Determining the Surface-To-Bulk Progression in the Normal-State Electronic Structure of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>Sr</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>RuO</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:math>by Angle-Resolved Photoemission and Density Functional Theory
Bibliographic record
Abstract
We revisit the normal-state electronic structure of Sr(2)RuO(4) by angle-resolved photoemission spectroscopy with improved data quality, as well as ab initio band structure calculations in the local-density approximation with the inclusion of spin-orbit coupling. We find that the current model of a single surface layer (√2×√2)R45° reconstruction does not explain all detected features. The observed depth-dependent signal degradation, together with the close quantitative agreement with the slab calculations based on the surface crystal structure as determined by low-energy electron diffraction, reveal that-at a minimum-the subsurface layer also undergoes a similar although weaker reconstruction. This model accounts for all features-a key step in understanding the electronic structure-and indicates a surface-to-bulk progression of the electronic states driven by structural instabilities. Finally, we find no evidence for other phases stemming from either topological bulk properties or, alternatively, the interplay between spin-orbit coupling and the broken symmetry of the surface.
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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 | 0.000 |
| Scholarly communication | 0.000 | 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".