SIMBAD references

Context. Open clusters serve as important tools for accurately studying the chemical evolution of the Milky Way. By combining precise chemical data from high-resolution spectra with information on their distances and ages, we can effectively uncover the processes that have shaped our Galaxy.
Aims. This study aims to derive non-local thermodynamic equilibrium (NLTE) atmospheric parameters and chemical abundances for approximately one hundred giant stars across 33 open clusters with near-solar metallicity. The clusters span a wide range of ages, enabling an assessment of the presence and extent of any age-related abundance gradients.
Methods. In the Stellar Population Astrophysics (SPA) project, we acquired new high-resolution spectra of giant stars in a sample of open clusters using the HARPS-N echelle spectrograph at the Telescopio Nazionale Galileo. We chemically characterized nine open clusters for the first time and reanalyzed previously studied SPA clusters, resulting in a consistent and homogeneous sample.
Results. We determined NLTE atmospheric parameters using the equivalent width method and derived NLTE chemical abundances through spectral synthesis for various elements, including α elements (Mg, Si, and Ti), light odd-Z elements (Na, Al), iron-peak elements (Mn, Co, and Ni), and neutron-capture elements (Sr, Y, and Eu). We compared our findings with the existing literature, which revealed a good agreement. We examined the trends of [X/Fe] versus age, confirming previous observations and the enrichment patterns predicted by nucleosynthesis processes. Positive correlations with age are present for a elements such as Mg, Si, Ti, and odd-Z Al, and iron-peak elements Mn, Co, Ni, and Sr, while Na and neutron-capture Y and Eu show a negative trend. This study emphasizes the significance of NLTE corrections and reinforces the utility of open clusters as tracers of Galactic chemical evolution. Furthermore, we provide a benchmark sample of NLTE abundances for upcoming open cluster surveys within large-scale projects, such as 4MOST and WEAVE.