Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient
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Acal González, Christian José; Maldonado Correa, David; Aguilera Del Pino, Ana María; Roldán Aranda, Juan BautistaEditorial
American Chemical Society
Materia
Resistive memories Variability Variability coefficient Functional data analysis Holistic methodology
Date
2023-04-07Referencia bibliográfica
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]
Sponsorship
Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain); FEDER: B-TIC-624-UGR20, PID2020-113961GB-I00, A-FQM-66-UGR20, FQM-307; IMAG María de Maeztu CEX2020-001105-M/AEI/10.13039/501100011033; King Abdullah University of Science and TechnologyAbstract
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