中国物理B ›› 2025, Vol. 34 ›› Issue (12): 128101-128101.doi: 10.1088/1674-1056/ae1817

• • 上一篇    

Artificial synapse based on Co3O4 nanosheets for high-accuracy pattern recognition

Ying Li(李颖)1, Xiaofan Zhou(周晓凡)1, Jiajun Guo(郭家俊)1,†, Tong Chen(陈通)2,3, Xiaohui Zhang(张晓辉)1, Xia Xiao(肖夏)1, Guangyu Wang(王光宇)1,‡, Mehran Khan Alam4, Qi Zhang(张琪)5, and Liqian Wu(武力乾)6,§   

  1. 1 School of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China;
    2 School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China;
    3 Institute of Advanced Semiconductors, Hangzhou Innovation Center, Zhejiang University, Hangzhou 311200, China;
    4 Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education), School of Materials Science and Engineering, Shandong University, Jinan 250061, China;
    5 School of Medical Information Engineering, Department of Physics, Jining Medical University, Jining 272067, China;
    6 Wenzhou Institute of Hangzhou Dianzi University, Wenzhou 325038, China
  • 收稿日期:2025-07-22 修回日期:2025-09-22 接受日期:2025-10-28 发布日期:2025-11-25
  • 通讯作者: Jiajun Guo, Guangyu Wang, Liqian Wu E-mail:guojiajun@lcu.edu.cn;wangguangyu@lcu.edu.cn;wulq@hdu.edu.cn
  • 基金资助:
    This work was supported by the Natural Science Foundation of Shandong Province (Grant Nos. ZR2024MA019 and ZR2023QA106) and the “Pioneer” and “Leading Goose” R&D Program of Zhejiang (Grant No. 2023C01018).

Artificial synapse based on Co3O4 nanosheets for high-accuracy pattern recognition

Ying Li(李颖)1, Xiaofan Zhou(周晓凡)1, Jiajun Guo(郭家俊)1,†, Tong Chen(陈通)2,3, Xiaohui Zhang(张晓辉)1, Xia Xiao(肖夏)1, Guangyu Wang(王光宇)1,‡, Mehran Khan Alam4, Qi Zhang(张琪)5, and Liqian Wu(武力乾)6,§   

  1. 1 School of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China;
    2 School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China;
    3 Institute of Advanced Semiconductors, Hangzhou Innovation Center, Zhejiang University, Hangzhou 311200, China;
    4 Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education), School of Materials Science and Engineering, Shandong University, Jinan 250061, China;
    5 School of Medical Information Engineering, Department of Physics, Jining Medical University, Jining 272067, China;
    6 Wenzhou Institute of Hangzhou Dianzi University, Wenzhou 325038, China
  • Received:2025-07-22 Revised:2025-09-22 Accepted:2025-10-28 Published:2025-11-25
  • Contact: Jiajun Guo, Guangyu Wang, Liqian Wu E-mail:guojiajun@lcu.edu.cn;wangguangyu@lcu.edu.cn;wulq@hdu.edu.cn
  • About author:2025-128101-251257.pdf
  • Supported by:
    This work was supported by the Natural Science Foundation of Shandong Province (Grant Nos. ZR2024MA019 and ZR2023QA106) and the “Pioneer” and “Leading Goose” R&D Program of Zhejiang (Grant No. 2023C01018).

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摘要： Two-dimensional (2D) metal oxides are promising candidates for constructing neuromorphic systems because of their intriguing physical properties, such as atomic thinness and ionic activity. In this work, Co$_{3}$O$_{4}$ nanosheets were synthesized using a solvothermal method and integrated into artificial synapses. Based on the synaptic plasticity of the Co$_{3}$O$_{4}$ nanosheet-based memristive device, an artificial neural network (ANN) was designed and tested. A recognition accuracy of approximately 96 % was achieved for the Modified National Institute of Standards and Technology (MNIST) handwritten digit classification task using this ANN. These results highlight the potential of Co$_{3}$O$_{4}$ nanosheet-based artificial synapses and Al/Co$_{3}$O$_{4}$ nanosheet/ITO memristor devices as excellent material candidates for neuromorphic hardware.

关键词: artificial synapse, memristor, Co3O4 nanosheet, synaptic plasticity

Abstract: Two-dimensional (2D) metal oxides are promising candidates for constructing neuromorphic systems because of their intriguing physical properties, such as atomic thinness and ionic activity. In this work, Co$_{3}$O$_{4}$ nanosheets were synthesized using a solvothermal method and integrated into artificial synapses. Based on the synaptic plasticity of the Co$_{3}$O$_{4}$ nanosheet-based memristive device, an artificial neural network (ANN) was designed and tested. A recognition accuracy of approximately 96 % was achieved for the Modified National Institute of Standards and Technology (MNIST) handwritten digit classification task using this ANN. These results highlight the potential of Co$_{3}$O$_{4}$ nanosheet-based artificial synapses and Al/Co$_{3}$O$_{4}$ nanosheet/ITO memristor devices as excellent material candidates for neuromorphic hardware.

Key words: artificial synapse, memristor, Co3O4 nanosheet, synaptic plasticity

中图分类号:  (Nanoscale materials and structures: fabrication and characterization)

  • 81.07.-b
84.35.+i (Neural networks) 85.35.-p (Nanoelectronic devices) 73.40.Rw (Metal-insulator-metal structures)