Journal of Computational Electronics

, Volume 16, Issue 4, pp 1095–1120 | Cite as

\({ SIM}^2{ RRAM}\): a physical model for RRAM devices simulation

  • Marco A. Villena
  • Juan B. Roldán
  • Francisco Jiménez-Molinos
  • Enrique Miranda
  • Jordi Suñé
  • Mario Lanza
S.I.: Computational Electronics of Emerging Memory Elements
  • 245 Downloads

Abstract

In the last few years, resistive random access memory (RRAM) has been proposed as one of the most promising candidates to overcome the current Flash technology in the market of non-volatile memories. These devices have the ability to change their resistance state in a reversible and controlled way applying an external voltage. In this way, the resulting high- and low-resistance states allow the electrical representation of the binary states “0” and “1” without storing charge. Many physical models have been developed with the aim of understanding the mechanisms that control the resistive switching. In this work, we have compiled the main theories accepted as well as their corresponding models for the conduction characteristics. In addition, simulation tools play a very important role in the task of checking these theories and understanding these mechanisms. For this reason, the simulation tool called \(\hbox {SIM}^{2}\hbox {RRAM}\) has been presented. This simulator is capable of replicating the global behavior of RRAM cell based on \(\hbox {HfO}_{x}\).

Keywords

RRAM Resistive switching Memristor Simulation Physical modeling 

Abbreviations

BD

Dielectric breakdown

CAFM

Conductive atomic force microscopy

CBRAM

Conductive bridge RAM

CF

Conductive filament

ECM-RRAM

Electrochemical metallization memories RRAM

HRS

High resistance state

IM

Inert metal

LRS

Low resistance state

MIM

Metal/insulator/metal

NVM

Non-volatile electronic memory

P–F

Poole–Frenkel emission

QPC

Quantum Point Contact

RRAM

Resistive random access memory

RS

Resistive switching

SCH

Schottky barrier

SCLC

Space-charge limited current

SS

Stainless steel

STM

Scanning tunneling microscopy

TCM-RRAM

Thermochemical memories RRAM

TELC

Thermionic emission limited conduction

VCM-RRAM

Valence change memory RRAM

X-TEM

Cross-sectional transmission electron microscopy

Notes

Acknowledgements

This work has been supported by the Young 1000 Global Talent Recruitment Program of the Ministry of Education of China, the National Natural Science Foundation of China (Grants Nos. 61502326, 41550110223, 11661131002), the Jiangsu Government (Grant No. BK20150343), the Ministry of Finance of China (Grant No. SX21400213) and the Young 973 National Program of the Chinese Ministry of Science and Technology (Grant No. 2015CB932700). The Collaborative Innovation Center of Suzhou Nano Science & Technology, the Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices and the Priority Academic Program Development of Jiangsu Higher Education Institutions are also acknowledged. M. A. Villena acknowledges generous support from the Suzhou NANO-CIC fellowship program.

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© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Institute of Functional Nano and Soft Materials, Collaborative Innovation Center of Suzhou Nanoscience and TechnologySoochow UniversitySuzhouChina
  2. 2.Departamento de Electrónica y Tecnología de ComputadoresFacultad de Ciencias, Universidad de GranadaGranadaSpain
  3. 3.Departament d’Enginyeria ElectrònicaUniversitat Autònoma de BarcelonaBellaterraSpain

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