The interplay of selective occupation and magnetic properties of high entropy spinel oxides
Bibliographic record
Abstract
We investigate the interplay between the selective occupation (cationic site and valence preferences) and magnetic properties of three high entropy spinel oxides (HESOs). One of the samples ((Co,Cr,Fe,Mn,Ni) 3 O 4 ) is well known in the literature, while the other two HESOs ((Co,Fe,Mn) 3 O 4 , (Co,Fe,Mn,Ni) 3 O 4 ) are unstudied. XAS and RIXS of the transition metal L-edge, and ligand field theory (LFT) calculations were also used to determine the selective occupation. We found that nickel and chromium assume exclusively O h 2 + and O h 3 + sites, respectively. Iron undergoes a transition from O h 3 + to T d 3 + with increasing entropy. Manganese and cobalt adapt according to the remaining cations. The determined selective occupation can accurately predict the trend of the saturation magnetic moment μ s a t . The decrease in μ s a t correlates with the transition of iron cations. Gaining a more extensive understanding of how the selective occupation is directed, and what implications this has on the structural, electronic, and magnetic properties, will lead the way to tailoring HESOs to individual applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".