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Nano Research 2023, 16(7): 10222-10233 https://doi.org/10.1007/s12274-023-5639-5
Research Article | Issue | Published: 20 April 2023

Titanium oxide artificial synaptic device: Nanostructure modeling and synthesis, memristive cross-bar fabrication, and resistive switching investigation

Show Author's Information Vadim I. Avilov1,2,  Roman V. Tominov1,2,  Zakhar E. Vakulov1,2,  Lev G. Zhavoronkov1,2,  Vladimir A. Smirnov1,2( )
Research Laboratory Neuroelectronics and Memristive Nanomaterials (NEUROMENA Lab), Southern Federal University, Taganrog 347922, Russia
Institute of Nanotechnologies, Electronics and Electronic Equipment Engineering, Southern Federal University, Taganrog 347922, Russia
Keywords:
artificial intelligence, resistive switching, titanium oxide, scanning probe microscopy, neuromorphic systems, memristive cross bar
Topics:
Nanoelectronics
Cite this article:
Avilov VI, Tominov RV, Vakulov ZE, et al. Titanium oxide artificial synaptic device: Nanostructure modeling and synthesis, memristive cross-bar fabrication, and resistive switching investigation. Nano Research, 2023, 16(7): 10222-10233. https://doi.org/10.1007/s12274-023-5639-5
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Abstract Full text About this article

The paper shows the results of the mathematical model development and the numerical simulation of the oxygen vacancies, and the distribution of TiO, Ti2O3, and TiO2 oxides in the titanium oxide nanostructure obtained by local anodic oxidation (anodization). The effect of the anodization voltage pulse duration and amplitude on the titanium oxide composition distribution and the conduction channel formation was shown. Synaptic device prototypes based on electrochemical titanium oxide are fabricated and investigated. It was shown that forming free resistive switching between the low resistances state (LRS) 1.43 ± 0.54 kΩ and the high resistance state (HRS) 28.75 ± 9.75 kΩ were observed during 100,000 switching cycles and LRS 1.49 ± 0.23 kΩ was maintained for 10,000 s. Multilevel resistive switching of the synaptic device prototype was investigated. It was shown that increasing Uset from 0.5 to 1.5 V leads to different LRS from 3.96 ± 0.19 to 0.71 ± 0.10 kΩ. The results obtained can be used in the development of technological foundations for the formation of high-performance multilevel artificial synapses for elements of neuroelectronics and hardware neural networks.


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About this article

Titanium oxide artificial synaptic device: Nanostructure modeling and synthesis, memristive cross-bar fabrication, and resistive switching investigation

Show Author's information Vadim I. Avilov1,2, Roman V. Tominov1,2, Zakhar E. Vakulov1,2, Lev G. Zhavoronkov1,2, Vladimir A. Smirnov1,2( )
Research Laboratory Neuroelectronics and Memristive Nanomaterials (NEUROMENA Lab), Southern Federal University, Taganrog 347922, Russia
Institute of Nanotechnologies, Electronics and Electronic Equipment Engineering, Southern Federal University, Taganrog 347922, Russia

Abstract

The paper shows the results of the mathematical model development and the numerical simulation of the oxygen vacancies, and the distribution of TiO, Ti2O3, and TiO2 oxides in the titanium oxide nanostructure obtained by local anodic oxidation (anodization). The effect of the anodization voltage pulse duration and amplitude on the titanium oxide composition distribution and the conduction channel formation was shown. Synaptic device prototypes based on electrochemical titanium oxide are fabricated and investigated. It was shown that forming free resistive switching between the low resistances state (LRS) 1.43 ± 0.54 kΩ and the high resistance state (HRS) 28.75 ± 9.75 kΩ were observed during 100,000 switching cycles and LRS 1.49 ± 0.23 kΩ was maintained for 10,000 s. Multilevel resistive switching of the synaptic device prototype was investigated. It was shown that increasing Uset from 0.5 to 1.5 V leads to different LRS from 3.96 ± 0.19 to 0.71 ± 0.10 kΩ. The results obtained can be used in the development of technological foundations for the formation of high-performance multilevel artificial synapses for elements of neuroelectronics and hardware neural networks.

Keywords: artificial intelligence, resistive switching, titanium oxide, scanning probe microscopy, neuromorphic systems, memristive cross bar

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Publication history
Copyright
Acknowledgements

Publication history

Received: 23 December 2022
Revised: 17 February 2023
Accepted: 05 March 2023
Published: 20 April 2023
Issue date: July 2023

Copyright

© Tsinghua University Press 2023

Acknowledgements

Acknowledgements

The reported study was funded by the Russian Federation Government (Agreement No. 075-15-2022-1123) (mathematical model development and theoretical calculations). The fabrication of memristor structures and their resistive switching investigation were supported by a grant from the Russian Science Foundation No. 22-79-10215, https://rscf.ru/project/22-79-10215/, at Southern Federal University. Multilevel switching was researched with the financial support of the grant of the President of the Russian Federation МК-2290.2022.4.

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