Anisotropic Wetting Property of Superhydrophobic Surfaces and Electrokinetic Flow on Liquid-Filled Surfaces

Understanding the wetting property of rough surface is critical in guiding droplets and novel superhydrophobic surface design. The Cassie-Baxter model and Wenzel model are always used to describe the totally non-wetting and completely wetting states, however, there were few discussions about the intermediate state. Through measuring the contact angles of groove patterned surfaces in different groove orientations, the anisotropic wetting properties of groove patterned superhydrophobic surface were investigated. The degree of water penetration into the grooves was experimentally observed and it was found that the degree of water penetration was different with groove orientations, which would affect the corresponding contact angle. Besides guiding droplets, superhydrophobic surfaces are also very important in microfluidic due to their ability to generate fluid slip and flow enhancement. After a deeper understanding of the wetting property of groove patterned superhydrophobic surface, I further investigated its important role in microfluidics. In this dissertation, I mainly focus on electrokinetics on groove patterned surface and liquid-filled slippery surfaces, a new kind of surface by filling low surface tension oil into the interstices of groove patterned surfaces. I experimentally measured the streaming potential on flat parylene surface, air-filled groove patterned surface and liquid-filled surfaces and compared their effects in streaming potential enhancement. The liquid-filled surfaces were shown to be able to enhance the generated streaming potential due to its slippery property and liquid-oil interface charges. As the electrokinetic on liquid-filled surfaces is a new phenomenon, the underlying physics is still not clear. I further investigated the influences of filled oil properties and groove orientation on streaming potentials and fluid slip. Oils with different densities, viscosities, dielectric constant, conductivities and surface tensions were filled into the interstices of groove patterned surfaces to make different types of liquid-filled surfaces. The streaming potentials on liquid-filled surfaces with different oils were experimentally measured. An empirical relationship between streaming potential and oil properties was found and the effects of electrical properties, such as interface charge density and dielectric constant of filled oil, on fluid slip were also studied. Finally, the groove orientation was varied to study the tensorial effects on streaming potential. Through both streaming potential measurement and theoretical analysis, it was found that the streaming potential at 45° was always smaller than the arithmetic mean of those at 0° and 90°, and the pressure gradient in the transvers direction generated by tensorial effects was important in the streaming potential modification. My work will be important in guiding droplets, flow patterning, lab-on-chip devices and the development of electrokientic based power sources

Laplacian Mixture Modeling for Network Analysis and Unsupervised Learning on Graphs

Laplacian mixture models identify overlapping regions of influence in unlabeled graph and network data in a scalable and computationally efficient way, yielding useful low-dimensional representations. By combining Laplacian eigenspace and finite mixture modeling methods, they provide probabilistic or fuzzy dimensionality reductions or domain decompositions for a variety of input data types, including mixture distributions, feature vectors, and graphs or networks. Provable optimal recovery using the algorithm is analytically shown for a nontrivial class of cluster graphs. Heuristic approximations for scalable high-performance implementations are described and empirically tested. Connections to PageRank and community detection in network analysis demonstrate the wide applicability of this approach. The origins of fuzzy spectral methods, beginning with generalized heat or diffusion equations in physics, are reviewed and summarized. Comparisons to other dimensionality reduction and clustering methods for challenging unsupervised machine learning problems are also discussed.Comment: 13 figures, 35 reference

Phase-field-crystal models for condensed matter dynamics on atomic length and diffusive time scales: an overview

Here, we review the basic concepts and applications of the phase-field-crystal (PFC) method, which is one of the latest simulation methodologies in materials science for problems, where atomic- and microscales are tightly coupled. The PFC method operates on atomic length and diffusive time scales, and thus constitutes a computationally efficient alternative to molecular simulation methods. Its intense development in materials science started fairly recently following the work by Elder et al. [Phys. Rev. Lett. 88 (2002), p. 245701]. Since these initial studies, dynamical density functional theory and thermodynamic concepts have been linked to the PFC approach to serve as further theoretical fundaments for the latter. In this review, we summarize these methodological development steps as well as the most important applications of the PFC method with a special focus on the interaction of development steps taken in hard and soft matter physics, respectively. Doing so, we hope to present today's state of the art in PFC modelling as well as the potential, which might still arise from this method in physics and materials science in the nearby future.Comment: 95 pages, 48 figure

Brownian motors: noisy transport far from equilibrium

Transport phenomena in spatially periodic systems far from thermal equilibrium are considered. The main emphasize is put on directed transport in so-called Brownian motors (ratchets), i.e. a dissipative dynamics in the presence of thermal noise and some prototypical perturbation that drives the system out of equilibrium without introducing a priori an obvious bias into one or the other direction of motion. Symmetry conditions for the appearance (or not) of directed current, its inversion upon variation of certain parameters, and quantitative theoretical predictions for specific models are reviewed as well as a wide variety of experimental realizations and biological applications, especially the modeling of molecular motors. Extensions include quantum mechanical and collective effects, Hamiltonian ratchets, the influence of spatial disorder, and diffusive transport.Comment: Revised version (Aug. 2001), accepted for publication in Physics Report

Microgravity coagulation and particle gel formation

VIII+192hlm.;24c

Numerical simulation of destabilizing heterogeneous suspensions at vanishing Reynolds numbers

This work deals with the numerical investigation of destabilizing suspensions, which are governed by two basic processes: Clustering and sedimentation. After laying the foundation to an efficient numerical simulation based on the Stokesian Dynamics method, hydrodynamic clustering and clustering due to non-hydrodynamic interactions are investigated. It is shown that multi-particle simulations need parallelization and an efficient post-processing to yield reliable results within a reasonable time

