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dc.contributor.authorRoldan, Juan B
dc.contributor.authorMaldonado Correa, David 
dc.contributor.authorJiménez Molinos, Francisco 
dc.date.accessioned2023-10-20T08:36:02Z
dc.date.available2023-10-20T08:36:02Z
dc.date.issued2023-03-14
dc.identifier.citationRoldán, J. B., Miranda, E., Maldonado, D., Mikhaylov, A. N., Agudov, N. V., Dubkov, A. A., ... & Chua, L. O. (2023). Variability in resistive memories. Advanced Intelligent[DOI: 10.1002/aisy.202200338] Systems, 2200338.es_ES
dc.identifier.urihttps://hdl.handle.net/10481/85141
dc.description.abstractResistive 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.es_ES
dc.description.sponsorshipJunta de Andalucia B-TIC-624-UGR20 PID2021-128077NB-I00es_ES
dc.description.sponsorshipEuropean Union (EU)es_ES
dc.description.sponsorshipMCIN/AEI/FEDER A-FQM-66-UGR20 PGC2018-098860-B-I00es_ES
dc.description.sponsorshipSpanish Government RYC2020-030150-Ies_ES
dc.description.sponsorshipKing Abdullah University of Science & Technologyes_ES
dc.description.sponsorshipGovernment of the Russian Federation under Megagrant Program 074-02-2018-330 (2)es_ES
dc.description.sponsorshipMinistry of Science and Higher Education of the Russian Federation under "Priority-2030" Academic Excellence Program of the Lobachevsky State University of Nizhny Novgorod N-466-99_2021-2023es_ES
dc.description.sponsorshipEuropean project MEMQuD 20FUN06es_ES
dc.description.sponsorshipEMPIR programmees_ES
dc.description.sponsorshipHorizon 2020es_ES
dc.language.isoenges_ES
dc.publisherWileyes_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleVariability in Resistive Memorieses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1002/aisy.202200338
dc.type.hasVersionVoRes_ES


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