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A novel artificial synapse with dual modes using bilayer graphene as the bottom electrode

Resistive Random Access Memory (RRAM) shows great potential to be used as an artificial synapse for neuromorphic applications. The resistance can be gradually reduced during reset, which can enable enough states to mimic the "forgetting" process. However, the abrupt set (Mode I) cannot gen...

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Published in:Nanoscale 2017-07, Vol.9 (27), p.9275-9283
Main Authors: Tian, He, Mi, Wentian, Zhao, Haiming, Mohammad, Mohammad Ali, Yang, Yi, Chiu, Po-Wen, Ren, Tian-Ling
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cited_by cdi_FETCH-LOGICAL-c287t-657c0e774c38d15a188937981a2f8a522abbd61c736140015cf9e137daa03d963
cites cdi_FETCH-LOGICAL-c287t-657c0e774c38d15a188937981a2f8a522abbd61c736140015cf9e137daa03d963
container_end_page 9283
container_issue 27
container_start_page 9275
container_title Nanoscale
container_volume 9
creator Tian, He
Mi, Wentian
Zhao, Haiming
Mohammad, Mohammad Ali
Yang, Yi
Chiu, Po-Wen
Ren, Tian-Ling
description Resistive Random Access Memory (RRAM) shows great potential to be used as an artificial synapse for neuromorphic applications. The resistance can be gradually reduced during reset, which can enable enough states to mimic the "forgetting" process. However, the abrupt set (Mode I) cannot generate enough states to mimic the "learning" process, which results in depression-only behavior. In this work, we introduce another mode (Mode II) in an Al/AlO /graphene 'RRAM' stack by using oxygen vacancies as trapping centers and bottom electrode bilayer graphene as the channel material. In this way, since the pulse can gradually create the oxygen vacancies, post-synaptic current (PSC) can be gradually potentiated or depressed. By introducing Mode II, we can realize 166 potentiation states, which is higher than the previously reported conventional RRAM with insufficient potentiation states due to the abrupt set. Moreover, Mode II can help realize an inhibitory synapse. By combining modes I and II, we can realize both excitatory and inhibitory synapses in a single device. This work shows great potential to enable neuromorphic computations with greater learning and reconfigurability.
doi_str_mv 10.1039/c7nr03106h
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title A novel artificial synapse with dual modes using bilayer graphene as the bottom electrode
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