Modeling of thermodiffusion in liquid metal alloys
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Bibliographic record
Abstract
In this paper following the linear non-equilibrium thermodynamics approach, an expression is derived for the calculation of the thermodiffusion factor in binary liquid metal alloys. The expression is comprised of two terms; the first term accounts for the thermally driven interactions between metal ions, a phenomenon similar to that of the non-ionic binary mixtures, such as hydrocarbons; the second term is called the electronic contribution and is the mass diffusion due to an internal electric field that is induced as a result of the imposed thermal gradient. Both terms are formulated as functions of the net heats of transport. The ion-ion net heat of transport is simulated by the activation energy of viscous flow and the electronic net heat of transport is correlated with the force acting on the ions by the rearrangement of the conduction electrons and ions. A methodology is presented and used to estimate the liquid metal properties, such as the partial molar internal energies, enthalpies, volumes and the activity coefficients used for model validation. The prediction power of the proposed expression along with some other existing thermodiffusion models for liquid mixtures, such as the Haase, Kempers, Drickamer and Firoozabadi formulas are examined against available experimental data obtained on ground or in microgravity environment. The proposed model satisfactorily predicts the thermodiffusion data of mixtures that are composed of elements with comparable melting points. It is also potentially and qualitatively able to predict a sign change in thermodiffusion factor of Na-K liquid mixture. With some speculation, the sign change is attributed to an anomalous change in thermoelectric power of Na-K mixture with composition.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it