High-Resolution Multispectral Photovoltaic Imagers from Visible to Short-Wave Infrared

Wanqing Li; Cheng Bi; Min He; Xiaolong Zheng; Yuning Luo; Yimei Tan; Chenxi Liu; Salihuojia Talanti; Yanfei Liu; Ge Mu; Qun Hao; Kangkang Weng; Xin Tang

doi:10.1002/advs.202519991

High-Resolution Multispectral Photovoltaic Imagers from Visible to Short-Wave Infrared

Wanqing Li
, Cheng Bi
, Min He
, Xiaolong Zheng
, Yuning Luo
, Yimei Tan
, Chenxi Liu
, Salihuojia Talanti
, Yanfei Liu
, Ge Mu
, Qun Hao
, Kangkang Weng^*
, Xin Tang^*

^*此作品的通讯作者

光电学院

Beijing Institute of Technology
Ltd.
Changchun University of Science and Technology
Minzu University of China

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

Visible to short-wave infrared multispectral imaging is gaining significant attention across various fields, including agriculture, security, and medical diagnostics. Traditional multispectral imaging systems often rely on separate sensors for different spectral bands, leading to complex optical alignment and irreversible resolution loss. Here, we present hardware-algorithm co-designed architecture to achieve multispectral super-resolution imaging. Specifically, we demonstrate a monolithic quad-spectral photovoltaic imaging platform featuring a resolution of 640 × 512 pixels with <1% dead pixels per channel. The system achieves broadband spectral integration from visible to short-wave infrared (350–2350 nm) by combining an all-polymer bulk heterojunction with colloidal quantum dots within a single CMOS-compatible architecture. The compatibility of all-polymer bulk heterojunction with direct photopatterning allows for precise patterning and high-density integration, enabling the devices to operate efficiently in photovoltage mode. To address resolution degradation inherent in planar-integrated spectral sensing architectures, we applied a super-resolution reconstruction method, restoring images to a resolution of 640 × 512. The demonstrated capability to simultaneously capture and process multispectral data paves the way for CMOS integration, multispectral Imagers, organic photodetector, super-resolution reconstruction applications in diverse fields, from precision agriculture to medical diagnostics and beyond.

源语言	英语
期刊论文编号	e19991
期刊	Advanced Science
卷	13
期	18
DOI	https://doi.org/10.1002/advs.202519991
出版状态	已出版 - 27 3月 2026

访问文件

10.1002/advs.202519991

其它文件与链接

链接到 Scopus 的出版物

引用此

@article{f3db296dcce648f79ba77033f6907f45,

title = "High-Resolution Multispectral Photovoltaic Imagers from Visible to Short-Wave Infrared",

abstract = "Visible to short-wave infrared multispectral imaging is gaining significant attention across various fields, including agriculture, security, and medical diagnostics. Traditional multispectral imaging systems often rely on separate sensors for different spectral bands, leading to complex optical alignment and irreversible resolution loss. Here, we present hardware-algorithm co-designed architecture to achieve multispectral super-resolution imaging. Specifically, we demonstrate a monolithic quad-spectral photovoltaic imaging platform featuring a resolution of 640 {\texttimes} 512 pixels with <1\% dead pixels per channel. The system achieves broadband spectral integration from visible to short-wave infrared (350{\textendash}2350 nm) by combining an all-polymer bulk heterojunction with colloidal quantum dots within a single CMOS-compatible architecture. The compatibility of all-polymer bulk heterojunction with direct photopatterning allows for precise patterning and high-density integration, enabling the devices to operate efficiently in photovoltage mode. To address resolution degradation inherent in planar-integrated spectral sensing architectures, we applied a super-resolution reconstruction method, restoring images to a resolution of 640 {\texttimes} 512. The demonstrated capability to simultaneously capture and process multispectral data paves the way for CMOS integration, multispectral Imagers, organic photodetector, super-resolution reconstruction applications in diverse fields, from precision agriculture to medical diagnostics and beyond.",

keywords = "CMOS integration, multispectral imagers, organic photodetector, super-resolution reconstruction",

author = "Wanqing Li and Cheng Bi and Min He and Xiaolong Zheng and Yuning Luo and Yimei Tan and Chenxi Liu and Salihuojia Talanti and Yanfei Liu and Ge Mu and Qun Hao and Kangkang Weng and Xin Tang",

