Porous media such as metal-organic frameworks (MOFs) are widely used as functional adsorbents to store, separate, or chemically transform molecules of interest. Extensive work has demonstrated MOFs exceptional ability to uptake substrates through chemi- and physisorption, as well as molecular sieving effects. To date, significant progress has been made to demonstrate molecular uptake and diffusion of gaseous substrates within MOF pores. However, understanding adsorption in the solution state remains limited, due to the complexity of multi-component interactions at the solid-liquid interface. An important next step in leveraging MOFs full potential as functional adsorbents is accurately modeling and predicting substrate uptake from solution.
This work presents an integrated computational and experimental methodology to investigate the adsorption of aromatic substrates into MOFs from solution. The Zirconia-based MOF-808 is leveraged for its large open pore network to determine the uptake of toluene from chloroform-d solutions, where computational predictions, based on robust equations of state and advanced Monte Carlo simulations, are in great agreement with experimental measurements. Spatial probability density analysis reveals the affinity of adsorption sites for both the solvent and substrate. It is observed that the heat of adsorption for toluene in MOF-808 is ca. 95 kJ/mol which matches well with the experimental isosteric heat of ca. 101 kJ/mol for this system. It is demonstrated that through this integrated methodology, the accurate prediction of molecular uptake from solution can be achieved and implemented for MOF systems.
