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