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Infrared-Light Visualization by Organic Upconversion Devices

delete2023-09-26
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PRE
AI
X
Xin Hu
G
Gui Xiao
Y
Yiwei Li
S
Shuo‐En Wu
陈倩 封面图
陈倩 (Qian Chen)
李
李宁 (Ning Li)
X
Xiubao Sui *
DOI:10.1021/acsaelm.3c00943delete
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摘要

摘要

En 中文
Infrared-light sensing has a wide range of applications covering artificial intelligence, biomedicine, surveillance, and defense. With the rapidly increasing demand for various infrared photodetectors, the conventional infrared imagers based on InGaAs, HgCdTe, superlattices, quantum wells, and so on are facing difficulties in realizing flexibility, room-temperature operationality, large area, and low price. This raises the demand for infrared materials, device structures, and operational principles. The upconversion-type imagers with the ability to convert low-energy infrared photons to high-energy visible photons have become an important infrared detection and imaging technique due to their compact device geometry and direct optical signal conversion capability. Upconversion-type imagers exhibit pixel-less imaging capability with large active areas, potentially very attractive for high-resolution infrared imaging applications. In this spotlight, we focus on recent advances in the upconversion technique based on organic semiconductors. We give much attention to the current structure design and physical mechanisms of such upconversion devices. The metrics and optoelectronic properties of these devices are discussed. Specifically, the potential of such a technology for applications is highlighted. Lastly, the limitations and challenges of the upconversion technique are discussed, providing perspectives to promote the upconversion-type infrared-light detection and imaging in the future.
Keyword:
Upconversion
Organic semiconductors
Infraredsensing
Imaging
Resolution

期刊

ACS Applied Electronic Materials 封面图
ACS Applied Electronic Materials
IF:
4.7
论文数:
5.0K
被引数:
1.4W

机构

H
Harbin Engineering University
学者数:
1.9W
论文数: 1.3W
被引数: 1.3W
University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 6.6K
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