Variability in HfO2-based memristors described with a new bidimensional statistical technique

Abstract

A new statistical analysis is presented to assess cycle-to-cycle variability in resistive memories. This method employs two-dimensional (2D) distributions of parameters to analyse both set and reset voltages and currents, coupled with a 2D coefficient of variation (CV). This 2D methodology significantly enhances the analysis, providing a more thorough and comprehensive understanding of the data compared to conventional one-dimensional methods. Resistive switching (RS) data from two different technologies based on hafnium oxide are used in the variability study. The 2D CV allows a more compact assessment of technology suitability for applications such as non-volatile memories, neuromorphic computing and random number generation circuits.