Chemists Develop a Practical Toolbox for Predicting the Solubility of Small Molecules in Different Solvents

4 September 2017

Solvents are a vital part of the manufacturing and chemical industry, as they often make up the bulk of a chemical product, and dramatically affect how it works. For example, solvents influence how pesticides stay longer on leaves, how paints and inks dry faster, and how cosmetics are applied more easily.

One of the biggest challenges facing solvent manufacturers when developing new chemical products is predicting the solubility of small molecules in different solvents. But this task is about to become a lot easier as research chemists have created a ‘practical toolbox’ to aid solvent developers and chemical raw material suppliers in predicting how molecules will react in solvents.

Up until now, solubility has been predicted using the, so-called, Hansen Solubility Parameters: dispersion (D), polar interactions (P), and hydrogen bonding (H). Currently, this is used to great effect in the coatings and polymers industry for predicting the solubility of polymers.

However, the parameters have two major limitations that prevent them being used effectively in other industries, such as pharmaceuticals and cosmetics:

1. Drugs and cosmetics typically have more varied functional groups.
2. The original Hansen parameters exclude thermodynamic considerations regarding mixing, melting and dissolution. This is acceptable for polymers (where the thermodynamics cancel out) but not for small molecules.

Working with a team based at Solvay (headed by Dr Bernard Roux), Dr Manuel Louwerse and Prof. Gadi Rothenberg, have now improved Hansen’s model and adapted it to handle small-molecule solutes by including the thermodynamics of mixing, melting and dissolution.

As the online scientific journal explains, “The improvements are based on a better description of both the entropy and the enthalpy terms. 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 can be lost while keeping a negative ∆G (in other words, maintaining the driving force for the dissolution). Since the entropy effect depends on the concentration, the temperature, and the size of the molecules, these should all be included.”

The research team have now published their results in the journal ChemPhysChem, where they write, “The most important corrections include accounting for the solvent molecules’ size, the destruction of the solid’s crystal structure, and the specificity of hydrogen bonding interactions, as well as opportunities to predict the solubility at extrapolated temperatures.” Adding that, so far, “Testing the original and the improved methods on a large industrial dataset including solvent blends, fit qualities improved from 0.89 to 0.97 and the percentage of correct predictions rose from 54% to 78%.”

This is a significant improvement, as simply guessing the solubility of blends would give 50% correct predictions. The new model also enables predictions at extrapolated temperatures.

Furthermore, the research team has made access to the models and a full description of the theory publicly accessible, with the ‘full and annotated Matlab routines’ available. This has allowed other researchers to begin making adjustments to the HSPiP software.

The decision to share the ‘toolbox’ with everyone is based on a desire to bring academics and industry closer together. As Prof. Rothenberg notes, “Industrial partners need to keep their data confidential, but most of them realise that open-access publishing of the methods and tools creates goodwill 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.”

How far this ‘goodwill’ goes in the business world is uncertain, but what is clear is that the ‘toolbox’ for predicting small molecule solubility in solvents will shorten the time and lower the cost for developing improved chemical products. By sharing the information, the researchers are helping the entire chemical industry.