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dc.contributor.author
Di Francesco, Francisco
dc.contributor.author
Sanca, Gabriel Andrés
dc.contributor.author
Quinteros, Cynthia Paula
dc.date.available
2022-09-01T14:02:41Z
dc.date.issued
2021-11
dc.identifier.citation
Di Francesco, Francisco; Sanca, Gabriel Andrés; Quinteros, Cynthia Paula; Spatiotemporal evolution of resistance state in simulated memristive networks; American Institute of Physics; Applied Physics Letters; 119; 19; 11-2021; 1-5; 193502
dc.identifier.issn
0003-6951
dc.identifier.uri
http://hdl.handle.net/11336/167157
dc.description.abstract
Originally studied for their suitability to store information compactly, memristive networks are now being analyzed as implementations of neuromorphic circuits. An extremely high number of elements is, thus, mandatory. To surpass the limited achievable connectivity - due to the featuring size - exploiting self-assemblies has been proposed as an alternative, in turn posing new challenges. In an attempt for offering insight on what to expect when characterizing the collective electrical response of switching assemblies, in this work, networks of memristive elements are simulated. Collective electrical behavior and maps of resistance states are characterized upon different electrical stimuli. By comparing the response of homogeneous and heterogeneous networks, we delineate differences that might be experimentally observed when the number of memristive units is scaled up and disorder arises as an inevitable feature.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Institute of Physics
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Memristive networks
dc.subject
Memristor
dc.subject
Self assembly
dc.subject
SPICE
dc.subject.classification
Ingeniería Eléctrica y Electrónica
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Spatiotemporal evolution of resistance state in simulated memristive networks
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2022-08-31T14:40:18Z
dc.identifier.eissn
1077-3118
dc.journal.volume
119
dc.journal.number
19
dc.journal.pagination
1-5; 193502
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Nueva York
dc.description.fil
Fil: Di Francesco, Francisco. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
dc.description.fil
Fil: Sanca, Gabriel Andrés. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
dc.description.fil
Fil: Quinteros, Cynthia Paula. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
dc.journal.title
Applied Physics Letters
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://aip.scitation.org/doi/10.1063/5.0067048
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1063/5.0067048
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