Ab initio study of elastic, thermal physical properties and electronic structure of Fe–Ga alloys
Bibliographic record
Abstract
Abstract Ab initio spin polarized calculations were carried out to study the elastic, thermal physical properties and electronic structures of Fex Ga1–x alloys. To evaluate the elastic properties, dilute supercell models were constructed for Fe–6.25 at% Ga and Fe–12.5 at% Ga alloys. In addition, possible atomic models were explored for Fe–18.75 at% Ga, in which one model that contains a pair of Ga atoms forming a cluster was suggested to represent the quench state of the alloy. The experimentally observed softness of the tetragonal shear modulus 1/2(C11 – C12) in Fe–Ga alloys was reproduced in the calculations. The ductility of Fe–Ga alloys was analyzed in terms of the ratio G /B, where G and B are the shear and bulk modulus, respectively, and the Cauchy pressure 1/2(C12 – C44). The results show that the ductility of Fe–Ga was enhanced with increasing Ga concentration. The relation between linear thermal expansion coefficients α (T) and Ga content was also examined. It was demonstrated that both bulk modulus B and the Grüneisen parameter γ play a major role in determining the trend in thermal expansion coefficients. The electronic structures of Fe–Ga alloys were investigated, and the characteristics of electronic density of states were analyzed. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".