Prediction of phase behavior and transport properties of simple fluids and polymers confined to nanoscale pores is important to a wide range of chemical and biochemical engineering processes. A practical approach to investigate nanoscale systems is molecular simulation, specifically Monte Carlo (MC) methods. One of the most challenging problems is the need to calculate chemical potentials in simulated phases. Through the seminal work of Widom, practitioners have a powerful method for calculating chemical potentials. Yet, this method fails for dense and inhomogeneous systems, as well as for complex molecules such as polymers. In this dissertation, the gauge cell MC method, which had previously been successfully applied to confined simple fluids, was employed and extended to investigate nanoscale fluids in several key areas. Firstly, the process of cavitation (the formation and growth of bubbles) during desorption of fluids from nanopores was investigated. The dependence of cavitation pressure on pore size was determined with gauge cell MC calculations of the nucleation barriers correlated with experimental data. Additional computational studies elucidated the role of surface defects and pore connectivity in the formation of cavitation bubbles. Secondly, the gauge cell method was extended to polymers. The method was verified against the literature results and found significantly more efficient. It was used to examine adsorption of polymers in nanopores. These results were applied to model the dynamics of translocation, the act of a polymer threading through a small opening, which is implicated in drug packaging and delivery, and DNA sequencing. Translocation dynamics was studied as diffusion along the free energy landscape. Thirdly, we show how computer simulation of polymer adsorption could shed light on the specifics of polymer chromatography, which is a key tool for the analysis and purification of polymers. The quality of separation depends on the physico-chemical mechanisms of polymer/pore interaction. We considered liquid chromatography at critical conditions, and calculated the dependence of the partition coefficient on chain length. Finally, solvent-gradient chromatography was modeled using a statistical model of polymer adsorption. A model for predicting separation of complex polymers (with functional groups or copolymers) was developed for practical use in chromatographic separations.
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Chemical and Biochemical Engineering
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Rutgers University Electronic Theses and Dissertations
Rutgers University. Graduate School - New Brunswick
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