Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient Acal González, Christian José Maldonado Correa, David Aguilera Del Pino, Ana María Roldán Aranda, Juan Bautista Resistive memories Variability Variability coefficient Functional data analysis Holistic methodology The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsami.2c22617 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 2023-05-18T08:25:10Z 2023-05-18T08:25:10Z 2023-04-07 info:eu-repo/semantics/article Acal C. et al. Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient. ACS Appl. Mater. Interfaces 2023, 15, 19102−19110. [https://doi.org/10.1021/acsami.2c22617] https://hdl.handle.net/10481/81638 10.1021/acsami.2c22617 eng http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional American Chemical Society