Magnetostatic Interaction Investigation of CoFe Alloy Nanowires by First-Order Reversal-Curve Diagrams
Bibliographic record
Abstract
Magnetic CoFe alloy nanowires were alternating current (ac)-pulse electrodeposited into the nanopores of hard anodized aluminum oxide templates. The effect of nanowires lengths on the magnetostatic interactions was investigated using first-order reversal-curve (FORC) method. FORC diagrams obtained from nanowire arrays with different lengths show drastic improvement in magnetic properties with decreasing the nanowires length. The coercivity reaches 995 Oe from initially 790 Oe. Also, the squareness enhances from 0.62 to 0.92, showing the decrease in magnetostatic interactions between the nanowires. FORC diagrams prove the decrease in magnetostatic interactions in nanowires with shorter lengths. With decreasing the nanowires length, the spread of distribution in the${\rm H}_{\rm u}$-direction decreases. It varies from 1600 to 900 Oe when length decreases from 27 to 8$\mu$m. FORC diagrams also reveal formation of nanowire arrays with dominant interacting single domain (SD).
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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".