Kinetic Monte Carlo Simulations of M\!\!-\!\!H Loops for HAMR Recording Media: Comparison With MOKE Data

Our previously developed kinetic Monte Carlo algorithm is used to simulate M-H loops of high anisotropy magnetic recording media at long time scales relevant to the experimental measurements using the magneto-optic Kerr effect. Micromagnetic parameters are fit to loop data taken at 300 K and at a sw...

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Veröffentlicht in:IEEE transactions on magnetics 2014-03, Vol.50 (3), p.22-26
Hauptverfasser: Plumer, Martin L., Fal, Timothy J., Mercer, Jason I., Whitehead, John P., van Ek, Jan, Ajan, Antony
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container_issue 3
container_start_page 22
container_title IEEE transactions on magnetics
container_volume 50
creator Plumer, Martin L.
Fal, Timothy J.
Mercer, Jason I.
Whitehead, John P.
van Ek, Jan
Ajan, Antony
description Our previously developed kinetic Monte Carlo algorithm is used to simulate M-H loops of high anisotropy magnetic recording media at long time scales relevant to the experimental measurements using the magneto-optic Kerr effect. Micromagnetic parameters are fit to loop data taken at 300 K and at a sweep rate of 700 Oe/s on a single-layer media developed for heat-assisted magnetic recording. Significantly different fitted parameters result from standard micromagnetic simulations that can access only sweep rates many orders of magnitude faster. Sensitivities of the loops to anisotropy, saturation magnetization, and various distributions are reported.
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subjects Anisotropic magnetoresistance
Anisotropy
Computer simulation
Cross-disciplinary physics: materials science
rheology
Exact sciences and technology
Grain size
Heat-assisted magnetic recording
Heat-assisted magnetic recording (HAMR)
hysteresis loops
Kerr effects
kinetic MC (KMC)
Magnetic anisotropy
Magnetic recording
Materials science
Media
Monte Carlo methods
Other topics in materials science
Physics
Saturation (magnetic)
Saturation magnetization
title Kinetic Monte Carlo Simulations of M\!\!-\!\!H Loops for HAMR Recording Media: Comparison With MOKE Data
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