The <i>s</i> -Process in Massive Stars at Low Metallicity: The Effect of Primary <sup>14</sup> N from Fast Rotating Stars
Bibliographic record
Abstract
The goal of this Letter is to analyze the impact of a primary neutron source on the s -process nucleosynthesis in massive stars at halo metallicity. Recent stellar models including rotation at very low metallicity predict a strong production of primary 14 N. Part of the nitrogen produced in the H-burning shell diffuses by rotational mixing into the He core where it is converted to 22 Ne providing additional neutrons for the s -process. We present nucleosynthesis calculations for a 25 M ☉ star at [Fe/H] = –3, –4, where about 0.8% in mass is made of primary 22 Ne in the convective He-burning core. The usual weak s -process shape is changed by the additional neutron source with a peak between Sr and Ba, where the s -process yields increase by orders of magnitude with respect to the yields obtained without rotation. Iron seeds are fully consumed and the maximum production of Sr, Y, and Zr is reached. On the other hand, the s -process efficiency beyond Sr and the ratio Sr/Ba are strongly affected by the amount of 22 Ne and by nuclear uncertainties, first of all by the 22 Ne(α, n ) 25 Mg reaction. Finally, assuming that 22 Ne is primary in the considered metallicity range, the s -process efficiency decreases with metallicity due to the effect of the major neutron poisons 25 Mg and 22 Ne. This work represents a first step toward the study of primary neutron source effect in fast rotating massive stars, and its implications are discussed in the light of spectroscopic observations of heavy elements at halo metallicity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".