Hydrodynamics of Rod-Like Colloids and Vesicles

We investigate the dynamics of rod-like colloids and vesicles by means of computer simulations. These two systems are examples of the rich dynamics in "soft-matter" systems, which is characterized by large relaxation times. Therefore, dynamical behavior in soft-matter systems is easily accessable experimentally, and soft materials are driven into non-equilibrium states, already by weak external fields. Both systems have in common that they serve as model systems for transport phenomena in cell biology. We focus on the influence of hydrodynamic interactions. This is realized by the use of a mesoscale hydrodynamics simulation technique called the "Multi Particle Collision Dynamics" (MPC) method, which takes the solvent into account explicitly. We calculate self-diffusion constants of rod-like colloids in the isotropic and nematic phases. Rod diffusion is strongly influenced by steric and hydrodynamic interactions between rods. Due to the anisotropy of the nematic phase also diffusion is anisotropic in such systems. We find that hydrodynamic effects lead to an increased diffusion. Moreover, our simulations show that the diffusion anisotropy of the nematic phase depends on the rod aspect ratio. Our simulation results are compared to experimental measurements of our cooperation partners (group J. K. G. Dhont, FZ-Jülich) who measured diffusion constants of rod-like fd-viruses suspensions. Our observations of the hydrodynamic enhancement and the anisotropy of rod self-diffusion are in good agreement with the experiments. A small amount of spherical tracer colloids is added to the rod suspensions described above, and tracer-sphere diffusion constants are determined. They also exhibit a strong diffusion anisotropy in the nematic phase. The effect of the rod network on tracer-sphere diffusion can be divided into a steric and hydrodynamic contribution. Our results are in good agreement with theoretical predictions which incorporate hydrodynamic effects. An important quantity for the calculation of the theoretical diffusion constants is the hydrodynamic screening length, which is difficult to measure in experiments, but can be directly calculated in simulations. Due to the high concentration of rods, the typically long-ranged hydrodynamic interactions, which depend inversely proportional on the distance between colloids, are screened such that they decay exponentially. We have developed a method which allows us to calculate hydrodynamic screening lengths from the equilibrium fluctuations of solvent shear waves. With this method, we are also able to determine anisotropic screening lengths in nematic systems. We show that hydrodynamic screening lengths are of the order of typical distances between neighboring rods. The calculated screening lengths are able to explain tracer-sphere diffusion constants quantitatively. Far more complex than rod suspensions are vesicles, as they have an internal dynamics. We study vesicles in shear flow in a two-dimensional model system which shows a variety of interesting dynamical phenomena. Depending on the viscosity ratio, i.e. the ratio between the inner and the outer viscosity of the vesicle, they can either ``tumble'', ``swing'' or show ``tank-treading''. In the tumbling regime, the vesicle orientation permanently rotates, in the swinging regime the vesicle exhibits temporally periodical changes in shape and orientation and in the tank-treading regime both shape and orientation are constant, whereas the membrane rotates around the enclosed volume. For the first time, a transition from tank-treading to swinging with increasing viscosity contrast could be shown in computer simulations. Our simulations are in good agreement with a phenomenological theoretical description. Close to walls, tumbling is strongly suppressed. Furthermore, the vesicle is repelled from the wall. The origin of this repulsion is the hydrodynamical lift force. We find that the lift force decays inversely proportional to the squared wall distance and that it decays with increasing viscosity contrast. The lift force is of relevance for the motion of blood cells in blood flow

Effect of fullerene containing lubricants on wear resistance of machine components in boundary lubrication

Fullerenes, a new form of carbon nanomaterials, possess unique physical and mechanical properties that make their use as additives to liquid lubricants potentially beneficial. The goal of this study was to investigate the effect of fullerene containing lubricants on wear resistance of steel-bronze couples operating under boundary lubrication conditions. A mathematical model of deformed asperity contact was built to calculate real contact area and real contact pressure. Computer controlled wear friction testing methodology and equipment were designed, developed and implemented for obtaining reliable and objective experimental data. In addition, optical and scanning electron microscopy and standard surface texture analysis were employed. Heavy duty motor oil SAE 10 was modified by admixing fullerenes C60, a fullerene mixture of C60 and C70, fullerene containing soot, and graphite powder. The experiments showed that all of the selected fullerene additives dissolved in liquid lubricants reduce wear of the tested materials. In addition, it was found that despite improvements in wear resistance, the selected modified lubricants did not significantly change friction characteristics. Improvement of wear resistance of contact surfaces operating with fullerene modified lubricants can be explained by the presence of fullerenes in real contact while the liquid lubricant is squeezed out. Fullerenes are considered to function as minute hard particles that do not break down under applied normal force, and tend to separate direct contact of functional surfaces of selected materials

