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Chin. Phys. B, 2020, Vol. 29(7): 070701    DOI: 10.1088/1674-1056/ab892a
Special Issue: SPECIAL TOPIC — Physics in neuromorphic devices
SPECIAL TOPIC—Physics in neuromorphic devices Prev   Next  

An artificial synapse by superlattice-like phase-change material for low-power brain-inspired computing

Qing Hu(胡庆), Boyi Dong(董博义), Lun Wang(王伦), Enming Huang(黄恩铭), Hao Tong(童浩), Yuhui He(何毓辉), Ming Xu(徐明), Xiangshui Miao(缪向水)
Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information,Huazhong University of Science and Technology, Wuhan 430074, China
Abstract  Phase-change material (PCM) is generating widespread interest as a new candidate for artificial synapses in bio-inspired computer systems. However, the amorphization process of PCM devices tends to be abrupt, unlike continuous synaptic depression. The relatively large power consumption and poor analog behavior of PCM devices greatly limit their applications. Here, we fabricate a GeTe/Sb2Te3 superlattice-like PCM device which allows a progressive RESET process. Our devices feature low-power consumption operation and potential high-density integration, which can effectively simulate biological synaptic characteristics. The programming energy can be further reduced by properly selecting the resistance range and operating method. The fabricated devices are implemented in both artificial neural networks (ANN) and convolutional neural network (CNN) simulations, demonstrating high accuracy in brain-like pattern recognition.
Keywords:  superlattice-like      phase-change material      artificial synapse      low-power consumption  
Received:  27 February 2020      Revised:  11 April 2020      Published:  05 July 2020
PACS:  07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)  
  47.20.Hw (Morphological instability; phase changes)  
  83.10.Tv (Structural and phase changes)  
Fund: Project supported by the National Science and Technology Major Project of China (Grant No. 2017ZX02301007-002), the National Key R&D Plan of China (Grant No. 2017YFB0701701), and the National Natural Science Foundation of China (Grant Nos. 61774068 and 51772113). The authors acknowledge the support from Hubei Key Laboratory of Advanced Memories & Hubei Engineering Research Center on Microelectronics.
Corresponding Authors:  Hao Tong, Ming Xu     E-mail:;

Cite this article: 

Qing Hu(胡庆), Boyi Dong(董博义), Lun Wang(王伦), Enming Huang(黄恩铭), Hao Tong(童浩), Yuhui He(何毓辉), Ming Xu(徐明), Xiangshui Miao(缪向水) An artificial synapse by superlattice-like phase-change material for low-power brain-inspired computing 2020 Chin. Phys. B 29 070701

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