An RRAM with a 2D material embedded double switching layer for neuromorphic computing

Po An Chen, Rui Jing Ge, Jia Wei Lee, Chun Hsiang Hsu, Wei Chou Hsu, Deji Akinwande, Meng Hsueh Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Resistive random-access memory (RRAM) has shown great potential for neuromorphic engineering, due to its ability of emulating neural network and simple structure. To mimic the brain-learning behavior, two types of neural actions, short-term plasticity (STP) and long-term potentiation (LTP), should be imitated perfectly. In this work, we propose a unique RRAM cell with a double switching layer, in which a 2D material is embedded as a separation layer. Within a proper voltage range of stress, the mobile oxygen ions are blocked by the single atomic layer, and hence the subsequent relaxation of oxygen ions leads to a volatile switching characteristic. Owing to this volatile characteristic, the proposed device can mimic neural actions, STP and LTP, by a simple pulse train with different repetitions and frequencies without the complicated pulse settings of spike-timing-dependent plasticity (STDP). For various learning algorithms in future brain-inspired applications, different switching materials with different bind energies and relaxation times of oxygen ions can be utilized.

Original languageEnglish
Title of host publication2018 IEEE 13th Nanotechnology Materials and Devices Conference, NMDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538610169
DOIs
Publication statusPublished - 2019 Jan 8
Event13th IEEE Nanotechnology Materials and Devices Conference, NMDC 2018 - Portland, United States
Duration: 2018 Oct 142018 Oct 17

Publication series

Name2018 IEEE 13th Nanotechnology Materials and Devices Conference, NMDC 2018

Conference

Conference13th IEEE Nanotechnology Materials and Devices Conference, NMDC 2018
CountryUnited States
CityPortland
Period18-10-1418-10-17

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Surfaces, Coatings and Films
  • Instrumentation

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