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Micromagnetic Simulations of Systems with Shape-Induced Anisotropy
S. Hill Thompson Florida State University
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Manufactured Single-Domain Iron Nanopillars
Grown by STM-assisted CVD 1 200 nm 40 nm 1 S. Wirth, M. Field, D. D. Awschalom, and S. von Molnar, Phys. Rev. B 57, R14028 (1998); J. Appl. Phys. 85, 5249 (1999)
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Background – A Typical Simulation
Time(scaled units) Mz
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Metastable Decay Free energy vs. Mz Saddle point Free energy barrier
Metastable minimum +Mz Free energy vs. Mz
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Lattice Dynamic equation, Landau-Lifshitz-Gilbert (LLG) on a computational lattice
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Landau-Lifshitz-Gilbert (LLG)
: uniform magnetization density go: electron gyromagnetic ratio, 1.67x107 Hz/Oe a: phenomenological damping parameter, 0.1 : total local field at = z e d a n +
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Rescaling M = M/Ms H = H/Ms r = r/le t = γoMst
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Dipole interactions Handled by the Fast Multipole Method O(n2) O(n)
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Realistic Models – Computational Details
6x6x90 computational lattice -> 3240 sites 10 nm x 10 nm x 150 nm Fe nanopillar dt = picoseconds usin first-order Euler integration Temperature = 20 Kelvin Applied Field = 3160 Oe at 75 degrees from the easy axis Fields: dipole-dipole, thermal, exchange, Zeeman 3-4 days on IBM SP3 using 20 processors
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Cumulative Distribution Function of the Lifetime t – All Runs
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Phase Plot of the Total Magnetization
Faster Mode Slower Mode
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Phase Plot of the Total Energy
Faster Mode Slower Mode
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Two Distributions Fast Slow
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Thermalization out of the T=0K Metastable State
Quenched Slower mode
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Thermalization T = 0K T = 20K
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Quench/Relax vs Slow Mode
Q/R Slow
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Projective Dynamics Number of visits, N Growth Probability = G/N
Same, N – (G + S) Shrinkage, S Growth, G Mz Growth Probability = G/N Shrinkage Probability = S/N
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Projective Dynamics Slower mode Faster mode
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Location of Extrema
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Choosing the Correct Model
7x7x101 spins 1x1x17 spins Stoner-Wohlfarth 1-D models are not sufficient, full 3-D models are necessary Wirth, et al, J. Appl. Phys. 85, 5249 (1999). Li, et al, J. Appl Phys, 93, 7912 (2003). Li, et al, J. Appl. Phys. Lett 80, 4644 (2002)
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