In-Sensor Visible and Mid-Infrared Dual-Band Perception and Computing

Abstract Machine vision in complex environments requires hardware that can integrate multispectral sensing with real-time front-end information processing. Visible light (VIS) and mid-infrared (MIR) signals provide complementary scene information, yet existing photodetectors cannot directly support VIS–MIR dual-band image processing at the sensor front end because their outputs are difficult to make both spectrally distinguishable and computation-compatible. Here, we report an electrically tunable lateral back-to-back dual-heterojunction device based on multilayer graphene/tungsten diselenide/black phosphorus for VIS–MIR dual-band in-sensor computing. The device exhibits electrically defined photoresponse states with spectrally distinguishable and bipolar characteristics, enabling simultaneous pattern recognition and spectral-band identification directly at the sensor level with 100% accuracy across three letter classes. It further supports dual-band in-sensor convolution in MIR-suppression and MIR-enhancement modes, allowing task-oriented modulation of MIR information while extracting VIS features. In addition, the device enables effective sensor-level suppression of VIS glare superimposed on MIR targets, improving downstream recognition accuracy from 33 to 98%. This work provides a device-level route toward task-oriented VIS–MIR information processing and efficient multispectral machine vision in complex environments.

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Publication Details

Journal
ACS Nano
Published
2026-09-14
DOI
https://doi.org/10.1021/acsnano.6c14007
Primary Topic
Transition Metal Oxide Nanomaterials
Type
article
Field-Weighted Citation Impact
0.00

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article

In-Sensor Visible and Mid-Infrared Dual-Band Perception and Computing

Shi Fang, Wenduo Chen, Qijie Wang, Jiayue Han et al.
ACS Nano
Transition Metal Oxide Nanomaterials
article

In-Sensor Visible and Mid-Infrared Dual-Band Perception and Computing

Shi Fang, Wenduo Chen, Qijie Wang, Jiayue Han, Ziyi Fu, Zhenhan Zhang, Lei Guo, Jun Wang, Fakun Wang, Gongyuan Zhang, Chao Han, Yadong Jiang
article en

Abstract

Abstract Machine vision in complex environments requires hardware that can integrate multispectral sensing with real-time front-end information processing. Visible light (VIS) and mid-infrared (MIR) signals provide complementary scene information, yet existing photodetectors cannot directly support VIS–MIR dual-band image processing at the sensor front end because their outputs are difficult to make both spectrally distinguishable and computation-compatible. Here, we report an electrically tunable lateral back-to-back dual-heterojunction device based on multilayer graphene/tungsten diselenide/black phosphorus for VIS–MIR dual-band in-sensor computing. The device exhibits electrically defined photoresponse states with spectrally distinguishable and bipolar characteristics, enabling simultaneous pattern recognition and spectral-band identification directly at the sensor level with 100% accuracy across three letter classes. It further supports dual-band in-sensor convolution in MIR-suppression and MIR-enhancement modes, allowing task-oriented modulation of MIR information while extracting VIS features. In addition, the device enables effective sensor-level suppression of VIS glare superimposed on MIR targets, improving downstream recognition accuracy from 33 to 98%. This work provides a device-level route toward task-oriented VIS–MIR information processing and efficient multispectral machine vision in complex environments.

ACS Nano
University of Electronic Science and Technology of China (CN), Nanyang Technological University (SG), Yanshan University (CN), Nanyang Institute of Technology (CN), Huazhong University of Science and Technology Hospital (CN), Huazhong University of Science and Technology (CN)
Agency for Science, Technology and Research, National Research Foundation Singapore, Ministry of Education - Singapore
Openalex Percentile: Top 23%
Transition Metal Oxide Nanomaterials
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