Understanding the solubility of molecules in solvents is crucial to product development. The application of a diverse range of chemicals, from paints and inks to pesticides, relies on this knowledge.
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Since the late 1960s, Hansen Solubility Parameters (HSPs) have been the main tool for predicting if one material will dissolve in another and form a solution, especially when solvents for polymer solutions are needed.
The three parameters used are dispersion, polar interactions and hydrogen bonding. The coatings and polymers industry in particular has obtained excellent results when using these parameters to predict the solubility of polymers.
In principle, the same parameters can be used to find solvents for smaller molecules such as drugs and cosmetics. However, here HSP runs into twin prediction problems. First, drugs and cosmetics typically have more-varied functional groups than coatings and polymers. Second, the parameters exclude thermodynamic considerations regarding mixing, melting and dissolution — factors that can’t be ignored for small molecules.
To tackle these problems, scientists Manuel Louwerse and Gadi Rothenberg of the sustainable chemistry team — one of 20 research priority areas at the University of Amsterdam (UvA), the Netherlands — have teamed up with Bernard Roux and his team at Solvay’s Laboratory of the Future, Bordeaux, France. Since its foundation in 2004, the scientists in Bordeaux have had a particular focus on physical chemistry — with solubility and solvent behavior at the heart of their endeavors.
Together, the joint team has developed what it describes as a practical toolbox for predicting the solubility of small molecules in different solvents. These tools are available open access and free of charge, and can enhance solvent selection and formulations of many industrial products, they say.
The team says it has improved Hansen’s model, adapting it to handle small molecule solutes by including the thermodynamics of mixing, melting and dissolution.
They have done this by studying the details of entropy and enthalpy and making several corrections that make the Hansen methodology thermodynamically sound without losing its traditional ease of use.
When a compound dissolves, molecules leave the crystal and mix into the solvent. This increases the entropy but usually costs some enthalpy. The key issue here is that the amount of entropy gained by mixing determines how much enthalpy is lost while keeping a negative change in energy. Because the entropy effect depends on the concentration, the temperature, and the size of the molecules, these should all be included, notes the team.
Splitting the contributions of electron donors and acceptors among the solvent and solute is another improvement made to the Hansen parameters.
The team notes that this is especially important in hydrogen bonding, which is relevant to many solvents and solutes. The mantra “like dissolves like,” is too simplistic here. Hydrogen bonds form between donors and acceptors, so one needs donors to dissolve acceptors, and vice versa. By splitting the donor and acceptor contributions of each solvent and solute, the UvA team obtained more accurate models.
These new models are much better at predicting the solubility of small molecules in solvents and solvent blends. Tests on a large industrial dataset of 15 different solutes and 48 solvents and their blends showed that fit qualities improved from 0.89 to 0.97. The percentage of correct predictions rose from 54% to 78%. Another important advantage, notes the team, is that the new model enables predictions at extrapolated temperatures.
The results and the models are published as an open-access paper in the international journal ChemPhysChem. According to the authors, the paper has already raised many comments and the improvements suggested are currently being incorporated into a newer version of the widely used Hansen Solubility Parameters in Practice (HSPiP) software.
Most of the industrial formulation data are confidential. However, the team has published open access the full description of the theory and the models. Also included are the full and annotated Matlab routines in the supporting information, enabling everyone to use these new tools for designing new solvent mixtures and formulations.
“Industrial partners need to keep their data confidential, but most of them realize that open-access publishing of the methods and tools creates good will and enables further developments by both collaborators and competitors. By sharing methods and tools, companies can benefit from each other’s knowledge without sacrificing data,” notes Rothenberg.
