SPICE modeling of cycle-to-cycle variability in RRAM devices

In this work, we investigated how to include uncorrelated cycle-to-cycle (C2C) variability in the LTSpice quasi-static memdiode model for RRAM devices. Variability in the I-V curves is first addressed through an in-depth study of the experimental data using the fitdistrplus package for the R languag...

Descripción completa

Detalles Bibliográficos
Autores: Salvador Aguilera, Emili|||0000-0002-1613-6784, Bargallo Gonzalez, Mireia|||0000-0001-6792-4556, Campabadal, Francesca|||0000-0001-7758-4567, Martin Martinez, Javier|||0000-0001-5938-5898, Rodríguez Martínez, Rosana|||0000-0002-4565-6703, Miranda, E.|||0000-0003-0470-5318
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:249236
Acceso en línea:https://ddd.uab.cat/record/249236
https://dx.doi.org/urn:doi:10.1016/j.sse.2021.108040
Access Level:acceso abierto
Palabra clave:RRAM
Variability
Modeling
LTSpice
Fitdistrplus
Descripción
Sumario:In this work, we investigated how to include uncorrelated cycle-to-cycle (C2C) variability in the LTSpice quasi-static memdiode model for RRAM devices. Variability in the I-V curves is first addressed through an in-depth study of the experimental data using the fitdistrplus package for the R language. This provides a first approximation to the identification of the most suitable model parameter distributions. Next, the selected candidate distributions are incorporated into the model script and used for carrying out Monte Carlo simulations. Finally, the experimental and simulated observables (set and reset currents, transition voltages, etc.) are statistically compared and the model estimands recalculated if it is necessary. Here, we put special emphasis on describing the main difficulties behind this seemingly simple procedure.