Toward a Reliable Synaptic Simulation Using Al-Doped HfO2 RRAM

Sourav Roy; Gang Niu; Qiang Wang; Yankun Wang; Yijun Zhang; Heping Wu; Shijie Zhai; Peng Shi; Sannian Song; Zhitang Song; Zuo-Guang Ye; Christian Wenger; Thomas Schroeder; Ya-Hong Xie; Xiangjian Meng; Wenbo Luo; Wei Ren

doi:10.1021/acsami.9b21530

Toward a Reliable Synaptic Simulation Using Al-Doped HfO₂ RRAM

ACS Appl Mater Interfaces. 2020 Mar 4;12(9):10648-10656. doi: 10.1021/acsami.9b21530. Epub 2020 Feb 20.

Authors

Sourav Roy¹, Gang Niu¹, Qiang Wang¹, Yankun Wang¹, Yijun Zhang¹, Heping Wu¹, Shijie Zhai¹, Peng Shi¹, Sannian Song², Zhitang Song², Zuo-Guang Ye³, Christian Wenger⁴, Thomas Schroeder⁵, Ya-Hong Xie⁵, Xiangjian Meng⁶, Wenbo Luo⁷, Wei Ren¹

Affiliations

¹ 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 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 20050, China.
³ Department of Chemistry and 4D LABS, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada.
⁴ IHP-Leibniz-Institut für Innovative Mikroelektronik, Im Technologiepark 25, 15236 Frankfurt (Oder), Germany.
⁵ Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States.
⁶ National Laboratory for Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
⁷ State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu 611731 China.

PMID: 32043352
DOI: 10.1021/acsami.9b21530

Abstract

The potential in a synaptic simulation for neuromorphic computation has revived the research interest of resistive random access memory (RRAM). However, novel applications require reliable multilevel resistive switching (RS), which still represents a challenge. We demonstrate in this work the achievement of reliable HfO₂-based RRAM devices for synaptic simulation by performing the Al doping and the postdeposition annealing (PDA). Transmission electron microscopy and operando hard X-ray photoelectron spectroscopy results reveal the positive impact of Al doping on the formation of oxygen vacancies. Detailed I-V characterizations demonstrate that the 16.5% Al doping concentration leads to better RS properties of the device. In comparison with the other reported results based on HfO₂ RRAM, our devices with 16.5% Al-doping and PDA at 450 °C show better reliable multilevel RS (∼20 levels) performance and an increased on/off ratio. The 16.5% Al:HfO₂ sample with PDA at 450 °C shows good potentiation/depression characteristics with low pulse width (10 μs) along with a good On/Off ratio (>1000), good data retention at room temperature, and high temperature and good program/erase endurance characteristics with a pulse width of 50 ns. The synapse features including potentiation, depression, and spike time-dependent plasticity were successfully achieved using optimized Al-HfO₂ RRAM devices. Our results demonstrate the beneficial effects of Al doping and PDA on the enhancement of the performances of RRAM devices for the synaptic simulation in neuromorphic computing applications.

Keywords: Al doping; HfO2; PDA; RRAM; synaptic simulation.