{
  "annotation_id": "65cb634a-ddd8-465d-a342-8c6abef73e62",
  "date_created": "2026-02-17T05:53:04.667000Z",
  "date_modified": "2026-02-17T05:53:04.667000Z",
  "file_hash": "34bb002833139f273ae5699745dac41072ce90d3d7f42e05ae4dc3150488a5ef",
  "private": false,
  "record": {
    "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\u0027 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/Msun = 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.",
    "arxiv_id": "2601.05723",
    "authors": [
      "Umberto Battino",
      "Marco Pignatari",
      "Ashley Tattersall",
      "Pavel Denissenkov",
      "Falk Herwig"
    ],
    "categories": [
      "astro-ph.SR"
    ],
    "doi": "10.3390/universe8030170",
    "journal_ref": "Universe 2022, 8, 170",
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "The NuGrid AGB Evolution and Nucleosynthesis Data Set",
    "url": "https://arxiv.org/abs/2601.05723",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "7ccc26be-e77a-4b9b-b4b2-2f2546c89be4",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}