CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Compact thermo-diffusion based physical memristor model
Authors
Andrew Adamatzky
Panagiotis Bousoulas
+8 more
Theodoros Panagiotis Chatzinikolaou
Iosif-Angelos Fyrigos
Stavros Kitsios
Vasileios Ntinas
Jose Antonio Rubio Sola
Georgios Ch. Sirakoulis
Michael-Antisthenis Tsompanas
Dimitris Tsoukalas
Publication date
1 January 2022
Publisher
'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The threshold switching effect is critical in memristor devices for a range of applications, from crossbar design reliability to simulating neuromorphic features using artificial neural networks. The rich inherit dynamics of a metallic conductive filament (CF) formation are thought to be linked to this characteristic. Simulating these dynamics is necessary to develop an accurate memristor model. In this work we present a compact memristor model that utilizes the drift, diffusion and thermo-diffusion effects. These three effects are taken into consideration to derive the switching behavior of a memristor. The resistance of a memristor is calculated based on the evolution of a truncated cone shaped filament. The objective of this model is to achieve a realistic integration of switching mechanisms of the memristor device, while minimizing the overhead on computing resources and being compatible with circuit design tools. The model incorporates the effect of thermo-diffusion on the switching pattern, providing a different perception of the ionic transport processes, which enable the unipolar switching. SPICE simulation results provide an exact match with experimental results of Metal-Insulator-Metal (MIM) memristive devices of Ag/Si2/SiO2.07/Pt nanoparticles (NPs) configuration.Peer ReviewedPostprint (published version
Similar works
Full text
Available Versions
UPCommons. Portal del coneixement obert de la UPC
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:upcommons.upc.edu:2117/381...
Last time updated on 17/02/2023