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Manufacturing of graphene based synaptic devices for optoelectronic applications
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Manufacturing of graphene based synaptic devices for optoelectronic applications
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Journal Article
Manufacturing of graphene based synaptic devices for optoelectronic applications
2023
Overview
Neuromorphic computing systems can perform memory and computing tasks in parallel on artificial synaptic devices through simulating synaptic functions, which is promising for breaking the conventional von Neumann bottlenecks at hardware level. Artificial optoelectronic synapses enable the synergistic coupling between optical and electrical signals in synaptic modulation, which opens up an innovative path for effective neuromorphic systems. With the advantages of high mobility, optical transparency, ultrawideband tunability, and environmental stability, graphene has attracted tremendous interest for electronic and optoelectronic applications. Recent progress highlights the significance of implementing graphene into artificial synaptic devices. Herein, to better understand the potential of graphene-based synaptic devices, the fabrication technologies of graphene are first presented. Then, the roles of graphene in various synaptic devices are demonstrated. Furthermore, their typical optoelectronic applications in neuromorphic systems are reviewed. Finally, outlooks for development of synaptic devices based on graphene are proposed. This review will provide a comprehensive understanding of graphene fabrication technologies and graphene-based synaptic device for optoelectronic applications, also present an outlook for development of graphene-based synaptic device in future neuromorphic systems. Fabrication technologies for graphene, including synthesis, transfer and patterning are discussed. The roles of graphene in synaptic devices (memristors and synaptic transistors) are reviewed. Recent emerging optoelectronic applications of graphene-based synaptic devices are introduced. Challenges and future perspectives for graphene-based synaptic device in optoelectronic neuromorphic application are outlined.
Publisher
IOP Publishing
