Statistical characteristics of reset switching in Cu-HfO2-Pt resistive switching memoryReport as inadecuate




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Nanoscale Research Letters

, 9:694

2nd International Conference on ALD Applications and 3rd China ALD conference

Abstract

A major challenge of resistive switching memory resistive random access memory RRAM for future application is how to reduce the fluctuation of the resistive switching parameters. In this letter, with a statistical methodology, we have systematically analyzed the reset statistics of the conductive bridge random access memory CBRAM with a Cu-HfO2-Pt structure which displays bipolar switching property. The experimental observations show that the distributions of the reset voltage Vreset and reset current Ireset are greatly influenced by the initial on-state resistance Ron which is closely related to the size of the conductive filament CF before the reset process. The reset voltage increases and the current decreases with the on-state resistance, respectively, according to the scatter plots of the experimental data. Using resistance screening method, the statistical data of the reset voltage and current are decomposed into several ranges and the distributions of them in each range are analyzed by the Weibull model. Both the Weibull slopes of the reset voltage and current are demonstrated to be independent of the on-state resistance which indicates that no CF dissolution occurs before the reset point. The scale factor of the reset voltage increases with on-state resistance while that of the reset current decreases with it. These behaviors are fully in consistency with the thermal dissolution model, which gives an insight on the physical mechanism of the reset switching. Our work has provided an inspiration on effectively reducing the variation of the switching parameters of RRAM devices.

KeywordsRRAM Statistics Conductive filament Weibull model Thermal dissolution Electronic supplementary materialThe online version of this article doi:10.1186-1556-276X-9-694 contains supplementary material, which is available to authorized users.

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Author: Meiyun Zhang - Shibing Long - Guoming Wang - Ruoyu Liu - Xiaoxin Xu - Yang Li - Dinlin Xu - Qi Liu - Hangbing Lv - Enriqu

Source: https://link.springer.com/



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