Designing carbon conductive filament memristor devices for memory and electronic synapse applications

Electronic synaptic memristor systems have the potential to bring revolutionary change to traditional computer structures and to lay a solid foundation for the development of computer architectures simulating artificial brains. Among them, silver (Ag) or copper (Cu) filament-based memristor devices...

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Veröffentlicht in:Materials horizons 2020-04, Vol.7 (4), p.116-1114
Hauptverfasser: Zhou, Zhenyu, Zhao, Jianhui, Chen, Andy Paul, Pei, Yifei, Xiao, Zuoao, Wang, Gong, Chen, Jingsheng, Fu, Guangsheng, Yan, Xiaobing
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container_end_page 1114
container_issue 4
container_start_page 116
container_title Materials horizons
container_volume 7
creator Zhou, Zhenyu
Zhao, Jianhui
Chen, Andy Paul
Pei, Yifei
Xiao, Zuoao
Wang, Gong
Chen, Jingsheng
Fu, Guangsheng
Yan, Xiaobing
description Electronic synaptic memristor systems have the potential to bring revolutionary change to traditional computer structures and to lay a solid foundation for the development of computer architectures simulating artificial brains. Among them, silver (Ag) or copper (Cu) filament-based memristor devices have increasingly attracted attention due to their excellent functional properties in plasticity and as memristors. However, the randomly dynamic process of nucleation during device fabrication results in nonuniform switching parameters. Here, we demonstrate the viability of a high-performance neuromorphic memristor device based on a carbon conductive filament mechanism, with the advantages of high switching stability and low power consumption. The memristor is also able to emulate faithfully different functions of artificial synapses, including paired-pulse facilitation (PPF) and spike-timing-dependent plasticity (STDP). According to detailed electron energy loss spectroscopy (EELS) and transmission electron microscopy (TEM) characterization, it is confirmed that carbon conductive filaments are formed in aluminum nitride (AlN) films comprising the middle layer of the memristor. First principles calculations provide insight into the energetics of defects involved in the diffusion of carbon atoms into the AlN film. This work probes the viability of a new physical conduction mechanism for use in neuromorphic memristor performance, with evidence of improved device performance. Utilizing the instability of the edge atoms of graphene defects, carbon conductive filaments were formed under the regulation of the electric field and the synaptic function was achieved.
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First principles calculations provide insight into the energetics of defects involved in the diffusion of carbon atoms into the AlN film. This work probes the viability of a new physical conduction mechanism for use in neuromorphic memristor performance, with evidence of improved device performance. 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source Royal Society Of Chemistry Journals 2008-; Alma/SFX Local Collection
subjects Aluminum nitride
Carbon
Computer simulation
Conductivity
Copper
Diffusion
Electron energy loss spectroscopy
Electronic devices
Energy dissipation
Filaments
First principles
Mathematical analysis
Memory devices
Memristors
Nucleation
Plastic properties
Power consumption
Silver
Switching
Synapses
Viability
title Designing carbon conductive filament memristor devices for memory and electronic synapse applications
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