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Chin. Phys. B, 2022, Vol. 31(7): 078502    DOI: 10.1088/1674-1056/ac3ece

Fabrication and investigation of ferroelectric memristors with various synaptic plasticities

Qi Qin(秦琦)1, Miaocheng Zhang(张缪城)1,†, Suhao Yao(姚苏昊)1, Xingyu Chen(陈星宇)1, Aoze Han(韩翱泽)1, Ziyang Chen(陈子洋)1, Chenxi Ma(马晨曦)2, Min Wang(王敏)1, Xintong Chen(陈昕彤)1, Yu Wang(王宇)1, Qiangqiang Zhang(张强强)1, Xiaoyan Liu(刘晓燕)1, Ertao Hu(胡二涛)1, Lei Wang(王磊)1,‡, and Yi Tong(童祎)1,§
1 College of Electronic and Optical Engineering and College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;
2 Key Laboratory for Organic Electronics and Information Displays and Jiangsu Key Laboratory for Biosensors, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Abstract  In the post-Moore era, neuromorphic computing has been mainly focused on breaking the von Neumann bottlenecks. Memristors have been proposed as a key part of neuromorphic computing architectures, and can be used to emulate the synaptic plasticities of the human brain. Ferroelectric memristors represent a breakthrough for memristive devices on account of their reliable nonvolatile storage, low write/read latency and tunable conductive states. However, among the reported ferroelectric memristors, the mechanisms of resistive switching are still under debate. In addition, there needs to be more research on emulation of the brain synapses using ferroelectric memristors. Herein, Cu/PbZr0.52Ti0.48O3 (PZT)/Pt ferroelectric memristors have been fabricated. The devices are able to realize the transformation from threshold switching behavior to resistive switching behavior. The synaptic plasticities, including excitatory post-synaptic current, paired-pulse facilitation, paired-pulse depression and spike time-dependent plasticity, have been mimicked by the PZT devices. Furthermore, the mechanisms of PZT devices have been investigated by first-principles calculations based on the interface barrier and conductive filament models. This work may contribute to the application of ferroelectric memristors in neuromorphic computing systems.
Keywords:  brain-inspired computing      ferroelectric memristors      mechanisms      resistive-switching  
Received:  13 September 2021      Revised:  05 November 2021      Accepted manuscript online:  01 December 2021
PACS:  85.35.-p (Nanoelectronic devices) (Learning and memory)  
Fund: Project supported by Jiangsu Province Research Foundation (Grant Nos. BK20191202, RK106STP18003, and SZDG2018007), the Jiangsu Province Research Foundation (Grant Nos. BK20191202, RK106STP18003, and SZDG2018007), the Research Innovation Program for College Graduates of Jiangsu Province (Grant Nos. KYCX20 0806, KYCX19 0960, and SJCX19 0268), and NJUPTSF (Grant Nos. NY217116, NY220078, and NY218107).
Corresponding Authors:  Miaocheng Zhang, Lei Wang, Yi Tong     E-mail:;;

Cite this article: 

Qi Qin(秦琦), Miaocheng Zhang(张缪城), Suhao Yao(姚苏昊), Xingyu Chen(陈星宇), Aoze Han(韩翱泽),Ziyang Chen(陈子洋), Chenxi Ma(马晨曦), Min Wang(王敏), Xintong Chen(陈昕彤), Yu Wang(王宇),Qiangqiang Zhang(张强强), Xiaoyan Liu(刘晓燕), Ertao Hu(胡二涛), Lei Wang(王磊), and Yi Tong(童祎) Fabrication and investigation of ferroelectric memristors with various synaptic plasticities 2022 Chin. Phys. B 31 078502

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