Type-printable photodetector arrays for multichannel meta-infrared imaging

Junxiong Guo (), Shuyi Gu, Lin Lin, Yu Liu (), Ji Cai, Hongyi Cai, Yu Tian, Yuelin Zhang, Qinghua Zhang, Ze Liu, Yafei Zhang, Xiaosheng Zhang, Yuan Lin, Wen Huang (), Lin Gu and Jinxing Zhang ()
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Junxiong Guo: Chengdu University
Shuyi Gu: Chengdu University
Lin Lin: University of Electronic Science and Technology of China
Yu Liu: Tsinghua University
Ji Cai: Chengdu University
Hongyi Cai: Chengdu University
Yu Tian: Beijing Normal University
Yuelin Zhang: Beijing Normal University
Qinghua Zhang: Beijing National Laboratory of Condensed Matter Physics
Ze Liu: Chengdu University
Yafei Zhang: Chengdu University
Xiaosheng Zhang: University of Electronic Science and Technology of China
Yuan Lin: University of Electronic Science and Technology of China
Wen Huang: University of Electronic Science and Technology of China
Lin Gu: Tsinghua University
Jinxing Zhang: Beijing Normal University

Nature Communications, 2024, vol. 15, issue 1, 1-9

Abstract: Abstract Multichannel meta-imaging, inspired by the parallel-processing capability of neuromorphic computing, offers considerable advancements in resolution enhancement and edge discrimination in imaging systems, extending even into the mid- to far-infrared spectrum. Currently typical multichannel infrared imaging systems consist of separating optical gratings or merging multi-cameras, which require complex circuit design and heavy power consumption, hindering the implementation of advanced human-eye-like imagers. Here, we present printable graphene plasmonic photodetector arrays driven by a ferroelectric superdomain for multichannel meta-infrared imaging with enhanced edge discrimination. The fabricated photodetectors exhibited multiple spectral responses with zero-bias operation by directly rescaling the ferroelectric superdomain instead of reconstructing the separated gratings. We also demonstrated enhanced and faster shape classification (98.1%) and edge detection (98.2%) using our multichannel infrared images compared with single-channel detectors. Our proof-of-concept photodetector arrays simplify multichannel infrared imaging systems and offer potential solutions in efficient edge detection in human-brain-type machine vision.

Date: 2024
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DOI: 10.1038/s41467-024-49592-4

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