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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.004 | 0.009 |
| Meta-epidemiology (broad) | 0.002 | 0.009 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.010 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.619 | 0.008 |
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; both teacher heads agree on what is shown here.
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".