| Abstract
| - Context. Thanks to the modern understanding of stellar evolution, we can accurately measure the ages of open clusters (OCs). Given their position, they are ideal tracers of the Galactic disc. Gaia data release 2, besides providing precise parallaxes, led to the detection of many new clusters, opening a new era for the study of the Galactic disc. However, detailed information on the chemical abundance for OCs is necessary to accurately date them and to efficiently use them to probe the evolution of the disc. Aims. Mapping and exploring the Milky Way structure is the main aim of the Stellar Population Astrophysics project. Part of this work involves the use of OCs and the derivation of their precise and accurate chemical composition. Here, we aim to analyse a sample of OCs located within about 2 kpc from the Sun, with ages from about 50 Myr to a few gigayears. Methods. We used HARPS-N at the Telescopio Nazionale Galileo and collected very high-resolution spectra ( R = 115 000) of 40 red giant/red clump stars in 18 OCs (16 never or scarcely studied plus two comparison clusters). We measured their radial velocities and derived the stellar parameters ( Teff, log g, vmicro, and [Fe/H]) based on equivalent width measurement combined with a 1D - LTE atmospherical model. Results. We discuss the relationship between metallicity and Galactocentric distance, adding literature data to our results to enlarge the sample and also taking age into account. We compared the result of observational data with the findings of chemo-dynamical models. These models generally reproduce the metallicity gradient well. However, at young ages we find a large dispersion in metallicity, that is not reproduced by models. Several possible explanations are explored, including uncertainties in the derived metallicity. We confirm the difficulties in determining parameters for young stars (age < 200 Myr), which is attributable to a combination of intrinsic factors (activity, fast rotation, magnetic fields, etc) which atmospheric models cannot easily reproduce and which affect the uncertainty on parameters.
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