First-Principles Determination of Transference Numbers in Cryolitic Melts
Bibliographic record
Abstract
Abstract The charge and electron-transport properties of molten ionic systems are among the most relevant properties to consider in the control of several electrochemical processes. First-principles-based equilibrium molecular dynamics (EMD) can provide reliable predictions of both total and partial charge-transport properties. In this work, we calculate the charge-transport properties of the electrolytic bath (Na3AlF6–AlF3–Al2O3) of the Hall–Héroult electrolysis cells. We predict both individual and collective charge-transport properties (total and partial conductivities and self-diffusion coefficients) for 11 different compositions typical of industrial conditions via a series of EMD simulations. The predicted total and partial ionic conductivities and their composition dependence are compared to available experimental data. A good agreement is obtained for all studied compositions. From a more fundamental point of view, the microscopic aspect of the charge-transport properties of cryolitic melts is discussed through its correlation with the local structure of different melts. Deviations between the calculated partial conductivities and those derived via the Nernst–Einstein approximation can be explained by the presence of strong short-range ordering within the melts.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".