This licentiate thesis reports analytical results for the electrostatic response to a test charge moving through dusty plasma. Two particular cases for a slowly moving test charge, namely, grain size distribution and grain charging dynamics are considered. Analytical results for the delayed shielding of a test charge due to dynamical grain charging in dusty plasma are also reported. In the first case, a dusty plasma in thermal equilibrium and with a distribution of grain sizes is considered. A size distribution is assumed which decreases exponentially with the grain mass for large sizes and gives a simple smooth reduction for small sizes. The electrostatic response to a slowly moving test charge, using a second order approximation is found and the effects of collisions are also investigated. It turns out that for this particular size distribution, there is a remarkably simple result that the resulting effective distribution for the electrostatic response is a kappa (generalized Lorentzian) distribution. In the second case, we present an analytical model for the shielding of a slowly moving test charge in a dusty plasma with dynamical grain charging for cases both with and without the collision effects. The response potential is treated as a power series in test charge velocity. Analytical expressions for the response potential are found up to second order in test charge velocity. The first-order dynamical charging term is shown to be the consequence of the delay in the shielding due to the dynamics of the charging process. It is concluded that the dynamical charging of the grains in a dusty plasma enhances the shielding of a test charge. To clarify the physics, a separate study is made where the charging is approximated by using a time delay. The resulting potential shows the delayed shielding effect explicitly. The terms in the potential that depend on the charging dynamics involve a spatial shift given by the test charge velocity and the charging time. This kind of work has relevance both in space and astrophysical plasmas. / QC 20101220

The Sultanate of Oman is a rapidly modernizing country with a significant length of its coastline slated for development. Much of the coastline is still in its natural state and basic studies describing the sedimentary systems need to be conducted in order to plan effectively for their sustainable development and to monitor changes in them with time. For such purposes, sediment samples (surface and sub-surface), elevation data, and serial sediment cores were collected at Sur Lagoon during three field seasons. The research objectives, procedures, results, and analyses for Sur lagoon are presented in three chapters. The first chapter compares textural facies, identified on the basis of particle-size distribution (PSD) of surface sediments from Sur Lagoon and evaluated using multi-variate cluster analysis, for their value in recognizing modem sedimentary environments. Clustering the full PSD size spectrum (0.0375- 1888 μm) shows that facies identification is possible is closely tied to surface elevation, particle-size decreasing with increasing elevation above mean sea level. This analytical technique should be tested under different conditions to assess further its utility. The second chapter discusses the taphonomically distinct and laterally extensive (> 1 km2) bivalve shell bed deposited by a tsunami on November 28th, 1945. Taphonomic characteristics of this unit are compared to those of the shell-rich tsunamite from Caesarea, Israel, and resulted in the identification of three generic, tsunamigenic-specific traits in shell beds: 1) thickly bedded and laterally extensive shell deposit, 2) presence of allochthonous articulated bivalves not in life position, and 3) extensive angular fragmentation. When these three traits are found together, a tsunamigenic origin should be considered for the shell bed. The third chapter analyzes the PSD of the tsunamite in eight sediment cores for digested and undigested samples. Cluster analysis of the PSD extended the upper or lower tsunamite contacts in four cores, but in general, the tsunamite thickness is consistent with the previously identified shell beds (Chapter 3). The tsunamigenic processes that resulted in the deposition of the shell bed were complex, and deposition occurred during run-up, flooding, and backwash stages of the tsunami, incorporating marine, lagoonal, and terrestrial (wadi) sediment into the tsunamite. The results of this study provide baseline sedimentological data for an understudied region of the world. New applications of cluster analysis of PSD and taphonomic analysis have the potential to identify previously unknown tsunamites in the geological record, and lithological facies using textural analysis. / Thesis / Doctor of Philosophy (PhD)

