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We study the impact of astrophysically relevant nuclear isomers (astromers) in the context of the rapid neutron capture process (r-process) nucleosynthesis. We compute thermally mediated transition rates between long-lived isomers and the corresponding ground states in neutron-rich nuclei. We calculate the temperature-dependent beta-decay feeding factors which represent the fraction of material going to each of the isomer and ground state daughter species from the beta-decay parent species. We simulate nucleosynthesis by including as separate species nuclear excited states with measured terrestrial half-lives greater than 100 microseconds. We find a variety of isomers throughout the chart of nuclides are populated, and we identify those most likely to be influential. We comment on the capacity of isomer production to alter radioactive heating in an r-process environment.
We report on the creation and application of a novel decay network that uses the latest data from experiment and evaluation. We use the network to simulate the late-time phase of the rapid neutron capture (r) process. In this epoch, the bulk of nucle
We study the neutrino-induced production of nuclides in explosive supernova nucleosynthesis for progenitor stars with solar metallicity and initial main sequence masses between 15 M$_odot$ and 40 M$_odot$. We improve previous investigations i) by usi
We develop a method to compute thermally-mediated transition rates between the ground state and long-lived isomers in nuclei. We also establish criteria delimiting a thermalization temperature above which a nucleus may be considered a single species
We have performed r-process calculations for matter ejected dynamically in neutron star mergers based on a complete set of trajectories from a three-dimensional relativistic smoothed particle hydrodynamic simulation. Our calculations consider an exte
Any simulation of the r-process is affected by uncertainties in our present knowledge of nuclear physics quantities and astrophysical conditions. It is common to quantify the impact of these uncertainties through a global sensitivity metric, which is