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Organismic Memristive Structures With Variable Functionality for Neuroelectronics
In this paper, we report an approach to design nanolayered memristive compositions based on TiO(2)/Al(2)O(3) bilayer structures with analog non-volatile and volatile tuning of the resistance. The structure of the TiO(2) layer drives the physical mechanism underlying the non-volatile resistance switc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238295/ https://www.ncbi.nlm.nih.gov/pubmed/35774561 http://dx.doi.org/10.3389/fnins.2022.913618 |
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author | Andreeva, Natalia V. Ryndin, Eugeny A. Mazing, Dmitriy S. Vilkov, Oleg Y. Luchinin, Victor V. |
author_facet | Andreeva, Natalia V. Ryndin, Eugeny A. Mazing, Dmitriy S. Vilkov, Oleg Y. Luchinin, Victor V. |
author_sort | Andreeva, Natalia V. |
collection | PubMed |
description | In this paper, we report an approach to design nanolayered memristive compositions based on TiO(2)/Al(2)O(3) bilayer structures with analog non-volatile and volatile tuning of the resistance. The structure of the TiO(2) layer drives the physical mechanism underlying the non-volatile resistance switching, which can be changed from electronic to ionic, enabling the synaptic behavior emulation. The presence of the anatase phase in the amorphous TiO(2) layer induces the resistive switching mechanism due to electronic processes. In this case, the switching of the resistance within the range of seven orders of magnitude is experimentally observed. In the bilayer with amorphous titanium dioxide, the participation of ionic processes in the switching mechanism results in narrowing the tuning range down to 2–3 orders of magnitude and increasing the operating voltages. In this way, a combination of TiO(2)/Al(2)O(3) bilayers with inert electrodes enables synaptic behavior emulation, while active electrodes induce the neuronal behavior caused by cation density variation in the active Al(2)O(3) layer of the structure. We consider that the proposed approach could help to explore the memristive capabilities of nanolayered compositions in a more functional way, enabling implementation of artificial neural network algorithms at the material level and simplifying neuromorphic layouts, while maintaining all benefits of neuromorphic architectures. |
format | Online Article Text |
id | pubmed-9238295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92382952022-06-29 Organismic Memristive Structures With Variable Functionality for Neuroelectronics Andreeva, Natalia V. Ryndin, Eugeny A. Mazing, Dmitriy S. Vilkov, Oleg Y. Luchinin, Victor V. Front Neurosci Neuroscience In this paper, we report an approach to design nanolayered memristive compositions based on TiO(2)/Al(2)O(3) bilayer structures with analog non-volatile and volatile tuning of the resistance. The structure of the TiO(2) layer drives the physical mechanism underlying the non-volatile resistance switching, which can be changed from electronic to ionic, enabling the synaptic behavior emulation. The presence of the anatase phase in the amorphous TiO(2) layer induces the resistive switching mechanism due to electronic processes. In this case, the switching of the resistance within the range of seven orders of magnitude is experimentally observed. In the bilayer with amorphous titanium dioxide, the participation of ionic processes in the switching mechanism results in narrowing the tuning range down to 2–3 orders of magnitude and increasing the operating voltages. In this way, a combination of TiO(2)/Al(2)O(3) bilayers with inert electrodes enables synaptic behavior emulation, while active electrodes induce the neuronal behavior caused by cation density variation in the active Al(2)O(3) layer of the structure. We consider that the proposed approach could help to explore the memristive capabilities of nanolayered compositions in a more functional way, enabling implementation of artificial neural network algorithms at the material level and simplifying neuromorphic layouts, while maintaining all benefits of neuromorphic architectures. Frontiers Media S.A. 2022-06-14 /pmc/articles/PMC9238295/ /pubmed/35774561 http://dx.doi.org/10.3389/fnins.2022.913618 Text en Copyright © 2022 Andreeva, Ryndin, Mazing, Vilkov and Luchinin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Andreeva, Natalia V. Ryndin, Eugeny A. Mazing, Dmitriy S. Vilkov, Oleg Y. Luchinin, Victor V. Organismic Memristive Structures With Variable Functionality for Neuroelectronics |
title | Organismic Memristive Structures With Variable Functionality for Neuroelectronics |
title_full | Organismic Memristive Structures With Variable Functionality for Neuroelectronics |
title_fullStr | Organismic Memristive Structures With Variable Functionality for Neuroelectronics |
title_full_unstemmed | Organismic Memristive Structures With Variable Functionality for Neuroelectronics |
title_short | Organismic Memristive Structures With Variable Functionality for Neuroelectronics |
title_sort | organismic memristive structures with variable functionality for neuroelectronics |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9238295/ https://www.ncbi.nlm.nih.gov/pubmed/35774561 http://dx.doi.org/10.3389/fnins.2022.913618 |
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