Lithium-ion Battery Electrolyte (LIBE) is a dataset composed of a diverse set of lithium-ion battery solid electrolyte interface (SEI) species. These structures were generated via fragmentation and combination operations on the principal molecules known to be present in the Li-ion battery SEIs. The dataset contains 17,000 structures of varying spin and charge states "labeled" with both raw and corrected enthalpies, entropies, and free energies . We used the rigid-rotor harmonic oscillator (RRHO) approximated free energies as a training target, units are reported in eV as in the original publication(Figure ). To approximate molecular formation energies, we performed an energy correction calculation via linear regression to approximate individual atomic energies at infinite separation (Figure , Table ). We constructed a random train-test split of 90/10 and the validation set was constructed from the training set with a random split of 80/20 for model selection and hyperparameter tuning. The inclusion of the LIBE dataset was also of note as there is currently no benchmark predicting molecular properties on this dataset and it would allow us to test the ability of QTAIM descriptors to generalize across different charge and spin states. LIBE also contains metals with nonstandard bonding interactions -an instance where QTAIM's rigorous bonding definitions should fare well. TPSS 33 /def2-SVP with D3BJ 35 dispersion.