Adaptive threshold in TiO2-based synapses

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Abstract: We measured and analyzed the dynamic and remnant current-voltages curves of Al/TiO2/Au and Ni/TiO2/Ni/Au memory devices in order to understand the conduction mechanisms and their synapselike memory properties. Current levels and switching threshold voltages are strongly affected by the m...

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Detalles Bibliográficos
Autores principales: Ghenzi, N., Barella, M., Rubi, D., Acha, C.
Formato: Artículo
Lenguaje:Inglés
Publicado: IOP Publishing 2022
Materias:
COMPUTACION
SINAPSIS
MEMORIA
Acceso en línea:https://repositorio.uca.edu.ar/handle/123456789/14709
Aporte de:
Repositorio Institucional de la Universidad Católica Argentina (UCA) de Universidad Católica Argentina
id I33-R139-123456789-14709
record_format dspace
institution Universidad Católica Argentina
institution_str I-33
repository_str R-139
collection Repositorio Institucional de la Universidad Católica Argentina (UCA)
language Inglés
topic COMPUTACION
SINAPSIS
MEMORIA
spellingShingle COMPUTACION
SINAPSIS
MEMORIA
Ghenzi, N.
Barella, M.
Rubi, D.
Acha, C.
Adaptive threshold in TiO2-based synapses
topic_facet COMPUTACION
SINAPSIS
MEMORIA
description Abstract: We measured and analyzed the dynamic and remnant current-voltages curves of Al/TiO2/Au and Ni/TiO2/Ni/Au memory devices in order to understand the conduction mechanisms and their synapselike memory properties. Current levels and switching threshold voltages are strongly affected by the metal used for the electrode. We propose a non-trivial circuit model which captures in detail the currentvoltage response of both kinds of devices. We found that, for the former device, the voltage threshold can be maintained constant, independently of the applied voltage history, while for the latter, a limiting resistor controls the threshold voltages behavior, being the origin of their dependence on the resistance value previous to the switching. The identification of the conduction mechanisms across the device allows optimizing the memristor performance and determining the best electrode choice to improve the device synapse-emulation abilities.
format Artículo
author Ghenzi, N.
Barella, M.
Rubi, D.
Acha, C.
author_facet Ghenzi, N.
Barella, M.
Rubi, D.
Acha, C.
author_sort Ghenzi, N.
title Adaptive threshold in TiO2-based synapses
title_short Adaptive threshold in TiO2-based synapses
title_full Adaptive threshold in TiO2-based synapses
title_fullStr Adaptive threshold in TiO2-based synapses
title_full_unstemmed Adaptive threshold in TiO2-based synapses
title_sort adaptive threshold in tio2-based synapses
publisher IOP Publishing
publishDate 2022
url https://repositorio.uca.edu.ar/handle/123456789/14709
work_keys_str_mv AT ghenzin adaptivethresholdintio2basedsynapses
AT barellam adaptivethresholdintio2basedsynapses
AT rubid adaptivethresholdintio2basedsynapses
AT achac adaptivethresholdintio2basedsynapses
bdutipo_str Repositorios
_version_ 1764820523712249856

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