2μm wavelength band. By introducing Sn into the well, the direct bandgap is reduced, thereby extending the absorption edge into longer wavelengths. The optical responsivity measurements reveal that the detection of the fabricated PDs is extended beyond 2000 nm. These results demonstrate the feasibility of GeSn/Ge MQW PDs for optical detection at the 2μm wavelength band.

© 2017 Japan Society of Applied Physics, Optical Society of America

PDF Article
More Like This
Pseudomorphic GeSn/Ge Multiple-quantum-well on Silicon for Photo Detection and Modulation at 2 µm Wavelength Range

Shengqiang Xu, Wei Wang, Yuan Dong, Yi-Chiau Huang, Saeid Masudy-Panah, Hong Wang, Xiao Gong, and Yee-Chia Yeo
Th2A.10 Optical Fiber Communication Conference (OFC) 2019

High-efficiency photo detection at 2 µm realized by GeSn/Ge multiple-quantum-well photodetectors with photon-trapping microstructure

Hao Zhou, Shengqiang Xu, Yiding Lin, Yi-Chiau Huang, Bongkwon Son, Wei Li, Xin Guo, Lin Liu, Kwang Hong Lee, Xiao Gong, and Chuan Seng Tan
STh4L.1 CLEO: Science and Innovations (CLEO:S&I) 2020

Ge0.9Sn0.1 multiple-quantum-well p-i-n photodiodes for optical communications at 2 μm

Yuan Dong, Wei Wang, Shengqiang Xu, Dian Lei, Xiao Gong, Shuh Ying Lee, Wan Khai Loke, Soon-Fatt Yoon, Gengchiau Liang, and Yee-Chia Yeo
Th1A.4 Optical Fiber Communication Conference (OFC) 2017

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.