Impact of nuclear mass measurements in the vicinity of 132Sn on the r-process nucleosynthesis
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
Julkaistu sarjassa
HNPS Advances in Nuclear PhysicsToimittajat
Päivämäärä
2022Tekijänoikeudet
© 2022 Authors
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.
Julkaisija
National Documentation Centre (EKT)Konferenssi
Annual Symposium of the Hellenic Nuclear Physics SocietyKuuluu julkaisuun
HNPS 2021 : Proceedings of the 29th Annual Symposium of the Hellenic Nuclear Physics SocietyISSN Hae Julkaisufoorumista
2654-007XAsiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/159358575
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Euroopan komissioRahoitusohjelmat(t)
The content of the publication reflects only the author’s view. The funder is not responsible for any use that may be made of the information it contains.
Lisätietoja rahoituksesta
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.Lisenssi
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