This paper reports the fundamentals and the SPICE implementation of the Dynamic Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching (RS) devices. Following Prof. Chua's memristive devices theory, the memdiode model comprises two equations, one for the electron transport based on a heuristic extension of the quantum point-contact model for filamentary conduction in thin dielectrics and a second equation for the internal memory state related to the reversible displacement of atomic species within the oxide film. The DMM represents a breakthrough with respect to the previous Quasi-static Memdiode Model (QMM) since it describes the memory state of the device as a balance equation incorporating both the snapback and snapforward effects, features of utmost importance for the accurate and realistic simulation of the RS phenomenon. The DMM allows simple setting of the initial memory condition as well as decoupled modeling of the set and reset transitions. The model equations are implemented in the LTSpice simulator using an equivalent circuital approach with behavioral components and sources. The practical details of the model implementation and its modes of use are also discussed.
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http://dx.doi.org/10.3390/mi13020330 | DOI Listing |
Micromachines (Basel)
November 2022
Departament d'Enginyeria Electrònica, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain.
In this paper, the use of Artificial Neural Networks (ANNs) in the form of Convolutional Neural Networks (AlexNET) for the fast and energy-efficient fitting of the Dynamic Memdiode Model (DMM) to the conduction characteristics of bipolar-type resistive switching (RS) devices is investigated. Despite an initial computationally intensive training phase the ANNs allow obtaining a mapping between the experimental Current-Voltage () curve and the corresponding DMM parameters without incurring a costly iterative process as typically considered in error minimization-based optimization algorithms. In order to demonstrate the fitting capabilities of the proposed approach, a complete set of s obtained from YO-based RRAM devices, fabricated with different oxidation conditions and measured with different current compliances, is considered.
View Article and Find Full Text PDFMicromachines (Basel)
February 2022
Departament d'Enginyeria Electrònica, Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain.
This paper reports the fundamentals and the SPICE implementation of the Dynamic Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching (RS) devices. Following Prof. Chua's memristive devices theory, the memdiode model comprises two equations, one for the electron transport based on a heuristic extension of the quantum point-contact model for filamentary conduction in thin dielectrics and a second equation for the internal memory state related to the reversible displacement of atomic species within the oxide film.
View Article and Find Full Text PDFJ Colloid Interface Sci
October 2016
Department of Technology and Metallurgy, University of Belgrade, 4 Karnegijeva St., 11120 Belgrade, Serbia.
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