001     1020894
005     20240226075319.0
024 7 _ |a 10.48550/ARXIV.2301.10158
|2 doi
024 7 _ |a 10.34734/FZJ-2024-00370
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037 _ _ |a FZJ-2024-00370
100 1 _ |a Völkel, Lukas
|0 P:(DE-HGF)0
|b 0
245 _ _ |a Resistive Switching and Current Conduction Mechanisms in Hexagonal Boron Nitride Threshold Memristors with Nickel Electrodes
260 _ _ |c 2023
|b arXiv
336 7 _ |a Preprint
|b preprint
|m preprint
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|s 1704980508_2197
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336 7 _ |a WORKING_PAPER
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336 7 _ |a Electronic Article
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336 7 _ |a preprint
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336 7 _ |a ARTICLE
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520 _ _ |a The two-dimensional (2D) insulating material hexagonal boron nitride (h BN) has attracted much attention as the active medium in memristive devices due to its favorable physical properties, among others, a wide bandgap that enables a large switching window. Metal filament formation is frequently suggested for h-BN devices as the resistive switching (RS) mechanism, usually supported by highly specialized methods like conductive atomic force microscopy (C-AFM) or transmission electron microscopy (TEM). Here, we investigate the switching of multilayer hexagonal boron nitride (h-BN) threshold memristors with two nickel (Ni) electrodes through their current conduction mechanisms. Both the high and the low resistance states are analyzed through temperature-dependent current-voltage measurements. We propose the formation and retraction of nickel filaments along boron defects in the h-BN film as the resistive switching mechanism. We corroborate our electrical data with TEM analyses to establish temperature-dependent current-voltage measurements as a valuable tool for the analysis of resistive switching phenomena in memristors made of 2D materials. Our memristors exhibit a wide and tunable current operation range and low stand-by currents, in line with the state of the art in h-BN-based threshold switches, a low cycle-to-cycle variability of 5%, and a large On/Off ratio of 10${^7}$.
536 _ _ |a 5233 - Memristive Materials and Devices (POF4-523)
|0 G:(DE-HGF)POF4-5233
|c POF4-523
|f POF IV
|x 0
536 _ _ |a BMBF 16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K)
|0 G:(DE-82)BMBF-16ME0398K
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588 _ _ |a Dataset connected to DataCite
650 _ 7 |a Applied Physics (physics.app-ph)
|2 Other
650 _ 7 |a Materials Science (cond-mat.mtrl-sci)
|2 Other
650 _ 7 |a FOS: Physical sciences
|2 Other
700 1 _ |a Braun, Dennis
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Belete, Melkamu
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Kataria, Satender
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Wahlbrink, Thorsten
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Ran, Ke
|0 P:(DE-Juel1)174238
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700 1 _ |a Kistermann, Kevin
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700 1 _ |a Mayer, Joachim
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700 1 _ |a Menzel, Stephan
|0 P:(DE-Juel1)158062
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700 1 _ |a Daus, Alwin
|0 P:(DE-HGF)0
|b 9
700 1 _ |a Lemme, Max C.
|0 P:(DE-HGF)0
|b 10
773 _ _ |a 10.48550/ARXIV.2301.10158
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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914 1 _ |y 2023
915 _ _ |a OpenAccess
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980 1 _ |a FullTexts


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