DocumentCode :
27102
Title :
Statistical Model and Rapid Prediction of RRAM SET Speed–Disturb Dilemma
Author :
Wun-Cheng Luo ; Jen-Chieh Liu ; Yen-Chuan Lin ; Chun-Li Lo ; Jiun-Jia Huang ; Kuan-Liang Lin ; Tuo-Hung Hou
Author_Institution :
Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume :
60
Issue :
11
fYear :
2013
fDate :
Nov. 2013
Firstpage :
3760
Lastpage :
3766
Abstract :
A comprehensive study of SET speed-disturb dilemma in resistive-switching random access memory (RRAM) is presented using statistically based prediction methodologies, accounting for the stochastic nature of SET. An analytical percolation model has been successful in explaining the statistical Weibull distribution of SET time and SET voltage in addition to the power-law voltage-time dependence. Two prediction methodologies using constant voltage stress (CVS) and ramp voltage stress (RVS) are proposed to evaluate the SET speed-disturb properties. The RVS method reduces analysis time and cost and yields equivalent results as the CVS method. Furthermore, the RVS method is used to evaluate the device design space and the current status of RRAM technology to meet the strict requirement of the SET speed-disturb dilemma.
Keywords :
random-access storage; statistical analysis; RRAM SET speed-disturb dilemma; analytical percolation model; constant voltage stress; power-law voltage-time dependence; ramp voltage stress; rapid prediction; resistive-switching random access memory; statistical model; stochastic nature; Acceleration; Electric breakdown; Hafnium compounds; Stress; Testing; Voltage measurement; Weibull distribution; Disturb; SET speed; SET statistics; ramp voltage stress (RVS); resistive-switching random access memory (RRAM);
fLanguage :
English
Journal_Title :
Electron Devices, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9383
Type :
jour
DOI :
10.1109/TED.2013.2281991
Filename :
6612680
Link To Document :
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