Pencil and Paper Estimation of Hansen Solubility Parameters

Abstract

Simple procedures to estimate Hansen solubility parameter (HSP) components from structural formulas are investigated. The best results are obtained using a simple relationship with molar volume and refractivity for the dispersion component, and using additivity models based on tailored fragments specifically designed for the polar and hydrogen bonding components. Despite large errors for some classes of chemicals, including small inorganic molecules, ionic liquids, and high halogen compounds, these models yield average absolute deviations from reference on par with state-of-the-art models and lower than reported using molecular dynamics simulations or nonlinear quantitative structure-property relationship models based on a limited set of quantum chemical descriptors. In contrast to group contribution methods that are either more restricted in scope or heavily parameterized, they are thoroughly validated and very easy to apply. Furthermore, the errors observed are easy to rationalize and may usually be anticipated. This work sheds light on some limitations inherent to pure additivity approaches for HSP prediction and provides a first step toward better models. A Python script implementing the procedure and the fully detailed results are provided as the Supporting Information.