(610d) Accelerating Solvent Selection for Type II Porous Liquids

Type II porous liquids are comprised of intrinsically porous molecules, usually porous organic cages, dissolved in a liquid solvent, potentially combining the advantages of higher adsorbate loading and selectivity of solid porous adsorbents with the handling convenience of liquids. Despite growing interest in type II porous liquids, little is known about the solubility trends of porous organic cages or other similar host molecules. This situation means that despite the potential benefits of using type II porous liquids it is currently difficult to find solvent/cage pairs that lead to viable and safe porous liquids for practical use. We demonstrate an efficient screening approach that uses COSMO-RS, a thermodynamic modeling tool which treats solvent implicitly, for high-throughput solubility predictions. In addition, we make predictions of solvent pKa values from a machine-learning model as well as several other features and apply this approach to select solvents from a library of more than 11,000 compounds based on the constraints of forming type II porous liquid. This method is shown to give qualitative agreement with experimental observations for two [4+6] imine based porous organic cages, CC13 (non-polar) and TG-TFB-CHEDA (polar), identifying solvents with higher solubility for these molecules than had previously been known. Ultimately, the algorithm streamlines the down selection of suitable solvents for porous organic cages to enable more rapid discovery of Type II porous liquids.