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作 者:Pengfei JIANG Kunran XU Jie YU Yannan XU Peng YUAN Yuan WANG Yuting CHEN Yaxin DING Shuxian LV Zhiwei DANG Tiancheng GONG Yang YANG Yan WANG Qing LUO
机构地区:[1]Key Laboratory of Microelectronics Devices and Integrated Technology,Institute of Microelectronics,Chinese Academy of Sciences,Beijing 100029,China [2]University of Chinese Academy of Sciences,Beijing 100049,China [3]School of Microelectronics,Xidian University,Xi’an 710071,China [4]Peng Cheng Laboratory,Shenzhen 518000,China
出 处:《Science China(Information Sciences)》2023年第2期263-272,共10页中国科学(信息科学)(英文版)
基 金:supported in part by National Key Research and Development Program of China (Grant No. 2017YFA0206102);National Natural Science Foundation of China (Grant Nos. 61922083, 61904200, 61974049);Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB44000000)。
摘 要:The Hf_(0.5)Zr_(0.5)O_(2)(HZO)-based ferroelectric field-effect transistor(Fe FET) synapse is a promising candidate for at-scale deep neural network(DNN) applications, because of its high symmetry, great accuracy and fast operation speed. However, the degradation of the remanent polarization(Pr) over time caused by the depolarization field has not been effectively resolved, greatly affecting the accuracy of the trained DNN. In this study, we demonstrate a ferroelectric(FE)-resistive switching(RS) switchable synapse using the FE mode for high-speed weight training and the RS mode for stable weight storage to overcome accuracy degradation. The FE-RS hybrid characteristic is accomplished by an HZO-based metal-ferroelectricmetal(MFM) capacitor with asymmetric electrodes, and the best FE endurance, as well as the most reliable RS behavior, is demonstrated by testing several electrodes materials. High memory windows are achieved in both FE and RS modes. Through this design, excellent accuracy is maintained over time, as verified by network simulation.
关 键 词:Hf_(0.5)Zr_(0.5)O_(2)films FERROELECTRIC resistive switching accuracy on-chip DNN
分 类 号:TM934.1[电气工程—电力电子与电力传动]
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