Controlling the structure of porous polymer monoliths through porogen solubility parameters and the effect on chromatographic performance — ASN Events

Controlling the structure of porous polymer monoliths through porogen solubility parameters and the effect on chromatographic performance (#68)

Kelly Flook 1 , Yury Agroskin 1 , Chris Pohl 1
  1. Thermo Fisher Scientific, Sunnyvale, CA, United States

Over the years as the use of polymer monolith technology in analytical chemistry has grown and groups have chosen their preferred system based on several factors including historical precedence. However, in many cases we find the chromatographic properties of these materials to be very similar. As the pore structure of porous polymer monoliths is governed by the composition of the monomer-solvent (porogen) mixture as well as the polymerization conditions the desired final structure and chemistry can be controlled and optimized by adjusting these parameters. As more analytical groups adopt this technology and develop their materials from an application perspective, the reason behind the choice of system used is often poorly understood.
Since the pore size and monolith structure is governed by phase separations mechanisms we investigated the relationship between different solubility components of the solvent system and the resulting monolith structure. By adjusting these parameters through choice of porogen one can attempt to predict the outcome and properties of the system. This is demonstrated by controlling the experimental parameters of a poly(styrene-co-divinyl benzene) system and observing the effect of porogen properties on the resulting monolith. Within a monomer system, relationships can be found between porogen solubility parameters the resulting pore structure. This also translates to equivalent column performance across different porogen systems with similar solubility parameters. This allows replacement of one porogen system for another as well as providing a less empirical approach towards structure and performance optimization.