# Fusion data analysis of imaging data of hydrogenpermeated steel obtained by complementary methods

https://mdr.nims.go.jp/datasets/3485bda1-84ab-4830-ac75-02961ce1a6b1

## File

- [2020_AkiymaAoyagi_JVST.pdf](https://mdr.nims.go.jp/filesets/1adba1c9-8f9f-423b-9875-d45b8ba33a89/download) ([Detail](https://mdr.nims.go.jp/filesets/1adba1c9-8f9f-423b-9875-d45b8ba33a89.md))

## Id

3485bda1-84ab-4830-ac75-02961ce1a6b1

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-10-24T13:54:40.661556Z

## Updated at

2024-01-05T13:11:49.712498Z

## Published at

2023-10-26T04:30:16.557126Z

## Doi



## First published url

https://doi.org/10.1116/6.0000009

## Date published

2020-05-01

## Recorded date published

2020-5-1

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Fusion data analysis of imaging data of hydrogenpermeated steel obtained
    by complementary methods
  title_type: original
  lang: en

## Description

- description: "オペランド水素顕微鏡で取得したステンレス鋼透過水素の時間応答挙動を、電子顕微鏡画像との画像融合後に数種の計算科学的手法で解析した。\r\n主成分分析（PCA）、スパースモデリングの代表であるLASSO、ニューラルネットワークを使用した次元圧縮のひとつであるオートエンコーダ、で構造解析画像と水素分布画像を解析し、これらの手法が構造と水素vs構造の材料評価に有力であることがわかった。また、局所水素透過の画像解析を計算科学的解釈に行うことで、よりこれまで見えていなかったより複雑な（複数の構造が関与していると推測できる）拡散挙動を抽出した。"
  description_type: abstract
  lang: eng

## Creator

- name: Tomomi Akiyama
  role: author
- name: Naoya Miyauchi
  role: author
  orcid: https://orcid.org/0000-0002-7716-3049
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Akiko N. Itakura
  role: author
  orcid: https://orcid.org/0000-0001-5783-141X
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Takayuki Yamagishi
  role: author
- name: Satoka Aoyagi
  role: author

## Contact agent



## Publisher

organization: American Vacuum Society

## Managing organization



## Keyword

- subject: Hydrogen diffusion
  schema: not_defined
- subject: Principal component analysis
  schema: not_defined
- subject: Least absolute shrinkage and selection operator
  schema: not_defined
- subject: Autoencoder
  schema: not_defined

## Rights

- description: Copyright (2020) Author(s). This article is distributed under a Creative
    Commons Attribution (CC BY) License.
  identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin



## Embargo



## Journal

- title: JOURNAL OF VACUUM SCIENCE & TECHNOLOGY B
  issn: '21662754'
  volume: '38'
  issue: '3'
  start_page: 34007
  end_page: 34007

## Conference



## Related item



## Funding

- identifier: 18H03849
  funder_name: JSPS

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: 1adba1c9-8f9f-423b-9875-d45b8ba33a89
  filename: 2020_AkiymaAoyagi_JVST.pdf
  content_type: application/pdf
  size: 2845644
  md5: ca7d24dd51dd613a47091dd0420503eb

## Thumbnail

fileset_id: 1adba1c9-8f9f-423b-9875-d45b8ba33a89
filename: 2020_AkiymaAoyagi_JVST.pdf