001020894 001__ 1020894
001020894 005__ 20240226075319.0
001020894 0247_ $$2doi$$a10.48550/ARXIV.2301.10158
001020894 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-00370
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001020894 1001_ $$0P:(DE-HGF)0$$aVölkel, Lukas$$b0
001020894 245__ $$aResistive Switching and Current Conduction Mechanisms in Hexagonal Boron Nitride Threshold Memristors with Nickel Electrodes
001020894 260__ $$barXiv$$c2023
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001020894 520__ $$aThe two-dimensional (2D) insulating material hexagonal boron nitride (h BN) has attracted much attention as the active medium in memristive devices due to its favorable physical properties, among others, a wide bandgap that enables a large switching window. Metal filament formation is frequently suggested for h-BN devices as the resistive switching (RS) mechanism, usually supported by highly specialized methods like conductive atomic force microscopy (C-AFM) or transmission electron microscopy (TEM). Here, we investigate the switching of multilayer hexagonal boron nitride (h-BN) threshold memristors with two nickel (Ni) electrodes through their current conduction mechanisms. Both the high and the low resistance states are analyzed through temperature-dependent current-voltage measurements. We propose the formation and retraction of nickel filaments along boron defects in the h-BN film as the resistive switching mechanism. We corroborate our electrical data with TEM analyses to establish temperature-dependent current-voltage measurements as a valuable tool for the analysis of resistive switching phenomena in memristors made of 2D materials. Our memristors exhibit a wide and tunable current operation range and low stand-by currents, in line with the state of the art in h-BN-based threshold switches, a low cycle-to-cycle variability of 5%, and a large On/Off ratio of 10${^7}$.
001020894 536__ $$0G:(DE-HGF)POF4-5233$$a5233 - Memristive Materials and Devices (POF4-523)$$cPOF4-523$$fPOF IV$$x0
001020894 536__ $$0G:(DE-82)BMBF-16ME0398K$$aBMBF 16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K)$$cBMBF-16ME0398K$$x1
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001020894 650_7 $$2Other$$aApplied Physics (physics.app-ph)
001020894 650_7 $$2Other$$aMaterials Science (cond-mat.mtrl-sci)
001020894 650_7 $$2Other$$aFOS: Physical sciences
001020894 7001_ $$0P:(DE-HGF)0$$aBraun, Dennis$$b1
001020894 7001_ $$0P:(DE-HGF)0$$aBelete, Melkamu$$b2
001020894 7001_ $$0P:(DE-HGF)0$$aKataria, Satender$$b3
001020894 7001_ $$0P:(DE-HGF)0$$aWahlbrink, Thorsten$$b4
001020894 7001_ $$0P:(DE-Juel1)174238$$aRan, Ke$$b5$$ufzj
001020894 7001_ $$0P:(DE-HGF)0$$aKistermann, Kevin$$b6
001020894 7001_ $$0P:(DE-Juel1)130824$$aMayer, Joachim$$b7$$ufzj
001020894 7001_ $$0P:(DE-Juel1)158062$$aMenzel, Stephan$$b8$$ufzj
001020894 7001_ $$0P:(DE-HGF)0$$aDaus, Alwin$$b9
001020894 7001_ $$0P:(DE-HGF)0$$aLemme, Max C.$$b10
001020894 773__ $$a10.48550/ARXIV.2301.10158
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001020894 9141_ $$y2023
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001020894 9201_ $$0I:(DE-Juel1)PGI-7-20110106$$kPGI-7$$lElektronische Materialien$$x0
001020894 9201_ $$0I:(DE-Juel1)PGI-10-20170113$$kPGI-10$$lJARA Institut Green IT$$x1
001020894 9201_ $$0I:(DE-82)080009_20140620$$kJARA-FIT$$lJARA-FIT$$x2
001020894 9201_ $$0I:(DE-Juel1)ER-C-2-20170209$$kER-C-2$$lMaterialwissenschaft u. Werkstofftechnik$$x3
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