Multilevel resistive switching and synaptic plasticity of nanoparticulated cobaltite oxide memristive device

Tukaram D. Dongale; Atul C. Khot; Ashkan V. Takaloo; Kyung Rock Son; Tae Geun Kim

doi:10.1016/j.jmst.2020.10.046

Multilevel resistive switching and synaptic plasticity of nanoparticulated cobaltite oxide memristive device

Tukaram D. Dongale, Atul C. Khot, Ashkan V. Takaloo, Kyung Rock Son, Tae Geun Kim

Research output: Contribution to journal › Article › peer-review

35 Citations (Scopus)

Abstract

Multilevel resistive switching (RS) is a key property to embrace the full potential of memristive devices for non-volatile memory and neuromorphic computing applications. In this study, we employed nanoparticulated cobaltite oxide (Co₃O₄) as a model material to demonstrate the multilevel RS and synaptic learning capabilities because of its multiple and stable redox state properties. The Pt/Co₃O₄/Pt memristive device exhibited tunable RS properties with respect to different voltages and compliance currents (CC) without the electroforming process. That is, the device showed voltage-dependent RS at a higher CC whereas CC-dependent RS was observed at lower CC. The device showed four different resistance states during endurance and retention measurements and non-volatile memory results indicated that the CC-based measurement had less variation. Besides, we investigated the basic and complex synaptic plasticity properties using the analog current-voltage characteristics of the Pt/Co₃O₄/Pt device. In particular, we mimicked the potentiation–depression and four-spike time-dependent plasticity (STDP) rules such as asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The results of the present work indicate that the cobaltite oxide is an excellent nanomaterial for both multilevel RS and neuromorphic computing applications.

Original language	English
Pages (from-to)	81-91
Number of pages	11
Journal	Journal of Materials Science and Technology
Volume	78
DOIs	https://doi.org/10.1016/j.jmst.2020.10.046
Publication status	Published - 2021 Jul 10

Bibliographical note

Funding Information:
This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2016R1A3B 1908249). The authors would like to thank the Samsung Semiconductor Research Center in Korea University for its support.

Funding Information:
This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2016R1A3B 1908249 ). The authors would like to thank the Samsung Semiconductor Research Center in Korea University for its support.

Publisher Copyright:
© 2020

Keywords

Cobaltite oxide
Memristive device
Multilevel resistive switching
STDP
Synaptic plasticity

ASJC Scopus subject areas

Ceramics and Composites
Mechanics of Materials
Mechanical Engineering
Polymers and Plastics
Metals and Alloys
Materials Chemistry

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10.1016/j.jmst.2020.10.046

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title = "Multilevel resistive switching and synaptic plasticity of nanoparticulated cobaltite oxide memristive device",

abstract = "Multilevel resistive switching (RS) is a key property to embrace the full potential of memristive devices for non-volatile memory and neuromorphic computing applications. In this study, we employed nanoparticulated cobaltite oxide (Co3O4) as a model material to demonstrate the multilevel RS and synaptic learning capabilities because of its multiple and stable redox state properties. The Pt/Co3O4/Pt memristive device exhibited tunable RS properties with respect to different voltages and compliance currents (CC) without the electroforming process. That is, the device showed voltage-dependent RS at a higher CC whereas CC-dependent RS was observed at lower CC. The device showed four different resistance states during endurance and retention measurements and non-volatile memory results indicated that the CC-based measurement had less variation. Besides, we investigated the basic and complex synaptic plasticity properties using the analog current-voltage characteristics of the Pt/Co3O4/Pt device. In particular, we mimicked the potentiation–depression and four-spike time-dependent plasticity (STDP) rules such as asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The results of the present work indicate that the cobaltite oxide is an excellent nanomaterial for both multilevel RS and neuromorphic computing applications.",

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author = "Dongale, {Tukaram D.} and Khot, {Atul C.} and Takaloo, {Ashkan V.} and Son, {Kyung Rock} and Kim, {Tae Geun}",

note = "Funding Information: This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2016R1A3B 1908249). The authors would like to thank the Samsung Semiconductor Research Center in Korea University for its support. Funding Information: This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2016R1A3B 1908249 ). The authors would like to thank the Samsung Semiconductor Research Center in Korea University for its support. Publisher Copyright: {\textcopyright} 2020",

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AU - Khot, Atul C.

AU - Takaloo, Ashkan V.

AU - Son, Kyung Rock

AU - Kim, Tae Geun

N1 - Funding Information: This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2016R1A3B 1908249). The authors would like to thank the Samsung Semiconductor Research Center in Korea University for its support. Funding Information: This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. 2016R1A3B 1908249 ). The authors would like to thank the Samsung Semiconductor Research Center in Korea University for its support. Publisher Copyright: © 2020

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N2 - Multilevel resistive switching (RS) is a key property to embrace the full potential of memristive devices for non-volatile memory and neuromorphic computing applications. In this study, we employed nanoparticulated cobaltite oxide (Co3O4) as a model material to demonstrate the multilevel RS and synaptic learning capabilities because of its multiple and stable redox state properties. The Pt/Co3O4/Pt memristive device exhibited tunable RS properties with respect to different voltages and compliance currents (CC) without the electroforming process. That is, the device showed voltage-dependent RS at a higher CC whereas CC-dependent RS was observed at lower CC. The device showed four different resistance states during endurance and retention measurements and non-volatile memory results indicated that the CC-based measurement had less variation. Besides, we investigated the basic and complex synaptic plasticity properties using the analog current-voltage characteristics of the Pt/Co3O4/Pt device. In particular, we mimicked the potentiation–depression and four-spike time-dependent plasticity (STDP) rules such as asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The results of the present work indicate that the cobaltite oxide is an excellent nanomaterial for both multilevel RS and neuromorphic computing applications.

AB - Multilevel resistive switching (RS) is a key property to embrace the full potential of memristive devices for non-volatile memory and neuromorphic computing applications. In this study, we employed nanoparticulated cobaltite oxide (Co3O4) as a model material to demonstrate the multilevel RS and synaptic learning capabilities because of its multiple and stable redox state properties. The Pt/Co3O4/Pt memristive device exhibited tunable RS properties with respect to different voltages and compliance currents (CC) without the electroforming process. That is, the device showed voltage-dependent RS at a higher CC whereas CC-dependent RS was observed at lower CC. The device showed four different resistance states during endurance and retention measurements and non-volatile memory results indicated that the CC-based measurement had less variation. Besides, we investigated the basic and complex synaptic plasticity properties using the analog current-voltage characteristics of the Pt/Co3O4/Pt device. In particular, we mimicked the potentiation–depression and four-spike time-dependent plasticity (STDP) rules such as asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The results of the present work indicate that the cobaltite oxide is an excellent nanomaterial for both multilevel RS and neuromorphic computing applications.

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Multilevel resistive switching and synaptic plasticity of nanoparticulated cobaltite oxide memristive device

Abstract

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Keywords

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