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Download fileDemonstration of Enhanced Switching Variability and Conductance Quantization Properties in a SiO2 Conducting Bridge Resistive Memory with Embedded Two-Dimensional MoS2 Material
journal contribution
posted on 2022-05-20, 08:14 authored by Stavros Kitsios, Panagiotis Bousoulas, Dimitris Spithouris, Maria Kainourgiaki, Menelaos Tsigkourakos, Polyxeni Chatzopoulou, George P. Dimitrakopulos, Philomela Komninou, Dimitris TsoukalasIn this work, we explore the resistive
switching behavior of a
thin layer of SiO2 with embedded two-dimensional (2D) molybdenum
disulfide, MoS2, in a conductive bridge random access memory
(CBRAM) configuration. The proposed device exhibits enhanced conductance
quantization behavior, reduced variability due to the suppression
of the stochastic filament formation process, and synaptic properties.
The device operates under the bipolar switching mode without the application
of any electroforming procedure; eight different quantized conductance
states were captured during direct current (DC) operation and 10 quantized
states were recorded under pulse measurements. On top of that, both
improved endurance and retention properties as well as linearity of
the synaptic potentiation and depression procedures were attained;
the underlying origins of these effects are attributed to the control
of the Ag ion diffusion barrier through the existence of the atomic
sieve of MoS2. Our work paves the way for the development
of robust memristive elements for the implementation of stable resistive
switching and neuromorphic functionalities.
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Keywords
stable resistive switchingrobust memristive elementsresistive switching behaviorreduced variability dueenhanced switching variability10 quantized statesconductance quantization properties2 </ subsynaptic propertiesretention propertiesunderlying originsthin layersynaptic potentiationpulse measurementsneuromorphic functionalitiesmolybdenum disulfideimproved enduranceembedded twoelectroforming proceduredirect currentdevice operatesdepression proceduresatomic sieve