English

A PMT-like high gain avalanche photodiode based on GaN/AlN periodical stacked structure

Instrumentation and Detectors 2017-01-04 v1 Optics

Abstract

Avalanche photodiode (APD) has been intensively investigated as a promising candidate to replace photomultiplier tubes (PMT) for weak light detection. However, in conventional APDs, a large portion of carrier energy drawn from the electric field is thermalized, and the multiplication efficiencies of electron and hole are low and close. In order to achieve high gain, the device should work under breakdown bias, where carrier multiplication proceeds bi-directionally to form a positive feedback multiplication circle. However, breakdown is hard to control, in practice, APDs should work under Geiger mode as a compromise between sustainable detection and high gain. The complexity of system seriously restricts the application. Here, we demonstrate an avalanche photodiode holding high gain without breakdown, which means no quenching circuit is needed for sustainable detection. The device is based on a GaN/AlN periodically-stacked-structure (PSS), wherein electron holds much higher efficiency than hole to draw energy from the electric field, and avalanche happens uni-directionally with high efficiency. and a recorded high gain (10^4) tested under constant bias is obtained in a prototype device, wherein the stable gain can be determined by the periodicity of the GaN/AlN PSS. This work not only brings a new light into avalanche multiplication mechanism, but also paves a technological path with high commercial value to realize highly sensitive avalanche devices working under constant bias like PMT.

Keywords

Cite

@article{arxiv.1608.00561,
  title  = {A PMT-like high gain avalanche photodiode based on GaN/AlN periodical stacked structure},
  author = {Ji-yuan Zheng and Lai Wang and Di Yang and Jia-dong Yu and Xiao Meng and Yan-xiong E and Chao Wu and Zhi-biao Hao and Chang-zheng Sun and Bing Xiong and Yi Luo and Yan-jian Han and Jian Wang and Hong-tao Li and Julien Brault and Samuel Matta and Mohamed Al Khalfioui and Jian-chang Yan and Tong-bo Wei and Yun Zhang and Jun-xi Wang},
  journal= {arXiv preprint arXiv:1608.00561},
  year   = {2017}
}