Thermodynamic Evaluation and Optimization of the As–Cd, As–Zn and As–Cd–Zn Systems
Bibliographic record
Abstract
Abstract In this work, a critical evaluation of all available phase diagrams and thermodynamic data for the As–Cd, As–Zn and As–Cd–Zn systems has been performed and thermodynamic assessments over the whole composition ranges are presented using the CALPHAD method. To predict thermodynamic properties and phase equilibria for these systems, the Modified Quasichemical Model for short range ordering was used for the liquid phase and the Compound Energy Formalism was used for the solid solutions. The optimized binary systems are in good agreement with existing experimental data. Within the ternary system predicted phase equilibria, the $${\text{ZnAs}}_{2}{-}{\text{CdAs}}_{2}$$ ZnAs 2 - CdAs 2 and $${{\text{Zn}}_{3}\text{As}}_{2}{-}{{\text{Cd}}_{3}\text{As}}_{2}$$ Zn 3 As 2 - Cd 3 As 2 sections are in good agreement with the experimental data. Also, the eutectic temperature is accurately optimized for $${\text{ZnAs}}_{2}{-}{{\text{Cd}}_{3}\text{As}}_{2}$$ ZnAs 2 - Cd 3 As 2 and $${{\text{Zn}}_{3}\text{As}}_{2}{-}{\text{CdAs}}_{2}$$ Zn 3 As 2 - CdAs 2 . However, the calculated liquidus of these two joins are less satisfactory compared to the experimental data. This is most likely due to the polymerization behavior of arsenic and its multivalence, which is not considered by the model used in this work.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".