Abstract

Owing to their attractive application potentials in both non-volatile memory and unconventional computing, memristive devices have drawn substantial research attention in the last decade. However, major roadblocks still remain in device performance, especially concerning relatively large parameter variability and limited cycling endurance. The response of the active region in the device within and between switching cycles plays the dominating role, yet the microscopic details remain elusive. This Review summarizes recent progress in scientific understanding of the physical origins of the non-idealities and propose a synergistic approach based on in situ characterization and device modeling to investigate switching mechanism. At last, the Review offers an outlook for commercialization viability of memristive technology.

Memristor as the fourth basic element of electric circuits has drawn substantial attention for developing future computing technologies. Sun et al. report the progress and the challenges facing researchers on understanding memristive switching, and advocate continuous studies using a synergistic approach.

Details

Title
Understanding memristive switching via in situ characterization and device modeling
Author
Sun, Wen 1 ; Gao, Bin 2 ; Miaofang, Chi 3   VIAFID ORCID Logo  ; Xia Qiangfei 4   VIAFID ORCID Logo  ; Joshua, Yang J 4   VIAFID ORCID Logo  ; He, Qian 2 ; Wu, Huaqiang 2 

 Institute of Microelectronics, Tsinghua University, Beijing, China; Oak Ridge National Laboratory, Center for Nanophase Materials Sciences, Oak Ridge, USA (GRID:grid.135519.a) (ISNI:0000 0004 0446 2659); University of Massachusetts, Department of Electrical and Computer Engineering, Amherst, USA (GRID:grid.135519.a) 
 Institute of Microelectronics, Tsinghua University, Beijing, China (GRID:grid.135519.a) 
 Oak Ridge National Laboratory, Center for Nanophase Materials Sciences, Oak Ridge, USA (GRID:grid.135519.a) (ISNI:0000 0004 0446 2659) 
 University of Massachusetts, Department of Electrical and Computer Engineering, Amherst, USA (GRID:grid.135519.a) 
Publication year
2019
Publication date
2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2267715717
Copyright
© The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.