We have observed high-dispersion echelle spectra of red giant members in the five open clusters NGC 1342, NGC 1662, NGC 1912, NGC 2354 and NGC 2447 and determined their radial velocities and chemical compositions. These are the first chemical abundan
ce measurements for all but NGC 2447. We combined our clusters from this and previous papers with a sample drawn from the literature for which we remeasured the chemical abundances to establish a common abundance scale. With this homogeneous sample of open clusters, we study the relative elemental abundances of stars in open clusters in comparison with field stars as a function of age and metallicity. We find a range of mild enrichment of heavy (Ba-Eu) elements in young open cluster giants over field stars of the same metallicity. Our analysis succinct that the youngest stellar generations in cluster might be under-represented by the solar neighbourhood field stars.
Identification of metal-poor stars among field stars is extremely useful for studying the structure and evolution of the Galaxy and of external galaxies. We search for metal-poor stars using the artificial neural network (ANN) and extend its usage to
determine absolute magnitudes. We have constructed a library of 167 medium-resolution stellar spectra (R ~ 1200) covering the stellar temperature range of 4200 to 8000 K, log g range of 0.5 to 5.0, and [Fe/H] range of -3.0 to +0.3 dex. This empirical spectral library was used to train ANNs, yielding an accuracy of 0.3 dex in [Fe/H], 200 K in temperature, and 0.3 dex in log g. We found that the independent calibrations of near-solar metallicity stars and metal-poor stars decreases the errors in T_eff and log g by nearly a factor of two. We calculated T_eff, log g, and [Fe/H] on a consistent scale for a large number of field stars and candidate metal-poor stars. We extended the application of this method to the calibration of absolute magnitudes using nearby stars with well-estimated parallaxes. A better calibration accuracy for M_V could be obtained by training separate ANNs for cool, warm, and metal-poor stars. The current accuracy of M_V calibration is (+-)0.3 mag. A list of newly identified metal-poor stars is presented. The M_V calibration procedure developed here is reddening-independent and hence may serve as a powerful tool in studying galactic structure.
We have analyzed high-resolution echelle spectra of red giant members for seven open clusters in the Galactic anticentre direction to explore their chemical positions. Cluster membership has been confirmed by radial velocity. The spread in temperatur
es and gravities being very small among the red giants, nearly the same stellar lines were employed for all stars thereby reducing the abundance errors: the errors of the average abundance for a cluster were generally in the 0.02 to 0.05 dex range. Our present sample covers Galactocentric distances of 8.3 to 11.3 kpc and an age range of 0.2 to 4.3 Gyr. A careful comparison of our results for the cluster NGC 2682 (M 67) to other high-resolution abundance studies in the literature shows general good agreement for almost all elements in common.
An update on recent methods for automated stellar parametrization is given. We present preliminary results of the ongoing program for rapid parametrization of field stars using medium resolution spectra obtained using Vainu Bappu Telescope at VBO, Ka
valur, India. We have used Artificial Neural Network for estimating temperature, gravity, metallicity and absolute magnitude of the field stars. The network for each parameter is trained independently using a large number of calibrating stars. The trained network is used for estimating atmospheric parameters of unexplored field stars.
