QM9 is a comprehensive dataset that provides geometric, energetic, electronic and thermodynamic properties for a subset of GDB-17
database, comprising 134 thousand stable organic molecules with up to 9 heavy atoms. All molecules are modeled using density functional theory (B3LYP/6-31G(2df,p) based DFT). This database may serve the benchmarking of existing methods, development of new methods, such as hybrid quantum mechanics/machine learning, and systematic identification of structure-property relationships.
The original dataset can be found at (https://figshare.com/collections/Quantum_chemistry_structures_and_properties_of_134_kilo_molecules/978904)
Paper : R. Ramakrishnan, P. O. Dral, M. Rupp, O. A. von Lilienfeld https://www.nature.com/articles/sdata201422
code for parsing the dataset to csv can be found at:
https://github.com/n0w0f/qm9_dataprep
