Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing

In this work, we demonstrate the potential of HfO₂-based memristors as artificial synapses capable of reproducing biologically plausible spike-timing-dependent plasticity (STDP). W/HfO₂/Ti/TiN devices were fabricated and characterized, exhibiting reliable bipolar resistive switching, stable enduranc...

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Detalles Bibliográficos
Autores: Shooshtar, Mostafa, Pahlavan, Saeideh, Serrano Gotarredona, María Teresa, Linares Barranco, Bernabé
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/179766
Acceso en línea:https://hdl.handle.net/11441/179766
https://doi.org/10.1088/2634-4386/ae1da1
Access Level:acceso abierto
Palabra clave:HfO₂ memristor
Spike-timing-dependent plasticity (STDP)
Neuromorphic computing
Synaptic plasticity
Resistive switching
Artificial synapse
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spelling Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computingShooshtar, MostafaPahlavan, SaeidehSerrano Gotarredona, María TeresaLinares Barranco, BernabéHfO₂ memristorSpike-timing-dependent plasticity (STDP)Neuromorphic computingSynaptic plasticityResistive switchingArtificial synapseIn this work, we demonstrate the potential of HfO₂-based memristors as artificial synapses capable of reproducing biologically plausible spike-timing-dependent plasticity (STDP). W/HfO₂/Ti/TiN devices were fabricated and characterized, exhibiting reliable bipolar resistive switching, stable endurance, and reproducible resistance states across multiple cells and devices. The excitatory postsynaptic current (EPSC) response under sequential voltage pulses revealed gradual potentiation, depression, and saturation dynamics, closely resembling long-term potentiation, long-term depression, and synaptic consolidation in biological systems. Furthermore, the memristors successfully emulated higher-order learning rules, including triplet-STDP and frequency-dependent plasticity, while maintaining robust performance under biologically realistic noise conditions, exhibiting less than ±2% variation under voltage perturbations and ±2.5% under spike-timing jitter across 25 trials. A compact physical model captured the interplay between vacancy-driven filament dynamics and time-dependent weight modulation, yielding STDP curves consistent withexperimentalobservations in neuroscience. These findings highlight HfO₂ memristors as promising candidates for neuromorphic computing, providing not only a faithful hardware realization of synaptic learning but also compatibility with large-scale, CMOS-integrated architectures for next-generation cognitive processors.IOP PublishingArquitectura y Tecnología de ComputadoresEuropean Union (UE). H2020Ministerio para la Transformación Digital y de la Función Pública. EspañaEuropean Commission (EC)2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/179766https://doi.org/10.1088/2634-4386/ae1da1reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésNeuromorphic Computing and Engineering, 5 (4), 044008.EU Grant 101070908PID2023- 149071NB-C51TSI-069100-2023-001https://iopscience.iop.org/article/10.1088/2634-4386/ae1da1info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1797662026-06-17T12:51:07Z
dc.title.none.fl_str_mv Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
title Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
spellingShingle Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
Shooshtar, Mostafa
HfO₂ memristor
Spike-timing-dependent plasticity (STDP)
Neuromorphic computing
Synaptic plasticity
Resistive switching
Artificial synapse
title_short Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
title_full Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
title_fullStr Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
title_full_unstemmed Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
title_sort Spike-timing-dependent plasticity and synaptic consolidation in Hfo₂ memristors for adaptive neuromorphic computing
dc.creator.none.fl_str_mv Shooshtar, Mostafa
Pahlavan, Saeideh
Serrano Gotarredona, María Teresa
Linares Barranco, Bernabé
author Shooshtar, Mostafa
author_facet Shooshtar, Mostafa
Pahlavan, Saeideh
Serrano Gotarredona, María Teresa
Linares Barranco, Bernabé
author_role author
author2 Pahlavan, Saeideh
Serrano Gotarredona, María Teresa
Linares Barranco, Bernabé
author2_role author
author
author
dc.contributor.none.fl_str_mv Arquitectura y Tecnología de Computadores
European Union (UE). H2020
Ministerio para la Transformación Digital y de la Función Pública. España
European Commission (EC)
dc.subject.none.fl_str_mv HfO₂ memristor
Spike-timing-dependent plasticity (STDP)
Neuromorphic computing
Synaptic plasticity
Resistive switching
Artificial synapse
topic HfO₂ memristor
Spike-timing-dependent plasticity (STDP)
Neuromorphic computing
Synaptic plasticity
Resistive switching
Artificial synapse
description In this work, we demonstrate the potential of HfO₂-based memristors as artificial synapses capable of reproducing biologically plausible spike-timing-dependent plasticity (STDP). W/HfO₂/Ti/TiN devices were fabricated and characterized, exhibiting reliable bipolar resistive switching, stable endurance, and reproducible resistance states across multiple cells and devices. The excitatory postsynaptic current (EPSC) response under sequential voltage pulses revealed gradual potentiation, depression, and saturation dynamics, closely resembling long-term potentiation, long-term depression, and synaptic consolidation in biological systems. Furthermore, the memristors successfully emulated higher-order learning rules, including triplet-STDP and frequency-dependent plasticity, while maintaining robust performance under biologically realistic noise conditions, exhibiting less than ±2% variation under voltage perturbations and ±2.5% under spike-timing jitter across 25 trials. A compact physical model captured the interplay between vacancy-driven filament dynamics and time-dependent weight modulation, yielding STDP curves consistent withexperimentalobservations in neuroscience. These findings highlight HfO₂ memristors as promising candidates for neuromorphic computing, providing not only a faithful hardware realization of synaptic learning but also compatibility with large-scale, CMOS-integrated architectures for next-generation cognitive processors.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/179766
https://doi.org/10.1088/2634-4386/ae1da1
url https://hdl.handle.net/11441/179766
https://doi.org/10.1088/2634-4386/ae1da1
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Neuromorphic Computing and Engineering, 5 (4), 044008.
EU Grant 101070908
PID2023- 149071NB-C51
TSI-069100-2023-001
https://iopscience.iop.org/article/10.1088/2634-4386/ae1da1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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