Distillation of <sup>56</sup>Fe in Ultramassive O–Ne White Dwarfs
Bibliographic record
Abstract
Abstract When white dwarfs freeze, the plasma mixtures inside them undergo separation processes that can produce radical changes in the composition profile of the star. The abundance of neutron-rich elements, such as 22Ne or 56Fe, determines whether or not the first crystals are more or less dense than the surrounding fluid and thus whether they sink or float. These processes have now been studied for C–O–Ne and C–O–Fe mixtures, finding that distillation and precipitation processes are possible in white dwarfs. In this work, we calculate the phase diagram of more complicated O–Ne–Fe mixtures and make predictions for the internal structure of the separated white dwarf. There are two possible outcomes determined by a complicated interplay between the Ne abundance, the 22Ne fraction, and the 56Fe abundance. Either Fe distills to form an inner core because the first O–Ne solids are buoyant, or an O–Ne inner core forms and Fe accumulates in the liquid until Fe distillation begins and forms an Fe shell. In the case of an Fe shell, a Rayleigh–Taylor instability may arise and overturn the core. In either case, Fe distillation may only produce a cooling delay of order 0.1 Gyr, as these processes occur early at high white dwarf luminosities. Fe inner cores and shells may be detectable through asteroseismology and could enhance the yield of neutron-rich elements such as 55Mn and 58Ni in supernovae.
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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".