Multisensory synapses based on FeO/graphene transistors for neuromorphic computing

Multisensory artificial synapses stimulated by multi-physical signals are highly pursued for their promising application prospects in biomimicry and artificial intelligence. An electric field and an optical field are the most effective stimuli for functional solid materials, due to their extraordina...

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Veröffentlicht in:Journal of materials chemistry. C, Materials for optical and electronic devices Materials for optical and electronic devices, 2023-06, Vol.11 (23), p.7732-7739
Hauptverfasser: Miao, Tingting, Liu, Weikang, Huang, Cungang, Cui, Bin, Chu, Ruiyue, Zhao, Xiangxiang, Wu, Xinyi, Wu, Shuyun, Xie, Jihao, Liu, Huiyang, Chen, Juan, Bin Cheng, Hu, Jifan
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container_issue 23
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container_title Journal of materials chemistry. C, Materials for optical and electronic devices
container_volume 11
creator Miao, Tingting
Liu, Weikang
Huang, Cungang
Cui, Bin
Chu, Ruiyue
Zhao, Xiangxiang
Wu, Xinyi
Wu, Shuyun
Xie, Jihao
Liu, Huiyang
Chen, Juan
Bin Cheng
Hu, Jifan
description Multisensory artificial synapses stimulated by multi-physical signals are highly pursued for their promising application prospects in biomimicry and artificial intelligence. An electric field and an optical field are the most effective stimuli for functional solid materials, due to their extraordinary potential in manipulating the electron band structure, spin ordering or even ion migration. Among them, the electric field induced reversible conductance regulations and ultraviolet light-induced ultrafast conductance changes are caused by proton migration under the ionic liquid gating effect and electron transition from the valence band to the conductance band, respectively. Here, we have realized synaptic behavior and logical operation in Fe 3 O 4 /graphene artificial synapses by using electrical and optical dual field regulation, which is of great significance for future artificial intelligence devices to recognize and make choices in complex systems. A three-layer artificial neural network consisting of Fe 3 O 4 /graphene synapses is built up to simulate handwritten digit recognition with high accuracy. Our work provides an intriguing opportunity for the development of multisensory artificial synapses with low energy consumption. Not only synaptic behaviors, but also logical operations are achieved by the optical and electrical stimulations, which provides a new arena for multi-field regulation and an opportunity for recognition and decision making in brain-like computing.
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title Multisensory synapses based on FeO/graphene transistors for neuromorphic computing
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