Stochastic based compact model to predict highly variable electrical characteristics of organic CBRAM devices - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Solid-State Electronics Année : 2021

Stochastic based compact model to predict highly variable electrical characteristics of organic CBRAM devices

Résumé

A compact model is proposed using a stochastic approach to capture the resistive switching behavior of conductive-bridge random access memory (CBRAM) device featuring a solid polymer electrolyte consisting of Polyethylene Oxide (PEO). This model considers the statistical distribution of five electrical parameters used to describe the resistive switching observed in experimental data. A switching probability is defined to control the change of resistive state. This approach gives the model the stochastic behavior of current–voltage characteristics observed in this kind of devices. A good agreement between the simulation and the experimental curves is observed despite the unusual variability cycle-to-cycle for this type of ReRAM.
Fichier principal
Vignette du fichier
StochasticModelForCBRAM_a.pdf (634.49 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03252877 , version 1 (15-02-2022)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Silvana Guitarra, P. Mahato, D. Deleruyelle, L. Raymond, L. Trojman. Stochastic based compact model to predict highly variable electrical characteristics of organic CBRAM devices. Solid-State Electronics, 2021, 185, pp.108055. ⟨10.1016/j.sse.2021.108055⟩. ⟨hal-03252877⟩
96 Consultations
24 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More