Utilizing Fluorescent Nanoscale Particles to Create a Map of the Electric Double Layer

The interactions between charged particles in solution and an applied electric field follow several models, most notably the Gouy-Chapman-Stern model, for the establishment of an electric double layer along the electrode, but these models make several assumptions of ionic concentrations and an infinite bulk solution. As more scientific progress is made for the finite and single molecule reactions inside microfluidic cells, the limitations of the models become more extreme. Thus, creating an accurate map of the precise response of charged nanoparticles in an electric field becomes increasingly vital. Another compounding factor is Brownian motion’s inverse relationship with size: large easily observable particles have relatively small Brownian movements, while nanoscale particles are simultaneously more difficult to be observed directly and have much larger magnitude Brownian movements. The research presented here tackles both cases simultaneously using fluorescently tagged, negatively charged, 20 nm diameter polystyrene nanoparticles. By utilizing parallel plate electrodes within a specially constructed microfluidic device that limits the z-direction, the nanoparticle movements become restricted to two dimensions. By using one axis to measure purely Brownian motion, while the other axis has both Brownian motion and ballistic movement from the applied electric field, the ballistic component can be disentangled and isolated. Using this terminal velocity to calculate the direct effect of the field on a single nanoparticle, as opposed to the reaction of the bulk solution, several curious phenomena were observed: the trajectory of the nanoparticle suggests that the charge time of the electrode is several magnitudes larger than the theoretical value, lasting for over a minute instead of tens of milliseconds. Additionally, the effective electric field does not reduce to below the Brownian limit, but instead has a continued influence for far longer than the model suggests. Finally, when the electrode was toggled off, a repeatable response was observed where the nanoparticle would immediately alter course in the opposite direction of the previously established field, rebounding with a high degree of force for several seconds after the potential had been cut before settling to a neutral and stochastic Brownian motion. While some initial hypotheses are presented in this dissertation as possible explanations, these findings indicate the need for additional experiments to find the root cause of these unexpected results and observations

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

The Effect of Biopolymer Properties on Bacterial Adhesion: an Atomic Force Microscopy (AFM) Study

The effect of bacterial surface biopolymers on bacterial adhesion to surfaces was studied through experiments and modeling. Atomic Force Microscopy (AFM) provided the tool to measure the interaction forces between different bacterial cells and silicon nitride tips under different chemical conditions at a nanoscopic level. Two bacterial strains were considered: Pseudomonas putida KT2442 and Escherichia coli K-12 JM109. This study addressed the following issues: 1) the effect of solution ionic strength and solvent polarity on adhesion between Pseudomonas putida KT2442 and the silicon nitride AFM tip, 2) role of heterogeneity of bacterial surface biopolymers on bacterial adhesion, 3) role of lipopolysaccharides (LPS) on adhesion at three different scales: continuous, batch, and nanoscale, and 4) nature of interactions between E. coli JM109 and a model surface (silicon nitride tip). To address the first issue, formamide, water, and methanol were used to investigate the effect of polarity on surface characteristics of biopolymers on the bacterial surface while a range of salt concentrations between that of water to 1 M KCl were used to study the effect of ionic strength. The adhesion increased with decreasing polarity of the solvent, indicating that the polymers on the bacterial surface are hydrophilic in nature. The adhesion was slightly affected by ionic strength variations up to a concentration of 0.1 M KCl; this may have been due to the fact that the ionic concentration in the solution did not counterbalance the ionic concentration in the biopolymer brush on the bacterial surface. However, a dramatic increase in the adhesion magnitude was observed when the salt concentration increased above 0.1 M KCl. This transition in adhesion with ionic strength from a low to high value induced a transition in the elasticity of the bacterial surface biopolymers. The biopolymer brush layer did change from rigid to soft with increasing the ionic strength. The elasticity was quantified mainly by the use of the freely jointed chain (FJC) model. Our interest in investigating the role of heterogeneity on adhesion developed from the results of the first study. The bacterial surface polymers were thought to be different in their chemical and physical nature since they were found to span a range of segment lengths. Analyzing the adhesion forces for P. putida KT2442 showed that the bacterial surface is heterogeneous. The heterogeneity was evident on the same cell surface and between different cells from the same population. To resolve the third issue, approximately, 80% of the surface LPS of E. coli K-12 JM109 were removed by treating the cells with 100 mM ethylenediaminetetraacetic acid (EDTA). The effect of LPS removal on the adhesion of the cells to the silicon nitride tip was studied in water and phosphate buffered silane (PBS). The adhesion results from the AFM experiments were compared to batch retention experiments with glass as the substratum and column attachment experiments with columns packed with quartz sand. LPS controlled bacterial adhesion to the different surfaces in the study at three scales: batch, continuous, and nano-scale. Finally, the nature of interactions between E. coli JM109 and a model surface (silicon nitride tip) were investigated in solvents of varying polarity (formamide, water, and methanol). The Young’s modulus of elasticity for the bacterial surface was estimated by fitting of the Hertzian model to the force-indentation curves. Young’s modulus values increased as the solvent polarity decreased, indicating a stiffer bacterial surface in lower polarity solvents. The average adhesion force in each solvent was negatively correlated with the dielectric constant of the solvent, suggesting hydrophilic biopolymers. Specific and non-specific interaction forces between the AFM tip and the biopolymers were further characterized by applying a Poisson statistical analysis to the discrete adhesion data. The specific and non-specific interaction forces were the highest in methanol (-4 and -1.48 nN respectively). These values are in accordance with the high adhesion magnitude values measured with AFM in methanol. The results of my different studies emphasized the important role of AFM in studying biological interactions to different surfaces and in characterizing bacterial surface biopolymers