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October 15, 2025Journal of Physics D Applied Physics3 citations

Recent progress in neuromorphic computing based on spin-orbit torque devices

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QLQi LiangYHYujie HuangYTYinlong Tan

Key Points

  • Neuromorphic computing leverages spintronic devices to replicate brain functionalities and optimize performance.
  • The exploration of devices like Domain Wall-SOT and Skyrmion-SOT reveals their potential in advanced neuromorphic tasks.
  • Understanding the interplay between biological neural networks and SOT devices aids in developing effective neuromorphic hardware.
  • Current challenges in the field underline the need for innovative designs and solutions in SOT device applications.

Abstract

Abstract Neuromorphic computing, inspired by the structure and functionality of the biological brain, aims to simulate brain processes through the design of innovative devices, algorithms, and architectures. Neuromorphic devices constitute the foundational hardware components essential for the realization of neuromorphic computing. In recent years, spintronic devices based on the Spin-Orbit Torque (SOT) effect have emerged as the central focus due to their exceptional durability, rapid response times, and low energy consumption. By designing SOT devices with diverse structures and functionalities, researchers have successfully emulated the roles of synapses and neurons in the human brain, thereby enabling the execution of neuromorphic computing tasks. This paper presents a comprehensive review of recent advancements in the application of SOT spintronic devices for neuromorphic computing. We first introduce the underlying mechanisms and testing methods of SOT spintronic devices, then commence with an introduction to biological neural networks in the human brain, followed by an exposition of widely adopted algorithmic architectures and hardware requirements for neuromorphic computing based on SOT devices. After that, we discuss the practical applications of four primary types of SOT devices: Domain Wall (DW)-SOT, Skyrmion-SOT, Nucleation-SOT, and spin Hall nano-oscillators(SHNO) in neuromorphic computing. Finally, we address the current challenges in the field and proposes potential solutions for the future.

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Cite This Study

Liang et al. (2025) studied this question.

synapsesocial.com/papers/68eff7392ae617e5891a93behttps://doi.org/10.1088/1361-6463/ae1241
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