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Implementation of Physical Reservoir Computing in a TaO x /FTO-Based Memristor Device

Author

Listed:
  • Dongyeol Ju

    (Department of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of Korea
    Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea)

  • Junyoung Ahn

    (Department of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of Korea)

  • Jungwoo Ho

    (Department of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of Korea)

  • Sungjun Kim

    (Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea)

  • Daewon Chung

    (Department of Advanced Battery Convergence Engineering, Dongguk University, Seoul 04620, Republic of Korea)

Abstract

As one of the solutions to overcome the current problems of computing systems, a resistive switching device, the TiN/TaO x /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 x /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 x /FTO device.

Suggested Citation

  • Dongyeol Ju & Junyoung Ahn & Jungwoo Ho & Sungjun Kim & Daewon Chung, 2023. "Implementation of Physical Reservoir Computing in a TaO x /FTO-Based Memristor Device," Mathematics, MDPI, vol. 11(20), pages 1-12, October.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:20:p:4325-:d:1261665
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