# Topological data analysis of TEM-based structural features affecting the thermal conductivity of amorphous Ge

https://mdr.nims.go.jp/datasets/7ac0464e-7e04-4ad1-8938-1dd6fd1987d7

## File

- [2024_press_release_paper.pdf](https://mdr.nims.go.jp/filesets/3553ffb2-5e17-40bd-9dc4-3c1a39ca9cc1/download) ([Detail](https://mdr.nims.go.jp/filesets/3553ffb2-5e17-40bd-9dc4-3c1a39ca9cc1.md))

## Id

7ac0464e-7e04-4ad1-8938-1dd6fd1987d7

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-10-02T08:36:20.616094Z

## Updated at

2024-10-04T07:30:17.965068Z

## Published at

2024-10-04T07:30:19.254796Z

## Doi



## First published url

https://doi.org/10.1016/j.ijheatmasstransfer.2023.125012

## Date published

2023-12-06

## Recorded date published

2024-4

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Topological data analysis of TEM-based structural features affecting the
    thermal conductivity of amorphous Ge
  title_type: original
  lang: en

## Description

- description: Compared to crystalline materials, amorphous materials lack periodicity
    and exhibit distinct thermal and lattice vibration properties. Hence, analyzing
    atomic networks in the transmission electron microscopy (TEM) images of amorphous
    materials is challenging. In this study, we employ topological data analysis (TDA)
    and principal component analysis (PCA) to extract structural features from the
    TEM images of amorphous germanium (a-Ge) and analyze its atomic networks. Our
    findings demonstrate that the thermal conductivity of a-Ge is influenced by larger
    atomic rings with more vertices, which facilitates the heat transfer through longer
    atomic chains and results in a higher thermal conductivity. A comparison of the
    experimental and simulation data confirms the non-random nature of the atomic
    arrangements in a-Ge. We propose herein an approach that employs the TDA to identify
    and analyze the atomic networks in amorphous materials, establishing connections
    to their thermal properties. This study enhances our understanding of amorphous
    materials and paves a way for tailored material design and engineering to achieve
    the desired thermal properties.
  description_type: abstract
  lang: und

## Creator

- name: Yen-Ju Wu
  role: author
  orcid: https://orcid.org/0000-0003-2647-3407
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Kazuto Akagi
  role: author
- name: Masahiro Goto
  role: author
  orcid: https://orcid.org/0000-0002-1003-2781
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Yibin Xu
  role: author
  orcid: https://orcid.org/0000-0001-8600-8748
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: Amorphous materials
  schema: not_defined
- subject: Topological data analysis
  schema: not_defined
- subject: Atomic network
  schema: not_defined
- subject: Structure feature
  schema: not_defined
- subject: Thermal conductivity
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: International Journal of Heat and Mass Transfer
  issn: '00179310'
  volume: '221'
  article_number: '125012'

## Conference



## Related item



## Funding

- funder_name: Japan Society for the Promotion of Science
- identifier: 20H00119
  funder_name: Japan Science and Technology Agency
- identifier: 22H05109
  funder_name: Japan Science and Technology Agency
- identifier: JPMJCR21O2
  funder_name: Japan Science and Technology Agency

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## Fileset

- id: 3553ffb2-5e17-40bd-9dc4-3c1a39ca9cc1
  filename: 2024_press_release_paper.pdf
  content_type: application/pdf
  size: 5670434
  md5: 4bc06feb77f633f86640e72bd6fac41b

## Thumbnail

fileset_id: 3553ffb2-5e17-40bd-9dc4-3c1a39ca9cc1
filename: 2024_press_release_paper.pdf