Approaching the theoretical coercivity of Nd2Fe14B: Microstructural evaluation and interparticle interactions
Bibliographic record
Abstract
The microstructure of melt–spun rapidly quenched NdδFe13.1B (2.05⩽δ⩽147.6) and NdδFe14B (δ=40.6,151.7) ribbons was tailored by appropriate annealing from strongly interacting to magnetically isolated single domain Nd2Fe14B grains embedded in a nonmagnetic matrix of α-Nd and γ-Nd. This microstructure, as characterized by a variation in the magnetic interaction between Nd2Fe14B grains, was found to have a large impact on coercivity, μ0Hc, i.e., coercivity increases with an increase in the Nd concentration from 1.2 T in Nd2.05Fe13.1B to 2.75 T in Nd147.6Fe13.1B at 290 K. A detailed study of the microstructure of NdδFe13.1B (δ=38.1,148.7), carried out by conventional transmission electron microscopy, energy-filtered imaging, and energy dispersive x-ray microanalysis, showed that the majority of the Nd2Fe14B grains are completely isolated only in Nd147.6Fe13.1B. The Nd2Fe14B grains, in Nd147.6Fe13.1B, are found to be randomly oriented platelets with the c axis normal to the platelet and an average size of 100×40×25 nm. For these randomly oriented, noninteracting, single domain Nd2Fe14B grains, the coercivity was calculated using the Stoner–Wohlfarth model and including the shape anisotropy of the grains. The observed coercivity of Nd2Fe14B in Nd147.6Fe13.1B is ∼83% of this theoretical value and is the largest so far reported for Nd2Fe14B.
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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".