Field Effect Transistor-Type Devices Using High-κ Gate Insulator Stacks for Neuromorphic Applications

Min Kyu Park, Ho Nam Yoo, Young Tak Seo, Sung Yun Woo, Jong Ho Bae, Byung Gook Park, Jong Ho Lee

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

With ability to process data in an energy-efficient way, neuromorphic computing is suggested to overcome the issues of a traditional von Neumann computing system. Neuromorphic computing is composed of two crucial features of neurons and synapses, in which neurons integrate all the charges while synapses retain these charges. In this paper, we fabricate and analyze devices for mimicking neurons and synapses in a single Si-based metal-oxide-semiconductor field-effect transistor (MOSFET) structure. We fabricate and analyze Al2O3/Si3N4 (A/N) and Al2O3/HfO2/Si3N4/SiO2 (A/H/N/O) devices to suggest that an A/N device could be used as a neuron device due to its fast charge emission characteristics, while the A/H/N/O device could be used as a synaptic device as added tunneling SiO2 causes the device to retain its charges for a long-period of time. We suggest the possibility of fabricating both neurons and synapses by adopting different gate insulator stack structures in MOSFETs.

Original languageEnglish
Pages (from-to)323-328
Number of pages6
JournalACS Applied Electronic Materials
Volume2
Issue number2
DOIs
StatePublished - 25 Feb 2020

Keywords

  • field-effect transistor
  • HfO
  • high-κ
  • neuromorphic computing
  • neuron device
  • retention
  • SiN
  • synaptic device

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