Flexible optoelectronic synaptic transistors for neuromorphic visual systems
Neuromorphic visual systems that integrate the functionalities of sensing, memory, and processing are expected to overcome the shortcomings of conventional artificial visual systems, such as data redundancy, data access delay, and high-energy consumption. Neuromorphic visual systems based on emergin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-09-01
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| Series: | APL Machine Learning |
| Online Access: | http://dx.doi.org/10.1063/5.0163926 |
| _version_ | 1797635475958136832 |
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| author | Xiao Liu Dongke Li Yue Wang Deren Yang Xiaodong Pi |
| author_facet | Xiao Liu Dongke Li Yue Wang Deren Yang Xiaodong Pi |
| author_sort | Xiao Liu |
| collection | DOAJ |
| description | Neuromorphic visual systems that integrate the functionalities of sensing, memory, and processing are expected to overcome the shortcomings of conventional artificial visual systems, such as data redundancy, data access delay, and high-energy consumption. Neuromorphic visual systems based on emerging flexible optoelectronic synaptic devices have recently opened up innovative applications, such as robot visual perception, visual prosthetics, and artificial intelligence. Various flexible optoelectronic synaptic devices have been fabricated, which are either two-terminal memristors or three-terminal transistors. In flexible optoelectronic synaptic transistors (FOSTs), the synaptic weight can be modulated by the electricity and light synergistically, which endows the neuromorphic visual systems with versatile functionalities. In this Review, we present an overview of the working mechanisms, device structures, and active materials of FOSTs. Their applications in neuromorphic visual systems for color recognition, image recognition and memory, motion detection, and pain perception are presented. Perspectives on the development of FOSTs are finally outlined. |
| first_indexed | 2024-03-11T12:22:27Z |
| format | Article |
| id | doaj.art-2b72aa7c6e6d4c0cbdfe755fe0a0b46f |
| institution | Directory Open Access Journal |
| issn | 2770-9019 |
| language | English |
| last_indexed | 2024-03-11T12:22:27Z |
| publishDate | 2023-09-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | APL Machine Learning |
| spelling | doaj.art-2b72aa7c6e6d4c0cbdfe755fe0a0b46f2023-11-06T21:29:45ZengAIP Publishing LLCAPL Machine Learning2770-90192023-09-0113031501031501-1710.1063/5.0163926Flexible optoelectronic synaptic transistors for neuromorphic visual systemsXiao Liu0Dongke Li1Yue Wang2Deren Yang3Xiaodong Pi4Institute of Carbon Neutrality and New Energy, School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310018, ChinaInstitute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices, ZJU-Hangzhou Global Scientific and Technological Innovation Center; State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, ChinaInstitute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices, ZJU-Hangzhou Global Scientific and Technological Innovation Center; State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, ChinaInstitute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices, ZJU-Hangzhou Global Scientific and Technological Innovation Center; State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, ChinaInstitute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices, ZJU-Hangzhou Global Scientific and Technological Innovation Center; State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, ChinaNeuromorphic visual systems that integrate the functionalities of sensing, memory, and processing are expected to overcome the shortcomings of conventional artificial visual systems, such as data redundancy, data access delay, and high-energy consumption. Neuromorphic visual systems based on emerging flexible optoelectronic synaptic devices have recently opened up innovative applications, such as robot visual perception, visual prosthetics, and artificial intelligence. Various flexible optoelectronic synaptic devices have been fabricated, which are either two-terminal memristors or three-terminal transistors. In flexible optoelectronic synaptic transistors (FOSTs), the synaptic weight can be modulated by the electricity and light synergistically, which endows the neuromorphic visual systems with versatile functionalities. In this Review, we present an overview of the working mechanisms, device structures, and active materials of FOSTs. Their applications in neuromorphic visual systems for color recognition, image recognition and memory, motion detection, and pain perception are presented. Perspectives on the development of FOSTs are finally outlined.http://dx.doi.org/10.1063/5.0163926 |
| spellingShingle | Xiao Liu Dongke Li Yue Wang Deren Yang Xiaodong Pi Flexible optoelectronic synaptic transistors for neuromorphic visual systems APL Machine Learning |
| title | Flexible optoelectronic synaptic transistors for neuromorphic visual systems |
| title_full | Flexible optoelectronic synaptic transistors for neuromorphic visual systems |
| title_fullStr | Flexible optoelectronic synaptic transistors for neuromorphic visual systems |
| title_full_unstemmed | Flexible optoelectronic synaptic transistors for neuromorphic visual systems |
| title_short | Flexible optoelectronic synaptic transistors for neuromorphic visual systems |
| title_sort | flexible optoelectronic synaptic transistors for neuromorphic visual systems |
| url | http://dx.doi.org/10.1063/5.0163926 |
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