Effect of Ga addition on the valence state of Ce and magnetic properties of melt-spun Ce17Fe78-xB6Gax (x = 0-1.0) ribbons
Bibliographic record
Abstract
The Ce17Fe78-xB6Gax (x=0-1.0) ribbons were fabricated by a melt-spinning technique in order to study the mechanism of the valence variation of Ce and their magnetic properties as well as improve the thermal stability of Ce-based rare earth permanent magnets. The systematic investigations of the Ce17Fe78-xB6Gax (x=0-1.0) alloys show that the room-temperature coercivity increases significantly from 352 kA/m at x = 0 to 492 kA/m at x = 1.0. The Curie temperature (Tc) increases monotonically from 424.5 K to 433.6 K, and the temperature coefficients of remanence (α) and coercivity (β) of the ribbons are better off from -0.56 %/K, -0.75 %/K for x = 0 to -0.45 %/K, -0.65 %/K for x = 0.75 in the temperature range of 300–400 K, respectively. The Ce L3-edge X-ray absorption near edge structure (XANES) spectrums reveal that there is more Ce4+ in ribbons under total electron yield than fluorescence yield as Ce has a high affinity with oxygen. The weight of Ce3+ increases while the weight of Ce4+ decreases in Ga-added alloys. The refined grain size and a more uniform microstructure are mainly attributed to the improved magnetic properties and thermal stability with Ga doping. This paper may serve as a reference for further developing the so-called gap magnets and the effective utilization of the rare earth resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".