Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport

Abstract This paper presents a method for integrating neuronal and synaptic functions within a thin dual‐layer featuring distinct dielectric strengths. The dual‐layer consists of a conductive bottom layer (e.g., MXenes or rGOs) and a top layer with a lower dielectric strength (e.g., gallium oxide)....

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Main Authors: Suji Ha, YoungJu Park, Chanjin Lim, Eunyeong Yang, Taegil Kim, Seon Joon Kim, Junwoo Park
Format: Article
Language:English
Published: Wiley-VCH 2025-08-01
Series:Advanced Electronic Materials
Subjects:
Online Access:https://doi.org/10.1002/aelm.202500029
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author Suji Ha
YoungJu Park
Chanjin Lim
Eunyeong Yang
Taegil Kim
Seon Joon Kim
Junwoo Park
author_facet Suji Ha
YoungJu Park
Chanjin Lim
Eunyeong Yang
Taegil Kim
Seon Joon Kim
Junwoo Park
author_sort Suji Ha
collection DOAJ
description Abstract This paper presents a method for integrating neuronal and synaptic functions within a thin dual‐layer featuring distinct dielectric strengths. The dual‐layer consists of a conductive bottom layer (e.g., MXenes or rGOs) and a top layer with a lower dielectric strength (e.g., gallium oxide). The differing dielectric strengths between the layers facilitate the modulation of breakdown, as the magnitude of the electric field applied in one layer varies with the configuration of charge transport in the other layer. In a vertical configuration, the dual‐layer exhibits volatile and abrupt switching (neuronal behavior), while in a horizontal configuration, it demonstrates non‐volatile and gradual changes in conductance (synaptic behavior). The experimental results indicate that the abrupt switching is attributed to filament formation, while the gradual change in conductance arises from charge transport in gallium oxide. The dual‐layer shows the characteristics of integrate‐and‐fire depending on spiking signals with synaptic plasticity and achieves training accuracies of 91.4% and 82.3% for MNIST digit classification based on MXene and rGO, respectively.
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institution Kabale University
issn 2199-160X
language English
publishDate 2025-08-01
publisher Wiley-VCH
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series Advanced Electronic Materials
spelling doaj-art-de3b183e8bee4aa8a534fd80d101313d2025-08-20T03:59:22ZengWiley-VCHAdvanced Electronic Materials2199-160X2025-08-011112n/an/a10.1002/aelm.202500029Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge TransportSuji Ha0YoungJu Park1Chanjin Lim2Eunyeong Yang3Taegil Kim4Seon Joon Kim5Junwoo Park6Department of Chemistry Sogang University Seoul 04107 Republic of KoreaDepartment of Chemistry Sogang University Seoul 04107 Republic of KoreaDepartment of Chemistry Sogang University Seoul 04107 Republic of KoreaConvergence Research Center for Solutions to Electromagnetic Interference in Future‐mobility Korea Institute of Science and Technology Seoul 02792 Republic of KoreaDepartment of Chemistry Sogang University Seoul 04107 Republic of KoreaConvergence Research Center for Solutions to Electromagnetic Interference in Future‐mobility Korea Institute of Science and Technology Seoul 02792 Republic of KoreaDepartment of Chemistry Sogang University Seoul 04107 Republic of KoreaAbstract This paper presents a method for integrating neuronal and synaptic functions within a thin dual‐layer featuring distinct dielectric strengths. The dual‐layer consists of a conductive bottom layer (e.g., MXenes or rGOs) and a top layer with a lower dielectric strength (e.g., gallium oxide). The differing dielectric strengths between the layers facilitate the modulation of breakdown, as the magnitude of the electric field applied in one layer varies with the configuration of charge transport in the other layer. In a vertical configuration, the dual‐layer exhibits volatile and abrupt switching (neuronal behavior), while in a horizontal configuration, it demonstrates non‐volatile and gradual changes in conductance (synaptic behavior). The experimental results indicate that the abrupt switching is attributed to filament formation, while the gradual change in conductance arises from charge transport in gallium oxide. The dual‐layer shows the characteristics of integrate‐and‐fire depending on spiking signals with synaptic plasticity and achieves training accuracies of 91.4% and 82.3% for MNIST digit classification based on MXene and rGO, respectively.https://doi.org/10.1002/aelm.202500029artificial neuronartificial synapsecharge transportconductance switchingneuromorphic computing
spellingShingle Suji Ha
YoungJu Park
Chanjin Lim
Eunyeong Yang
Taegil Kim
Seon Joon Kim
Junwoo Park
Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport
Advanced Electronic Materials
artificial neuron
artificial synapse
charge transport
conductance switching
neuromorphic computing
title Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport
title_full Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport
title_fullStr Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport
title_full_unstemmed Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport
title_short Bifunctional Memristive Behavior of a Dual‐Layer Structure Depending on the Configuration of Charge Transport
title_sort bifunctional memristive behavior of a dual layer structure depending on the configuration of charge transport
topic artificial neuron
artificial synapse
charge transport
conductance switching
neuromorphic computing
url https://doi.org/10.1002/aelm.202500029
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AT eunyeongyang bifunctionalmemristivebehaviorofaduallayerstructuredependingontheconfigurationofchargetransport
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