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Biological Spiking Synapse Constructed from Solution Processed Bimetal Core–Shell Nanoparticle Based Composites
Author(s) -
Zhou Li,
Mao JingYu,
Ren Yi,
Yang JiaQin,
Zhang ShiRui,
Zhou Ye,
Liao Qiufan,
Zeng YuJia,
Shan Haiquan,
Xu Zongxiang,
Fu Jingjing,
Wang Yan,
Chen Xiaoli,
Lv Ziyu,
Han SuTing,
Roy Vellaisamy A. L.
Publication year - 2018
Publication title -
small
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.785
H-Index - 236
eISSN - 1613-6829
pISSN - 1613-6810
DOI - 10.1002/smll.201800288
Subject(s) - neuromorphic engineering , materials science , bimetal , synapse , bistability , resistive random access memory , nanotechnology , nanoparticle , memristor , optoelectronics , computer science , artificial neural network , voltage , electronic engineering , neuroscience , electrical engineering , composite material , artificial intelligence , biology , engineering
Inspired by the highly parallel processing power and low energy consumption of the biological nervous system, the development of a neuromorphic computing paradigm to mimic brain‐like behaviors with electronic components based artificial synapses may play key roles to eliminate the von Neumann bottleneck. Random resistive access memory (RRAM) is suitable for artificial synapse due to its tunable bidirectional switching behavior. In this work, a biological spiking synapse is developed with solution processed Au@Ag core–shell nanoparticle (NP)‐based RRAM. The device shows highly controllable bistable resistive switching behavior due to the favorable Ag ions migration and filament formation in the composite film, and the good charge trapping and transport property of Au@Ag NPs. Moreover, comprehensive synaptic functions of biosynapse including paired‐pulse depression, paired‐pulse facilitation, post‐tetanic potentiation, spike‐time‐dependent plasticity, and the transformation from short‐term plasticity to long‐term plasticity are emulated. This work demonstrates that the solution processed bimetal core–shell nanoparticle‐based biological spiking synapse provides great potential for the further creation of a neuromorphic computing system.