Evidence map›Paper›PMID 41916973›Full record

ArticleNature communications2026

A statistical understanding of oxygen vacancies in distorted high-entropy perovskite oxides.

Adam Potter, Yifan Wang, Kiran Hamkins, Dongjae Kong, Yuzhe Li, Jian Qin, Xiaolin Zheng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Artificial Intelligence-Assisted Design of High-Entropy Oxide Catalysts.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Adam PotterDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-7889-6180
Yifan WangDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9468-2484
Kiran HamkinsDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0009-0008-9450-9970
Dongjae KongDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA.
Yuzhe LiDepartment of Material Science and Engineering, Stanford University, Stanford, CA, USA.
Jian QinDepartment of Chemical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-6271-068X
Xiaolin ZhengDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA. xlzheng@stanford.edu.ORCID http://orcid.org/0000-0002-8889-7873

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-entropy perovskite oxides have emerged as promising electrode materials for solid oxide electrolyzers. However, their compositional complexity makes the formation of oxygen vacancies, which influence properties such as oxygen ionic conductivity and thermal expansion, challenging to predict. Here, we experimentally measure changes in oxygen vacancy concentration for fourteen perovskite oxides with high and low-entropy A-site compositions, finding a dependence on cation size variance in addition to divalent cation fraction. Atomistic simulations using a machine-learned universal interatomic potential reveal cation size mismatches broaden a distribution of vacancy formation energies, shown through statistical thermodynamics to shift bulk formation thermodynamics. Treating oxygen vacancies statistically enables accurate predictions of oxygen vacancy formation compared to traditional models. Practically, increasing the size variance between A-site cations reduces the temperature sensitivity of oxygen vacancy concentrations, making it key for tuning critical properties. More broadly, this study demonstrates statistical treatment of oxygen vacancies is essential for understanding high-entropy perovskite oxides.

Identifiers

PMID41916973
PMCPMC13199509

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.