# Machine Learning Approach for Evaluation of Nanodefects and Magnetic Anisotropy in FePt Granular Films

https://mdr.nims.go.jp/datasets/888b9782-7b08-4a97-9ed6-03043108c477

## Files

- [manuscript.docx](https://mdr.nims.go.jp/filesets/ed138c63-c897-4be4-b5c6-b879562091cf/download) ([Detail](https://mdr.nims.go.jp/filesets/ed138c63-c897-4be4-b5c6-b879562091cf.md))

## Id

888b9782-7b08-4a97-9ed6-03043108c477

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-10-11T03:46:01.937216Z

## Updated at

2024-10-15T07:30:13.515263Z

## Published at

2024-10-15T07:30:14.795717Z

## Doi

https://doi.org/10.48505/nims.4848

## First published url

https://doi.org/10.1016/j.scriptamat.2022.114797

## Date published

2022-05-13

## Recorded date published

2022-9

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: Machine Learning Approach for Evaluation of Nanodefects and Magnetic Anisotropy
    in FePt Granular Films
  title_type: original
  lang: en

## Description

- description: This paper reports a machine learning approach for evaluating micromagnetic
    and microstructural parameters from demagnetization curves of FePt granular films
    for heat-assisted magnetic recording (HAMR) media. We developed a neural network
    to predict parameters of magnetic anisotropy and volume fractions of defects such
    as [200] misoriented grains, {111} twined variants and disordered grains. his
    work paves the way for high-throughput magnetometry-based characterization of
    FePt granular media for its structural optimization toward higher areal density
    of HAMR.
  description_type: abstract
  lang: und

## Creator

- name: E. Dengina
  role: author
  organization: National Institute for Materials Science
- name: A. Bolyachkin
  role: author
  orcid: https://orcid.org/0000-0003-0420-1806
  organization: National Institute for Materials Science
- name: H. Sepehri-Amin
  role: author
  orcid: https://orcid.org/0000-0002-7856-7897
  organization: National Institute for Materials Science
- name: K. Hono
  role: author
  orcid: https://orcid.org/0000-0001-7367-0193
  organization: National Institute for Materials Science

## Contact agent



## Publisher

organization: Elsevier BV

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## Keyword

- subject: Magnetic recording
  schema: not_defined
- subject: Micromagnetic simulations
  schema: not_defined
- subject: Machine learning
  schema: not_defined
- subject: FePt media
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Scripta Materialia
  issn: '13596462'
  volume: '218'
  article_number: '114797'

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## Specimen



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## Fileset

- id: ed138c63-c897-4be4-b5c6-b879562091cf
  filename: manuscript.docx
  content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
  size: 1383013
  md5: 6c06e86ab8b13b336b56340c5c73ab43

## Thumbnail

fileset_id: ed138c63-c897-4be4-b5c6-b879562091cf
filename: manuscript.docx