Electronic structure of FeO, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>γ</mml:mi><mml:mo>−</mml:mo><mml:msub><mml:mi>Fe</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:mrow></mml:math>, and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Fe</mml:mi><mml:mn>3</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:mrow></mml:math> epitaxial films using high-energy spectroscopies
Bibliographic record
Abstract
We study the electronic structure of well-characterized epitaxial films of FeO (wustite), $\ensuremath{\gamma}\ensuremath{-}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$ (maghemite), and ${\mathrm{Fe}}_{3}{\mathrm{O}}_{4}$ (magnetite) using hard x-ray photoelectron spectroscopy (HAXPES), x-ray absorption near-edge spectroscopy (XANES), and electron energy loss spectroscopy (EELS). We carry out HAXPES with incident photon energies of 12 and 15 keV in order to probe the bulk-sensitive Fe $1s$ and Fe $2p$ core level spectra. Fe $K$-edge XANES is used to characterize and confirm the Fe valence states of FeO, $\ensuremath{\gamma}\ensuremath{-}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$, and ${\mathrm{Fe}}_{3}{\mathrm{O}}_{4}$ films. EELS is used to identify the bulk plasmon loss features. A comparison of HAXPES results with model calculations for an $M{\mathrm{O}}_{6}$ cluster provides us with microscopic electronic structure parameters such as the onsite Coulomb energy ${U}_{dd}$, the charge-transfer energy $\mathrm{\ensuremath{\Delta}}$, and the metal-ligand hybridization strength $V$. The results also provide estimates for the ground-state and final-state contributions in terms of the ${d}^{n}, {d}^{n+1}{\underline{L}}^{1}$, and ${d}^{n+2}{\underline{L}}^{2}$ configurations. Both FeO and $\ensuremath{\gamma}\ensuremath{-}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$ can be described as charge-transfer insulators in the Zaanen-Sawatzky-Allen picture with ${U}_{dd}\phantom{\rule{4pt}{0ex}}>\phantom{\rule{4pt}{0ex}}\mathrm{\ensuremath{\Delta}}$, consistent with earlier work. However, the $M{\mathrm{O}}_{6}$ cluster calculations do not reproduce an extra satellite observed in Fe $1s$ spectra of $\ensuremath{\gamma}\ensuremath{-}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$ and ${\mathrm{Fe}}_{3}{\mathrm{O}}_{4}$. Based on simplified calculations using an ${M}_{2}{\mathrm{O}}_{7}$ cluster with renormalized parameters, it is suggested that nonlocal screening plays an important role in explaining the two satellites observed in the Fe $1s$ core level HAXPES spectra of $\ensuremath{\gamma}\ensuremath{-}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$ and ${\mathrm{Fe}}_{3}{\mathrm{O}}_{4}$.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.234 | 0.043 |
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".