272287 Modeling Solvent-Gradient Chromatography of Complex Polymers Using Statistical Theory of Interaction Polymer Chromatography

Thursday, November 1, 2012: 9:00 AM
Butler East (Westin )
Christopher J. Rasmussen1, Yefim Brun2, Brian McCauley2 and Alexander V. Neimark1, (1)Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, (2)Central Research and Development, DuPont, Wilmington, DE

Polymer chromatography is a standard analytical tool for the separation and characterization of polymeric materials. The majority of work is done using size-exclusion chromatography (SEC), where a polymer analyte is separated according to its hydrodynamic volume by exclusion interactions with the stationary phase. There are many types of complex polymers that differ by chemical or structural properties which cannot be separated by SEC. An alternative mode of chromatography, Interaction Polymer Chromatography (IPC), occurs when a polymer analyte interacts with the substrate, e.g. by adsorbing onto porous media. In IPC, retention is a function both the steric repulsion resulting from confining the polymer chain, and the attractive adsorption force exerted by the solid surfaces. A condition known as the Critical Point of Adsorption (CPA) occurs when these contributions are perfectly balanced, and isocratic elution of homopolymers from the chromatography column is found to be independent of molar mass (e.g. no dependence on the hydrodynamic volume). This permits separation by chemical composition, end-group, chain topology and microstructure of macromolecules, and other molecular properties. Maintaining experimental conditions at CPA is difficult as it is a complicated function of solute, solvent, substrate, and temperature. One practical alternative is solvent-gradient chromatography, where an elution starts with a poor solvent, so that the polymer remains adsorbed in the column, and is gradually changed to a good solvent. In doing so, the CPA is reached and then crossed; homopolymers of similar mass elute at this point. One factor hindering the use of gradient elution is the inability to interpret and design experiments due to the lack an appropriate physical model.

In this work, we utilize the molecular-statistical theory of polymer elution to model solvent-gradient chromatography. This approach assumes an ideal chain that interacts with specific boundary conditions to mimic interaction and confinement. The molecular-statistical theory of polymer elution allows one to relate retention time to molecular structure of the polymer chain and its segment interaction energy. The theory was developed originally for isocratic elution and predicted, among other things, the existence of the CPA. In previous works, we have generalized the theory to gradient elution, which led to a substantial extension of experimental gradient chromatography capabilities. For example, we described a separation of statistical copolymers by chemical composition and microstructure of polymer chains can be achieved. In the current work, we further extend the theory of gradient elution to include the separations of oligomers by type of end-groups, block-copolymers by the length of individual blocks and star-shaped macromolecules by the number and length of the individual arms. In all these cases we demonstrated that one can achieve the superior separations in the gradient mode compared to similar isocratic elution at CPA. The theoretical predictions are verified experimentally using liner and star-shaped polyethylene oxides with different end-groups, as well as ethylene oxide/propylene oxide block copolymers.

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See more of this Session: Modeling and Simulation of Polymers I
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