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Chin. Phys. B, 2022, Vol. 31(11): 117106    DOI: 10.1088/1674-1056/ac89dd
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Switching plasticity in compensated ferrimagnetic multilayers for neuromorphic computing

Weihao Li(李伟浩)1,2, Xiukai Lan(兰修凯)1,2, Xionghua Liu(刘雄华)1,2, Enze Zhang(张恩泽)1,2, Yongcheng Deng(邓永城)1,2, and Kaiyou Wang(王开友)1,2,3,4,†
1 State Key Laboratory for Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China;
2 Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
3 Beijing Academy of Quantum Information Sciences, Beijing 100193, China;
4 Center for Excellence in Topological Quantum Computation, University of Chinese Academy of Sciences, Beijing 100049, China
Abstract  Current-induced multilevel magnetization switching in ferrimagnetic spintronic devices is highly pursued for the application in neuromorphic computing. In this work, we demonstrate the switching plasticity in Co/Gd ferrimagnetic multilayers where the binary states magnetization switching induced by spin-orbit toque can be tuned into a multistate one as decreasing the domain nucleation barrier. Therefore, the switching plasticity can be tuned by the perpendicular magnetic anisotropy of the multilayers and the in-plane magnetic field. Moreover, we used the switching plasticity of Co/Gd multilayers for demonstrating spike timing-dependent plasticity and sigmoid-like activation behavior. This work gives useful guidance to design multilevel spintronic devices which could be applied in high-performance neuromorphic computing.
Keywords:  switching plasticity      compensated ferrimagnet      spin-orbit torque      spike timing-dependent plasticity      sigmoidal neuron      handwritten digits recognition      neuromorphic computing  
Received:  16 June 2022      Revised:  21 July 2022      Accepted manuscript online:  16 August 2022
PACS:  71.20.Eh (Rare earth metals and alloys)  
  75.50.Gg (Ferrimagnetics)  
  84.35.+i (Neural networks)  
  85.70.-w (Magnetic devices)  
Fund: This work was supported by Beijing Natural Science Foundation Key Program (Grant No. Z190007), Beijing Natural Science Foundation (Grant No. 2212048), the National Natural Science Foundation of China (Grant Nos. 11474272, 61774144, and 12004212), and the Chinese Academy of Sciences (Grant Nos. QYZDY-SSW-JSC020, XDB28000000, and XDB44000000).
Corresponding Authors:  Kaiyou Wang     E-mail:  kywang@semi.ac.cn

Cite this article: 

Weihao Li(李伟浩), Xiukai Lan(兰修凯), Xionghua Liu(刘雄华), Enze Zhang(张恩泽), Yongcheng Deng(邓永城), and Kaiyou Wang(王开友) Switching plasticity in compensated ferrimagnetic multilayers for neuromorphic computing 2022 Chin. Phys. B 31 117106

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