DocumentCode :
3607250
Title :
Noise-Induced Resistance Broadening in Resistive Switching Memory—Part II: Array Statistics
Author :
Ambrogio, Stefano ; Balatti, Simone ; McCaffrey, Vincent ; Wang, Daniel C. ; Ielmini, Daniele
Author_Institution :
Dipt. di Elettron., Inf. e Bioingegneria, Politec. di Milano, Milan, Italy
Volume :
62
Issue :
11
fYear :
2015
Firstpage :
3812
Lastpage :
3819
Abstract :
Noise in resistive switching memory (RRAM) is among the main concerns due to its impact on the reliability of single-bit and multilevel cell devices. Although noise in typical RRAM cells is understood fairly well, the statistics of noise and the presence and impact of statistical tails in the current fluctuation is what mostly affects the RRAM reliability at the array level. This paper addresses current noise in RRAM arrays, focusing on high-resistance state distribution and its broadening with time. We highlight two main contributions to the tail behavior, namely, random walk (RW) and random telegraph noise (RTN) with random start and stop. We provide evidence for a time decay of RW amplitude with time, which we explain by time-dependent stabilization of defects. We finally develop a statistical Monte Carlo model for noise, which is capable of explaining the broadening of the resistance distribution based on a physical description of RW and RTN components.
Keywords :
Monte Carlo methods; integrated circuit noise; integrated circuit reliability; random noise; resistive RAM; RRAM reliability; RTN; RW amplitude; array statistic; current fluctuation; current noise; high-resistance state distribution; multilevel cell device; noise statistic; noise-induced resistance broadening; random telegraph noise; random walk; resistive switching memory; statistical Monte Carlo model; statistical tail; time decay; time-dependent stabilization; Arrays; Electrical resistance measurement; Monte Carlo methods; Noise; Predictive models; Resistance; Switches; Low-frequency noise; memory reliability; random telegraph noise (RTN); reliability modeling; resistive switching memory (RRAM); statistical Monte Carlo modeling; statistical Monte Carlo modeling.;
fLanguage :
English
Journal_Title :
Electron Devices, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9383
Type :
jour
DOI :
10.1109/TED.2015.2477135
Filename :
7283593
Link To Document :
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