Predictive Materials Design of Magnetic Random-Access Memory Based on Nanoscale Atomic Structure and Element Distribution-Reference-Cited by-同舟云学术

Predictive Materials Design of Magnetic Random-Access Memory Based on Nanoscale Atomic Structure and Element Distribution

Published:2019-11-07 Issue:12 Volume:19 Page:8621-8629
ISSN:1530-6984
Container-title:Nano Letters
language:en
Short-container-title:Nano Lett.

Author:

Li Xiang¹²³^ORCID,Sasaki Taisuke⁴,Grezes Cecile¹,Wu Di¹,Wong Kin¹,Bi Chong⁵,Ong Phuong-Vu⁶^ORCID,Ebrahimi Farbod²,Yu Guoqiang¹^ORCID,Kioussis Nicholas⁶,Wang Weigang⁵,Ohkubo Tadakatsu⁴,Khalili Amiri Pedram¹,Wang Kang L.¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of California, Los Angeles, California 90095, United States

2. Inston, Inc., Los Angeles, California 90095, United States

3. Department of Electrical Engineering, Stanford University, Stanford, California 94305, United States

4. National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba 305-0047, Japan

5. Department of Physics, University of Arizona, Tucson, Arizona 85721, United States

6. Department of Physics and Astronomy, California State University Northridge, Northridge, California 91330, United States

Funder

King Abdulaziz City for Science and Technology

U.S. Department of Energy

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science,General Chemistry,Bioengineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.nanolett.9b03190

Reference42 articles.

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3. Current-driven spin torque induced by the Rashba effect in a ferromagnetic metal layer

4. Current-Induced Switching of Perpendicularly Magnetized Magnetic Layers Using Spin Torque from the Spin Hall Effect

5. Large voltage-induced magnetic anisotropy change in a few atomic layers of iron

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