Oxygen-vacancy-induced ferromagnetism in undoped SnO<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mrow/><mml:mn>2</mml:mn></mml:msub></mml:math>thin films
Bibliographic record
Abstract
We investigated the possible formation and segregation of oxygen vacancies near the surface of SnO${}_{2}$ thin films from oxygen $K$-edge x-ray emission and absorption spectra and found that the distribution of O 2$p$ unoccupied states for ferromagnetic SnO${}_{2}$ thin films is different from that of postannealed SnO${}_{2}$ films under oxygen atmosphere showing diamagnetic behavior. This spectroscopic result suggests that oxygen vacancies can be the source of the surface-induced magnetism in SnO${}_{2}$ thin films. This possibility was then explored by calculating the lowest energy levels of the structural defects (impurities or neutral vacancies) with two localized carriers near the surface of SnO${}_{2}$ film using a quantum-mechanical approach combined with the image charge method. A magnetic triplet state is found to be the ground state of those defects in the vicinity of the SnO${}_{2}$ surface, whereas the nonmagnetic singlet is the ground state of bulk SnO${}_{2}$. Surface-induced ferromagnetic order can appear at room temperature via 2D magnetic percolation once the vacancy concentration is greater than 3 $\ifmmode\times\else\texttimes\fi{}$ 10${}^{16}$ m${}^{\ensuremath{-}2}$.
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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".