Multiscale micromagnetic / atomistic modeling of heat assisted magnetic recording

Fuente: arXiv
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Hauptverfasser: Gija, Mohammed, Dobrynin, Alexey, McNeill, Kevin, Gubbins, Mark, Mercer, Tim, Bissell, Philip, Lepadatu, Serban
Format: Preprint
Veröffentlicht: 2025
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author Gija, Mohammed
Dobrynin, Alexey
McNeill, Kevin
Gubbins, Mark
Mercer, Tim
Bissell, Philip
Lepadatu, Serban
author_facet Gija, Mohammed
Dobrynin, Alexey
McNeill, Kevin
Gubbins, Mark
Mercer, Tim
Bissell, Philip
Lepadatu, Serban
contents Heat-assisted magnetic recording (HAMR) is a recent advancement in magnetic recording, allowing to significantly increase the areal density capability (ADC) of hard disk drives (HDDs) compared to the perpendicular magnetic recording (PMR) technology. This is enabled by high anisotropy FePt media, which needs to be heated through its Curie temperature ($T_C$) to facilitate magnetization reversal by an electromagnetic write pole. HAMR micromagnetic modeling is therefore challenging, as it needs to be performed in proximity to and above $T_C$, where a ferromagnet has no spontaneous magnetization. An atomistic model is an optimal solution here, as it doesn't require any parameter renormalization or non-physical assumptions for modeling at any temperature. However, a full track atomistic recording model is extremely computationally expensive. Here we demonstrate a true multiscale HAMR modeling approach, combining atomistic spin dynamics modeling for high temperature regions and micromagnetic modeling for lower temperature regions, in a moving simulation window embedded within a long magnetic track. The advantages of this approach include natural emergence of $T_C$ and anisotropy distributions of FePt grains. Efficient GPU optimization of the code provides very fast running times, with a 60~nm wide track of twenty-five 20~nm - long bits being recorded in several hours on a single GPU. The effects of realistic FePt L$_{10}$ vs simple cubic crystal structure is discussed, with the latter providing further running time gains while keeping the advantages of the multiscale approach.
format Preprint
id arxiv_https___arxiv_org_abs_2502_02236
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multiscale micromagnetic / atomistic modeling of heat assisted magnetic recording
Gija, Mohammed
Dobrynin, Alexey
McNeill, Kevin
Gubbins, Mark
Mercer, Tim
Bissell, Philip
Lepadatu, Serban
Materials Science
Computational Physics
Heat-assisted magnetic recording (HAMR) is a recent advancement in magnetic recording, allowing to significantly increase the areal density capability (ADC) of hard disk drives (HDDs) compared to the perpendicular magnetic recording (PMR) technology. This is enabled by high anisotropy FePt media, which needs to be heated through its Curie temperature ($T_C$) to facilitate magnetization reversal by an electromagnetic write pole. HAMR micromagnetic modeling is therefore challenging, as it needs to be performed in proximity to and above $T_C$, where a ferromagnet has no spontaneous magnetization. An atomistic model is an optimal solution here, as it doesn't require any parameter renormalization or non-physical assumptions for modeling at any temperature. However, a full track atomistic recording model is extremely computationally expensive. Here we demonstrate a true multiscale HAMR modeling approach, combining atomistic spin dynamics modeling for high temperature regions and micromagnetic modeling for lower temperature regions, in a moving simulation window embedded within a long magnetic track. The advantages of this approach include natural emergence of $T_C$ and anisotropy distributions of FePt grains. Efficient GPU optimization of the code provides very fast running times, with a 60~nm wide track of twenty-five 20~nm - long bits being recorded in several hours on a single GPU. The effects of realistic FePt L$_{10}$ vs simple cubic crystal structure is discussed, with the latter providing further running time gains while keeping the advantages of the multiscale approach.
title Multiscale micromagnetic / atomistic modeling of heat assisted magnetic recording
topic Materials Science
Computational Physics
url https://arxiv.org/abs/2502.02236