Statistical modeling of program and read variability in resistive switching devices

Resistive-switching memory (RRAM) based on ion migration in metal oxide layers may provide a scalable, low-power alternative to Flash beyond the 10 nm technology node. However, low current operation in scaled RRAM is prone to switching variability and read noise, e.g., random telegraph noise (RTN). To develop a scalable RRAM technology, the statistical variability of program/read processes must be thoroughly addressed. In this paper we propose a novel Monte-Carlo analytical model for switching variability, accounting for the spread of programmed resistance at variable operation current. A numerical model for RTN is then presented, capable of describing size-dependence of RTN amplitude and its kinetics.