Literature DB >> 32052957

Artificial Synapse Based on van der Waals Heterostructures with Tunable Synaptic Functions for Neuromorphic Computing.

Congli He1, Jian Tang2,3, Da-Shan Shang4, Jianshi Tang5,6, Yue Xi5, Shuopei Wang2,3,7, Na Li2,3, Qingtian Zhang5, Ji-Kai Lu4, Zheng Wei2,3, Qinqin Wang2,3, Cheng Shen2,3, Jiawei Li2,3, Shipeng Shen1, Jianxin Shen1, Rong Yang2,3,8,7, Dongxia Shi2,3,8,7, Huaqiang Wu5,6, Shouguo Wang1, Guangyu Zhang2,3,8,7.   

Abstract

Two-dimensional (2D) materials and van der Waals heterostructures have attracted tremendous attention because of their appealing electronic, mechanical, and optoelectronic properties, which offer the possibility to extend the range of functionalities for diverse potential applications. Here, we fabricate a novel multiterminal device with dual-gate based on 2D material van der Waals heterostructures. Such a multiterminal device exhibited excellent nonvolatile multilevel resistance switching performance controlled by the source-drain voltage and back-gate voltage. Based on these features, heterosynaptic plasticity, in which the synaptic weight can be tuned by another modulatory interneuron, has been mimicked. A tunable analogue weight update (both on/off ratio and update nonlinearity) of synapse with high speed (50 ns) and low energy (∼7.3 fJ) programming has been achieved. These results demonstrate the great potential of the artificial synapse based on van der Waals heterostructures for neuromorphic computing.

Entities:  

Keywords:  2D materials; MoS2; artificial synapse; dual-gate; neuromorphic computing; van der Waals heterostructures

Year:  2020        PMID: 32052957     DOI: 10.1021/acsami.9b21747

Source DB:  PubMed          Journal:  ACS Appl Mater Interfaces        ISSN: 1944-8244            Impact factor:   9.229


  2 in total

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Authors:  C Kaspar; B J Ravoo; W G van der Wiel; S V Wegner; W H P Pernice
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2.  Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing.

Authors:  Dmitry Kireev; Samuel Liu; Harrison Jin; T Patrick Xiao; Christopher H Bennett; Deji Akinwande; Jean Anne C Incorvia
Journal:  Nat Commun       Date:  2022-07-28       Impact factor: 17.694

  2 in total

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