%A 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) %T An artificial synapse by superlattice-like phase-change material for low-power brain-inspired computing %0 Journal Article %D 2020 %J Chin. Phys. B %R 10.1088/1674-1056/ab892a %P 70701-070701 %V 29 %N 7 %U {https://cpb.iphy.ac.cn/CN/abstract/article_122578.shtml} %8 2020-07-05 %X 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.