Abstract
Abstract Nanomaterials have been put into practical use in many fields. Therefore, the ability to predict the properties of nanomaterials has gained utmost significance. In this study, we have presented a database of solubility of organically-modified and non-modified nanomaterials in organic solvents. Furthermore, we attempted to model the solubility of one collected nanoparticle using various data-driven statistical modeling techniques. The solubility prediction using data-driven models is more accurate than that of the conventional solute-solvent similarity method based on Hansen solubility parameters (HSPs). In addition, the modeling results exhibit that certain solvent features, such as dielectric constant and molar logP, also have a significant influence on the solubility of nanomaterials.
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