A comprehensive statistical study of the post-programming conductance drift in HfO2-based memristive devices

Abstract

The conductance drift in HfO2-based memristors is a critical reliability concern that impacts in their application in non-volatile memory and neuromorphic computing integrated circuits. In this work we present a comprehensive statistical analysis of the conductance drift behavior in resistive random access memories (RRAM) whose physics is based on valence change mechanisms. We experimentally characterize the conductance time evolution in six different resistance states and analyze the suitability of various probability distributions to model the observed variability. Our results reveal that the log-logistic probability distribution provides the best fit to the experimental data for the resistance multilevels and the measured post-programming times under consideration. Additionally, we employ an analysis of variance (ANOVA) to statistically analyze the post-programming time and current level effects on the observed variability. Finally, in the context of the Stanford compact model, we describe how variability has to be implemented to obtain the probability distribution of measured current values.