Due to rapid advancements in deep learning techniques, the demand for large-volume high-quality databases grows significantly in chemical researches. LanGroup has developed several quantum chemistry datasets to support machine learning studies in chemistry.
A comprehensive quantum-chemistry database that includes 443,106 small organic molecules with sizes up to 10 atoms, containing C, N, O and F heavy atoms. This database features both ground-state and excited-state properties, making it particularly valuable for machine learning applications in excited-state research.
This dataset includes 200 molecules (16-25 heavy atoms: C, N, O, F) from ChEMBL, with conformations generated by RDKit and StoL, then optimized at the B3LYP/6-31G/BJD3* level. It contains several optimized conformations for each molecule, providing a rich source of data for benchmarking conformation generation methods.
NAMD simulation results of keto isocytosine in Phys. Chem. Chem. Phys., 2022, 24, 24362-24382.
Each dataset page contains detailed information about accessing the data. Please visit the individual dataset pages for specific download links and access instructions.