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Highly Stable Artificial Synapse Consisting of Low-Surface Defect van der Waals and Self-Assembled Materials

  • Seyong Oh
  • , Sooyoung Jung
  • , Muhammad Hasnain Ali
  • , Jeong Hoon Kim
  • , Hyeongjun Kim
  • , Jin Hong Park
  • Sungkyunkwan University
  • University of California at San Diego

Research output: Contribution to journalArticlepeer-review

Abstract

The long-term plasticity of biological synapses was successfully emulated in an artificial synapse fabricated by combining low-surface defect van der Waals (vdW) and self-assembled (SA) materials. The synaptic operation could be achieved by facilitating hole trapping and releasing only via the amine (NH2) functional groups in 3-aminopropyltriethoxysilane, which consequently induced a gradual conductance change in the WSe2 channel. The vdW-SA synaptic device exhibited extremely stable long-term potentiation/depression (LTP/LTD) characteristics; its dynamic range and nonlinearity reproduced near 100 and 3.13/-6.53 (for LTP/LTD) with relative standard deviations (RSDs) below 2%. Furthermore, after conducting training and recognition tasks for the Modified National Institute of Standard and Technology (MNIST) digit patterns, we verified that the maximum recognition rate was 78.3%, and especially, its RSD was as low as 0.32% over several training/recognition cycles. This study provides a background for future research on advanced artificial synapses based on vdW and organic materials.

Original languageEnglish
Pages (from-to)38299-38305
Number of pages7
JournalACS Applied Materials and Interfaces
Volume12
Issue number34
DOIs
StatePublished - 26 Aug 2020
Externally publishedYes

Keywords

  • APTES
  • artificial synapses
  • neuromorphic computing
  • pattern recognition
  • vdW materials

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