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Robust Ag/ZrO2/WS2/Pt Memristor for Neuromorphic Computing.

Xiaobing Yan1,2, Cuiya Qin1, Chao Lu3

  • 1National-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices, Machine Vision Engineering Technology Center of Hebei Province, Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electron and Information Engineering , Hebei University , Baoding 071002 , P. R. China.

ACS Applied Materials & Interfaces
|December 3, 2019
PubMed
Summary

Researchers developed a novel Ag/ZrO2/WS2/Pt memristor device (MD) using a 2D material and oxide double-layer structure. This 2D material and oxide double-layer memristor device (2DOMD) significantly enhances resistive random-access memory (RRAM) reliability and performance for neuromorphic computing.

Keywords:
WS2 nanosheetsartificial synapsememristorneuromorphic computingresistive switching (RS)

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Electrical Engineering

Background:

  • Resistive random-access memory (RRAM) is crucial for the information age but suffers from reliability issues due to conductive filament (CF) randomness.
  • Existing memristor devices (MDs) require improved stability and performance for advanced applications.

Purpose of the Study:

  • To introduce a novel 2D material and oxide double-layer memristor device (2DOMD) for enhanced RRAM reliability.
  • To investigate the memristive switching characteristics and neuromorphic capabilities of the Ag/ZrO2/WS2/Pt structure.

Main Methods:

  • Fabrication of a novel Ag/ZrO2/WS2/Pt memristor device incorporating a 2D WS2 nanosheet layer.
  • Characterization of electrochemical metallization switching, speed, endurance, and voltage distribution.
  • Neuromorphic simulations using the MNIST dataset to evaluate synaptic functions and plasticity.

Main Results:

  • The 2DOMD demonstrated highly stable switching, concentrated voltage distribution, high speed (~10 ns), and robust endurance (>10^9 cycles).
  • The bilayer structure effectively limited CF rupture/rejuvenation to the interface, reducing randomness and improving reliability compared to single-layer devices.
  • Successful achievement of biosynaptic functions, including spike-timing-dependent plasticity and paired-pulse facilitation, was confirmed.

Conclusions:

  • The developed 2D material and oxide double-layer memristor device significantly enhances RRAM reliability and performance.
  • This approach offers a promising pathway for developing advanced artificial synapses for future brain-enhanced computing systems.