Predicting Solubility Limits of Organic Solutes for a Wide Range of Solvents and Temperatures

The
solubility of organic molecules is crucial in organic synthesis
and industrial chemistry; it is important in the design of many phase
separation and purification units, and it controls the migration of
many species into the environment. To decide which solvents and temperatures
can be used in the design of new processes, trial and error is often
used, as the choice is restricted by unknown solid solubility limits.
Here, we present a fast and convenient computational method for estimating
the solubility of solid neutral organic molecules in water and many
organic solvents for a broad range of temperatures. The model is developed
by combining fundamental thermodynamic equations with machine learning
models for solvation free energy, solvation enthalpy, Abraham solute
parameters, and aqueous solid solubility at 298 K. We provide free
open-source and online tools for the prediction of solid solubility
limits and a curated data collection (SolProp) that includes more
than 5000 experimental solid solubility values for validation of the
model. The model predictions are accurate for aqueous systems and
for a huge range of organic solvents up to 550 K or higher. Methods
to further improve solid solubility predictions by providing experimental
data on the solute of interest in another solvent, or on the solute’s
sublimation enthalpy, are also presented.