Long‐term and short‐term plasticity independently mimicked in highly reliable Ru‐doped Ge2Sb2Te5 electronic synapses
Qiang Wang,
Yachuan Wang,
Yankun Wang,
Luyue Jiang,
Jinyan Zhao,
Zhitang Song,
Jinshun Bi,
Libo Zhao,
Zhuangde Jiang,
Jutta Schwarzkopf,
Shengli Wu,
Bin Zhang,
Wei Ren,
Sannian Song,
Gang Niu
Affiliations
Qiang Wang
State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Yachuan Wang
National Key Laboratory of Human‐Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual information and Applications, and School of Software Xi'an Jiaotong University Xi'an the People's Republic of China
Yankun Wang
State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Luyue Jiang
State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Jinyan Zhao
State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Zhitang Song
State Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences Shanghai the People's Republic of China
Jinshun Bi
Key Laboratory of Microelectronics Device and Integrated Technology, The Institute of Microelectronics of Chinese Academy of Sciences Beijing the People's Republic of China
Libo Zhao
The State Key Laboratory for Manufacturing Systems Engineering & The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong University Xi'an the People's Republic of China
Zhuangde Jiang
The State Key Laboratory for Manufacturing Systems Engineering & The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong University Xi'an the People's Republic of China
Jutta Schwarzkopf
Leibniz‐Institut für Kristallzüchtung, Max‐Born‐Straße 2 Berlin Germany
Shengli Wu
Key Laboratory of Physical Electronics and Devices, Ministry of Education, School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Bin Zhang
National Key Laboratory of Human‐Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual information and Applications, and School of Software Xi'an Jiaotong University Xi'an the People's Republic of China
Wei Ren
State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Sannian Song
State Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences Shanghai the People's Republic of China
Gang Niu
State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research School of Electronic Science and Engineering Xi'an Jiaotong University Xi'an the People's Republic of China
Abstract In order to fulfill the complex cognitive behaviors in neuromorphic systems with reduced peripheral circuits, the reliable electronic synapses mimicked by single device that achieves diverse long‐term and short‐term plasticity are essential. Phase change random access memory (PCRAM) is of great potential for artificial synapses, which faces, however, difficulty to realize short‐term plasticity due to the long‐lasting resistance drift. This work reports the ruthenium‐doped Ge2Sb2Te5 (RuGST) based PCRAM, demonstrating a series of synaptic behaviors of short‐term potentiation, pair‐pulse facilitation, long‐term depression, and short‐term plasticity in the same single device. The optimized RuGST electronic synapse with the high transformation temperature of hexagonal phase >380°C, the outstanding endurance >108 cycles, the low resistance drift factor of 0.092, as well as the extremely high linearity with correlation coefficients of 0.999 and 0.976 in parts of potentiation and depression. Further investigations also go insight to mechanisms of Ru doping according to thorough microstructure characterization, revealing that Ru dopant is able to enter GST lattices thus changing and stabilizing atomic arrangement of GST. This leads to the short‐term plasticity realized by RuGST PCRAM. Eventually, the proposed RuGST electronic synapses performs a high accuracy of ~94.1% in a task of image recognition of CIFAR‐100 database using ResNet 101. This work promotes the development of PCRAM platforms for large‐scale neuromorphic systems.