Exchange Bias in NiFe/CoO/Fe<inf>2</inf>O<inf>3</inf> Trilayer
Bibliographic record
Abstract
The magnetic properties of magnetic trilayer structures are influenced by both the interfacial exchange coupling and the interlayer exchange coupling (IEC). Our previous results have shown strong IEC between ferromagnetic (FM) NiFe and Co through 12-nm-thick antiferromagnetic (AF) CoO spacer in FM1/AF/FM2 trilayer [1]. This has inspired us to further explore whether IEC between FM and AF2 also exists in FM/AF1/ AF2 trilayer. α-Fe2O3has AF coupling below 948 K. Large exchange bias (Hex) is observed in α-Fe2O3. /NiO nanocomposite, while the exchange coupling in α-Fe2O3/AF is not well understood [2]. In this work, the magnetic properties of NiFe/CoO/Fe2O3trilayers are comparatively studied with NiFe/CoO and NiFe/Fe2O3bilayers to investigate the exchange coupling in FM/AF1/AF2 geometry and to explore the mechanism of α-Fe2O3 interaction.
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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) | 0.002 | 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".