The Electrical Resistivity of Liquid Fe-16wt%S-2wt%Si at High Pressures and the Effect of S and Si on the Dynamo in the Ancient Vestan Core
Bibliographic record
Abstract
A critical component of predicting thermal convection and dynamo action in the cores of terrestrial planetary bodies is the adiabatic heat flux at the top of the core. Powders of Fe, FeS, and Fe-9wt%Si were mixed to imitate the core of Asteroid 4 Vesta, which studies of HED meteorites indicate is comprised of 13–16wt%S and 1–2wt%Si. In a 1000-ton cubic anvil press, the voltage drop across an Fe-16wt%S-2wt%Si sample of 8–10 mm3 was measured at 2, 3, 4, and 5 GPa and ~300–2000 K. The resistivity of Fe-16wt%S-2wt%Si is 400 ± 50 μΩ·cm for 2–5 GPa for the complete liquid state. Using the Wiedemann–Franz Law, this gives an electronic thermal conductivity of 11 ± 1.5 W/m/K for 2–4 GPa at complete melting and an adiabatic heat flow of 55 ± 15 MW at the top of an early Fe-16wt%S-2wt%Si Vestan core. The 2 GPa boundary of the miscibility of Fe-16wt%S-2wt%Si is observed. The adiabatic heat flow through an Fe-16wt%S-2wt%Si core of variable size is discussed, as well as the resistivity of liquid Fe alloy at small planetary core conditions as a function of S and Si alloying composition. On the basis of previous studies on binary and ternary alloys of Fe with S and/or Si, we interpolate the separate effects of S and Si on the resistivity (and inversely on thermal conductivity and core adiabatic heat flow).
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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 | 0.000 | 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 | 0.000 |
| 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".