Growth, structure, electronic, and magnetic properties of MgO/Fe(001) bilayers and Fe/MgO/Fe(001) trilayers
Bibliographic record
Abstract
Single-crystal epitaxial MgO thin films were grown directly onto high-quality Fe single crystal and Fe whisker substrates and covered with Fe/Au layers. Reflection high-energy electron diffraction and low-energy electron diffraction patterns and scanning tunneling microscopy images showed that the growth of MgO proceeded pseudomorphically in a nearly layer-by-layer mode up to six monolayers. A misfit dislocation network is formed for MgO layers thicker than six monolayers. The thin MgO films were characterized electrically by scanning tunneling spectroscopy. The tunneling barrier in MgO was found to depend on the MgO layer thickness, starting from 2.5 eV at two monolayer thickness to the expected full barrier of MgO of 3.6 eV at six monolayers. A small fraction of the scanned area showed randomly placed spikes in the tunneling conductance. Tunneling I-$V$ curves at the defects showed a lower tunneling barrier than that in the majority of the MgO film. The total tunneling current integrated over areas of $100\ifmmode\times\else\texttimes\fi{}100 {\mathrm{nm}}^{2},$ however, was not dominated by spikes of higher conductance. These local defects in the MgO barrier were neither related to atomic steps on the Fe substrates nor to individual misfit dislocations. Magnetic anisotropies and exchange coupling in Fe/MgO(001) and Fe/MgO/Fe(001) structures were studied using ferromagnetic resonance and Brillouin light scattering.
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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) | 0.000 | 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".