Parameter extraction techniques for the analysis and modeling of resistive memories
Metadatos
Mostrar el registro completo del ítemAutor
Maldonado Correa, David; Aldana Delgado, Samuel; González, M. B.; Jiménez Molinos, Francisco; Campabadal, F.; Roldán Aranda, Juan BautistaEditorial
Elsevier
Materia
Resistive switching memory RRAM parameter extraction Kinetic Monte Carlo simulation Variability Numerical methods Series resistance
Fecha
2022-09-08Referencia bibliográfica
Microelectronic Engineering 265 (2022) 111876 [https://doi.org/10.1016/j.mee.2022.111876]
Patrocinador
Consejería de Conocimiento, Investigaci ́on y Universidad, Junta de Andalucía (Spain) and the FEDER program for the projects A.TIC.117.UGR18, B-TIC-624-UGR20 and IE2017-5414; Ramón y Cajal grant No. RYC2020-030150-I; Funding for open access charge: Universidad de Granada/CBUAResumen
A revision of the different numerical techniques employed to extract resistive switching (RS) and modeling parameters is presented. The set and reset voltages, commonly used for variability estimation, are calculated for different resistive memory technologies. The methodologies to extract the series resistance and the parameters linked to the charge-flux memristive modeling approach are also described. It is found that the obtained cycle-to-cycle (C2C) variability depends on the numerical technique used. This result is important, and it implies that when analyzing C2C variability, the extraction technique should be described to perform fair comparisons between different resistive memory technologies. In addition to the use of extensive experimental data for different types of resistive memories, we have also included kinetic Monte Carlo (kMC) simulations to study the formation and rupture events of the percolation paths that constitute the conductive filaments (CF) that allow resistive switching operation in filamentary unipolar and bipolar devices.