Total-Reflection Inelastic X-Ray Scattering from a 10-nm Thick<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>La</mml:mi><mml:mn>0.6</mml:mn></mml:msub><mml:msub><mml:mi>Sr</mml:mi><mml:mn>0.4</mml:mn></mml:msub><mml:msub><mml:mi>CoO</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:math>Thin Film
Bibliographic record
Abstract
To study equilibrium changes in composition, valence, and electronic structure near the surface and into the bulk, we demonstrate the use of a new approach, total-reflection inelastic x-ray scattering, as a sub-keV spectroscopy capable of depth profiling chemical changes in thin films with nanometer resolution. By comparing data acquired under total x-ray reflection and penetrating conditions, we are able to separate the O K-edge spectra from a 10 nm La0.6Sr0.4CoO3 thin film from that of the underlying SrTiO3 substrate. With a smaller wavelength probe than comparable soft x-ray absorption measurements, we also describe the ability to easily access dipole-forbidden final states, using the dramatic evolution of the La N4,5 edge with momentum transfer as an example.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".