NdFeB Magnets Manufactured by Hot Pressing Using Strip-Cast and Melt-Spun Powders
Bibliographic record
Abstract
The initial powder used for the manufacturing of NdFeB permanent magnets is usually prepared through rapid cooling, either by melt spinning or strip casting. The powders produced by these two methods are suitable for different applications: while melt-spun powder is a good initial material for bonded and hot-deformed magnets, strip-cast powder is normally used for sintered magnets. To investigate the suitability of using strip-cast powder to manufacture hot-deformed magnets, NdFeB powder prepared by strip casting was hot pressed (without particle alignment) and compared with melt-spun powder prepared under the same conditions (700 °C, 45 MPa, 90 min). Although the processing parameters are the same (pressed in the same mold), the magnetic properties of the magnets made from the two powders are significantly different. Surprisingly, the magnet made from the strip-cast powder (after ball milling) shows comparable magnetic properties to those of isotropic magnets, with coercivity (HcJ) of 1270 kA/m and remanence (Br) of 0.7 T, while that made from the melt-spun powder exhibits much lower properties: HcJ = 480 kA/m, Br = 0.5 T, although the melt-spun powder initially shows much better magnetic properties than the strip-cast powder. Possible reasons for such a difference in magnetic properties are discussed. It was shown that the particle size of the initial powder plays an important role in determining the final magnetic properties of the hot-pressed magnets.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".