<p> The separation of a mixture of carbon tetrachloride in water was studied in a 2 inch diameter glass hydrocyclone. First, the effect of a mixing valve and of oil/water ratio on the volume/surface diameter of the dispersion in the feed to the hydrocyclone was studied using a statistical experiment design. Secondly, the effect of feed drop size distribution, oil/water ratio, and overflow/underflow split on the separation in the hydrocyclone was determined, again using a statistical experiment design. In both designs, five levels of each variable were studied. Flow rate, design shape, and temperature were kept constant. The range of variables was: </p> <p> 1. Mixing Value Pressure Drop 17.95 to 88.25 mm. Hg </p> <p> 2. Oil/Water Ratio 0.132 to 0.211 </p> <p> 3. Overflow/Underflow Split 4/1 to 8/1 </p> <p> From the first part of the work it was found that oil/water ratio had no significant effect on the volume/surface diameter, and that there was a linear relationship between the volume/surface diameter and mixing valve pressure drop. </p> <p> From the second part of the work it was found that volume split had most significant effect on hydrocyclone separation for the range of variables studied. The oil/water ratio had the next most significant effect on separation, and finally, drop size distribution was also found to be significant, but was the least important of the three variables. The interactions of the variables were no significant. The hydrocyclone separation could be predicted. The prediction of the overflow drop-size distribution agreed very well with the distribution observed photographically. Both predictions required assumptions that short-circuit flow and drop-drop coalescence was negligible. </p> / Thesis / Master of Engineering (ME)

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Inkjet printing has generated considerable interest as a technique for the patterning of functional materials in the liquid phase onto a substrate. Despite its high promise, the phenomena associated with inkjet printing remain incompletely understood. This research project investigates inkjet printing of cellulose nanocrystals (CNCs) as a possible method for the fabrication of cellulose micropatterns. CNCs were prepared from wood pulp by H₂SO₄ hydrolysis and characterized in terms of length, width, and thickness distributions by atomic force microscopy (AFM) and dynamic light scattering. Aqueous CNC suspensions were characterized in terms of shear viscosity with a rheometer. Glass substrates were cleaned with a detergent solution, aqua regia, or a solvent mixture, and characterized in terms of surface chemical composition, surface free energy, polarity, roughness, ζ-potential, and surface charge distribution in air by X-ray photoelectron spectroscopy, contact angle measurements, AFM, streaming potential, and scanning Kelvin probe microscopy (SKPM). Additionally, poly(ethylene glycol)-grafted glass substrates were prepared and characterized in terms of surface free energy, polarity, and roughness. Aqueous CNC suspensions were printed in different patterns onto the different glass substrates with a commercial, piezoelectric drop-on-demand inkjet printer. Inkjet deposited droplet residues and micropatterns were analyzed by AFM, scanning electron microscopy, and polarized-light microscopy. At low CNC concentrations (0.05 wt %), inkjet-deposited droplets formed ring-like residues due to the "coffee drop effect". The "coffee drop effect" could be suppressed by the use of higher CNC concentrations. The resulting dot-like droplet residues exhibited Maltese cross interference patterns between crossed polarizers, indicating a radial orientation of the birefringent, elongated CNCs in these residues. The observed Maltese cross interference patterns represent unprecedented indirect evidence for a center-to-edge radial flow in drying droplets. The degree of definition of the micropatterns depended strongly on the surface properties of the glass substrates. Well-defined micropatterns were obtained on aqua regia-cleaned substrates. In addition to the surface free energy and polarity, other factors seemed to play a role in the formation of the inkjet-printed micropatterns. If these factors can be identified and controlled, inkjet deposition of CNCs could become an attractive method for the fabrication of cellulose micropatterns. / Ph. D.

