Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device
As one of the solutions to overcome the current problems of computing systems, a resistive switching device, the TiN/TaO<sub>x</sub>/fluorine-doped tin oxide (FTO) stacked device, was fabricated to investigate its capability in embodying neuromorphic computing. The device showed good uni...
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MDPI AG
2023-10-01
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author | Dongyeol Ju Junyoung Ahn Jungwoo Ho Sungjun Kim Daewon Chung |
author_facet | Dongyeol Ju Junyoung Ahn Jungwoo Ho Sungjun Kim Daewon Chung |
author_sort | Dongyeol Ju |
collection | DOAJ |
description | As one of the solutions to overcome the current problems of computing systems, a resistive switching device, the TiN/TaO<sub>x</sub>/fluorine-doped tin oxide (FTO) stacked device, was fabricated to investigate its capability in embodying neuromorphic computing. The device showed good uniformity during the resistive switching phenomenon under time and cycle-to-cycle dependent switching, which may be due to the oxygen reservoir characteristics of the FTO bottom electrode, storing oxygen ions during resistive switching and enhancing the device property. Based on the uniform switching phenomenon of the TiN/TaO<sub>x</sub>/FTO device, the pulse applications were performed to seek its ability to mimic the biological brain. It was revealed that the volatile and non-volatile nature of the device can be altered by controlling the pulse stimuli, where strong stimuli result in long-term memory while weak stimuli result in short-term memory. To further investigate the key functions of the biological brain, various learning rules such as paired-pulse facilitation, excitatory postsynaptic current, potentiation and depression, spike-rate dependent plasticity, and spike-time dependent plasticity were tested, with reservoir computing implemented based on the volatile characteristic of the TiN/TaO<sub>x</sub>/FTO device. |
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language | English |
last_indexed | 2024-03-10T21:05:01Z |
publishDate | 2023-10-01 |
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spelling | doaj.art-ba57680467014706be733091e5b14cc72023-11-19T17:14:25ZengMDPI AGMathematics2227-73902023-10-011120432510.3390/math11204325Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor DeviceDongyeol Ju0Junyoung Ahn1Jungwoo Ho2Sungjun Kim3Daewon Chung4Department of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of KoreaDivision of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of KoreaAs one of the solutions to overcome the current problems of computing systems, a resistive switching device, the TiN/TaO<sub>x</sub>/fluorine-doped tin oxide (FTO) stacked device, was fabricated to investigate its capability in embodying neuromorphic computing. The device showed good uniformity during the resistive switching phenomenon under time and cycle-to-cycle dependent switching, which may be due to the oxygen reservoir characteristics of the FTO bottom electrode, storing oxygen ions during resistive switching and enhancing the device property. Based on the uniform switching phenomenon of the TiN/TaO<sub>x</sub>/FTO device, the pulse applications were performed to seek its ability to mimic the biological brain. It was revealed that the volatile and non-volatile nature of the device can be altered by controlling the pulse stimuli, where strong stimuli result in long-term memory while weak stimuli result in short-term memory. To further investigate the key functions of the biological brain, various learning rules such as paired-pulse facilitation, excitatory postsynaptic current, potentiation and depression, spike-rate dependent plasticity, and spike-time dependent plasticity were tested, with reservoir computing implemented based on the volatile characteristic of the TiN/TaO<sub>x</sub>/FTO device.https://www.mdpi.com/2227-7390/11/20/4325neuromorphicresistive switchingspike-time dependent plasticitynumber recognition systemreservoir computing |
spellingShingle | Dongyeol Ju Junyoung Ahn Jungwoo Ho Sungjun Kim Daewon Chung Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device Mathematics neuromorphic resistive switching spike-time dependent plasticity number recognition system reservoir computing |
title | Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device |
title_full | Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device |
title_fullStr | Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device |
title_full_unstemmed | Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device |
title_short | Implementation of Physical Reservoir Computing in a TaO<sub>x</sub>/FTO-Based Memristor Device |
title_sort | implementation of physical reservoir computing in a tao sub x sub fto based memristor device |
topic | neuromorphic resistive switching spike-time dependent plasticity number recognition system reservoir computing |
url | https://www.mdpi.com/2227-7390/11/20/4325 |
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