Pignatari, M, Herwig, F, Hirschi, R, Bennett, M, Rockefeller, G, Fryer, C, Timmes, FX, Ritter, C, Heger, A, Jones, S, Battino, U, Dotter, A, Trappitsch, R, Diehl, S, Frischknecht, U, Hungerford, A, Magkotsios, G, Travaglio, C and Young, P (2016) Nugrid stellar data set. I. Stellar yields from H to BI for stars with metallicities z=0.02 and z=0.01. Astrophysical Journal Supplement Series, 225 (2). ISSN 0067-0049

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R Hirschi - Nugrid stellar data set 1.pdf - Published Version

We provide a set of stellar evolution and nucleosynthesis calculations that applies established physics assumptions simultaneously to low- and intermediate-mass and massive star models. Our goal is to provide an internally consistent and comprehensive nuclear production and yield database for applications in areas such as presolar grain studies. Our non-rotating models assume convective boundary mixing (CBM) where it has been adopted before. We include 8 (12) initial masses for Z = 0.01 (0.02). Models are followed either until the end of the asymptotic giant branch phase or the end of Si burning, complemented by simple analytic core-collapse supernova (SN) models with two options for fallback and shock velocities. The explosions show which pre-SN yields will most strongly be effected by the explosive nucleosynthesis. We discuss how these two explosion parameters impact the light elements and the s and p process. For low- and intermediate-mass models, our stellar yields from H to Bi include the effect of CBM at the He-intershell boundaries and the stellar evolution feedback of the mixing process that produces the ${}^{13}{\rm{C}}$ pocket. All post-processing nucleosynthesis calculations use the same nuclear reaction rate network and nuclear physics input. We provide a discussion of the nuclear production across the entire mass range organized by element group. The entirety of our stellar nucleosynthesis profile and time evolution output are available electronically, and tools to explore the data on the NuGrid VOspace hosted by the Canadian Astronomical Data Centre are introduced.