Stellar Population Astrophysics (SPA) with the TNG

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.