Published November 2021 | Version v1
Journal article

Pulse frequency dependent synaptic characteristics in Ta/SiN/Si memristor device for neuromorphic system

  • 1. Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, South (Korea, Republic of)
  • 2. Department of Electronic Engineering, Korea National University of Transportation, Chungju-si, Chungbuk 27469, South (Korea, Republic of)

Description

Highlights: • We fabricated the memristor device stacked with Ta/SiN/Si. • Homogeneous and filamentary resistive switching type is investigated for neuromorphic system. • Pulse frequency dependent synaptic plasticity is studied. • Potentiation and depression is compared between two modes. -- Abstract: We compare the filamentary resistive switching and the homogeneous resistive switching of the Ta/SiN/Si memristor device for the implementation of hardware-based neuromorphic system. The switching mode can be determined by the first switching curve. The low-resistance state (LRS) of filamentary resistive switching has stable retention properties without the resistance degradation, indicating the existence of different switching mechanisms between two. In homogeneous resistive switching mode, a more gradual increase and decrease in conductance control is possible. The multi-level states property provides better performance of pattern recognition when applied to neural network model. Finally, we demonstrate the improved frequency dependent conductance modulation in homogeneous resistive switching mode.

Additional details

Identifiers

DOI
10.1016/j.jallcom.2021.160760;
PII
S0925838821021691;

Publishing Information

Journal Title
Journal of Alloys and Compounds
Journal Volume
882
Journal Page Range
vp.
ISSN
0925-8388
CODEN
JALCEU

INIS

Country of Publication
Switzerland
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55048011
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; S74: ATOMIC AND MOLECULAR PHYSICS;
Descriptors DEI
FREQUENCY DEPENDENCE; MODULATION; NEURAL NETWORKS; PATTERN RECOGNITION; PERFORMANCE; PLASTICITY; PULSES; SILICON NITRIDES
Descriptors DEC
MECHANICAL PROPERTIES; NITRIDES; NITROGEN COMPOUNDS; PNICTIDES; SILICON COMPOUNDS

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.