# Extraction of local structure differences in silica based on unsupervised learning

https://mdr.nims.go.jp/datasets/b64b402c-8483-417d-8a21-c24d3b0854f9

## File

- [d3cp06298h.pdf](https://mdr.nims.go.jp/filesets/eebd8733-f17a-45b6-946e-64f5646c4caf/download) ([Detail](https://mdr.nims.go.jp/filesets/eebd8733-f17a-45b6-946e-64f5646c4caf.md))

## Id

b64b402c-8483-417d-8a21-c24d3b0854f9

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-08-09T07:21:14.449459Z

## Updated at

2024-08-19T23:30:29.054496Z

## Published at

2024-08-19T23:30:29.224497Z

## Doi



## First published url

https://doi.org/10.1039/d3cp06298h

## Date published

2024-03-28

## Recorded date published

2024-4-17

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Extraction of local structure differences in silica based on unsupervised
    learning
  title_type: original
  lang: en

## Description

- description: "Silica exhibits a rich phase diagram with numerous stable structures
    existing at different temperature and pressure conditions, including its glassy
    form. In large-scale atomistic simulations, due to the small energy difference,
    several phases may coexist. While, in terms of long-range order, there are clear
    differences between these phases, their short- or medium-range structural properties
    are similar for many phases, thus making it difficult to detect the structural
    differences. \r\n\r\nIn this study, a methodology based on unsupervised learning
    is proposed to detect the differences in local structures between eight phases
    of silica, using atomic models prepared by molecular dynamics (MD) simulations.
    A combination of two-step locality preserving projections (TS-LPP) and locally
    averaged atomic fingerprints (LAAF) descriptor was employed to and a low-dimensional
    space in which the differences among all the phases can be detected. From the
    distance between each structure in the found low-dimensional space, the similarity
    between the structures can be discussed and subtle local changes in the structures
    can be detected. \r\n\r\nUsing the obtained low-dimensional space, the β −α transition
    in quartz at a low temperature was analyzed, as well as the structural evolution
    during the melt-quench process starting from α-quartz. The proper differentiation
    and ease of visualization make the present methodology promising for improving
    the analysis of the structure\r\nand properties of glasses, where subtle difference
    in structure appear due to differences in the\r\ntemperature and pressure conditions
    at which they were synthesized.\r\n"
  description_type: abstract
  lang: und

## Creator

- name: Anh Khoa Augustin Lu
  role: author
  orcid: https://orcid.org/0000-0003-4702-0933
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Jianbo Lin
  role: author
  orcid: https://orcid.org/0000-0003-0769-9857
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Yasunori Futamura
  role: author
- name: Tetsuya Sakurai
  role: author
- name: Ryo Tamura
  role: author
  orcid: https://orcid.org/0000-0002-0349-358X
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Tsuyoshi Miyazaki
  role: author
  orcid: https://orcid.org/0000-0003-3534-4404
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: Royal Society of Chemistry (RSC)

## Managing organization



## Keyword

- subject: silica
  schema: not_defined
- subject: unsupervised learning
  schema: not_defined
- subject: Machine Learning
  schema: not_defined
- subject: Molecular Dynamics(MD)
  schema: not_defined
- subject: Density Functional Theory (DFT)
  schema: not_defined
- subject: local structure analysis
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Physical Chemistry Chemical Physics
  issn: '14639084'
  start_page: 11657
  end_page: 11666

## Conference



## Related item



## Funding

- identifier: 20H05883
  funder_name: Japan Society for the Promotion of Science
- identifier: 18H01143
  funder_name: Japan Society for the Promotion of Science
- identifier: 21H01008
  funder_name: Japan Society for the Promotion of Science

## Instrument



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## Specimen



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## Fileset

- id: eebd8733-f17a-45b6-946e-64f5646c4caf
  filename: d3cp06298h.pdf
  content_type: application/pdf
  size: 2682346
  md5: 167b5680a90ccdec59348a74bfa2ec6e

## Thumbnail

fileset_id: eebd8733-f17a-45b6-946e-64f5646c4caf
filename: d3cp06298h.pdf