| Literature DB >> 27389343 |
Meiyun Zhang1,2, Shibing Long3,4, Yang Li1,2, Qi Liu1,2, Hangbing Lv1,2, Enrique Miranda5, Jordi Suñé5, Ming Liu1,2.
Abstract
The resistive switching (RS) process of resistive random access memory (RRAM) is dynamically correlated with the evolution process of conductive path or conductive filament (CF) during its breakdown (rupture) and recovery (reformation). In this study, a statistical evaluation method is developed to analyze the filament structure evolution process in the reset operation of Cu/HfO2/Pt RRAM device. This method is based on a specific functional relationship between the Weibull slopes of reset parameters' distributions and the CF resistance (R on). The CF of the Cu/HfO2/Pt device is demonstrated to be ruptured abruptly, and the CF structure of the device has completely degraded in the reset point. Since no intermediate states are generated in the abrupt reset process, it is quite favorable for the reliable and stable one-bit operation in RRAM device. Finally, on the basis of the cell-based analytical thermal dissolution model, a Monte Carlo (MC) simulation is implemented to further verify the experimental results. This work provides inspiration for RRAM reliability and performance design to put RRAM into practical application.Entities:
Keywords: Conductive filament (CF); Monte Carlo simulator; RRAM; Structure evolution
Year: 2016 PMID: 27389343 PMCID: PMC4936978 DOI: 10.1186/s11671-016-1484-8
Source DB: PubMed Journal: Nanoscale Res Lett ISSN: 1556-276X Impact factor: 4.703
Fig. 1a Structure of the Cu/HfO2/Pt RRAM device. b I–V curves of Cu/HfO2/Pt RRAM device under the compliance current of 500 μA
Fig. 2a The scatter plot of V reset of Cu/HfO2/Pt device as a function of R on. The straight line is the fitting line. V reset is independent of R on. b The scatter plot of I reset of Cu/HfO2/Pt device as a function of R on. The straight line is the fitting line. I reset decreases with R on
Fig. 3The distributions of V reset (a) and I reset (b) of Cu/HfO2/Pt RRAM device in different R on groups. The straight lines are those of fitting to the standard Weibull distribution. c The dependence of Weibull slope (β ) and scale factor (V reset63%) of V reset distributions on 1/R on. β the Weibull slope and 1/R on have a linear relation while V reset63% the scale factor keeps constant. d The dependence of Weibull slope (β ) and scale factor (I reset63%) of I reset distributions on 1/R on. Both β and I reset63% are in linear to 1/R on
Fig. 4Schematic of the cell-based model of the CF in the RS layer. N is the number of slices (CF length) of the most constrictive part of the CF and n is the number of cells in each slice (CF width)
Fig. 5The MC-simulated Weibull distributions of V reset (a) and I reset (b) in different n groups. The straight lines are fitting lines. c The dependence of the MC-simulated β and V reset63% on n. β the Weibull slope and n have a linear relation while V reset63% the scale factor keeps constant. d The dependence of the MC-simulated β and I reset63% Weibull slope and scale factor as a function of n. Both of them increase with n linearly