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Multilevel-3D Bit Patterned Magnetic Media with 8 Signal Levels Per Nanocolumn

Overview of attention for article published in PLOS ONE, July 2012
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Title
Multilevel-3D Bit Patterned Magnetic Media with 8 Signal Levels Per Nanocolumn
Published in
PLOS ONE, July 2012
DOI 10.1371/journal.pone.0040134
Pubmed ID
Authors

Nissim Amos, John Butler, Beomseop Lee, Meir H. Shachar, Bing Hu, Yuan Tian, Jeongmin Hong, Davil Garcia, Rabee M. Ikkawi, Robert C. Haddon, Dmitri Litvinov, Sakhrat Khizroev

Abstract

This letter presents an experimental study that shows that a 3(rd) physical dimension may be used to further increase information packing density in magnetic storage devices. We demonstrate the feasibility of at least quadrupling the magnetic states of magnetic-based data storage devices by recording and reading information from nanopillars with three magnetically-decoupled layers. Magneto-optical Kerr effect microscopy and magnetic force microscopy analysis show that both continuous (thin film) and patterned triple-stack magnetic media can generate eight magnetically-stable states. This is in comparison to only two states in conventional magnetic recording. Our work further reveals that ferromagnetic interaction between magnetic layers can be reduced by combining Co/Pt and Co/Pd multilayers media. Finally, we are showing for the first time an MFM image of multilevel-3D bit patterned media with 8 discrete signal levels.

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The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 2 5%
United States 1 3%
Japan 1 3%
Unknown 33 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 35%
Researcher 5 14%
Student > Doctoral Student 4 11%
Other 3 8%
Student > Master 3 8%
Other 5 14%
Unknown 4 11%
Readers by discipline Count As %
Physics and Astronomy 12 32%
Materials Science 9 24%
Engineering 7 19%
Immunology and Microbiology 1 3%
Social Sciences 1 3%
Other 1 3%
Unknown 6 16%