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 LanzaEmail author
S.I.: Computational Electronics of Emerging Memory Elements


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 \(\hbox {HfO}_{x}\).


RRAM Resistive switching Memristor Simulation Physical modeling 



Dielectric breakdown


Conductive atomic force microscopy


Conductive bridge RAM


Conductive filament


Electrochemical metallization memories RRAM


High resistance state


Inert metal


Low resistance state




Non-volatile electronic memory


Poole–Frenkel emission


Quantum Point Contact


Resistive random access memory


Resistive switching


Schottky barrier


Space-charge limited current


Stainless steel


Scanning tunneling microscopy


Thermochemical memories RRAM


Thermionic emission limited conduction


Valence change memory RRAM


Cross-sectional transmission electron microscopy



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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