Cd-doping effects in Ni–Mn–Sn: experiment and <i>ab-initio</i> study
Bibliographic record
Abstract
Abstract Martensitic transformation (MT), magnetic properties, and magnetocaloric effect (MCE) in Heusler-type Ni47Mn40Sn13−x Cd x (x= 0, 0.75, 1, 1.25 at. %) metamagnetic shape memory alloys (MetaMSMAs) are investigated, both experimentally and theoretically, as a function of doping with Cd. Ab-initio computations reveal that the ferromagnetic (FM) configuration is energetically more favorable in the cubic phase than the antiferromagnetic (AFM) state in undoped and doped alloys as well. Moreover, it is revealed that the alloys in the ground state exhibit a tetragonal structure confirming the existence of MT, in agreement with the experiments. It was indicated, both in theory and practice, that a reduction of the unit cell volume and an increase of the MT temperature as a function of the Cd doping. Indirect estimations of MCE in the vicinity of MT were carried out by using thermomagnetization curves measured under different magnetic fields up to 5 T. The results demonstrated that the doped alloys exhibit enhanced values of the inverse MCE comparable with those of Ni-Mn-based MetaMSMAs. Maximum magnetic entropy change in a field change of 2 T increases from 3.0 J .k g − 1 K − 1 for the undoped alloy to 3.4 and 5.0 J .k g − 1 K − 1 for the alloys doped with 0.75 and 1 at.% of Cd, respectively. The inverse and conventional MCE were explored by direct measurements of the adiabatic temperature change under the magnetic field change of 1.96 T. The Cd doping increased the maximum of inverse MCE by nearly 78% from 0.9 K to 1.6 K for the undoped and doped alloys, respectively. The results depicted that Cd doping can effectively tailor the structural, magnetic, and MCE properties of the Ni–Mn–Sn MetaMSMAs.
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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 | 0.001 | 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".