ACS Appl Mater Interfaces. 2023 Apr 7. doi: 10.1021/acsami.2c22617. Online ahead of print.
ABSTRACT
We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data points extracted from current versus voltage (I–V) plots, such as switching voltages or state resistances, we take into account the whole I–V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I–V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memories.
PMID:37027783 | DOI:10.1021/acsami.2c22617
