Evidence map›Paper›PMID 40897701›Full record

ArticleNature communications2025

Thermodynamics-inspired high-entropy oxide synthesis.

Saeed S I Almishal, Matthew Furst, Yueze Tan, Jacob T Sivak, Gerald Bejger, Joseph Petruska, Sai Venkata Gayathri Ayyagari, Dhiya Srikanth, Nasim Alem, Christina M Rost and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Improved Deformability of Co-Free Medium Entropy Oxides by Controlled Entropy Destabilization.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Artificial Intelligence-Assisted Design of High-Entropy Oxide Catalysts.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  3. Article
  4. Article
  5. Chemically-Disordered Transparent Conductive Perovskites With High Crystalline Fidelity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  6. Synthesis-Driven Functionality in High-Entropy Materials.Small (Weinheim an der Bergstrasse, Germany) · 2025
    Review
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

13 authors.

Saeed S I AlmishalDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA. saeedsialmishal@gmail.com.ORCID http://orcid.org/0000-0003-2964-6000
Matthew FurstDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0009-0005-1729-2526
Yueze TanDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0009-0005-9657-4475
Jacob T SivakDepartment of Chemistry, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0000-0001-9464-3821
Gerald BejgerDepartment of Materials Science and Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Joseph PetruskaDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.
Sai Venkata Gayathri AyyagariDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0009-0005-0242-8574
Dhiya SrikanthDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.
Nasim AlemDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0000-0003-0009-349X
Christina M RostDepartment of Materials Science and Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.ORCID http://orcid.org/0000-0002-6153-6066
Susan B SinnottDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0000-0002-3598-0403
Long-Qing ChenDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.ORCID http://orcid.org/0000-0003-3359-3781
Jon-Paul MariaDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-entropy oxide (HEO) thermodynamics transcend temperature-centric approaches, spanning a multidimensional landscape where oxygen chemical potential plays a decisive role. Here, we experimentally demonstrate how controlling the oxygen chemical potential coerces multivalent cations into divalent states in rock salt HEOs. We construct a preferred valence phase diagram based on thermodynamic stability and equilibrium analysis, alongside a high throughput enthalpic stability map derived from atomistic calculations leveraging machine learning interatomic potentials. We identify and synthesize seven equimolar, single-phase rock salt compositions incorporating Mn, Fe, or both, as confirmed by X-ray diffraction and fluorescence. Energy-dispersive X-ray spectroscopy confirms homogeneous cation distribution, whereas X-ray absorption fine structure analysis reveals predominantly divalent Mn and Fe states, despite their inherent multivalent tendencies. Ultimately, we introduce oxygen chemical potential overlap as a key complementary descriptor for predicting HEO stability and synthesizability. Although we focus on rock salt HEOs, our methods are chemically and structurally agnostic, providing a broadly adaptable framework for navigating HEOs thermodynamics and enabling a broader compositional range with contemporary property interest.

Identifiers

PMID40897701
PMCPMC12405472

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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.