A thermodynamic description for water, hydrogen fluoride and hydrogen dissolutions in cryolite-base molten salts
Bibliographic record
Abstract
This paper presents a quantitative thermodynamic description for water, hydrogen fluoride and hydrogen dissolutions in cryolite-base molten salts, which is of technological importance to the Hall-Héroult electrolytic aluminum extraction cell. The Modified Quasichemical Model in the Quadruplet Approximation (MQMQA), as used to treat a large variety of molten salt systems, was adopted to thermodynamically describe the present liquid phase; all solid solutions were modeled using the Compound Energy Formalism (CEF); the gas phase was thermodynamically treated as an ideal mixture of all possible species. The model parameters were mainly obtained by critical evaluations and optimizations of thermodynamic and phase equilibrium data available from relative experimental measurements and theoretical predictions (first-principles calculations and empirical estimations) for the lower-order subsystems. These optimized model parameters were thereafter merged within the Kohler/Toop interpolation scheme, facilitating the prediction of gas solubility (H2O, HF and H2) in multicomponent cryolite-base molten salts using the FactSage thermochemical software. Several interesting diagrams were finally obtained in order to provide useful information for the industrial partners dedicated to the Hall-Héroult electrolytic aluminum production or other molten-salt technologies (the purification process and electroslag refining).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".