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

  • S.I.: Computational Electronics of Emerging Memory Elements
  • Published:
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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 \(\hbox {HfO}_{x}\).

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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

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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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Authors and Affiliations

  1. Institute of Functional Nano and Soft Materials, Collaborative Innovation Center of Suzhou Nanoscience and Technology, Soochow University, 199 Ren-Ai Road, Suzhou, 215123, China

    Marco A. Villena & Mario Lanza

  2. Departamento de Electrónica y Tecnología de Computadores, Facultad de Ciencias, Universidad de Granada, Avd. Fuentenueva s/n, 18071, Granada, Spain

    Juan B. Roldán & Francisco Jiménez-Molinos

  3. Departament d’Enginyeria Electrònica, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain

    Enrique Miranda & Jordi Suñé

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Correspondence to Mario Lanza.

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Villena, M.A., Roldán, J.B., Jiménez-Molinos, F. et al. \({ SIM}^2{ RRAM}\): a physical model for RRAM devices simulation. J Comput Electron 16, 1095–1120 (2017). https://doi.org/10.1007/s10825-017-1074-8

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