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Understanding memristive switching via in situ characterization and device modeling.

Publication ,  Journal Article
Sun, W; Gao, B; Chi, M; Xia, Q; Yang, JJ; Qian, H; Wu, H
Published in: Nature communications
August 2019

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.

Duke Scholars

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Published In

Nature communications

DOI

EISSN

2041-1723

ISSN

2041-1723

Publication Date

August 2019

Volume

10

Issue

1

Start / End Page

3453
 

Citation

APA
Chicago
ICMJE
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NLM
Sun, W., Gao, B., Chi, M., Xia, Q., Yang, J. J., Qian, H., & Wu, H. (2019). Understanding memristive switching via in situ characterization and device modeling. Nature Communications, 10(1), 3453. https://doi.org/10.1038/s41467-019-11411-6
Sun, Wen, Bin Gao, Miaofang Chi, Qiangfei Xia, J Joshua Yang, He Qian, and Huaqiang Wu. “Understanding memristive switching via in situ characterization and device modeling.Nature Communications 10, no. 1 (August 2019): 3453. https://doi.org/10.1038/s41467-019-11411-6.
Sun W, Gao B, Chi M, Xia Q, Yang JJ, Qian H, et al. Understanding memristive switching via in situ characterization and device modeling. Nature communications. 2019 Aug;10(1):3453.
Sun, Wen, et al. “Understanding memristive switching via in situ characterization and device modeling.Nature Communications, vol. 10, no. 1, Aug. 2019, p. 3453. Epmc, doi:10.1038/s41467-019-11411-6.
Sun W, Gao B, Chi M, Xia Q, Yang JJ, Qian H, Wu H. Understanding memristive switching via in situ characterization and device modeling. Nature communications. 2019 Aug;10(1):3453.

Published In

Nature communications

DOI

EISSN

2041-1723

ISSN

2041-1723

Publication Date

August 2019

Volume

10

Issue

1

Start / End Page

3453