# Interpretable evaluation of STEM images of nanostructures via homology analysis

https://mdr.nims.go.jp/datasets/39f3d015-2d79-4f7e-95ee-d0752a697df3

## File

- [abstract.docx](https://mdr.nims.go.jp/filesets/58449a26-e01e-4975-a3d9-1231fbabbbe8/download) ([Detail](https://mdr.nims.go.jp/filesets/58449a26-e01e-4975-a3d9-1231fbabbbe8.md))

## Id

39f3d015-2d79-4f7e-95ee-d0752a697df3

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-11-26T09:29:11.442715Z

## Updated at

2024-12-03T07:31:06.157664Z

## Published at

2024-12-03T07:31:06.256437Z

## Doi

https://doi.org/10.48505/nims.5080

## First published url



## Date published



## Recorded date published



## Resource type

conference_poster

## Manuscript type

na

## Collection



## Title

- title: Interpretable evaluation of STEM images of nanostructures via homology analysis
  title_type: original
  lang: en

## Description

- description: "Persistent homology (PH) quantitatively expresses the \"hole\" structures
    of any data in terms of their \"birth\" and \"death\" and their scales. We applied
    PH analysis to STEM images of phase-separated nanostructures, particularly extracting
    interpretable features of inhomogenous structures. The target image data consisted
    of HAADF-STEM images of two-phase Pt/CeO2 nanocomposites. This material exhibits
    different morphologies such as maze-like and striped structures depending on synthesis
    conditions (temperature and CO/O2 synthesis gas ratio).STEM images were binarized
    and analyzed focusing on the CeO2 phase. PH analysis extracted features corresponding
    to the number of isolated CeO2 domains, width and length of CeO2 stripes,\r\nas
    well as the number of rings and gulf-like structures. Furthermore, using these
    features in random forest classification revealed the significance of gulf-like
    structures derived from 1st PDs as structural descriptors."
  description_type: abstract
  lang: eng

## Creator

- name: Eguchi Ryuto
  role: author
  orcid: https://orcid.org/0009-0003-2859-6934
  organization: National Institute for Materials Science
  department: Research Center for Energy and Environmental Materials (GREEN)/Battery
    and Cell Materials Field/Environment-Controlled Microscopy Group
- name: Yu Wen
  role: author
  organization: National Institute for Materials Science
  department: Research Center for Advanced Measurement and Characterization/Atomic
    Structure and Physics Field/In-situ Characterization Technique Development Group
- name: Ayako Hashimoto
  role: author
  organization: National Institute for Materials Science
  department: Research Center for Energy and Environmental Materials (GREEN)/Battery
    and Cell Materials Field/Environment-Controlled Microscopy Group

## Contact agent



## Publisher



## Managing organization



## Keyword

- subject: persistent homology
  schema: not_defined

## Rights

- identifier: http://rightsstatements.org/vocab/InC/1.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal



## Conference

name: 17th European Microscopy Congress 2024 (EMC24)
start_date: 2024-08-25
end_date: 2024-08-30
identifier: https://emc2024.eu/

## Related item



## Funding



## 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: 58449a26-e01e-4975-a3d9-1231fbabbbe8
  filename: abstract.docx
  content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
  size: 411428
  md5: fe576773c2d6322d9e657c59a3f2c609

## Thumbnail

fileset_id: 58449a26-e01e-4975-a3d9-1231fbabbbe8
filename: abstract.docx