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

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 significa...

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Published in:Nanoscale 2024-06, Vol.16 (22), p.1812-1818
Main Authors: Acal, C, Maldonado, D, Cantudo, A, González, M. B, Jiménez-Molinos, F, Campabadal, F, Roldán, J. B
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container_end_page 1818
container_issue 22
container_start_page 1812
container_title Nanoscale
container_volume 16
creator Acal, C
Maldonado, D
Cantudo, A
González, M. B
Jiménez-Molinos, F
Campabadal, F
Roldán, J. B
description 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. A new two-dimensional statistical technique has been developed to describe cycle-to-cycle variability in resistive memories. A two-dimensional coefficient of variation is introduced to characterize variability in a better manner.
doi_str_mv 10.1039/d4nr01237b
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title Variability in HfO-based memristors described with a new bidimensional statistical technique
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