# Study of the ion mobility in defect-laden                    <math>                      <msub>                        <mi>ZrO</mi>                        <mn>2</mn>                      </msub>                    </math>                    under an electric field using neural network with predictions for Born effective charges

https://mdr.nims.go.jp/datasets/563b1fb9-a76b-4e14-865e-962152439fdd

## File

- [Lu_PhysrevMaterials_2026.pdf](https://mdr.nims.go.jp/filesets/391f107f-1c74-4289-8c65-f639495f272f/download) ([Detail](https://mdr.nims.go.jp/filesets/391f107f-1c74-4289-8c65-f639495f272f.md))

## Id

563b1fb9-a76b-4e14-865e-962152439fdd

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-06-08T03:38:38.644147Z

## Updated at

2026-06-08T04:01:57.801531Z

## Published at

2026-06-08T06:26:37.702398Z

## Doi



## First published url

https://doi.org/10.1103/jcsd-dbl2

## Date published

2026-06-02

## Recorded date published

2026-6

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Study of the ion mobility in defect-laden                    <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">                      <mml:msub>                        <mml:mi>ZrO</mml:mi>                        <mml:mn>2</mml:mn>                      </mml:msub>                    </mml:math>                    under
    an electric field using neural network with predictions for Born effective charges
  title_type: original
  lang: en

## Description

- description: Unusual mass transport behavior in tetragonal ZrO2 ceramics have attracted
    attention under flash events induced by strong electric fields. However, this
    observation cannot be attributed solely to Joule heating, suggesting the importance
    of understanding the ion behaviors associated with defective states under a strong
    electric field. Previous studies have studied the impact of an external electric
    field, but were typically limited to fixed formal charges for the ions. In this
    work, to incorporate the response of ions to an electric field, we calculate Born
    effective charges, and use them in addition to the energy and forces to train
    neural network potentials. Our molecular dynamics simulations using trained models
    show that under an applied electric field, the diffusivity of oxygen ions is enhanced
    in defect-laden ZrO2 with a pre-existing oxygen vacancy, which could be associated
    with the observed unusual mass transport behavior. This is a milestone towards
    accurate description of defect-laden materials under an applied electric field.
  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
- name: Naoki Maekawa
  role: author
- name: Akane Ikeda
  role: author
- name: Koji Shimizu
  role: author
- name: Hiroshi Masuda
  role: author
  orcid: https://orcid.org/0000-0003-1032-8790
  organization: National Institute for Materials Science
- name: Hidehiro Yoshida
  role: author
  orcid: https://orcid.org/0000-0002-0759-8258
  organization: National Institute for Materials Science
- name: Satoshi Watanabe
  role: author
  orcid: https://orcid.org/0000-0002-8069-6938
  organization: National Institute for Materials Science

## Contact agent



## Publisher

organization: American Physical Society (APS)
ror: https://ror.org/

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## Keyword

- subject: Machine learning force field
  schema: not_defined
- subject: Zirconia
  schema: not_defined
- subject: Ion diffusion
  schema: not_defined
- subject: Point defect
  schema: not_defined
- subject: Electric field
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/
  date_licensed: 2026-06-02

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Physical Review Materials
  issn: '24759953'
  volume: '10'
  issue: '6'
  article_number: '066001'

## Conference



## Related item



## Funding

- identifier: 24K01284
  funder_name: Japan Society for the Promotion of Science
- identifier: JPMJCR1996
  funder_name: Japan Science and Technology Agency
- funder_name: University of Tokyo

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## Fileset

- id: 391f107f-1c74-4289-8c65-f639495f272f
  filename: Lu_PhysrevMaterials_2026.pdf
  content_type: application/pdf
  size: 2967641
  md5: e05812cc17c0b26824c71d0cb503cb09

## Thumbnail

fileset_id: 391f107f-1c74-4289-8c65-f639495f272f
filename: Lu_PhysrevMaterials_2026.pdf