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Record W1590668246 · doi:10.1086/367887

<i>s</i>‐Process Nucleosynthesis in Asymptotic Giant Branch Stars: A Test for Stellar Evolution

2003· article· en· W1590668246 on OpenAlexaff
Maria Lugaro, Falk Herwig, John C. Lattanzio, R. Gallino, O. Straniero

Bibliographic record

VenueThe Astrophysical Journal · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNucleosynthesisPhysicsAsymptotic giant branchAstrophysicsMetallicityStellar nucleosynthesisProtonStellar evolutionRadiative transfers-processNeutron starNeutronStarsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

We study the slow neutron capture process ( s -process) in asymptotic giant branch (AGB) stars using three different stellar evolutionary models computed for a 3 M ☉ , solar metallicity star. First we investigate the formation and the efficiency of the main neutron source: the 13 C(α, n ) 16 O reaction that occurs in radiative conditions. A tiny region rich in 13 C (the 13 C pocket ) is created by proton captures on the abundant 12 C in the top layers of the He intershell, the zone between the H shell and the He shell. We parametrically vary the number of protons mixed from the envelope. For high local proton-to- 12 C number ratios, p / 12 C ≳ 0.3, most of the 13 C nuclei produced are further converted by proton capture to 14 N. Besides, 14 N nuclei represent a major neutron poison. We find that a linear relationship exists between the amount of 12 C in the He intershell and the maximum value of the time-integrated neutron flux. Then we generate detailed s -process calculations on the basis of stellar evolutionary models constructed with three different codes, all of them self-consistently finding the third dredge-up, although with different efficiency. One of the codes includes a mechanism at each convective boundary that simulates time-dependent hydrodynamic overshoot. This mechanism depends on a free parameter f and results in partial mixing beyond convective boundaries, the most efficient third dredge-up, and the formation of the 13 C pocket. For the other two codes, an identical 13 C pocket is introduced in the postprocessing nucleosynthesis calculations. The models typically produce enhancements of heavy elements of about 2 orders of magnitude in the He intershell and of up to 1 order of magnitude at the stellar surface, after dilution with the convective envelope, thus generally reproducing spectroscopic observations. The results of the cases without overshoot are remarkably similar, pointing out that the important uncertainty in s -process predictions is the 13 C pocket and not the intrinsic differences among different codes when no overshoot mechanism is included. The code including hydrodynamic overshoot at each convective boundary finds that the He intershell convective zone driven by the recurrent thermal instabilities of the He shell (thermal pulses) penetrates the C-O core, producing a He intershell composition near that observed in H-deficient central stars of planetary nebulae. As a result of this intershell dredge-up, the neutron fluxes have a higher efficiency, both during the interpulse periods and within thermal pulses. The s -element distribution is pushed toward the heavier s -process elements, and large abundances of neutron-rich isotopes fed by branching points in the s -process path are produced. Several observational constraints are better matched by the models without overshoot. Our study needs to be extended to different masses and metallicities and in the space of the free overshoot parameter f .

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.262
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations216
Published2003
Admission routes1
Has abstractyes

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