Spin-Orbit-Torque-Driven Two-Terminal Giant Magnetoresistance Memristive Devices for In-Memory Computing.

Journal: ACS applied materials & interfaces
Published Date: Jun 9, 2025

Abstract

The rising complexity of artificial intelligence and data-intensive applications drives the demand for memristive devices to support high-performance and scalable processing-in-memory (PIM) architectures. While three- and four-terminal spintronic PIM solutions show promise, they face scalability challenges due to large footprints. This study demonstrates a two-terminal spin-orbit torque (SOT)-driven giant magnetoresistance (GMR) memristive device utilizing a Pt/Co/Cu/CoTb stack, integrating data storage and logic functions within a single unit. Ten nonvolatile resistance states are achieved by modulating the SOT current amplitude, and additional states with opposite polarities are created by tuning the CoTb alloy composition. Synaptic plasticity, including long-term potentiation and depression, is demonstrated through current pulse modulation. Simulations of a deep neural network constructed with this GMR device achieve 92% accuracy in handwritten digit recognition and image visualization tasks. Moreover, basic Boolean logic functions further showcase the processing capabilities. This two-terminal GMR device offers a scalable solution for advanced memristive memory and in-memory computing.

Authors

  • Tianli Jin
    School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore.
  • Bo Zhang
    Department of Clinical Pharmacology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310006, PR China.
  • Dihua Wu
    College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi, China 712100; Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling, Shaanxi, China 712100; Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Services, Yangling, China 712100; School of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China 310058.
  • Eng Kang Koh
    School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore. WenSiang@ntu.edu.sg.
  • Funan Tan
    School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore.
  • Calvin Xiu Xian Lee
    School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore. WenSiang@ntu.edu.sg.
  • Ze Chen
    Department of Neurology, Xijing Hospital, Air Force Medical University, Xi'an, PR China. Electronic address: chenz_e@126.com.
  • Gerard Joseph Lim
    School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore. WenSiang@ntu.edu.sg.
  • Kaiming Cai
    School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China.
  • Jiangwei Cao
    School of Physical Science and Technology, Lanzhou University, Lanzhou 730000, China.
  • Wen Siang Lew
    School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore. WenSiang@ntu.edu.sg.

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