Understanding memristive switching via in situ characterization and device modeling

Wen Sun, Bin Gao, Miaofang Chi, Qiangfei Xia, J. Joshua Yang, He Qian, Huaqiang Wu

Research output: Contribution to journalReview articlepeer-review

294 Scopus citations

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.

Original languageEnglish
Article number3453
JournalNature Communications
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2019

Fingerprint

Dive into the research topics of 'Understanding memristive switching via in situ characterization and device modeling'. Together they form a unique fingerprint.

Cite this