Artificial Synaptic Performance with Learning Behavior for Memristor Fabricated with Stacked Solution-Processed Switching Layers

Zongjie Shen; Chun Zhao; Tianshi Zhao; Wangying Xu; Yina Liu; Yanfei Qi; Ivona Z. Mitrovic; Li Yang; Ce Zhou Zhao

doi:10.1021/acsaelm.0c01094

Artificial Synaptic Performance with Learning Behavior for Memristor Fabricated with Stacked Solution-Processed Switching Layers

Zongjie Shen, Chun Zhao^*, Tianshi Zhao, Wangying Xu, Yina Liu, Yanfei Qi, Ivona Z. Mitrovic, Li Yang, Ce Zhou Zhao

^*Corresponding author for this work

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

26 Citations (Scopus)

Abstract

As one of the promising next-generation electronics, brain-inspired synaptic resistive random access memory (RRAM) devices with stacked solution-processed (SP) spin-coated resistive switching (RS) layers were fabricated in this work. Compared with the RRAM device with a single SP-RS layer (Ag/SP-AlOx/ITO), the device with stacked SP-RS layers (Ag/SP-GaOx/SP-AlOx/ITO) is induced by the metal conductive filament performed with lower power consumption (∼±0.6 V operation voltage), larger read and write capability (∼2 × 104 ON/OFF ratio), and enhanced stability (>2 × 104 s retention time and >1000 endurance cycles). Multiple conductance states with long-term potentiation and depression (200 pulses) were obtained on Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, which resulted in the human brain-like behavior (learning-forgetting-relearning) of a matrix comprising of RRAM devices with SP-GaOx/SP-AlOx layers. Based on the synaptic performance of Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, an image recognition process based on a neuron network was conducted and the average recognition accuracy was close to 90%.

Original language	English
Pages (from-to)	1288-1300
Number of pages	13
Journal	ACS Applied Electronic Materials
Volume	3
Issue number	3
DOIs	https://doi.org/10.1021/acsaelm.0c01094
Publication status	Published - 23 Mar 2021

Keywords

image recognition
resistive switching
solution-processed RRAM
stacked layers
synaptic behavior

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10.1021/acsaelm.0c01094

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Shen, Z., Zhao, C., Zhao, T., Xu, W., Liu, Y., Qi, Y., Mitrovic, I. Z., Yang, L., & Zhao, C. Z. (2021). Artificial Synaptic Performance with Learning Behavior for Memristor Fabricated with Stacked Solution-Processed Switching Layers. ACS Applied Electronic Materials, 3(3), 1288-1300. https://doi.org/10.1021/acsaelm.0c01094

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title = "Artificial Synaptic Performance with Learning Behavior for Memristor Fabricated with Stacked Solution-Processed Switching Layers",

abstract = "As one of the promising next-generation electronics, brain-inspired synaptic resistive random access memory (RRAM) devices with stacked solution-processed (SP) spin-coated resistive switching (RS) layers were fabricated in this work. Compared with the RRAM device with a single SP-RS layer (Ag/SP-AlOx/ITO), the device with stacked SP-RS layers (Ag/SP-GaOx/SP-AlOx/ITO) is induced by the metal conductive filament performed with lower power consumption (∼±0.6 V operation voltage), larger read and write capability (∼2 × 104 ON/OFF ratio), and enhanced stability (>2 × 104 s retention time and >1000 endurance cycles). Multiple conductance states with long-term potentiation and depression (200 pulses) were obtained on Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, which resulted in the human brain-like behavior (learning-forgetting-relearning) of a matrix comprising of RRAM devices with SP-GaOx/SP-AlOx layers. Based on the synaptic performance of Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, an image recognition process based on a neuron network was conducted and the average recognition accuracy was close to 90%.",

keywords = "image recognition, resistive switching, solution-processed RRAM, stacked layers, synaptic behavior",

author = "Zongjie Shen and Chun Zhao and Tianshi Zhao and Wangying Xu and Yina Liu and Yanfei Qi and Mitrovic, {Ivona Z.} and Li Yang and Zhao, {Ce Zhou}",

