Surface Modification and Transport Modeling of Micron- and Nano-Sized Materials
Guardado, Erick Salvador Vasquez
AdvisorWalters, Keisha B.
Myers, Oliver J.
Walters, D. Keith
French, W. Todd
Elmore, Billy B.
Nanoparticle-based technologies are an emerging field with the promise to impact a wide range of application areas. However, that potential is somewhat married to a host of research questions that remain to be answered. This work explores the surface modification of magnetic nanoparticles in a controlled fashion to produce hybrid nanoparticle (metal/polymer) systems with different morphologies, understand in-situ behavior of stimuli-responsive polymers grafted to a substrate, and obtain better computational methods for particle-tracking and -deposition. Nanoparticle surface modification was performed using ATRP, obtaining homo-, block-co-, and ‘two-faced/biphasic’ polymer structures on the nanoparticle surfaces. Biphasic Janus nanoparticles (JPs) were formed using a magnetic nanoparticle core and an innovative technique combining non-covalent solid protection with sequential controlled radical polymerization to form the two surface-grafted polymer phases. Surface-confined polymerizations were conducted using pH- and thermo-responsive materials. Poly(methacrylic acid) (PMAA) and a series of (aminoalkyl) methacrylate polymers were used as pH responsive polymers. Additionally, poly(N-isopropylacrylamide) (PNIPAM) was selected as the thermo-responsive material for this study. In-situ characterization techniques, including atomic force microscopy (AFM), dynamic light scattering (DLS), and ellipsometry, were used to evaluate the thermo- and pH-responsiveness of these stimuli responsive materials. A new general-oscillator (GENOSC) model was used to determine swelling ratio, thickness, and optical constant changes in the polymer brush as pH was changed in-situ. AFM was used to study morphological changes due to changes in pH and temperature. Nanoparticle temperature responsiveness was investigated using DLS. A related effort involved the use of computational fluid dynamic (CFD) methods to track (micron-sized) particles in certain geometries, including a human lung morphology. Predicted particle transport and deposition was compared to Lagrangian computational approaches and available experimental data. The Eulerian particle phase modeling method developed resulted in the accurate prediction of both near-wall particle tracking and wall deposition. This Eulerian-Eulerian model is a new tool that has potential for particle tracking in physiological morphologies. This combination of experimental and computational research has led to new nano- and micro-particle surface modification methods and particle transport modeling.