Flexible optoelectronic synaptic transistors for neuromorphic visual systems

Autor: Xiao Liu, Dongke Li, Yue Wang, Deren Yang, Xiaodong Pi
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: APL Machine Learning, Vol 1, Iss 3, Pp 031501-031501-17 (2023)
Druh dokumentu: article
ISSN: 2770-9019
DOI: 10.1063/5.0163926
Popis: 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.
Databáze: Directory of Open Access Journals
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