Nature Communications (May 2024)

Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware

  • Long Liu,
  • Di Wang,
  • Dandan Wang,
  • Yan Sun,
  • Huai Lin,
  • Xiliang Gong,
  • Yifan Zhang,
  • Ruifeng Tang,
  • Zhihong Mai,
  • Zhipeng Hou,
  • Yumeng Yang,
  • Peng Li,
  • Lan Wang,
  • Qing Luo,
  • Ling Li,
  • Guozhong Xing,
  • Ming Liu

DOI
https://doi.org/10.1038/s41467-024-48631-4
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 12

Abstract

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Abstract We report a breakthrough in the hardware implementation of energy-efficient all-spin synapse and neuron devices for highly scalable integrated neuromorphic circuits. Our work demonstrates the successful execution of all-spin synapse and activation function generator using domain wall-magnetic tunnel junctions. By harnessing the synergistic effects of spin-orbit torque and interfacial Dzyaloshinskii-Moriya interaction in selectively etched spin-orbit coupling layers, we achieve a programmable multi-state synaptic device with high reliability. Our first-principles calculations confirm that the reduced atomic distance between 5d and 3d atoms enhances Dzyaloshinskii-Moriya interaction, leading to stable domain wall pinning. Our experimental results, supported by visualizing energy landscapes and theoretical simulations, validate the proposed mechanism. Furthermore, we demonstrate a spin-neuron with a sigmoidal activation function, enabling high operation frequency up to 20 MHz and low energy consumption of 508 fJ/operation. A neuron circuit design with a compact sigmoidal cell area and low power consumption is also presented, along with corroborated experimental implementation. Our findings highlight the great potential of domain wall-magnetic tunnel junctions in the development of all-spin neuromorphic computing hardware, offering exciting possibilities for energy-efficient and scalable neural network architectures.