# High-Fidelity Phase-Field Simulation of Solid-State Sintering Enabled by Bayesian Data Assimilation Using In Situ Electron Tomography Data

https://mdr.nims.go.jp/datasets/126e9201-a364-488f-9a35-09a8f5686acf

## File

- [High-fidelity phase-field simulation of solid-state sintering enabled by Bayesian data assimilation using in situ electron tomography data.pdf](https://mdr.nims.go.jp/filesets/e8f064af-b1d8-45a6-8c25-733906cfe34e/download) ([Detail](https://mdr.nims.go.jp/filesets/e8f064af-b1d8-45a6-8c25-733906cfe34e.md))

## Id

126e9201-a364-488f-9a35-09a8f5686acf

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-08-27T03:39:57.274524Z

## Updated at

2026-08-27T07:18:14.412871Z

## Published at

2026-08-27T09:27:15.906917Z

## Doi



## First published url

https://doi.org/10.1016/j.actamat.2024.120251

## Date published

2024-08-02

## Recorded date published

2024-10

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: High-Fidelity Phase-Field Simulation of Solid-State Sintering Enabled by
    Bayesian Data Assimilation Using In Situ Electron Tomography Data
  title_type: original
  lang: en

## Description

- description: Although the experimental characterization of the industrially important
    solid-state sintering is essential for the development of new materials and devices,
    it has never been performed in full, not least because of the limitations imposed
    by the complexity of target materials, experimental equipment, and observation
    conditions. Therefore, hybrid techniques for predicting sintering behavior based
    on experimental datasets and physics-based simulation models are highly sought
    after. Herein, a technique for constructing a digital twin of solid-state sintering
    is developed using a nonsequential Bayesian data assimilation (DA) method that
    integrates the experimental data obtained by in situ electron tomography/scanning
    transmission electron microscopy into the corresponding phase-field model and
    allows the inverse estimation of material parameters included therein. This technique
    is used to build a digital twin quantitatively capturing the solid-state sintering
    of copper nanoparticles and successfully estimate seven parameters (including
    temperature-dependent diffusion coefficients) from the time-series information
    on the morphology of sintered nanoparticles observed in situ. Thus, this study
    pioneers the establishment of digital twins for solid-state sintering based on
    DA-integrated phase-field simulations and real in situ observation datasets and
    deepens our understanding of the sintering process.
  description_type: abstract
  lang: und

## Creator

- name: Akimitsu Ishii
  role: author
  orcid: https://orcid.org/0000-0002-9261-4047
  organization: National Institute for Materials Science
- name: Akinori Yamanaka
  role: author
- name: Mizumo Yoshinaga
  role: author
- name: Shunsuke Sato
  role: author
- name: Midori Ikeuchi
  role: author
- name: Hikaru Saito
  role: author
- name: Satoshi Hata
  role: author
- name: Akiyasu Yamamoto
  role: author

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: Bayesian data assimilation
  schema: not_defined
- subject: In situ
  schema: not_defined
- subject: Phase-field simulation
  schema: not_defined
- subject: Sintering
  schema: not_defined
- subject: Nanoparticles
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/
  date_licensed: 2024-08-02

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Acta Materialia
  issn: '13596454'
  volume: '278'
  article_number: '120251'

## Conference



## Related item



## Funding

- funder_name: Japan Science and Technology Agency
- funder_name: Core Research for Evolutional Science and Technology
- identifier: JPMJCR18J4
  funder_name: Japan Science and Technology Agency Strategic Basic Research Programs
    CREST

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## Fileset

- id: e8f064af-b1d8-45a6-8c25-733906cfe34e
  filename: High-fidelity phase-field simulation of solid-state sintering enabled
    by Bayesian data assimilation using in situ electron tomography data.pdf
  content_type: application/pdf
  size: 9074981
  md5: 0f3cc5730ad76216a34ae1c0fb11e971

## Thumbnail

fileset_id: e8f064af-b1d8-45a6-8c25-733906cfe34e
filename: High-fidelity phase-field simulation of solid-state sintering enabled by
  Bayesian data assimilation using in situ electron tomography data.pdf