A Python tool for predicting optimal solvent blends based on Hansen solubility parameters

Abstract The Hansen solubility parameters (HSPs) describe the solubility behavior of substances, allowing the prediction of a substance’s solubility in combination with solvents with known HSP values. This work introduces a “solvent finder,” a user-friendly Python program designed to calculate suitable solvents for substances based on their HSPs. The application facilitates and accelerates the solvent selection process for specific substances and is freely accessible. The program is based on HSPs, which indicate the compatibility of two compounds based on their solubility parameters. Its primary goal is to automate the selection process by systematically calculating all possible solvent combinations based on the given HSP values. Users can input and configure the HSP values for any number of solvents within the parameter setup. Additionally, the program provides the flexibility to consider up to five substances simultaneously when dealing with polymer mixtures or the general compatibility of mixtures. The applicability of the HSP is not restricted to specific substance classes, such as polymers or solvents, allowing the tool to be used for a wide range of formulations and coatings.