Multivariate analysis and extraction of parameters in resistive RAMs using the Quantum Point Contact model

A multivariate analysis of the parameters that characterize the reset process in Resistive Random Access Memory (RRAM) has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology consider...

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Bibliographic Details
Published in:Journal of applied physics 2018-01, Vol.123 (1)
Main Authors: Roldán, J. B., Miranda, E., González-Cordero, G., García-Fernández, P., Romero-Zaliz, R., González-Rodelas, P., Aguilera, A. M., González, M. B., Jiménez-Molinos, F.
Format: Article
Language:English
Subjects:
Applied physics
Genetic algorithms
Low resistance
Low voltage
Mathematical models
Multivariate analysis
Numerical methods
Parameters
Point contact
Rams
Random access memory
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Summary:A multivariate analysis of the parameters that characterize the reset process in Resistive Random Access Memory (RRAM) has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose, the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole Resistive Switching (RS) series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.
ISSN:0021-8979
1089-7550
DOI:10.1063/1.5006995