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Artificial synaptic characteristics of TiO2/HfO2 memristor with self-rectifying switching for brain-inspired computing

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  • Ryu, Ji-Ho
  • Kim, Sungjun

Abstract

In this work, a built-in selector synaptic memristor is proposed to minimize sneak current in synapse array. The Ti/TiO2/HfO2/Si device exhibits nonlinear and high rectifying current-voltage characteristics compared to Ti/TiO2/Si device. Under negative bias conditions, the physical model supported by material analysis reveals that the Schottky barrier at the interface between Ti and TiO2 suppresses the current. Due to nonlinear and self-rectifying characteristics, a bilayer device has a significantly larger array size (> 105 × 105) with a securing read margin of 10%, using the modified half-bias scheme. A multi-level interface-type switching behavior is desired to implement synaptic functions, including potentiation and depression, and spike-timing-dependent plasticity. It was verified that the recognition rate in the bilayer device is significantly more accurate in a neural network model employing the Fashion MNIST dataset.

Suggested Citation

  • Ryu, Ji-Ho & Kim, Sungjun, 2020. "Artificial synaptic characteristics of TiO2/HfO2 memristor with self-rectifying switching for brain-inspired computing," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    • Handle: RePEc:eee:chsofr:v:140:y:2020:i:c:s0960077920306329
    DOI: 10.1016/j.chaos.2020.110236
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    References listed on IDEAS

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    1. Spagnolo, B. & Valenti, D. & Guarcello, C. & Carollo, A. & Persano Adorno, D. & Spezia, S. & Pizzolato, N. & Di Paola, B., 2015. "Noise-induced effects in nonlinear relaxation of condensed matter systems," Chaos, Solitons & Fractals, Elsevier, vol. 81(PB), pages 412-424.
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    Cited by:

    1. Yang, Jinwoong & Ryu, Hojeong & Kim, Sungjun, 2021. "Resistive and synaptic properties modulation by electroforming polarity in CMOS-compatible Cu/HfO2/Si device," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    2. Ryu, Hojeong & Kim, Sungjun, 2021. "Implementation of a reservoir computing system using the short-term effects of Pt/HfO2/TaOx/TiN memristors with self-rectification," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    3. Li, Kexin & Bao, Bocheng & Ma, Jun & Chen, Mo & Bao, Han, 2022. "Synchronization transitions in a discrete memristor-coupled bi-neuron model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    4. Surazhevsky, I.A. & Demin, V.A. & Ilyasov, A.I. & Emelyanov, A.V. & Nikiruy, K.E. & Rylkov, V.V. & Shchanikov, S.A. & Bordanov, I.A. & Gerasimova, S.A. & Guseinov, D.V. & Malekhonova, N.V. & Pavlov, D, 2021. "Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    5. Kim, Dahye & Kim, Sunghun & Kim, Sungjun, 2021. "Logic-in-memory application of CMOS compatible silicon nitride memristor," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).

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