Evidence map›Paper›PMID 39928874›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Resolving the dynamic correlated disorder in KTa

Xing He, Mayanak K Gupta, Douglas L Abernathy, Garrett E Granroth, Feng Ye, Barry L Winn, Lynn Boatner, Olivier Delaire

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Resolving the dynamic correlated disorder in KTaProceedings of the National Academy of Sciences of the United States of America · 2025
    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

8 authors.

Xing HeDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708.ORCID 0000-0002-6594-5721
Mayanak K GuptaDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708.ORCID 0000-0002-9016-2438
Douglas L AbernathyNeutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830.ORCID 0000-0002-3533-003X
Garrett E GranrothNeutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830.ORCID 0000-0002-7583-8778
Feng YeNeutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830.ORCID 0000-0001-7477-4648
Barry L WinnNeutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830.ORCID 0000-0001-6383-4318
Lynn BoatnerMaterials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830.
Olivier DelaireDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708.ORCID 0000-0003-1230-2834

Funding

U.S. Department of Energy (DOE) DE-SC0019978
6 · The paper itself

Abstract

Understanding the complex temporal and spatial correlations of ions in disordered perovskite oxides is critical to rationalize their functional properties. Here, we provide insights into the longstanding controversy regarding the off-centering of transition metal (TM) ions in the archetypal ferroelectric alloy KTa[Formula: see text]Nb[Formula: see text]O[Formula: see text] (KTN). By mapping the full energy ([Formula: see text]) and wavevector ([Formula: see text]) dependence of the dynamical structure factor [Formula: see text] using neutron scattering, and rationalizing our observations with atomistic simulations leveraging machine learning, we fully resolve the static

Indexed as

atomistic simulationsdisordered alloysferroelectricsneutron scatteringphase transitions

Identifiers

PMID39928874
PMCPMC11848325

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.