Soft magnetic FeSiBPCu heteroamorphous alloys with high Fe content
Bibliographic record
Abstract
Fe–Si–B amorphous alloys with less than 80 at. % Fe are now in practical use because of their excellent magnetic softness and rather high magnetization (Js) basically owing to the lack of intrinsic magnetic anisotropy and the high Fe content, respectively. A strict upper limit of the Fe content (about 80 at. %) for the formation of a single amorphous phase with good magnetic softness hinders the improvement in Js of the Fe-based amorphous alloys. The alloys with the high Fe content exceeding the limit commonly have the as-quenched structure consisting of coarse α-Fe grains in an amorphous matrix, which inevitably results in inferior magnetic softness. The simultaneous addition of proper amounts of P and Cu is found to be significantly effective in decreasing the grain size of α-Fe phase, formed in an amorphous matrix in the as-quenched Fe82Si9B9 amorphous alloys with high Fe content exceeding the limit. Fe-rich Fe81.7Si9B7P2Cu0.3 heteroamorphous alloy with an as-quenched structure consisting of extremely small α-Fe-like clusters of about 3 nm or smaller in diameter, randomly dispersed within the amorphous matrix, exhibits the lower coercivity of 7 A m−1 and the higher Js of 1.56 T than the typical Fe-based monolithic amorphous alloy at an as-quenched state.
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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".