Elucidating oxide-ion and proton transport in ionic conductors using machine learning potentials

Ying Zhou, Sacha Fop, Abbie C. Mclaughlin, James A. Dawson

Open source

DOI: 10.1038/s41524-025-01807-y
Published: 2025-11-05
Container: npj Computational Materials
Publisher: Springer Science and Business Media LLC
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1038/s41524-025-01807-y,
  title = {Elucidating oxide-ion and proton transport in ionic conductors using machine learning potentials},
  author = {Ying Zhou and Sacha Fop and Abbie C. Mclaughlin and James A. Dawson},
  year = {2025},
  journal = {npj Computational Materials},
  doi = {10.1038/s41524-025-01807-y},
  url = {https://doi.org/10.1038/s41524-025-01807-y}
}

RIS

TY  - JOUR
TI  - Elucidating oxide-ion and proton transport in ionic conductors using machine learning potentials
AU  - Ying Zhou
AU  - Sacha Fop
AU  - Abbie C. Mclaughlin
AU  - James A. Dawson
PY  - 2025
JO  - npj Computational Materials
DO  - 10.1038/s41524-025-01807-y
UR  - https://doi.org/10.1038/s41524-025-01807-y
ER  -

APA

Zhou, Y., Fop, S., Mclaughlin, A. C., & Dawson, J. A. (2025). Elucidating oxide-ion and proton transport in ionic conductors using machine learning potentials. npj Computational Materials. https://doi.org/10.1038/s41524-025-01807-y

Source records

crossref · retrieved 2026-09-26T15:18:18.346Z