Finally, the third database of structures originates from Knattrup et al., who compiled small (up to 4-molecule) clusters composed of various NPF precursors such as (SA, MSA = methanesulfonic, NTA = nitric, and FA = formic) acids and (AM, MA = methy-lamine, DMA = dimethylamine, TMA = triethylamine, and EDA = ethylenediamine) bases. Knattrup et al. combined the Clusteromics I-V databases consisting of equilibrium structures optimized at ωB97X-D/6-31++G(d,p). Furthermore, they employed MD simulations at GFN1-xTB to greatly expand the database to ∼221k structures, denoted Clusterome. Ultimately, the system properties (single-point energies) were evaluated for each geometry at r2SCAN-3c. The entire Clusterome database offers an opportunity to examine the capability of NN for learning on structurally complex (clusters composed of nine different molecules) and large databases or appropriately reduced databases. We emphasize the importance of consistency during data preparation. For instance, a mismatch of quantum chemistry (QC) program versions or methods could cause great errors in the modeling. Therefore, to deal with the database and the QC evaluations systematically, we have used the JK framework, a set of computational tools for handling molecular clusters. The following QC programs were used for QC calculations: xtb 6.4, 57 Gaussian 16 B.01, and ORCA 5.0.3. 59,60