Another facet of the diversity in the dataset that is not captured by the pairwise interaction matrix is the presence of different hydrogen bond motifs. As noted in , it is the description of these hydrogen bonding structures which tends to pose the biggest challenge to the force-field parameterization. During the database construction, we identified potential intermolecular hydrogen bonds solely from the presence of H *,*,O or H *,*,N atoms in the molecule, however this approach is inadequate for the intended analysis here. In some structures, there are multiple valid donor/acceptor pairings and the actual hydrogen bonding motifs cannot be inferred from the molecular description alone. Also, several molecules have conformations that could favour intramolecular hydrogen bonds over intermolecular hydrogen bonds. In reality, even amongst polymorphs of the same molecule, hydrogen bonding motifs can differ , further emphasizing the need for a more robust approach to elucidate the presence of intermolecular hydrogen bonds within the crystals. To that end, we employ the CCDC's Python API to identify hydrogen bonds through geometric criteria (details in the Supporting Information). The effect of applying these criteria is immediately apparent. Analysis of the primary datasets based solely on the presence of H *,*,O and/or H *,*,N suggests that they contain 132 hydrogen bonding structures. Conversely, the geometric approach identifies only 126 structures containing intermolecular hydrogen bonds. In the full dataset, using the geometric criteria, 314 hydrogen bonding structures are found, approximately 41.6% of the entire dataset.