Experimental investigation and mass transfer modelling of 3D printed monolithic cation exchangers

Abstract 3D printing has recently found application in chromatography as a means to create ordered stationary phases with improved separation efficiency. Currently, 3D printed stationary phases are limited by the lack of 3D printing materials suitable for chromatographic applications, and require a strict compromise in terms of desired resolution, model size and the associated model time. Modelling of mass transfer in 3D printed monoliths is also fundamental to understand and further optimise separation performance of 3D printed stationary phases. In this work, a novel 3D printing material was formulated and employed to fabricate monolithic cation exchangers (CEXs) with carboxyl functionalities. CEXs were printed with ligand densities of 0.7, 1.4, 2.1 and 2.8 mmol/g and used in batch adsorption experiments with lysozyme as model protein. All CEXs demonstrated high binding strength towards lysozyme, with maximum binding capacities of up to 108 mg/mL. The experimental results were described using mass transfer models based on lumped pore diffusion and lumped solid diffusion mechanisms adapted to reflect the complex geometry of the 3D printed monoliths. An exact 3D model as well as less computationally demanding 1D and 2D approximations were evaluated in terms of their quality to capture the experimental trend of batch adsorption kinetic data. Overall, the model results indicate that mass transfer in the fabricated CEXs is mostly controlled by pore diffusion at high protein concentrations, with solid diffusion becoming important at low protein concentrations in the mobile phase. Also, the kinetic data were approximated equally well by both the full 3D model as well as the 2D approximation, indicating leaner mathematical models of lower dimensionality can be employed to describe mass transfer in complex three dimensional geometries. We believe this work will help spur the development of 3D printable materials for separations and aid in the development of quantitative platforms to evaluate and optimise the performance of 3D printed monoliths.