note = "Funding Information: Author I.Z.M. acknowledges the British Council UKIERI project no. IND/CONT/G/17-18/18 and f.no.184-1/2018(IC). Funding Information: This research was funded in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China Program (19KJB510059), the Suzhou Science and Technology Development Planning Project: Key Industrial Technology Innovation (SYG201924), and the Key Program Special Fund in XJTLU (KSF-P-02, KSF-T-03, KSF-A-04, KSF-A-05, KSF-A-07). Publisher Copyright: {\textcopyright} 2021 American Chemical Society.",

year = "2021",

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doi = "10.1021/acsaelm.0c01094",

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T1 - Artificial Synaptic Performance with Learning Behavior for Memristor Fabricated with Stacked Solution-Processed Switching Layers

AU - Shen, Zongjie

AU - Zhao, Chun

AU - Zhao, Tianshi

AU - Xu, Wangying

AU - Liu, Yina

AU - Qi, Yanfei

AU - Mitrovic, Ivona Z.

AU - Yang, Li

AU - Zhao, Ce Zhou

N1 - Funding Information: Author I.Z.M. acknowledges the British Council UKIERI project no. IND/CONT/G/17-18/18 and f.no.184-1/2018(IC). Funding Information: This research was funded in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China Program (19KJB510059), the Suzhou Science and Technology Development Planning Project: Key Industrial Technology Innovation (SYG201924), and the Key Program Special Fund in XJTLU (KSF-P-02, KSF-T-03, KSF-A-04, KSF-A-05, KSF-A-07). Publisher Copyright: © 2021 American Chemical Society.

PY - 2021/3/23

Y1 - 2021/3/23

N2 - As one of the promising next-generation electronics, brain-inspired synaptic resistive random access memory (RRAM) devices with stacked solution-processed (SP) spin-coated resistive switching (RS) layers were fabricated in this work. Compared with the RRAM device with a single SP-RS layer (Ag/SP-AlOx/ITO), the device with stacked SP-RS layers (Ag/SP-GaOx/SP-AlOx/ITO) is induced by the metal conductive filament performed with lower power consumption (∼±0.6 V operation voltage), larger read and write capability (∼2 × 104 ON/OFF ratio), and enhanced stability (>2 × 104 s retention time and >1000 endurance cycles). Multiple conductance states with long-term potentiation and depression (200 pulses) were obtained on Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, which resulted in the human brain-like behavior (learning-forgetting-relearning) of a matrix comprising of RRAM devices with SP-GaOx/SP-AlOx layers. Based on the synaptic performance of Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, an image recognition process based on a neuron network was conducted and the average recognition accuracy was close to 90%.

AB - As one of the promising next-generation electronics, brain-inspired synaptic resistive random access memory (RRAM) devices with stacked solution-processed (SP) spin-coated resistive switching (RS) layers were fabricated in this work. Compared with the RRAM device with a single SP-RS layer (Ag/SP-AlOx/ITO), the device with stacked SP-RS layers (Ag/SP-GaOx/SP-AlOx/ITO) is induced by the metal conductive filament performed with lower power consumption (∼±0.6 V operation voltage), larger read and write capability (∼2 × 104 ON/OFF ratio), and enhanced stability (>2 × 104 s retention time and >1000 endurance cycles). Multiple conductance states with long-term potentiation and depression (200 pulses) were obtained on Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, which resulted in the human brain-like behavior (learning-forgetting-relearning) of a matrix comprising of RRAM devices with SP-GaOx/SP-AlOx layers. Based on the synaptic performance of Ag/SP-GaOx/SP-AlOx/ITO RRAM devices, an image recognition process based on a neuron network was conducted and the average recognition accuracy was close to 90%.

KW - image recognition

KW - resistive switching

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KW - stacked layers

KW - synaptic behavior

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JO - ACS Applied Electronic Materials

JF - ACS Applied Electronic Materials

IS - 3

ER -

Artificial Synaptic Performance with Learning Behavior for Memristor Fabricated with Stacked Solution-Processed Switching Layers

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Keywords

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