Journal Article

FZJ-2022-03453

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Disentangling ionic and electronic contributions to the switching dynamics of memristive Pr 0.7 Ca 0.3 MnO 3 / Al devices by employing a two-resistor model

Gutsche, A. (Corresponding author)FZJ* ; Hambsch, S. ; Branca, N. C. ; Dittmann, R.FZJ* ; Scholz, S. ; Knoch, J.

2022
APS College Park, MD

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Please use a persistent id in citations: http://hdl.handle.net/2128/31878  doi:10.1103/PhysRevMaterials.6.095002

Abstract: Area-dependent memristive devices such as Al/Pr0.7Ca0.3MnO3 (PCMO) stacks are highly interesting candidates for synapses in neuromorphic circuits due to their gradual switching properties, their reduced variability and the possibility to tune the resistance with the device area. However, due to the complexity of the different processes taking place, the electronic and ionic transport in theses devices is so far only poorly understood and physical compact models to simulate their behavior are missing so far. We developed a mathematical description of the dynamics of theses devices based on a simple two-resistor model that reproduces the device behavior very well. Based on x-ray photoelectron spectroscopy and impedance spectroscopy we assign the two resistors to the AlOx layer and a depletion zone at the Pr0.7Ca0.3MnO3 layer, respectively. We assign the parameters used within the mathematical model to physical parameters and make use of them in order to explain the dynamics of the switching processes during the SET and RESET process in different voltage regimes. For both poly- and single crystalline PCMO thin film devices, oxygen migration between the AlOx and the PCMO depletion zone is responsible for the resistance change. However, the dynamics differ significantly due to the increased mobility of oxygen vacancies with increasing defect density in the case of the polycrystalline samples. Moreover, we observe volatile subloops in our current-voltage curves, which vanish within millisecond time scale. Based on our two-resistor model and the band diagram derived from spectroscopic measurements, we assign these subloops to the injection of electrons into traps within the AlOx barrier.

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Contributing Institute(s):

1. Elektronische Materialien (PGI-7)
2. JARA-FIT (JARA-FIT)

Research Program(s):

1. 5233 - Memristive Materials and Devices (POF4-523) (POF4-523)
2. BMBF-16ME0399 - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0399) (BMBF-16ME0399)
3. BMBF-16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K) (BMBF-16ME0398K)
4. Advanced Computing Architectures (aca_20190115) (aca_20190115)
5. BMBF-03ZU1106AB - NeuroSys: "Memristor Crossbar Architekturen (Projekt A) - B" (BMBF-03ZU1106AB) (BMBF-03ZU1106AB)

Appears in the scientific report 2022

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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