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We calculate Galactic Chemical Evolution (GCE) of Mo and Ru by taking into account the contribution from $ u p$-process nucleosynthesis. We estimate yields of $p$-nuclei such as $^{92,94}mathrm{Mo}$ and $^{96,98}mathrm{Ru}$ through the $ u p$-process in various supernova (SN) progenitors based upon recent models. In particular, the $ u p$-process in energetic hypernovae produces a large amount of $p$-nuclei compared to the yield in ordinary core-collapse SNe. Because of this the abundances of $^{92,94}mathrm{Mo}$ and $^{96,98}mathrm{Ru}$ in the Galaxy are significantly enhanced at [Fe/H]=0 by the $ u p$-process. We find that the $ u p$-process in hypernovae is the main contributor to the elemental abundance of $^{92}$Mo at low metallicity [Fe/H$]<-2$. Our theoretical prediction of the elemental abundances in metal-poor stars becomes more consistent with observational data when the $ u p$-process in hypernovae is taken into account.
The $ u p$ process appears in proton-rich, hot matter which is expanding in a neutrino wind and may be realised in explosive environments such as core-collapse supernovae or in outflows from accretion disks. The impact of uncertainties in nuclear rea
We test the hypothesis that the observed first-peak (Sr, Y, Zr) and second-peak (Ba) s-process elemental abundances in low metallicity Milky Way stars ($text{[Fe/H]} lesssim -0.5$), and the abundances of the intervening elements Mo and Ru, can be exp
It has been suggested that a $ u$p process can occur when hot, dense, and proton-rich matter is expanding within a strong flux of anti-neutrinos. In such an environment, proton-rich nuclides can be produced in sequences of proton captures and (n,p) r
Modeling the evolution of the elements in the Milky Way is a multidisciplinary and challenging task. In addition to simulating the 13 billion years evolution of our Galaxy, chemical evolution simulations must keep track of the elements synthesized an
The solar s-process abundances have been analyzed in the framework of a Galactic Chemical Evolution (GCE) model. The aim of this work is to implement the study by Bisterzo et al. (2014), who investigated the effect of one of the major uncertainties o