<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>β</mml:mi></mml:math>-NMR Investigation of the Depth-Dependent Magnetic Properties of an Antiferromagnetic Surface
Bibliographic record
Abstract
By measuring the prototypical antiferromagnet $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$, we show that it is possible to determine the static spin orientation and dynamic spin correlations within nanometers from an antiferromagnetic surface using the nuclear spin polarization of implanted $^{8}{\mathrm{Li}}^{+}$ ions detected with $\ensuremath{\beta}$-NMR. Remarkably, the first-order Morin spin reorientation in single crystal $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{Fe}}_{2}{\mathrm{O}}_{3}$ occurs at the same temperature at all depths between 1 and 100 nm from the (110) surface; however, the implanted nuclear spin experiences an increased $1/{T}_{1}$ relaxation rate at shallow depths revealing soft-surface magnons. The surface-localized dynamics decay towards the bulk with a characteristic length of $\ensuremath{\epsilon}=11\ifmmode\pm\else\textpm\fi{}1\text{ }\text{ }\mathrm{nm}$, closely matching the finite-size thresholds of hematite nanostructures.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.234 | 0.096 |
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".