Compaction and Melt Transport in Ammonia‐Rich Ice Shells: Implications for the Evolution of Triton
Bibliographic record
Abstract
Abstract Ammonia, if present in the ice shells of icy satellites, could lower the temperature for the onset of melting to 176 K and create a large temperature range where partial melt is thermally stable. The evolution of regions of ammonia‐rich partial melt could strongly influence the geological and thermal evolution of icy bodies. For melt to be extracted from partially molten regions, the surrounding solid matrix must deform and compact. Whether ammonia‐rich melts sink to the subsurface ocean or become frozen into the ice shell depends on the compaction rate and thermal evolution. Here we construct a model for the compaction and thermal evolution of a partially molten, ammonia‐rich ice shell in a one‐dimensional geometry. We model the thickening of an initially thin ice shell above an ocean with 10% ammonia. We find that ammonia‐rich melts can freeze into the upper 5 to 10 km of the ice shell, when ice shell thickening is rapid compared to the compaction rate. The trapping of near‐surface volatiles suggests that, upon reheating of the ice shell, eutectic melting events are possible. However, as the ice shell thickening rate decreases, ammonia‐rich melt is efficiently excluded from the ice shell and the bulk of the ice shell is pure water ice. We apply our results to the thermal evolution of Neptune's moon Triton. As Triton's ice shell thickens, the gradual increase of ammonia concentration in Triton's subsurface ocean helps to prevent freezing and increases the predicted final ocean thickness by up to 50 km.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".