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We introduce a new version of the database SC1MC (SC1MC-2022), obtained byextension of the recent SC1MC-2020, which includes artificial mono transitionmetal complexes. The database involves reference data used as inputs fortraining of machine learning models, one- and two-site entropies, and mutualinformation obtained at the DMRG level for canonical and split-localisedorbitals. The purpose of this database is to obtain as much as possibleinformation about the electronic correlation structure, which could beexploited by machine learning models to estimate these important informationwithout a significant computational cost for any similar type of systems withsome degree of transferability.

SC1MC-2022: A database of transition metal complexes for training ML models to predict one-site entropies and mutual information