All-Inorganic Lead-Free Cs₂AgBiBr₆/ZnO Artificial Retina Synapse Based on Photoelectric Synergistic Dual-Mechanism for Neuromorphic Computing
Zhenpeng Cheng
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorTianle Wang
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorJunyan Zhu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorYaqi He
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorShijie Liu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorCorresponding Author
Ming-Yu Li
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
E-mail: [email protected]; [email protected]; [email protected]
Search for more papers by this authorHaifei Lu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorXiaoyan Wen
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorJihoon Lee
Department of Electronic Engineering, College of Electronics and Information, Kwangwoon University, Nowon-gu, Seoul, 01897 Republic of Korea
Search for more papers by this authorCorresponding Author
Sisi Liu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
E-mail: [email protected]; [email protected]; [email protected]
Search for more papers by this authorCorresponding Author
Sui Mao
Institute of Hybrid Materials, National Center of International Research for Hybrid Materials Technology, National Base of International Science & Technology Cooperation, College of Materials Science and Engineering, Qingdao University, Qingdao, 266071 China
E-mail: [email protected]; [email protected]; [email protected]
Search for more papers by this authorZhenpeng Cheng
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorTianle Wang
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorJunyan Zhu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorYaqi He
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorShijie Liu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorCorresponding Author
Ming-Yu Li
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
E-mail: [email protected]; [email protected]; [email protected]
Search for more papers by this authorHaifei Lu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorXiaoyan Wen
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
Search for more papers by this authorJihoon Lee
Department of Electronic Engineering, College of Electronics and Information, Kwangwoon University, Nowon-gu, Seoul, 01897 Republic of Korea
Search for more papers by this authorCorresponding Author
Sisi Liu
School of Physics and Mechanics, Wuhan University of Technology, Wuhan, 430070 China
E-mail: [email protected]; [email protected]; [email protected]
Search for more papers by this authorCorresponding Author
Sui Mao
Institute of Hybrid Materials, National Center of International Research for Hybrid Materials Technology, National Base of International Science & Technology Cooperation, College of Materials Science and Engineering, Qingdao University, Qingdao, 266071 China
E-mail: [email protected]; [email protected]; [email protected]
Search for more papers by this authorAbstract
Adaptive learning capability of optoelectronic synaptic hardware holds promising application prospects in next generation artificial intelligence, and the development of biometric retina perception is sternly hampered by three crucial issues, including well-balance between excitatory and inhibitory, non-volatile multi-state storage, and optimal energy consumption. In this work, a novel Cs2AgBiBr6/ZnO non-volatile optoelectronic synapse is proposed and successfully programmed with optical excitatory and electronic inhibitory in the light of dual-mechanism: Lead-free perovskite Cs2AgBiBr6 guarantees abundant photogenerated carrier concentration, and the process of carrier capture and release occurs in ZnO layer, which can collaboratively modulate various synaptic plasticity behaviors depending on distinct stimulus. Consequently, multi-bit storage is attained with the dual-mechanism non-volatile memory (DNVM) as a function of consecutive light spikes. The energy consumption of the DNVM is 1.85 nJ at a single light spike, and an ultra-low one of 13.8 fJ is triggered with a single electrical pulse, which approximatively meets the requirement of the biological synaptic event energy consumption. The performance of the DNVM is further evaluated with the Pavlov's classical conditioning experiment and visual hardware system, offering an exciting paradigm for implementing on-chip adaptive visual perception and neuromorphic computing.
Conflict of Interest
The authors declare no conflict of interest.
Open Research
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Supporting Information
| Filename | Description |
|---|---|
| smll202411129-sup-0001-SuppMat.docx2 MB | Supporting Information |
| smll202411129-sup-0002-VideoS1.mp436 MB | Supplemental Video 1 |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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