Interaction effect on switching behaviors of paired "Pac-Man" array
Bibliographic record
Abstract
Interactions between neighboring cells become increasingly important due to the miniaturization of magnetoelectronic devices. This paper studies the effect of magnetic interaction on the switching behaviors in two different configurations of paired Pac-man shape Permalloy elements: back-to-back and face-to-face configurations. From as-patterned state MFM images, it is observed that the face-to-face configuration is prone to form either two single domains with an antiferromagnetic configuration, one single domain with one vortex or a double vortex configuration. MOKE hysteresis loops show that the coercivity for the face-to-face configuration is smaller than the back-to-back configuration. These experimental results indicate that the back-to-back configuration has weaker interaction between the two Pac-man elements than the face-to-face configuration. We further varied the aspect ratio of Pac-man elements in the pair arrays to tune the magnetic interaction. It was found that the coercivity of pair array increased with the higher cell aspect ratio. Micromagnetic simulation was also performed to simulate the switching process for the two different configurations. Overall, the back-to-back configuration is recommended for applications that demands less inter-cell interactions.
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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".