Ordering and segregation in<i>X</i>Pt (<i>X</i>=V, Cu, and Au) random alloys
Bibliographic record
Abstract
We examine the phase stability and the ordering tendencies of some Pt-based fcc random alloys using the generalized perturbation method (GPM) implemented in the linear muffin-tin orbitals (LMTO) basis. The reference medium for the GPM is chosen as the completely disordered state of the alloy and its electronic structure is described in the coherent potential approximation (CPA). Ordering tendencies and phase stability are examined via effective pair interactions and their lattice Fourier transforms. Relativistic effects on the ground state cohesive properties and the ordering tendencies are determined by carrying out nonrelativistic and fully relativistic (in some cases also scalar-relativistic) LMTO-CPA calculations. In all cases considered, namely $X\mathrm{Pt}$ with $X=\mathrm{V},$ Cu, and Au, the correct ordering tendency is obtained. The ordering tendency is found to be somewhat overestimated in the GPM. Relativistic effects are found to be most prominent in AuPt, where the nonrelativistic LMTO-CPA-GPM description shows a tendency towards ${L1}_{1}$ ordering and the correct result, i.e., phase segregation, is obtained only in the fully relativistic description. The sensitivity of the ordering tendency to factors such as lattice relaxation and volume per atom is examined briefly. Finally, the effect on the phase stability of adding a third component, such as V or Au to CuPt alloy, is studied by extending the formalism to the case of a ternary alloy.
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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 | 0.001 | 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) | 0.000 | 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".