Variability in Resistive Memories

Juan B. Roldan, Enrique Miranda, David Maldonado, Alexey N. Mikhaylov, Nikolay V. Agudov, Alexander A. Dubkov, Maria N. Koryazhkina, Mireia B. González, Marco Antonio Villena, Samuel Poblador, Mercedes Saludes-Tapia, Rodrigo Picos, Francisco Jiménez-Molinos, Stavros G. Stavrinides, Emili Salvador, Francisco J. Alonso, Francesca Campabadal, Bernardo Spagnolo, Mario Lanza, Leon O. Chua

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and performance have been notably improved in the last few years to cope with the requirements of massive industrial production. However, the most important hurdle to progress in their development is the so-called cycle-to-cycle variability, which is inherently rooted in the resistive switching mechanism behind the operational principle of these devices. In order to achieve the whole picture, variability must be assessed from different viewpoints going from the experimental characterization to the adequation of modeling and simulation techniques. Herein, special emphasis is put on the modeling part because the accurate representation of the phenomenon is critical for circuit designers. In this respect, a number of approaches are used to the date: stochastic, behavioral, mesoscopic..., each of them covering particular aspects of the electron and ion transport mechanisms occurring within the switching material. These subjects are dealt with in this review, with the aim of presenting the most recent advancements in the treatment of variability in resistive memories.
Original languageEnglish (US)
Pages (from-to)2200338
JournalAdvanced Intelligent Systems
DOIs
StatePublished - Mar 14 2023

Fingerprint

Dive into the research topics of 'Variability in Resistive Memories'. Together they form a unique fingerprint.

Cite this