Investigation of multiplet splitting of Fe 2p XPS spectra and bonding in iron compounds
Bibliographic record
Abstract
Abstract Ferrous (Fe 2+ ) and ferric (Fe 3+ ) compounds were investigated by XPS to determine the usefulness of calculated multiplet peaks to fit high‐resolution iron 2p 3/2 spectra from high‐spin compounds. The multiplets were found to fit most spectra well, particularly when contributions attributed to surface peaks and shake‐up satellites were included. This information was useful for fitting of the complex Fe 2p 3/2 spectra for Fe 3 O 4 where both Fe 2+ and Fe 3+ species are present. It was found that as the ionic bond character of the iron —ligand bond increased, the binding energy associated with either the ferrous or ferric 2p 3/2 photoelectron peak also increased. This was determined to be due to the decrease in shielding of the iron cation by the more increasingly electronegative ligands. It was also observed that the difference in energy between a high‐spin iron 2p 3/2 peak and its corresponding shake‐up satellite peak increased as the electronegativity of the ligand increased. The extrinsic loss spectra for ion oxides are also reported; these are as characteristic of each species as are the photoelectron peaks. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".