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Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing

The development of brain-inspired neuromorphic computing, including artificial intelligence (AI) and machine learning, is of considerable importance because of the rapid growth in hardware and software capacities, which allows for the efficient handling of big data. Devices for neuromorphic computin...

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Autores principales: Lee, Tae-Ju, Kim, Su-Kyung, Seong, Tae-Yeon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113278/
https://www.ncbi.nlm.nih.gov/pubmed/32238846
http://dx.doi.org/10.1038/s41598-020-62642-3
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author Lee, Tae-Ju
Kim, Su-Kyung
Seong, Tae-Yeon
author_facet Lee, Tae-Ju
Kim, Su-Kyung
Seong, Tae-Yeon
author_sort Lee, Tae-Ju
collection PubMed
description The development of brain-inspired neuromorphic computing, including artificial intelligence (AI) and machine learning, is of considerable importance because of the rapid growth in hardware and software capacities, which allows for the efficient handling of big data. Devices for neuromorphic computing must satisfy basic requirements such as multilevel states, high operating speeds, low energy consumption, and sufficient endurance, retention and linearity. In this study, inorganic perovskite-type amorphous strontium vanadate (a-SrVO(x): a-SVO) synthesized at room temperature is utilized to produce a high-performance memristor that demonstrates nonvolatile multilevel resistive switching and synaptic characteristics. Analysis of the electrical characteristics indicates that the a-SVO memristor illustrates typical bipolar resistive switching behavior. Multilevel resistance states are also observed in the off-to-on and on-to-off transition processes. The retention resistance of the a-SVO memristor is shown to not significantly change for a period of 2 × 10(4) s. The conduction mechanism operating within the Ag/a-SVO/Pt memristor is ascribed to the formation of Ag-based filaments. Nonlinear neural network simulations are also conducted to evaluate the synaptic behavior. These results demonstrate that a-SVO-based memristors hold great promise for use in high-performance neuromorphic computing devices.
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spelling pubmed-71132782020-04-06 Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing Lee, Tae-Ju Kim, Su-Kyung Seong, Tae-Yeon Sci Rep Article The development of brain-inspired neuromorphic computing, including artificial intelligence (AI) and machine learning, is of considerable importance because of the rapid growth in hardware and software capacities, which allows for the efficient handling of big data. Devices for neuromorphic computing must satisfy basic requirements such as multilevel states, high operating speeds, low energy consumption, and sufficient endurance, retention and linearity. In this study, inorganic perovskite-type amorphous strontium vanadate (a-SrVO(x): a-SVO) synthesized at room temperature is utilized to produce a high-performance memristor that demonstrates nonvolatile multilevel resistive switching and synaptic characteristics. Analysis of the electrical characteristics indicates that the a-SVO memristor illustrates typical bipolar resistive switching behavior. Multilevel resistance states are also observed in the off-to-on and on-to-off transition processes. The retention resistance of the a-SVO memristor is shown to not significantly change for a period of 2 × 10(4) s. The conduction mechanism operating within the Ag/a-SVO/Pt memristor is ascribed to the formation of Ag-based filaments. Nonlinear neural network simulations are also conducted to evaluate the synaptic behavior. These results demonstrate that a-SVO-based memristors hold great promise for use in high-performance neuromorphic computing devices. Nature Publishing Group UK 2020-04-01 /pmc/articles/PMC7113278/ /pubmed/32238846 http://dx.doi.org/10.1038/s41598-020-62642-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Lee, Tae-Ju
Kim, Su-Kyung
Seong, Tae-Yeon
Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing
title Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing
title_full Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing
title_fullStr Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing
title_full_unstemmed Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing
title_short Sputtering-deposited amorphous SrVO(x)-based memristor for use in neuromorphic computing
title_sort sputtering-deposited amorphous srvo(x)-based memristor for use in neuromorphic computing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113278/
https://www.ncbi.nlm.nih.gov/pubmed/32238846
http://dx.doi.org/10.1038/s41598-020-62642-3
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