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A Collective Study on Modeling and Simulation of Resistive Random Access Memory

In this work, we provide a comprehensive discussion on the various models proposed for the design and description of resistive random access memory (RRAM), being a nascent technology is heavily reliant on accurate models to develop efficient working designs and standardize its implementation across...

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Autores principales: Panda, Debashis, Sahu, Paritosh Piyush, Tseng, Tseung Yuen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762646/
https://www.ncbi.nlm.nih.gov/pubmed/29322363
http://dx.doi.org/10.1186/s11671-017-2419-8
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author Panda, Debashis
Sahu, Paritosh Piyush
Tseng, Tseung Yuen
author_facet Panda, Debashis
Sahu, Paritosh Piyush
Tseng, Tseung Yuen
author_sort Panda, Debashis
collection PubMed
description In this work, we provide a comprehensive discussion on the various models proposed for the design and description of resistive random access memory (RRAM), being a nascent technology is heavily reliant on accurate models to develop efficient working designs and standardize its implementation across devices. This review provides detailed information regarding the various physical methodologies considered for developing models for RRAM devices. It covers all the important models reported till now and elucidates their features and limitations. Various additional effects and anomalies arising from memristive system have been addressed, and the solutions provided by the models to these problems have been shown as well. All the fundamental concepts of RRAM model development such as device operation, switching dynamics, and current-voltage relationships are covered in detail in this work. Popular models proposed by Chua, HP Labs, Yakopcic, TEAM, Stanford/ASU, Ielmini, Berco-Tseng, and many others have been compared and analyzed extensively on various parameters. The working and implementations of the window functions like Joglekar, Biolek, Prodromakis, etc. has been presented and compared as well. New well-defined modeling concepts have been discussed which increase the applicability and accuracy of the models. The use of these concepts brings forth several improvements in the existing models, which have been enumerated in this work. Following the template presented, highly accurate models would be developed which will vastly help future model developers and the modeling community.
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spelling pubmed-57626462018-01-25 A Collective Study on Modeling and Simulation of Resistive Random Access Memory Panda, Debashis Sahu, Paritosh Piyush Tseng, Tseung Yuen Nanoscale Res Lett Nano Review In this work, we provide a comprehensive discussion on the various models proposed for the design and description of resistive random access memory (RRAM), being a nascent technology is heavily reliant on accurate models to develop efficient working designs and standardize its implementation across devices. This review provides detailed information regarding the various physical methodologies considered for developing models for RRAM devices. It covers all the important models reported till now and elucidates their features and limitations. Various additional effects and anomalies arising from memristive system have been addressed, and the solutions provided by the models to these problems have been shown as well. All the fundamental concepts of RRAM model development such as device operation, switching dynamics, and current-voltage relationships are covered in detail in this work. Popular models proposed by Chua, HP Labs, Yakopcic, TEAM, Stanford/ASU, Ielmini, Berco-Tseng, and many others have been compared and analyzed extensively on various parameters. The working and implementations of the window functions like Joglekar, Biolek, Prodromakis, etc. has been presented and compared as well. New well-defined modeling concepts have been discussed which increase the applicability and accuracy of the models. The use of these concepts brings forth several improvements in the existing models, which have been enumerated in this work. Following the template presented, highly accurate models would be developed which will vastly help future model developers and the modeling community. Springer US 2018-01-10 /pmc/articles/PMC5762646/ /pubmed/29322363 http://dx.doi.org/10.1186/s11671-017-2419-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Nano Review
Panda, Debashis
Sahu, Paritosh Piyush
Tseng, Tseung Yuen
A Collective Study on Modeling and Simulation of Resistive Random Access Memory
title A Collective Study on Modeling and Simulation of Resistive Random Access Memory
title_full A Collective Study on Modeling and Simulation of Resistive Random Access Memory
title_fullStr A Collective Study on Modeling and Simulation of Resistive Random Access Memory
title_full_unstemmed A Collective Study on Modeling and Simulation of Resistive Random Access Memory
title_short A Collective Study on Modeling and Simulation of Resistive Random Access Memory
title_sort collective study on modeling and simulation of resistive random access memory
topic Nano Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762646/
https://www.ncbi.nlm.nih.gov/pubmed/29322363
http://dx.doi.org/10.1186/s11671-017-2419-8
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