多光谱图像
RGB颜色模型
光电探测器
光电子学
材料科学
光学
计算机科学
钙钛矿(结构)
遥感
人工智能
物理
地质学
工程类
化学工程
作者
Jiaxin Liu,Dawei Hu,Mingzhu Ni,Yousheng Zou,Yu Gu,Zeyao Han,Junyu Li,Yin He,Ze Zhang,Xiaobao Xu
标识
DOI:10.1021/acs.jpclett.2c00701
摘要
The multispectral fusion of near-infrared (NIR) and visible red–green–blue (RGB) photons can enhance target identification under weak light conditions. Nevertheless, the crosstalk between NIR and RGB photons in a traditional pixelated sensor impedes their practical application, while using complex algorithms and optical filters would significantly increase the cost, form factor, and frame latency. In this work, a delicate monolithic RGBN (RGB–NIR) multispectral photodetector (PD) is proposed on the basis of perovskite materials without complicated algorithms or optical filters. The multispectral response toward selective RGBN signals in this monolithic PD pixels can be achieved by switching the polarity of the applied bias, affording the following benefits: Ion/Ioff ratio of >104, detectivity of >1010 Jones, crosstalk of −74 dB, and fast response with −3 dB > 103 Hz. Moreover, proof-of-concept imaging of the iris and periocular with successful recognition in multispectral fusion further confirms its potential for identity authentication.
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