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

Overview of attention for article published in Discover Nano, January 2018
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120 Mendeley
Title
A Collective Study on Modeling and Simulation of Resistive Random Access Memory
Published in
Discover Nano, January 2018
DOI 10.1186/s11671-017-2419-8
Pubmed ID
Authors

Debashis Panda, Paritosh Piyush Sahu, Tseung Yuen Tseng

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 120 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 23%
Student > Master 22 18%
Researcher 16 13%
Student > Bachelor 8 7%
Other 4 3%
Other 13 11%
Unknown 30 25%
Readers by discipline Count As %
Engineering 47 39%
Materials Science 15 13%
Physics and Astronomy 10 8%
Computer Science 6 5%
Chemistry 3 3%
Other 12 10%
Unknown 27 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 February 2018.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Discover Nano
#802
of 1,149 outputs
Outputs of similar age
#391,181
of 451,175 outputs
Outputs of similar age from Discover Nano
#16
of 18 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,149 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 451,175 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.