Literature DB >> 29322363

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

Debashis Panda1, Paritosh Piyush Sahu2,3, Tseung Yuen Tseng4.   

Abstract

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.

Entities:  

Year:  2018        PMID: 29322363      PMCID: PMC5762646          DOI: 10.1186/s11671-017-2419-8

Source DB:  PubMed          Journal:  Nanoscale Res Lett        ISSN: 1556-276X            Impact factor:   4.703


  31 in total

1.  Progress with molecular electronic junctions: meeting experimental challenges in design and fabrication.

Authors:  Richard L McCreery; Adam Johan Bergren
Journal:  Adv Mater       Date:  2009-07-06       Impact factor: 30.849

2.  Comprehensive physical model of dynamic resistive switching in an oxide memristor.

Authors:  Sungho Kim; ShinHyun Choi; Wei Lu
Journal:  ACS Nano       Date:  2014-02-28       Impact factor: 15.881

3.  Nanofilamentary resistive switching in binary oxide system; a review on the present status and outlook.

Authors:  Kyung Min Kim; Doo Seok Jeong; Cheol Seong Hwang
Journal:  Nanotechnology       Date:  2011-05-16       Impact factor: 3.874

4.  Memristive switching mechanism for metal/oxide/metal nanodevices.

Authors:  J Joshua Yang; Matthew D Pickett; Xuema Li; Douglas A A Ohlberg; Duncan R Stewart; R Stanley Williams
Journal:  Nat Nanotechnol       Date:  2008-06-15       Impact factor: 39.213

5.  Conductive-bridging random access memory: challenges and opportunity for 3D architecture.

Authors:  Debanjan Jana; Sourav Roy; Rajeswar Panja; Mrinmoy Dutta; Sheikh Ziaur Rahaman; Rajat Mahapatra; Siddheswar Maikap
Journal:  Nanoscale Res Lett       Date:  2015-04-18       Impact factor: 4.703

6.  Physical electro-thermal model of resistive switching in bi-layered resistance-change memory.

Authors:  Sungho Kim; Sae-Jin Kim; Kyung Min Kim; Seung Ryul Lee; Man Chang; Eunju Cho; Young-Bae Kim; Chang Jung Kim; U -In Chung; In-Kyeong Yoo
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

7.  Characterization and Modeling of Nonfilamentary Ta/TaOx/TiO2/Ti Analog Synaptic Device.

Authors:  Yu-Fen Wang; Yen-Chuan Lin; I-Ting Wang; Tzu-Ping Lin; Tuo-Hung Hou
Journal:  Sci Rep       Date:  2015-05-08       Impact factor: 4.379

8.  TaOx-based resistive switching memories: prospective and challenges.

Authors:  Amit Prakash; Debanjan Jana; Siddheswar Maikap
Journal:  Nanoscale Res Lett       Date:  2013-10-09       Impact factor: 4.703

9.  Thickness effect of ultra-thin Ta2O5 resistance switching layer in 28 nm-diameter memory cell.

Authors:  Tae Hyung Park; Seul Ji Song; Hae Jin Kim; Soo Gil Kim; Suock Chung; Beom Yong Kim; Kee Jeung Lee; Kyung Min Kim; Byung Joon Choi; Cheol Seong Hwang
Journal:  Sci Rep       Date:  2015-11-03       Impact factor: 4.379

10.  Temperature-Dependent Non-linear Resistive Switching Characteristics and Mechanism Using a New W/WO3/WOx/W Structure.

Authors:  Somsubhra Chakrabarti; Subhranu Samanta; Siddheswar Maikap; Sheikh Ziaur Rahaman; Hsin-Ming Cheng
Journal:  Nanoscale Res Lett       Date:  2016-09-07       Impact factor: 4.703

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  5 in total

Review 1.  Resistive Random Access Memory (RRAM): an Overview of Materials, Switching Mechanism, Performance, Multilevel Cell (mlc) Storage, Modeling, and Applications.

Authors:  Furqan Zahoor; Tun Zainal Azni Zulkifli; Farooq Ahmad Khanday
Journal:  Nanoscale Res Lett       Date:  2020-04-22       Impact factor: 4.703

2.  SPICE Implementation of the Dynamic Memdiode Model for Bipolar Resistive Switching Devices.

Authors:  Fernando Leonel Aguirre; Jordi Suñé; Enrique Miranda
Journal:  Micromachines (Basel)       Date:  2022-02-19       Impact factor: 2.891

3.  Nonlinear ion drift-diffusion memristance description of TiO2 RRAM devices.

Authors:  Sahar Alialy; Koorosh Esteki; Mauro S Ferreira; John J Boland; Claudia Gomes da Rocha
Journal:  Nanoscale Adv       Date:  2020-04-21

Review 4.  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

5.  Transition between bipolar and abnormal bipolar resistive switching in amorphous oxides with a mobility edge.

Authors:  Christiane Ader; Andreas Falkenstein; Manfred Martin
Journal:  Sci Rep       Date:  2021-07-13       Impact factor: 4.379

  5 in total

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