Controlling the size and size distribution of colloidal nanoparticles have gained extraordinary attention as their physical and chemical properties are strongly affected by size. Ligands are widely used to control the size and size distribution of nanoparticles; however, their exact roles in controlling the nanoparticle size distribution and the way they affect the nucleation and growth kinetics are poorly understood. Therefore, understanding the nucleation and growth mechanisms and developing theoretical/modeling framework will pave the way towards controlled synthesis of colloidal nanoparticles with desired sizes and polydispersity. This dissertation focuses on identifying the possible roles of ligands and size on the kinetics of nanoparticle formation and growth using in-situ characterization tools such as small-angle X-ray scattering (SAXS) and kinetic modeling. The presented work further focuses on developing kinetic models to capture the main nucleation and growth reactions and examines how ligand-metal interactions could potentially alter the rate of nucleation and growth rates, and consequently the nanoparticle size distribution. Additionally, this work highlights the importance of using multi-observables including the concentration of nanoparticles, size and/or precursor consumption, and polydispersity to differentiate between different nucleation and growth models and extract accurate information on the rates of nanoparticle nucleation and growth. Specifically, during the formation and growth of colloidal nanoparticles, complex reactions are occurring and as such nucleation and growth can take place through various reaction pathways. Therefore, sensitivity analysis was applied to effectively compare different nucleation and growth models and identify the most important reactions and obtain a reduced model (e.g. a minimalistic model) required for efficient data analysis. In the following chapters, a more sophisticated modeling approach is presented (population balance model) capable of capturing the average-properties of nanoparticle size distribution. PBM allows us to predict the growth rate of nanoparticles of different sizes, the ligand surface coverage for each individual size, and the parameters involved in altering the size distribution. Additionally, thermodynamic calculations of nanoparticle growth and ligand-metal binding as a function of size and ligand surface coverage were conducted to further shed light on the kinetics of nanoparticle formation and growth. The combination of kinetic modeling, in-situ SAXS and thermodynamic calculations can significantly advance the understanding of nucleation and growth mechanisms and guide toward controlling size and polydispersity. / Doctor of Philosophy / The synthesis of colloidal metal nanoparticles with superior control over size and size distribution, and has attracted much attention given the wide applications of these nanomaterials in the fields of catalysis, photonics, and electronics. Obtaining nanoparticles with desired sizes and polydispersity is vital for enhancing the consistency and performance for specific applications (e.g., catalytic converters for automotive emission). Ligands are often employed to prevent agglomeration and also control the nanoparticle size and size distribution. Ligands can affect the precursor reactivity and therefore the reduction/nucleation by binding with the metal precursor. Nucleation refers to the assimilation of few atoms to form initial nuclei acting as templates for nanoparticle growth. Additionally, ligands can bind with the nanoparticle surface sites and change the rate of surface growth and therefore the final nanoparticle size. Despite strong effects of ligands in the colloidal nanoparticle synthesis, their exact role in the nucleation and growth kinetics is yet to be identified. Additionally, nucleation and growth models capable of unraveling the underlying mechanisms of nucleation and growth in the presence of ligands are still lacking in the literature. Therefore, obtaining nanoparticles with desired sizes and polydispersity mostly relies on trial-and-error approach making the synthesis costly and inefficient. As such, developing models capable of predicting suitable synthesis conditions is contingent upon understanding the chemistry and mechanism involved during nanoparticles formation. Therefore, in this study, novel kinetic models were developed to capture the nucleation and growth kinetics of colloidal metal nanoparticles under different synthetic conditions (different types of solvents, different concentrations of ligand and metal). In-situ SAXS was further employed to measure the average diameter, concentration of nanoparticles, and polydispersity during the synthesis and extract the nucleation and growth rates (evolution of concentration of nanoparticles and size). First, an average-property model was developed to account for ligand-metal bindings and capture the size and concentration of nanoparticles during the synthesis. Then, a more complex modeling approach; PBM, accompanied by the thermodynamic calculations of surface growth and ligand-nanoparticle binding enthalpies was implemented to capture the size distribution. As it will be shown later, the determination of the underlying mechanisms resulted in a highly predictive kinetic model capable of predicting the synthetic conditions to obtain nanoparticles with desired sizes. The proposed methodology can serve as a powerful tool to synthesize nanoparticles with specific sizes and polydispersity.