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Special Issue:
SPECIAL TOPIC—Post-Moore era: Materials and device physics
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| SPECIAL TOPIC—Post-Moore era: Materials and device physics |
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Reconfigurable Mott electronics for homogeneous neuromorphic platform |
| Zhen Yang(杨振)1, Ying-Ming Lu(路英明)1, and Yu-Chao Yang(杨玉超)1,2,3,4,† |
1 Beijing Advanced Innovation Center for Integrated Circuit, School of Integrated Circuits, Peking University, Beijing 100871, China;
2 School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China;
3 Center for Brain Inspired Chips, Institute for Artificial Intelligence, Frontiers Science Center for Nano-optoelectronics, Peking University, Beijing 100871, China;
4 Center for Brain Inspired Intelligence, Chinese Institute for Brain Research(CIBR), Beijing 102206, China |
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Abstract To simplify the fabrication process and increase the versatility of neuromorphic systems, the reconfiguration concept has attracted much attention. Here, we developed a novel electrochemical VO2 (EC-VO2) device, which can be reconfigured as synapses or LIF neurons. The ionic dynamic doping contributed to the resistance changes of VO2, which enables the reversible modulation of device states. The analog resistance switching and tunable LIF functions were both measured based on the same device to demonstrate the capacity of reconfiguration. Based on the reconfigurable EC-VO2, the simulated spiking neural network model exhibited excellent performances by using low-precision weights and tunable output neurons, whose final accuracy reached 91.92%.
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Received: 05 August 2023
Revised: 28 September 2023
Accepted manuscript online: 13 October 2023
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PACS:
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84.30.-r
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(Electronic circuits)
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85.40.-e
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(Microelectronics: LSI, VLSI, ULSI; integrated circuit fabrication technology)
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87.85.dq
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(Neural networks)
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81.07.-b
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(Nanoscale materials and structures: fabrication and characterization)
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| Fund: Project supported by the National Natural Science Foundation of China(Grant Nos.61925401, 92064004, 61927901, and 92164302) and the 111 Project (Grant No.B18001). Y. Y. acknowledges support from the Fok Ying-Tong Education Foundation and the Tencent Foundation through the XPLORER PRIZE. The authors acknowledge the support of TOF-SIMS characterization by Dr. Tinglu Song and the first-principal computation by Dr. Bing Zheng from Beijing Institute of Technology. |
Corresponding Authors:
Yu-Chao Yang
E-mail: yuchaoyang@pku.edu.cn
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Cite this article:
Zhen Yang(杨振), Ying-Ming Lu(路英明), and Yu-Chao Yang(杨玉超) Reconfigurable Mott electronics for homogeneous neuromorphic platform 2023 Chin. Phys. B 32 128401
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