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
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.
Received: 22 July 2025
Revised: 22 September 2025
Accepted manuscript online: 28 October 2025
Fund: 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).
Ying Li(李颖), Xiaofan Zhou(周晓凡), Jiajun Guo(郭家俊), Tong Chen(陈通), Xiaohui Zhang(张晓辉), Xia Xiao(肖夏), Guangyu Wang(王光宇), Mehran Khan Alam, Qi Zhang(张琪), and Liqian Wu(武力乾) Artificial synapse based on Co3O4 nanosheets for high-accuracy pattern recognition 2025 Chin. Phys. B 34 128101
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