Abstract
Molecular simulations have been extensively utilized to understand and predict the polymer partitioning in size-exclusion chromatography (SEC). However, idealized pore models (e.g., cylindrical, spherical, and slit pores) were often used to represent the porous media in an SEC column, which leads to significant deviations in describing the geometry and the size of the pores. In this work, several complex pore models were derived from body-centered cubic, random, and gel packing of monodisperse spherical sol particles using simulation methodology. The mechanical stabilities of these structures were determined based on particle coordination numbers. Pore size distributions of these porous structures were compared to a commercially available, wide-pore superficially porous particle. Then, Gibbs ensemble Monte Carlo simulations were performed to compute the pore-to-bulk partitioning coefficient KSEC of a polymer chain with complex pore models. The effects of particle size, packing structure, and porosity on KSEC were explored. In addition, structural analysis provides insight into the conformation of polymers in the pores and its effect on the partitioning behavior. This study promotes the understanding of pore structures in SEC columns and enables more accurate predictions of KSEC with less ambiguity in pore geometry.
Original language | English (US) |
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Pages (from-to) | 78-86 |
Number of pages | 9 |
Journal | Journal of Chromatography A |
Volume | 1573 |
DOIs | |
State | Published - Oct 26 2018 |
Bibliographical note
Funding Information:Financial support from the National Science Foundation (CHE-1152998) and from the Industrial Partnership for Research in Interfacial and Materials Engineering at the University of Minnesota are gratefully acknowledged. QPC thanks Advanced Materials Technology for hosting an internship during the summer of 2017. MRS gratefully acknowledges the support of the National Institutes of Health under grant R44-GM108122-02. Part of the computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota.
Funding Information:
Financial support from the National Science Foundation (CHE-1152998) and from the Industrial Partnership for Research in Interfacial and Materials Engineering at the University of Minnesota are gratefully acknowledged. QPC thanks Advanced Materials Technology for hosting an internship during the summer of 2017. MRS gratefully acknowledges the support of the National Institutes of Health under grant R44-GM108122-02. Part of the computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota.
Publisher Copyright:
© 2018 Elsevier B.V.
Keywords
- Molecular simulation
- Monte Carlo
- Pore size distribution
- Pore structure
- Size-exclusion chromatography