2016
DOI: 10.1093/mnras/stw1685
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Studying the evolution of AGB stars in theGaiaepoch

Abstract: We present asymptotic giant branch (AGB) models of solar metallicity, to allow the interpretation of observations of Galactic AGB stars, whose distances should be soon available after the first release of the Gaia catalogue. We find an abrupt change in the AGB physical and chemical properties, occurring at the threshold mass to ignite hot bottom burning,i.e. 3.5 M ⊙ . Stars with mass below 3.5 M ⊙ reach the C-star stage and eject into the interstellar medium gas enriched in carbon , nitrogen and 17 O. The high… Show more

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Cited by 36 publications
(30 citation statements)
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“…While this is a common property of all M ≥ 3.5 M⊙ models, the destruction of the surface oxygen, which requires higher HBB temperatures (∼ 80 MK), is sensitive to the metallicity, and is higher the lower is Z . The destruction of oxygen is extremely sensitive to the modelling of convection: in the present analysis, based on the FST description, we find significant depletion of oxygen in metal poor AGB stars; conversely, when a less efficient convective model is used, the HBB experienced is weaker, thus limiting the efficiency of oxygen burning (Ventura & D'Antona 2005;Di Criscienzo et al 2016). In this context, the detection of oxygen-poor PNe, enriched in nitrogen, would be an Table 1.…”
Section: Hot Bottom Burning and Helium Enrichment In Massive Agb Starsmentioning
confidence: 56%
“…While this is a common property of all M ≥ 3.5 M⊙ models, the destruction of the surface oxygen, which requires higher HBB temperatures (∼ 80 MK), is sensitive to the metallicity, and is higher the lower is Z . The destruction of oxygen is extremely sensitive to the modelling of convection: in the present analysis, based on the FST description, we find significant depletion of oxygen in metal poor AGB stars; conversely, when a less efficient convective model is used, the HBB experienced is weaker, thus limiting the efficiency of oxygen burning (Ventura & D'Antona 2005;Di Criscienzo et al 2016). In this context, the detection of oxygen-poor PNe, enriched in nitrogen, would be an Table 1.…”
Section: Hot Bottom Burning and Helium Enrichment In Massive Agb Starsmentioning
confidence: 56%
“…This feature is most likely due to the anticorrelation between C and N abundances (see, e.g., Smith et al 1996;Cohen et al 2005). In the multiple population paradigm, the mechanism responsible for the Na-O anticorrelation would also produce C-N anticorrelation (Ventura et al 2013;Di Criscienzo et al 2016). Our previous studies, however, found a significant CN-CH positive correlation, instead of an anticorrelation, among RGB stars in M22 and NGC 6273 Lim et al 2015).…”
Section: The Cn-ch Positive Correlation In Globular Clusters With Heamentioning
confidence: 71%
“…In this circumstance TDU leads to the mixing of M TDU ≃ 0.003M ⊙ from the H-free core into a H-rich envelope of M H env ≃ 0.027M ⊙ , significantly increasing the surface carbon abundance of the star. This example shows why it is necessary to keep in mind that final AGB thermal pulses coupled with low envelope masses can significantly change the surface abundances from those predicted by AGB stellar evolution models 8 We note that oxygen may not be a reliable metallicity indicator if significant amounts of O are dredged up to the surface or destroyed by hot bottom burning during the TP-AGB as predicted by some models -see section 3.1.1 in Di Criscienzo et al (2016) and Table 3 in Miller Bertolami (2016).…”
Section: Discussionmentioning
confidence: 90%
“…We now briefly review the treatment of these key ingredients in the four grids adopted here for the comparison: the MONASH grid (Karakas 2014;, the LPCODE grid (Miller Bertolami 2016), the ATON grid (Ventura et al 2015;Di Criscienzo et al 2016) and the FRUITY database (Cristallo et al 2011(Cristallo et al , 2015. While all the models discussed here include an upto-date treatment of the microphysics, and all of them neglect the impact of rotation, the theoretical models discussed in this section have some key differences in the modeling of winds and convective boundary mixing processes.…”
Section: Description Of the Model Codesmentioning
confidence: 99%
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