Journal Article

FZJ-2022-02087

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Toward Simplified Physics-Based Memristor Modeling of Valence Change Mechanism Devices

Ntinas, V. ; Ascoli, A. ; Messaris, I. ; Wang, Y.FZJ* ; Rana, V. (Corresponding author)FZJ* ; Menzel, S.FZJ* ; Tetzlaff, R.

2022
IEEE New York, NY

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Please use a persistent id in citations: http://hdl.handle.net/2128/31120  doi:10.1109/TCSII.2022.3160304

Abstract: Memristors are promising nanoelectronic devices for the implementation of future AI-driven sensor-processor electronic systems, which are essential for the ongoing digitalization of our world. Accurate and computationally cost-effective models for the manufactured memristors are essential for the design of such systems, especially for the simulation of large circuits. In this brief we address the simplification of the JART memristor model, a generic physics-based model of Valence Change Mechanism (VCM) memristors which accurately describes the dynamic behavior of fabricated memristor devices. Furthermore, the proposed model and simplification methodology have the potential to capture the dynamics of a wide range of memristor devices. Importantly, the implicit description of the current through the memristor is replaced by an explicit mathematical relationship. The proper reproduction of memristor dynamics, verified by applying the system-theoretic Dynamic Route Map (DRM) graphical analysis tool, applicable to first-order systems, can be observed through the proposed simplified model and enables the time-efficient simulation of large arrays of VCM devices.

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Contributing Institute(s):

1. Elektronische Materialien (PGI-7)
2. JARA-FIT (JARA-FIT)
3. JARA Institut Green IT (PGI-10)

Research Program(s):

1. 5233 - Memristive Materials and Devices (POF4-523) (POF4-523)
2. BMBF-16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K) (BMBF-16ME0398K)
3. BMBF-16ME0399 - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0399) (BMBF-16ME0399)
4. SFB 917 B01 - Schnelle transiente, elektrische Analyse von resistiven Schaltphänomenen (B01) (202259360) (202259360)
5. ACA - Advanced Computing Architectures (SO-092) (SO-092)

Appears in the scientific report 2022

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Current Contents - Electronics and Telecommunications Collection ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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