Threshold-Variation-Tolerant Coupling-Gate α-IGZO Synaptic Transistor for More Reliably Controllable Hardware Neuromorphic System

Dongyeon Kang, Jun Tae Jang, Shinyoung Park, Md Hasan Raza Ansari, Jong Ho Bae, Sung Jin Choi, Dong Myong Kim, Changwook Kim, Seongjae Cho, Dae Hwan Kim

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Hardware-oriented neuromorphic computing is gaining great deal of interest for highly parallel data processing and superb energy efficiency, as the candidate for replacement of conventional von Neumann computing. In this work, a novel synaptic transistor constructing the neuromorphic system is proposed, fabricated, and characterized. Amorphous indium-gallium-zinc-oxide ( $\alpha $ -IGZO) and Al2O3 are introduced as the channel and gate dielectric materials, respectively. Along with the high functionality and low-temperature processing viability, geometric peculiarity featuring extended gate structure improves the performances of the proposed transistor as synaptic component in the neuromorphic system. The insight into the substantial effect of optimal device structure design on energy efficiency is highlighted.

Original languageEnglish
Article number9400818
Pages (from-to)59345-59352
Number of pages8
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Hardware-oriented neuromorphic computing
  • amorphous indium-gallium-zinc-oxide
  • device structure design
  • energy efficiency
  • extended gate
  • parallel data processing
  • synaptic transistor

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