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Giant Ferroelectric Resistance Switching Controlled by a Modulatory Terminal for Low-Power Neuromorphic In-Memory Computing.
Xue, Fei; He, Xin; Wang, Zhenyu; Retamal, José Ramón Durán; Chai, Zheng; Jing, Lingling; Zhang, Chenhui; Fang, Hui; Chai, Yang; Jiang, Tao; Zhang, Weidong; Alshareef, Husam N; Ji, Zhigang; Li, Lain-Jong; He, Jr-Hau; Zhang, Xixiang.
Affiliation
  • Xue F; Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • He X; Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • Wang Z; National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Retamal JRD; Computer, Electrical, and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • Chai Z; Department of Electronics and Electrical Engineering, Liverpool John Moores University, Liverpool, L3 3AF, UK.
  • Jing L; National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Zhang C; Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • Fang H; Computer Science Department, Loughborough University, Loughborough, LE11 3TU, UK.
  • Chai Y; Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
  • Jiang T; CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China.
  • Zhang W; Department of Electronics and Electrical Engineering, Liverpool John Moores University, Liverpool, L3 3AF, UK.
  • Alshareef HN; Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • Ji Z; National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Li LJ; Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
  • He JH; Department of Materials Science and Engineering, University of New South Wales, Kensington, NSW, 2052, Australia.
  • Zhang X; Computer, Electrical, and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
Adv Mater ; 33(21): e2008709, 2021 May.
Article in En | MEDLINE | ID: mdl-33860581
ABSTRACT
Ferroelectrics have been demonstrated as excellent building blocks for high-performance nonvolatile memories, including memristors, which play critical roles in the hardware implementation of artificial synapses and in-memory computing. Here, it is reported that the emerging van der Waals ferroelectric α-In2 Se3 can be used to successfully implement heterosynaptic plasticity (a fundamental but rarely emulated synaptic form) and achieve a resistance-switching ratio of heterosynaptic memristors above 103 , which is two orders of magnitude larger than that in other similar devices. The polarization change of ferroelectric α-In2 Se3 channel is responsible for the resistance switching at various paired terminals. The third terminal of α-In2 Se3 memristors exhibits nonvolatile control over channel current at a picoampere level, endowing the devices with picojoule read-energy consumption to emulate the associative heterosynaptic learning. The simulation proves that both supervised and unsupervised learning manners can be implemented in α-In2 Se3 neutral networks with high image recognition accuracy. Moreover, these heterosynaptic devices can naturally realize Boolean logic without an additional circuit component. The results suggest that van der Waals ferroelectrics hold great potential for applications in complex, energy-efficient, brain-inspired computing systems and logic-in-memory computers.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Adv Mater Journal subject: BIOFISICA / QUIMICA Year: 2021 Document type: Article Affiliation country: Saudi Arabia

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Adv Mater Journal subject: BIOFISICA / QUIMICA Year: 2021 Document type: Article Affiliation country: Saudi Arabia