Retina‐Inspired Self‐Powered Artificial Optoelectronic Synapses with Selective Detection in Organic Asymmetric Heterojunctions
Abstract: The retina, the most crucial unit of the human visual perception system, combines sensing with wavelength selectivity and signal preprocessing. Incorporating energy conversion into these superior neurobiological features to generate core visual signals directly from incoming light under various conditions is essential for artificial optoelectronic synapses to emulate biological processing in the real retina. Herein, self‐powered optoelectronic synapses that can selectively detect and preprocess the ultraviolet (UV) light are presented, which benefit from high‐quality organic asymmetric heterojunctions with ultrathin molecular semiconducting crystalline films, intrinsic heterogeneous interfaces, and typical photovoltaic properties. These devices exhibit diverse synaptic behaviors, such as excitatory postsynaptic current, paired‐pulse facilitation, and high‐pass filtering characteristics, which successfully reproduce the unique connectivity among sensory neurons. These zero‐power optical‐sensing synaptic operations further facilitate a demonstration of image sharpening. Additionally, the charge transfer at the heterojunction interface can be modulated by tuning the gate voltage to achieve multispectral sensing ranging from the UV to near‐infrared region. Therefore, this work sheds new light on more advanced retinomorphic visual systems in the post‐Moore era.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Retina‐Inspired Self‐Powered Artificial Optoelectronic Synapses with Selective Detection in Organic Asymmetric Heterojunctions ; day:12 ; month:01 ; year:2022 ; extent:9
Advanced science ; (12.01.2022) (gesamt 9)
- Urheber
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Hao, Ziqian
Wang, Hengyuan
Jiang, Sai
Qian, Jun
Xu, Xin
Li, Yating
Pei, Mengjiao
Zhang, Bowen
Guo, Jianhang
Zhao, Huijuan
Chen, Jiaming
Tong, Yunfang
Wang, Jianpu
Wang, Xinran
Shi, Yi
Li, Yun
- DOI
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10.1002/advs.202103494
- URN
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urn:nbn:de:101:1-2022011314211115603254
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:29 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Hao, Ziqian
- Wang, Hengyuan
- Jiang, Sai
- Qian, Jun
- Xu, Xin
- Li, Yating
- Pei, Mengjiao
- Zhang, Bowen
- Guo, Jianhang
- Zhao, Huijuan
- Chen, Jiaming
- Tong, Yunfang
- Wang, Jianpu
- Wang, Xinran
- Shi, Yi
- Li, Yun
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