Electrostatic Repulsion of Positively Charged Vesicles and Negatively Charged Objects

A positively charged, mixed bilayer vesicle in the presence of negatively charged surfaces (for example, colloidal particles) can spontaneously partition into an adhesion zone of definite area, and another zone that repels additional negative objects. Although the membrane itself has nonnegative charge in the repulsive zone, negative counterions on the interior of the vesicle spontaneously aggregate there, and present a net negative charge to the exterior. Beyond the fundamental result that oppositely charged objects can repel, our mechanism helps explain recent experiments on surfactant vesicles.Comment: Latex using epsfig and afterpage; pdf available at http://www.physics.upenn.edu/~nelson/Mss/repel.pd

Visualizing Set Relations and Cardinalities Using Venn and Euler Diagrams

In medicine, genetics, criminology and various other areas, Venn and Euler diagrams are used to visualize data set relations and their cardinalities. The data sets are represented by closed curves and the data set relationships are depicted by the overlaps between these curves. Both the sets and their intersections are easily visible as the closed curves are preattentively processed and form common regions that have a strong perceptual grouping effect. Besides set relations such as intersection, containment and disjointness, the cardinality of the sets and their intersections can also be depicted in the same diagram (referred to as area-proportional) through the size of the curves and their overlaps. Size is a preattentive feature and so similarities, differences and trends are easily identified. Thus, such diagrams facilitate data analysis and reasoning about the sets. However, drawing these diagrams manually is difficult, often impossible, and current automatic drawing methods do not always produce appropriate diagrams. This dissertation presents novel automatic drawing methods for different types of Euler diagrams and a user study of how such diagrams can help probabilistic judgement. The main drawing algorithms are: eulerForce, which uses a force-directed approach to lay out Euler diagrams; eulerAPE, which draws area-proportional Venn diagrams with ellipses. The user study evaluated the effectiveness of area- proportional Euler diagrams, glyph representations, Euler diagrams with glyphs and text+visualization formats for Bayesian reasoning, and a method eulerGlyphs was devised to automatically and accurately draw the assessed visualizations for any Bayesian problem. Additionally, analytic algorithms that instantaneously compute the overlapping areas of three general intersecting ellipses are provided, together with an evaluation of the effectiveness of ellipses in drawing accurate area-proportional Venn diagrams for 3-set data and the characteristics of the data that can be depicted accurately with ellipses

Charge-Reversal Instability in Mixed Bilayer Vesicles

Bilayer vesicles form readily from mixtures of charged and neutral surfactants. When such a mixed vesicle binds an oppositely-charged object, its membrane partially demixes: the adhesion zone recruits more charged surfactants from the rest of the membrane. Given an unlimited supply of adhering objects one might expect the vesicle to remain attractive until it was completely covered. Contrary to this expectation, we show that a vesicle can instead exhibit {\it adhesion saturation,} partitioning spontaneously into an attractive zone with definite area fraction, and a repulsive zone. The latter zone rejects additional incoming objects because counterions on the interior of the vesicle migrate there, effectively reversing the membrane's charge. The effect is strongest at high surface charge densities, low ionic strength, and with thin, impermeable membranes. Adhesion saturation in such a situation has recently been observed experimentally [H. Aranda-Espinoza {\it et al.}, {\sl Science} {\bf285} 394--397 (1999)]

Decoding odor quality and intensity in the Drosophila brain

To internally reflect the sensory environment, animals create neural maps encoding the external stimulus space. From that primary neural code relevant information has to be extracted for accurate navigation. We analyzed how different odor features such as hedonic valence and intensity are functionally integrated in the lateral horn (LH) of the vinegar fly, Drosophila melanogaster. We characterized an olfactory-processing pathway, comprised of inhibitory projection neurons (iPNs) that target the LH exclusively, at morphological, functional and behavioral levels. We demonstrate that iPNs are subdivided into two morphological groups encoding positive hedonic valence or intensity information and conveying these features into separate domains in the LH. Silencing iPNs severely diminished flies' attraction behavior. Moreover, functional imaging disclosed a LH region tuned to repulsive odors comprised exclusively of third-order neurons. We provide evidence for a feature-based map in the LH, and elucidate its role as the center for integrating behaviorally relevant olfactory information

