THE WEAK<i>s</i>-PROCESS IN MASSIVE STARS AND ITS DEPENDENCE ON THE NEUTRON CAPTURE CROSS SECTIONS
Bibliographic record
Abstract
The slow neutron capture process in massive stars (weak s process) produces most of the s -process isotopes between iron and strontium. Neutrons are provided by the 22 Ne(α,n) 25 Mg reaction, which is activated at the end of the convective He-burning core and in the subsequent convective C-burning shell. The s -process-rich material in the supernova ejecta carries the signature of these two phases. In the past years, new measurements of neutron capture cross sections of isotopes beyond iron significantly changed the predicted weak s -process distribution. The reason is that the variation of the Maxwellian-averaged cross sections (MACS) is propagated to heavier isotopes along the s path. In the light of these results, we present updated nucleosynthesis calculations for a 25 M ☉ star of Population I (solar metallicity) in convective He-burning core and convective C-burning shell conditions. In comparison with previous simulations based on the Bao et al. compilation, the new measurement of neutron capture cross sections leads to an increase of s -process yields from nickel up to selenium. The variation of the cross section of one isotope along the s -process path is propagated to heavier isotopes, where the propagation efficiency is higher for low cross sections. New 74 Ge, 75 As, and 78 Se MACS result in a higher production of germanium, arsenic, and selenium, thereby reducing the s -process yields of heavier elements by propagation. Results are reported for the He core and for the C shell. In shell C-burning, the s -process nucleosynthesis is more uncertain than in the He core, due to higher MACS uncertainties at higher temperatures. We also analyze the impact of using the new lower solar abundances for CNO isotopes on the s -process predictions, where CNO is the source of 22 Ne, and we show that beyond Zn this is affecting the s -process yields more than nuclear or stellar model uncertainties considered in this paper. In particular, using the new updated initial composition, we obtain a high s -process production (overproduction higher than 16 O, ∼100) for Cu, Ga, Ge, and As. Using the older abundances by Anders & Grevesse, also Se, Br, Kr, and Rb are efficiently produced. Our results have important implications in explaining the origin of copper in the solar abundance distribution, pointing to a prevailing contribution from the weak s -process in agreement with spectroscopic observations and Galactic chemical evolution calculations. Because of the improvement due to the new MACS for nickel and copper isotopes, the nucleosynthesis of copper is less affected by nuclear uncertainties compared to heavier s -process elements. An experimental determination of the 63 Ni MACS is required for a further improvement of the abundance prediction of copper. The available spectroscopic observations of germanium and gallium in stars are also discussed, where most of the cosmic abundances of these elements derives from the s -process in massive stars.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".