Effects of post-deposition magnetic field annealing on magnetic properties of NiO/Co <sub>90</sub> Fe <sub>10</sub> bilayers
Bibliographic record
Abstract
Abstract The ferromagnetic (FM)/antiferromagnetic (AF) bilayer structures have drawn intensive attention because of their wide applications in modern spintronic devices. While abundant published works have been reported on the interface effects of the FM/AF bilayers caused by the magnetic field annealing (MFA) process, the volume effects caused by the MFA treatment have been rarely considered. In this work, the microstructural and magnetic properties of the NiO/CoFe bilayers with various CoFe thicknesses were investigated under different annealing temperatures. At high annealing temperature, the interlayer mixing and exchange coupling between NiO and CoFe layers were promoted and consequently the interface effects were facilitated. The interfacial oxides acted as pinning centers and randomly pinned the FM domains, leading to an increase of coercivity and a considerable degradation of uniaxial anisotropy. The increase of coercivity was also contributed by the enhancement of the interfacial exchange coupling between the NiO and CoFe layers after MFA. As the CoFe thickness increased, the volume effects tended to dominate over the interface effects, resulting in the preservation the uniaxially anisotropic features of CoFe. These results indicate that both the coercivity and anisotropic features of the NiO/CoFe bilayers can be directly affected by the MFA process, opening up the possibility of modifying the magnetism in the NiO/CoFe bilayers and offering an effective way to improve the performance of modern spintronic devices.
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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".