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Context. Open clusters (OCs) are valuable probes of stellar population characteristics. Their age and metallicity provide insights into the chemical enrichment history of the Milky Way. By studying the metallicity of OCs, we can explore the spatial distribution of composition across the Galaxy and understand stellar birth radii through chemical tagging. However, inferring the original positions of OCs remains a challenge. Aims. This study investigates the distribution of metallicity in the solar neighborhood using data from Gaia DR3 and LAMOST spectra. By measuring accurate ages and metallicities, we aim to derive birth radii and understand stellar migration patterns. Methods. We selected 1131 OCs within 3 kpc of the Sun from Gaia DR3 and LAMOST DR8 low-resolution spectra (R=1800). To correct the LAMOST data, we incorporated high-resolution spectra from GALAH DR3 (R=28000) using an artificial neural network. The average metallicity of the OCs was derived from reliable [Fe/H] values of their members. We examined the metallicity distribution across the Galaxy and calculated birth radii based on age and metallicity. Results. The correction method reduces the systematic offset in LAMOST data. We found a metallicity gradient as a function of Galactocentric distance and guiding radii. Comparisons with chemo-dynamic simulations show that observed metallicity values are slightly lower than predicted when uncertainties are ignored, but the metallicity gradients align with previous studies. We also inferred that many OCs near the Sun likely originated from the outer Galactic disk.

Context. Globular clusters are considered key objects for understanding the formation and evolution of the Milky Way. In this sense, their characterisation in terms of their chemical and orbital parameters can provide constraints to the chemical evolution models of the Galaxy. Aims. We use the heavy element abundances of globular clusters to trace their overall behaviour in the Galaxy, aiming to analyse potential relations between the hot H-burning and s-process elements. Methods. We measured the content of Cu I and s- and r-process elements (Y II, Ba II, La II, and Eu II) in a sample of 210 giant stars in 18 Galactic Globular Clusters from high-quality UVES spectra. The clusters span a large metallicity range, and the sample is the largest uniformly analysed for what concerns heavy elements in Globular Clusters. Results. Cu abundances did not show considerable spread in the sample nor correlation with Na, meaning that the Na nucleosynthesis process does not affect the Cu abundance. Most GCs closely follow the Cu, Y, Ba, La, and Eu field stars' distribution, revealing a similar chemical evolution. The Y abundances in mid-metallicity regime GCs (-1.10 dex <[Fe/H]<-1.80 dex) display a mildly significant correlation with the Na abundance, which should be further investigated. Finally, we did not find any significant difference between the n-capture abundances among GCs with Galactic and extragalactic origin., Comment: 23pages and 20 figures

With the unprecedented increase of known star clusters, quick and modern tools are needed for their analysis. In this work, we develop an artificial neural network trained on synthetic clusters to estimate the age, metallicity, extinction, and distance of $Gaia$ open clusters. We implement a novel technique to extract features from the colour-magnitude diagram of clusters by means of the QuadTree tool and we adopt a multi-band approach. We obtain reliable parameters for $\sim 5400$ clusters. We demonstrate the effectiveness of our methodology in accurately determining crucial parameters of $Gaia$ open clusters by performing a comprehensive scientific validation. In particular, with our analysis we have been able to reproduce the Galactic metallicity gradient as it is observed by high-resolution spectroscopic surveys. This demonstrates that our method reliably extracts information on metallicity from colour-magnitude diagrams (CMDs) of stellar clusters. For the sample of clusters studied, we find an intriguing systematic older age compared to previous analyses present in the literature. This work introduces a novel approach to feature extraction using a QuadTree algorithm, effectively tracing sequences in CMDs despite photometric errors and outliers. The adoption of ANNs, rather than Convolutional Neural Networks, maintains the full positional information and improves performance, while also demonstrating the potential for deriving clusters' parameters from simultaneous analysis of multiple photometric bands, beneficial for upcoming telescopes like the Vera Rubin Observatory. The implementation of ANN tools with robust isochrone fit techniques could provide further improvements in the quest for open clusters' parameters., Comment: 24 pages, 15 figures, Accepted in The Astronomical Journal. Temporally, data produced in this work are available at https://phisicslollo0.github.io/cavallo23.html

Globular clusters have been widely studied in terms of light element variations present in their different stellar populations. However, the nature of the polluter(s) responsible for this phenomenon is still debated. The study of heavy elements and their relation to light ones can provide further constraints. In particular, we aim to explore the possible contribution of asymptotic giant branch stars of different stellar masses to the internal pollution in the cluster. We derive abundances of elements from different nucleosynthetic chains, such as Na, Mg, Ca, Sc, Cu, Y, and Ba. We did not find clear relations between the light s-process elements (represented by Y II) or heavy ones (represented by Ba II) with light elements (Li, Na or Al). This indicates that the polluter(s) responsible for the Na (Al) or Li production does not produce large amounts of Y II and Ba II. Furthermore, the comparison with models discards a possible significant contribution to the cluster pollution from AGB stars with masses lower than 5M$_{\odot}$. In addition, we found a potential CH-star in our sample., Comment: 12 pages, 17 figures

This paper presents the chemical abundance analysis of 217 stars in the metal-poor globular cluster NGC 6752, distributed from the turn-off to the lower red giant branch. Aluminium and Lithium abundances were derived through spectral synthesis applied to spectra collected with FLAMES, both in GIRAFFE and UVES modes. The work aims to gain insight into the nature of the polluter(s) responsible for the abundance variations and C-N, Na-O, Al-Mg anti-correlations associated with the multiple population phenomenon. We found a plateau at A(Li)=2.33$\pm$0.06 dex in unevolved stars, with the average Li content decreasing continuously down to $\sim$1.25 dex at the bottom of the red giant branch. As expected in the classic anti-correlation scenario, we found stars low in Al and high Li abundance and stars high in Al and low in Li. However, in addition, we also found evidence of Al-rich, second-generation stars with high Li content. This finding suggests the need for Li production, known to happen in intermediate-mass ($\sim$4-8M$_{sun}$) AGB stars through the Cameron-Fowler mechanism. It is worth noticing that the Li abundance observed in Al-rich stars never exceeds that in Al-poor stars., Comment: Accepted by MNRAS. 11 pages, 12 figures, and 3 tables