Electrical Resistivity of Liquid Fe‐16S‐2Si up to 13 GPa With Implications for the Adiabatic Heat Flux Through the Core of Exoplanet TRAPPIST‐1h
Bibliographic record
Abstract
Abstract Thermal convective processes in the liquid cores of terrestrial planetary bodies with the capacity to generate magnetic dynamos may be better characterized by thermal conductivity estimates of core conditions. The composition of the core of asteroid 4 Vesta as determined by geochemical studies of HED meteorites is used as an analog for the core of exoplanet TRAPPIST‐1h. Earlier electrical resistivity measurements of the Fe‐S‐Si system up to 6 GPa are extended here to 13 GPa using a 3,000‐ton multi‐anvil press. Data were collected from ambient temperatures to ∼2,000 K in each experimental run. Temperature and voltage drop across the sample were measured in situ to derive resistivity from geometry measurements of the post‐experimental sample cross‐section. At temperatures above the liquidus of Fe‐16 wt%S–2 wt%Si, the electrical resistivity is 400–500 μΩ cm and is invariant in the pressure range 5–13 GPa. From the Wiedemann‐Franz Law, the electronic contribution to the thermal conductivity is calculated as 8–10 W/m/K at the completion of melting. The adiabatic heat flux at the top of the core of TRAPPIST‐1h is estimated as 5.3 ± 2 or 6.8 ± 3 mW/m 2 in the case of a surface ice layer. For a critical value of the magnetic Reynolds number of 10, a characteristic velocity in the core of ∼0.02 mm/s is required. With selected parameter values for the core of TRAPPIST‐1h, this velocity value is likely achieved by convective heat flux, sustaining a magnetic dynamo.
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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".