Influence of W doping on the structure, magnetism and exchange bias in Ni<sub>47</sub>Mn<sub>40</sub>Sn<sub>13<b>−</b> <i>x</i> </sub>W<sub> <i>x</i> </sub> Heusler alloys
Bibliographic record
Abstract
= 0, 0.5, 1, 1.25 at.%) magnetic shape memory alloys has been investigated. It is found that the W-doping causes a simultaneous reduction of both the ferromagnetic (FM) exchange coupling and enhancement of the magnetic anisotropy, leading to a decrease of the magnetic moment of the low-temperature phase and to a higher attainable EB. The magnetic memory measurements reveal the presence of a glassy magnetic ground state, which can significantly impact the reduction of magnetization and enhancement of EB in the studied bulk alloys. It is argued that the glassy magnetic ground state originates from the partial magnetic disorder resulting from the correlation between the antiferromagnetic and FM states. The results demonstrate that the doping by W instead of Sn is an efficient tool to tailor the EB effect in the Ni-Mn-Sn-based Heusler alloys, whereby they are promising for spintronic applications.
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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".