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Set/Reset Bilaterally Controllable Resistance Switching Ga-doped Ge2Sb2Te5 Long-Term Electronic Synapses for Neuromorphic Computing |
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| Authors: | Qiang Wang Ren Luo Yankun Wang Wencheng Fang Luyue Jiang Yangyang Liu Ruobing Wang Liyan Dai Jinyan Zhao Jinshun Bi Zenghui Liu Libo Zhao Zhuangde Jiang Zhitang Song Jutta Schwarzkopf Thomas Schroeder Shengli Wu Zuo-Guang Ye Wei Ren Sannian Song Gang Niu |
| Affiliation: | 1. Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research, School of Electronic Science and Engineering & The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology, Xi'an Jiaotong University, Xi'an, 710049 China;2. State Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 865 Changning Road, Shanghai, 200050 China;3. Key Laboratory of Microelectronics Device and Integrated Technology, The Institute of Microelectronics of Chinese Academy of Sciences, Beijing, 100029 China
University of Chinese Academy of Sciences, Beijing, 100049 China;4. 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, 710049 China;5. Leibniz-Institut für Kristallzüchtung, Max-Born-Straße 2, 12489 Berlin, Germany;6. Key Laboratory of Physical Electronics and Devices, Ministry of Education, School of Electronic Science and Engineering, Xi'an Jiaotong University, Xi'an, 710049 China;7. Department of Chemistry and 4D LABS, Simon Fraser University, Burnaby, British Columbia, V5A 1S6 Canada |
| Abstract: | Long-term plasticity of bio-synapses modulates the stable synaptic transmission that is quite related to the encoding of information and its emulation using electronic hardware is one of important targets for neuromorphic computing. Ge2Sb2Te5 (GST) based phase change random access memory (PCRAM) has become a strong candidate for complementary-metal-oxide-semiconductor (CMOS) compatible integrated long-term electronic synapses to cope with the high-efficient and low power consumption data processing tasks for neuromorphic computing. However, the performance of PCRAM electronic synapses is still quite limited due to the challenges in linear and continuous conductance regulation, which originates from the fast and uncontrollable resistance switching characteristic of conventional PCRAM for the data storage application. Here an in-depth study is reported on the impact of gallium (Ga) doping on GST (GaGST) structural properties and on the corresponding 0.13 µm CMOS technology fabricated PCRAM integrated devices with a mushroom structure. The Ga doping effectively retarded the crystallization process of GST by augmenting the local disorder of GeTe4-nGen tetrahedron, which subsequently leads to the Set/Reset bilaterally controllable resistance switching of corresponding PCRAM devices. The optimized 6.5%GaGST electronic synapses demonstrate gradual resistance switching characteristics and a good multilevel retention feature and eventually exhibit outstanding long-term synaptic plasticity like potentiation/depression and spiking time dependent plasticity in four forms. Such long-term electronic synapses are applied to handwritten digits recognition (96.22%) and CIFAR-10 image categorization (93.6%) and attain very high accuracy for both tasks. These results provide an effective method to achieve high performance PCRAM electronic synapses and highlight the great potential of GaGST PCRAM as a component for future high-performance neuromorphic computing. |
| Keywords: | electronic synapses neuromorphic computing PCRAM |
