Synaptic Barristor Based on Phase-Engineered 2D Heterostructures

Woong Huh, Seonghoon Jang, Jae Yoon Lee, Donghun Lee, Donghun Lee, Jung Min Lee, Hong Gyu Park, Jong Chan Kim, Hu Young Jeong, Gunuk Wang, Chul Ho Lee

Research output: Contribution to journalArticlepeer-review

131 Citations (Scopus)

Abstract

The development of energy-efficient artificial synapses capable of manifoldly tuning synaptic activities can provide a significant breakthrough toward novel neuromorphic computing technology. Here, a new class of artificial synaptic architecture, a three-terminal device consisting of a vertically integrated monolithic tungsten oxide memristor, and a variable-barrier tungsten selenide/graphene Schottky diode, termed as a ‘synaptic barrister,’ are reported. The device can implement essential synaptic characteristics, such as short-term plasticity, long-term plasticity, and paired-pulse facilitation. Owing to the electrostatically controlled barrier height in the ultrathin van der Waals heterostructure, the device exhibits gate-controlled memristive switching characteristics with tunable programming voltages of 0.2−0.5 V. Notably, by electrostatic tuning with a gate terminal, it can additionally regulate the degree and tuning rate of the synaptic weight independent of the programming impulses from source and drain terminals. Such gate tunability cannot be accomplished by previously reported synaptic devices such as memristors and synaptic transistors only mimicking the two-neuronal-based synapse. These capabilities eventually enable the accelerated consolidation and conversion of synaptic plasticity, functionally analogous to the synapse with an additional neuromodulator in biological neural networks.

Original languageEnglish
Article number1801447
JournalAdvanced Materials
Volume30
Issue number35
DOIs
Publication statusPublished - 2018 Aug 29

Bibliographical note

Funding Information:
W.H. and S.J. contributed equally to this work. This work was supported by the National Research Foundation (NRF) of Korea (2017R1D1A1B03035441, 2016R1C1B2007330, and 2017R1A5A1014862 (SRC Program: vdWMRC Center)), the KU-KIST School Project, and the Korea University Future Research Grant. C.-H.L. acknowledges the support from TJ Park Science Fellowship of POSCO TJ Park Foundation. G.W. acknowledges the support from Samsung Electronics. H.-G.P. acknowledges support from the NRF of Korea (2009-0081565). H.Y.J. acknowledges the support from Creative Materials Discovery Program (NRF-2016M3D1A1900035).

Funding Information:
W.H. and S.J. contributed equally to this work. This work was supported by the National Research Foundation (NRF) of Korea (2017R1D1A1B03035441, 2016R1C1B2007330, and 2017R1A5A1014862 (SRC Program: vdWMRC Center)), the KU-KIST School Project, and the Korea University Future Research Grant. C.-H.L. acknowledges the support from TJ Park Science Fellowship of POSCO TJ Park Foundation. G.W. acknowledges the support from Samsung Electronics. H.-G.P. acknowledges support from the NRF of Korea (2009-0081565). H.Y.J.

Publisher Copyright:
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Keywords

  • 2D materials
  • artificial synapse
  • barristor
  • heterostructure
  • memristor
  • neuromorphic application

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering

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