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The NuGrid AGB Evolution and Nucleosynthesis Data Set

Battino, Umberto; Pignatari, Marco; Tattersall, Ashley; Denissenkov, Pavel; Herwig, Falk

Authors

Umberto Battino

Marco Pignatari

Ashley Tattersall

Pavel Denissenkov

Falk Herwig



Abstract

Asymptotic Giant Branch (AGB) stars play a key role in the chemical evolution of galaxies. These stars are the fundamental stellar site for the production of light elements such as C, N and F, and half of the elements heavier than Fe via the slow neutron capture process (s-process). Hence, detailed computational models of AGB stars’ evolution and nucleosynthesis are essential for galactic chemical evolution. In this work, we discuss the progress in updating the NuGrid data set of AGB stellar models and abundance yields. All stellar models have been computed using the MESA stellar evolution code, coupled with the post-processing mppnp code to calculate the full nucleosynthesis. The final data set will include the initial masses Mini /Mʘ = 1, 1.65, 2, 3, 4, 5, 6 and 7 for initial metallicities Z = 0.0001, 0.001, 0.006, 0.01, 0.02 and 0.03. Observed s-process abundances on the surfaces of evolved stars as well as the typical light elements in the composition of H-deficient post-AGB stars are reproduced. A key short-term goal is to complete and expand the AGB stars data set for the full metallicity range. Chemical yield tables are provided for the available models.

Citation

Battino, U., Pignatari, M., Tattersall, A., Denissenkov, P., & Herwig, F. (2022). The NuGrid AGB Evolution and Nucleosynthesis Data Set. Universe, 8(3), Article 170. https://doi.org/10.3390/universe8030170

Journal Article Type Article
Acceptance Date Mar 2, 2022
Online Publication Date Mar 9, 2022
Publication Date Mar 1, 2022
Deposit Date Jul 25, 2024
Publicly Available Date Jul 30, 2024
Journal Universe
Electronic ISSN 2218-1997
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 8
Issue 3
Article Number 170
DOI https://doi.org/10.3390/universe8030170
Keywords Stellar evolution; Nucleosynthesis; AGB
Public URL https://hull-repository.worktribe.com/output/3960233

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Publisher Licence URL
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Copyright Statement
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).






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