Impact of nuclear mass measurements in the vicinity of 132Sn on the r-process nucleosynthesis
Abstract
Nuclear masses are a key aspect in the modelling of nuclear reaction rates for the r-process nucleosynthesis. High precision mass measurements drastically reduce the associated uncertainties in the modelling of r-process nucleosynthesis. We investigate the impact of nuclear mass uncertainties on neutron-capture rates calculations using a Hauser – Feshbach statistical code in the vicinity of 132Sn. Finally, we study the impact of the propagated neutron-capture reaction rates uncertainties on the r-process nucleosynthesis. We find that mass measurements with uncertainties higher than 20 keV affect the calculation of reaction rates. We also note that modelling of reaction rates can differ for more than a factor of two even for experimentally known nuclear masses.
Main Authors
Format
Conferences
Conference paper
Published
2022
Series
Subjects
Publication in research information system
Publisher
National Documentation Centre (EKT)
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202211015048Use this for linking
Review status
Peer reviewed
ISSN
2654-007X
DOI
https://doi.org/10.12681/hnps.3605
Conference
Annual Symposium of the Hellenic Nuclear Physics Society
Language
English
Published in
HNPS Advances in Nuclear Physics
Is part of publication
HNPS 2021 : Proceedings of the 29th Annual Symposium of the Hellenic Nuclear Physics Society
Citation
- Nikas, Stylianos, Kankainen, Anu, Beliuskina, Olga, Nesterenko, Dmitrii, IGISOL group. (2022). Impact of nuclear mass measurements in the vicinity of 132Sn on the r-process nucleosynthesis. In G. Apostolopoulos, M. Axiotis, A.-G. Karydas, A. Lagoyannis, A. Martinou, I. E. Stamatelatos, & T. Vasilopoulou (Eds.), HNPS 2021 : Proceedings of the 29th Annual Symposium of the Hellenic Nuclear Physics Society (pp. 86-92). National Documentation Centre (EKT). HNPS Advances in Nuclear Physics, 28. https://doi.org/10.12681/hnps.3605
License
Funder(s)
European Commission
Funding program(s)
ERC Consolidator Grant
ERC Consolidator Grant
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.
Additional information about funding
The authors want to acknowledge funding from the European Union’s Horizon 2020 research and innovation programme (ERC Consolidator Grant 2017) under grant agreement No. 771036 project MAIDEN.
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