  Past studies have already shown that stars in open clusters are chemically
homogeneous (e.g. De Silva et al. 2006, 2007 and 2009). These results support
the idea that stars born from the same giant molecular cloud should have the
same chemical composition. In this context, the chemical tagging technique was
proposed by Freeman & Bland-Hawthorn 2002. The principle is to recover
disrupted stellar clusters by looking only to the stellar chemical composition.
In order to evaluate the feasibility of this approach, it is necessary to test
if we can distinguish between stars born from different molecular clouds. For
this purpose, we studied the chemical composition of stars in 32 old and
intermediate-age open clusters, and we applied machine learning algorithms to
recover the original cluster by only considering the chemical signatures.