Computer simulation of colloidal powder processing

In Paper I, packing of colloidal particles is simulated in three-dimensions. Colloidal particles in each cluster are condensed from space towards their center. Clusters are then moved toward the center of agglomerates. The particle rearrangement process during or after condensation is simulated by moving each particle into a more stable position. Particle clusters rearranged during packing have higher packing density and average coordination number than particle clusters rearranged after packing. The effect of particle rearrangement on the packing density in a cluster is comparable to the effect of cluster rearrangement in the cluster agglomeration;In Paper II, agglomeration of colloidal particles in a suspension is simulated using the concepts of interparticle potential fields. Colloid particles move during agglomeration in the direction which decreases the potential energies between particles. Simulated conditions are based on experimental results and on agglomeration theory. The effects of the various types of potential curves between colloidal particles were checked. It was found that short- and long-range fields contribute to the agglomeration process under typical default conditions. Strong short range attractive energy without a repulsive energy barrier makes small strong clusters with hard contacts between particles but weak short-range force with a large repulsive energy barrier makes big agglomerates with soft contacts between particles;In Paper III, settling of colloidal particles was studied with a three-dimensional computer simulation technique. Special attention was paid to the metastable state, rearrangement, and network stress build-up during or after colloidal particle settling. The settling density through the whole process was checked and compared with experimental results. There is a big difference in packing density between particles settled with and without rearrangement. Internal sediment stresses and fracture energies of the settled colloidal powders were calculated. Stress condensation in a simulated powder compact by internal sediment stresses shows good approximation to the network compression stage of powder settling experiments. In a vertical distribution of fracture energy several minima are observed along the height of the particle compact which may cause laminar cracks in subsequent drying processes. Abrupt changes in the fracture energy become smoother with particle rearrangement. Angular fracture energy becomes more isotropic with rearrangement. Low density regions were observed in the settled powder compact near the corner of a tilted box and this is mainly due to the bridging of particles

Image-Based Modeling of Porous Media Using FEM and Lagrangian Particle Tracking

The study of fundamental flow and transport processes at the pore scale is essential to understanding how the mechanisms affect larger, field-scale, processes that occur in oil and gas recovery, groundwater flow, contaminant transport, and CO2 sequestration. Pore-scale imaging and modeling is one of the techniques used to investigate these fundamental mechanisms. Although extensive development of pore-scale imaging and modeling has occurred recently, some areas still need further advances. In this work, we address two areas: (1) imaging of bulk proppants and proppant-filled fractures under varying loading stress and flow simulation in these systems and (2) nanoparticle (NP) transport modeling in porous media. These are briefly explained below. Rock fracturing, followed by proppant injection, has been used for years to improve oil and gas production rates in low permeability reservoirs and is now routinely used in low-permeability resources such as a shales and tight sands. While field data makes clear the effectiveness of this technique, there is still much room to improve on the science, including how the proppant-filled fracture system responds to changes in loading stress which affect permeability and conductivity. Here, we use high-resolution x-ray computed tomography (XCT) to image two unsaturated rock/fracture/proppant systems under a series of stress levels typical of producing reservoirs: one with shale, one with Berea sandstone. The resulting XCT images were segmented, analyzed for structural and porosity changes, and then used for image-based flow modeling of Stokes flow using both finite element (FEM) and Lattice Boltzmann methods. NPs have been widely used commercially and have the potential to be extensively used in petroleum engineering as stabilizers in enhanced oil recovery operations or as tracers or sensors to detect rock and fluid properties. %In spite of a wide range of applications, many NP transport details are still unknown. In this work, we describe a Lagrangian particle tracking algorithm to model NP transport that can be used to better understand the impact of pore-scale hydrodynamics and surface forces on NP transport. Two XCT images, a Berea sandstone and a 2.5D micromodel, were meshed and used for image-based flow modeling of FEM Stokes flow. The effects of particle size, surface forces, flow rate, particle density, surface capacity, and surface forces mapped to XCT-image based mineralogy were studied