note = "Publisher Copyright: {\textcopyright} 2026 The Author(s). Advanced Science published by Wiley-VCH GmbH.",

year = "2026",

month = mar,

day = "27",

doi = "10.1002/advs.202519991",

language = "English",

volume = "13",

journal = "Advanced Science",

issn = "2198-3844",

publisher = "John Wiley and Sons Inc.",

number = "18",

}

TY - JOUR

T1 - High-Resolution Multispectral Photovoltaic Imagers from Visible to Short-Wave Infrared

AU - Li, Wanqing

AU - Bi, Cheng

AU - He, Min

AU - Zheng, Xiaolong

AU - Luo, Yuning

AU - Tan, Yimei

AU - Liu, Chenxi

AU - Talanti, Salihuojia

AU - Liu, Yanfei

AU - Mu, Ge

AU - Hao, Qun

AU - Weng, Kangkang

AU - Tang, Xin

PY - 2026/3/27

Y1 - 2026/3/27

N2 - Visible to short-wave infrared multispectral imaging is gaining significant attention across various fields, including agriculture, security, and medical diagnostics. Traditional multispectral imaging systems often rely on separate sensors for different spectral bands, leading to complex optical alignment and irreversible resolution loss. Here, we present hardware-algorithm co-designed architecture to achieve multispectral super-resolution imaging. Specifically, we demonstrate a monolithic quad-spectral photovoltaic imaging platform featuring a resolution of 640 × 512 pixels with <1% dead pixels per channel. The system achieves broadband spectral integration from visible to short-wave infrared (350–2350 nm) by combining an all-polymer bulk heterojunction with colloidal quantum dots within a single CMOS-compatible architecture. The compatibility of all-polymer bulk heterojunction with direct photopatterning allows for precise patterning and high-density integration, enabling the devices to operate efficiently in photovoltage mode. To address resolution degradation inherent in planar-integrated spectral sensing architectures, we applied a super-resolution reconstruction method, restoring images to a resolution of 640 × 512. The demonstrated capability to simultaneously capture and process multispectral data paves the way for CMOS integration, multispectral Imagers, organic photodetector, super-resolution reconstruction applications in diverse fields, from precision agriculture to medical diagnostics and beyond.

AB - Visible to short-wave infrared multispectral imaging is gaining significant attention across various fields, including agriculture, security, and medical diagnostics. Traditional multispectral imaging systems often rely on separate sensors for different spectral bands, leading to complex optical alignment and irreversible resolution loss. Here, we present hardware-algorithm co-designed architecture to achieve multispectral super-resolution imaging. Specifically, we demonstrate a monolithic quad-spectral photovoltaic imaging platform featuring a resolution of 640 × 512 pixels with <1% dead pixels per channel. The system achieves broadband spectral integration from visible to short-wave infrared (350–2350 nm) by combining an all-polymer bulk heterojunction with colloidal quantum dots within a single CMOS-compatible architecture. The compatibility of all-polymer bulk heterojunction with direct photopatterning allows for precise patterning and high-density integration, enabling the devices to operate efficiently in photovoltage mode. To address resolution degradation inherent in planar-integrated spectral sensing architectures, we applied a super-resolution reconstruction method, restoring images to a resolution of 640 × 512. The demonstrated capability to simultaneously capture and process multispectral data paves the way for CMOS integration, multispectral Imagers, organic photodetector, super-resolution reconstruction applications in diverse fields, from precision agriculture to medical diagnostics and beyond.

KW - CMOS integration

KW - multispectral imagers

KW - organic photodetector

KW - super-resolution reconstruction

UR - https://www.scopus.com/pages/publications/105028109130

U2 - 10.1002/advs.202519991

DO - 10.1002/advs.202519991

M3 - Article

AN - SCOPUS:105028109130

SN - 2198-3844

VL - 13

JO - Advanced Science

JF - Advanced Science

IS - 18

M1 - e19991

ER -

High-Resolution Multispectral Photovoltaic Imagers from Visible to Short-Wave Infrared

摘要

访问文件

其它文件与链接

学术指纹

引用此