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Title: Simulation and Experimental Studies of Flash NanoPrecipitation
Authors: Spaeth, Justin
Advisors: Panagiotopoulos, Athanassios Z
Kevrekidis, Yannis G
Contributors: Chemical and Biological Engineering Department
Keywords: Dissipative particle dynamics
Flash NanoPrecipitation
Subjects: Chemical engineering
Issue Date: 2011
Publisher: Princeton, NJ : Princeton University
Abstract: In recent years, nanoparticles have become a practical and powerful device for drug delivery and medical imaging. Flash NanoPrecipitation is a newly developed experimental technique for producing polymer-protected nanoparticles with narrow size distributions. Although experimentalists have successfully used this process to produce different types of nanoparticles in the laboratory, a microscopic understanding of the dynamics and how they are affected by different experimental parameters is unavailable. The nanoparticles that form are believed to be non-equilibrium structures, and thus, their final size and structure depend heavily on the system¡¦s dynamics. The length and time scales on which self-assembly takes place are too short to allow for direct observation of anything other than the final state of the system. However, computer simulations are a powerful alternative to lab experiments that can be used to understand the process at the molecular level. In this thesis, we develop molecular simulation methods and models as tools to gain a stronger understanding of the Flash NanoPrecipitation process. Additionally, we perform some simple Flash NanoPrecipitation experiments to check some of the predictions obtained from our molecular simulations A framework for coarse-graining particles within the dissipative particle dynamics method is extended to allow for the combining of an arbitrary number of particles into a single coarse-grained particle. Explicit-interface dissipative particle dynamics simulations are used to calculate phase diagrams for polymer-solvent systems with polymer lengths up to 40 beads. The coarse-graining procedure is applied to polymers, and the phase diagrams are shown to remain unchanged, with the exception of a trivial shifting with respect to the value of the polymer-solvent interaction strength. In addition, the coarse-graining scheme is applied separately to each block of an amphiphilic diblock copolymer, and the micellization dynamics are found to be well-preserved. An implicit-solvent model and explicit-solvent model are developed to study the Flash NanoPrecipitation process. The models parameters are chosen to match key experimental properties of the solvent, hydrophobic solute, and diblock copolymer used in a recent set of experiments from the literature. The implicit-solvent model is evolved using Brownian dynamics, and the explicit-solvent model is evolved using dissipative particle dynamics. The structural properties of the nanoparticles that form with each model are very similar, but the implicit-solvent model produces substantially slower aggregation dynamics than the explicit-solvent model. Nanoparticles diffusion coefficients are calculated and shown to exhibit unrealistic Rouse scaling (D,,fM-1) for the implicit-solvent model and realistic Stokes-Einstein scaling (D,,fR-1) for the explicit-solvent model. The surface area occupied per polymer for nanoparticles formed with the explicit-solvent model values show strong agreement with theory and experiment, but the implicit-solvent model nanoparticles are artificially stable, with surface area per polymer values roughly 3-4 times too large. The aforementioned explicit-solvent model is then used to study the effects of mixing time, solute solubility, relative and overall solute and polymer concentration, hydrophilic block length, and hydrophobic block length on aggregation dynamics and final nanoparticle size. Nanoparticle size increases with an increase in mixing time. When the solubility of the solute is lowered, the final nanoparticle size sharply increases if the polymer-solute interactions are unfavorable and remains unchanged when the interactions are favorable. An increase in the solute:polymer ratio leads to larger nanoparticles, and an increase in the overall concentration at a fixed solute:polymer ratio also leads to larger nanoparticles. Increasing the hydrophilic block length produces smaller nanoparticles when the number of polymer molecules is held constant. In general, increasing the hydrophobic block length produces larger nanoparticles; however, when the polymer-solute interactions are favorable and the mixing is not instantaneous, the nanoparticle size is a non-monotonic function of the hydrophobic block length and displays a minimum. A series of controlled Flash NanoPrecipitation experiments are conducted to check the conclusions drawn from the explicit-solvent simulations. In all instances, qualitative agreement is found between the simulations and experiments. Nanoparticle sizes in the experiments decrease with increasing Reynolds number in a multi-inlet vortex mixer. An increase in the solute concentration at a fixed diblock copolymer concentration leads to larger particles. Simultaneously and proportionally increasing the solute and diblock copolymer concentrations also leads to larger particles. Utilizing a diblock copolymer with a longer hydrophilic block, while holding the number of polymer molecules constant, reduces particle size. In summary, this thesis involves a combination of new molecular simulation methods and models and some simple lab experiments in an effort to gain a stronger grasp of the underlying physics of the Flash NanoPrecipitation process. The coarse-graining scheme could be used in the future to improve computational efficiency and develop simpler models. The comparison of an implicit-solvent model and explicit-solvent model can serve to point out the strengths and weaknesses of each approach to other researchers studying self-assembling systems. The simulation and experimental results may prove useful to experimentalists who use Flash NanoPrecipitation and seek to have more control over the outcome of their experiments. Ultimately, the models and methods in this thesis could be extended by others in an effort to develop a predictive framework.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Chemical and Biological Engineering

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