Literature DB >> 21847501

Device and SPICE modeling of RRAM devices.

Patrick Sheridan1, Kuk-Hwan Kim, Siddharth Gaba, Ting Chang, Lin Chen, Wei Lu.   

Abstract

We report the development of physics based models for resistive random-access memory (RRAM) devices. The models are based on a generalized memristive system framework and can explain the dynamic resistive switching phenomena observed in a broad range of devices. Furthermore, by constructing a simple subcircuit, we can incorporate the device models into standard circuit simulators such as SPICE. The SPICE models can accurately capture the dynamic effects of the RRAM devices such as the apparent threshold effect, the voltage dependence of the switching time, and multi-level effects under complex circuit conditions. The device and SPICE models can also be readily expanded to include additional effects related to internal state changes, and will be valuable to help in the design and simulation of memory and logic circuits based on resistive switching devices.

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Year:  2011        PMID: 21847501     DOI: 10.1039/c1nr10557d

Source DB:  PubMed          Journal:  Nanoscale        ISSN: 2040-3364            Impact factor:   7.790


  4 in total

Review 1.  Advances of RRAM Devices: Resistive Switching Mechanisms, Materials and Bionic Synaptic Application.

Authors:  Zongjie Shen; Chun Zhao; Yanfei Qi; Wangying Xu; Yina Liu; Ivona Z Mitrovic; Li Yang; Cezhou Zhao
Journal:  Nanomaterials (Basel)       Date:  2020-07-23       Impact factor: 5.076

Review 2.  On the Thermal Models for Resistive Random Access Memory Circuit Simulation.

Authors:  Juan B Roldán; Gerardo González-Cordero; Rodrigo Picos; Enrique Miranda; Félix Palumbo; Francisco Jiménez-Molinos; Enrique Moreno; David Maldonado; Santiago B Baldomá; Mohamad Moner Al Chawa; Carol de Benito; Stavros G Stavrinides; Jordi Suñé; Leon O Chua
Journal:  Nanomaterials (Basel)       Date:  2021-05-11       Impact factor: 5.076

3.  AHaH computing-from metastable switches to attractors to machine learning.

Authors:  Michael Alexander Nugent; Timothy Wesley Molter
Journal:  PLoS One       Date:  2014-02-10       Impact factor: 3.240

4.  A Bioinspired Artificial Injury Response System Based on a Robust Polymer Memristor to Mimic a Sense of Pain, Sign of Injury, and Healing.

Authors:  Xiaojie Xu; En Ju Cho; Logan Bekker; A Alec Talin; Elaine Lee; Andrew J Pascall; Marcus A Worsley; Jenny Zhou; Caitlyn C Cook; Joshua D Kuntz; Seongkoo Cho; Christine A Orme
Journal:  Adv Sci (Weinh)       Date:  2022-03-25       Impact factor: 17.521

  4 in total

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