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