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Sputtering-deposited amorphous SrVOx-based memristor for use in neuromorphic computing.
Sci Rep. 2020 Apr 01; 10(1):5761.SR

Abstract

The development of brain-inspired neuromorphic computing, including artificial intelligence (AI) and machine learning, is of considerable importance because of the rapid growth in hardware and software capacities, which allows for the efficient handling of big data. Devices for neuromorphic computing must satisfy basic requirements such as multilevel states, high operating speeds, low energy consumption, and sufficient endurance, retention and linearity. In this study, inorganic perovskite-type amorphous strontium vanadate (a-SrVOx: a-SVO) synthesized at room temperature is utilized to produce a high-performance memristor that demonstrates nonvolatile multilevel resistive switching and synaptic characteristics. Analysis of the electrical characteristics indicates that the a-SVO memristor illustrates typical bipolar resistive switching behavior. Multilevel resistance states are also observed in the off-to-on and on-to-off transition processes. The retention resistance of the a-SVO memristor is shown to not significantly change for a period of 2 × 104 s. The conduction mechanism operating within the Ag/a-SVO/Pt memristor is ascribed to the formation of Ag-based filaments. Nonlinear neural network simulations are also conducted to evaluate the synaptic behavior. These results demonstrate that a-SVO-based memristors hold great promise for use in high-performance neuromorphic computing devices.

Authors+Show Affiliations

Department of Nanophotonics, Korea University, Seoul, 02841, Korea.Department of Materials Science and Engineering, Korea University, Seoul, 02841, Korea.Department of Nanophotonics, Korea University, Seoul, 02841, Korea. tyseong@korea.ac.kr. Department of Materials Science and Engineering, Korea University, Seoul, 02841, Korea. tyseong@korea.ac.kr.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32238846

Citation

Lee, Tae-Ju, et al. "Sputtering-deposited Amorphous SrVOx-based Memristor for Use in Neuromorphic Computing." Scientific Reports, vol. 10, no. 1, 2020, p. 5761.
Lee TJ, Kim SK, Seong TY. Sputtering-deposited amorphous SrVOx-based memristor for use in neuromorphic computing. Sci Rep. 2020;10(1):5761.
Lee, T. J., Kim, S. K., & Seong, T. Y. (2020). Sputtering-deposited amorphous SrVOx-based memristor for use in neuromorphic computing. Scientific Reports, 10(1), 5761. https://doi.org/10.1038/s41598-020-62642-3
Lee TJ, Kim SK, Seong TY. Sputtering-deposited Amorphous SrVOx-based Memristor for Use in Neuromorphic Computing. Sci Rep. 2020 Apr 1;10(1):5761. PubMed PMID: 32238846.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Sputtering-deposited amorphous SrVOx-based memristor for use in neuromorphic computing. AU - Lee,Tae-Ju, AU - Kim,Su-Kyung, AU - Seong,Tae-Yeon, Y1 - 2020/04/01/ PY - 2020/01/04/received PY - 2020/03/17/accepted PY - 2020/4/3/entrez PY - 2020/4/3/pubmed PY - 2020/4/3/medline SP - 5761 EP - 5761 JF - Scientific reports JO - Sci Rep VL - 10 IS - 1 N2 - The development of brain-inspired neuromorphic computing, including artificial intelligence (AI) and machine learning, is of considerable importance because of the rapid growth in hardware and software capacities, which allows for the efficient handling of big data. Devices for neuromorphic computing must satisfy basic requirements such as multilevel states, high operating speeds, low energy consumption, and sufficient endurance, retention and linearity. In this study, inorganic perovskite-type amorphous strontium vanadate (a-SrVOx: a-SVO) synthesized at room temperature is utilized to produce a high-performance memristor that demonstrates nonvolatile multilevel resistive switching and synaptic characteristics. Analysis of the electrical characteristics indicates that the a-SVO memristor illustrates typical bipolar resistive switching behavior. Multilevel resistance states are also observed in the off-to-on and on-to-off transition processes. The retention resistance of the a-SVO memristor is shown to not significantly change for a period of 2 × 104 s. The conduction mechanism operating within the Ag/a-SVO/Pt memristor is ascribed to the formation of Ag-based filaments. Nonlinear neural network simulations are also conducted to evaluate the synaptic behavior. These results demonstrate that a-SVO-based memristors hold great promise for use in high-performance neuromorphic computing devices. SN - 2045-2322 UR - https://www.unboundmedicine.com/medline/citation/32238846/Sputtering_deposited_amorphous_SrVOx_based_memristor_for_use_in_neuromorphic_computing_ L2 - http://dx.doi.org/10.1038/s41598-020-62642-3 DB - PRIME DP - Unbound Medicine ER -
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