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Thermal design engineering for improving the variation of memristor threshold

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  • Li, Xing
  • Zou, Jianxun
  • Feng, Zhe
  • Wu, Zuheng
  • Xu, Zuyu
  • Yang, Fei
  • Zhu, Yunlai
  • Dai, Yuehua

Abstract

Memristor-based neural components and circuits are the key to building efficient brain-like computing systems, but their development is restricted by their unstable electrical properties of memristive artificial neurons. In this work, three thermal design schemes to regulate the electrical characteristics of threshold switching memristor were proposed, such as the thermal conductivity of the device electrode, the different substrate and local electrode. First, it was found that the lower the thermal conductivity of electrode, the lower the threshold variation of the device. Secondly, the smaller the thermal conductivity of the memristor substrate, the more stable the threshold. Thirdly, decreasing the electrode radius of the memristor from the original 50 nm to 10 nm will decrease the variation of threshold voltage by 27%. Additionally, due to the reduction of thermal dissipation, the proposed thermal design engineering also can lower the threshold voltage and power consumption. Those results on improving the threshold variation of memristor provide a stepping stone for the development of artificial neurons and neuromorphic computing systems.

Suggested Citation

  • Li, Xing & Zou, Jianxun & Feng, Zhe & Wu, Zuheng & Xu, Zuyu & Yang, Fei & Zhu, Yunlai & Dai, Yuehua, 2023. "Thermal design engineering for improving the variation of memristor threshold," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:chsofr:v:171:y:2023:i:c:s0960077923003673
    DOI: 10.1016/j.chaos.2023.113466
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    References listed on IDEAS

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