A Study of English Loanwords in Chinese through Chinese Newswriting

The purpose of the present study, therefore, is to research the signified loanwords found in current newspapers. More specifically, answer to the following questions are to be discovered: 1. How extensive is the standardization of the conventional translation or transliteration of English loanwords in Chinese in terms of explicative hybrid, loan-blend, independent hybrid, word-for-word translation, descriptive translation, and doublet? 2. What kind of proportion of these English loanwords in Chinese exist in selected newswriting in terms of the socio-political, technical-scientific, scholarly, sports, and business-economic terminology

Physical Reasoning for Intelligent Agent in Simulated Environments

Developing Artificial Intelligence (AI) that is capable of understanding and interacting with the real world in a sophisticated way has long been a grand vision of AI. There is an increasing number of AI agents coming into our daily lives and assisting us with various daily tasks ranging from house cleaning to serving food in restaurants. While different tasks have different goals, the domains of the tasks all obey the physical rules (classic Newtonian physics) of the real world. To successfully interact with the physical world, an agent needs to be able to understand its surrounding environment, to predict the consequences of its actions and to draw plans that can achieve a goal without causing any unintended outcomes. Much of AI research over the past decades has been dedicated to specific sub-problems such as machine learning and computer vision, etc. Simply plugging in techniques from these subfields is far from creating a comprehensive AI agent that can work well in a physical environment. Instead, it requires an integration of methods from different AI areas that considers specific conditions and requirements of the physical environment. In this thesis, we identified several capabilities that are essential for AI to interact with the physical world, namely, visual perception, object detection, object tracking, action selection, and structure planning. As the real world is a highly complex environment, we started with developing these capabilities in virtual environments with realistic physics simulations. The central part of our methods is the combination of qualitative reasoning and standard techniques from different AI areas. For the visual perception capability, we developed a method that can infer spatial properties of rectangular objects from their minimum bounding rectangles. For the object detection capability, we developed a method that can detect unknown objects in a structure by reasoning about the stability of the structure. For the object tracking capability, we developed a method that can match perceptually indistinguishable objects in visual observations made before and after a physical impact. This method can identify spatial changes of objects in the physical event, and the result of matching can be used for learning the consequence of the impact. For the action selection capability, we developed a method that solves a hole-in-one problem that requires selecting an action out of an infinite number of actions with unknown consequences. For the structure planning capability, we developed a method that can arrange objects to form a stable and robust structure by reasoning about structural stability and robustness

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

Numerical modelling of heat generation in porous planetesimal collisions

An important unanswered question in planetary science is how planetesimals, the ~1–100 km solid precursors to asteroids and planets, were heated in the early Solar System. This thesis quantifies one possible heat source: planetesimal collisions. Recent work has predicted that collision velocities and planetesimal porosities were likely to have been higher than previously thought; this is likely to have significant implications on collision heating. The approach adopted in this research was to numerically model shock heating during planetesimal collisions. Simulations showed that an increase in porosity can significantly increase heating: in a 5 km s-1 collision between equal sized, non-porous planetesimals, no material was heated to the solidus, compared to two thirds of the mass of 50% porous planetesimals. Velocity also strongly influences heating: at 4 km s-1, an eighth of the mass of 50% porous planetesimals was heated to the solidus, compared to the entire mass at 6 km s-1. Further simulations quantified the influence on heating of the impactor-to-target mass ratio, the initial planetesimal temperature and the impact angle. A Monte Carlo model was developed to examine the cumulative heating caused by a population of impactors striking a parent body. In the majority of collisions the impactor was much smaller than the parent body, and only minor heating was possible. However, some larger or faster impactors were capable of causing significant heating without disrupting the parent body; these collisions could have heated up to 10% of the parent body to the solidus. To cause global heating, the collision must have catastrophically disrupted the parent body. The increase in specific internal energy from collisions was compared with the decay of short-lived radionuclides. In the first ~6 Ma, radioactive decay was the most important heat source. After ~10 Ma, the energy caused by collisions was likely to have overtaken radioactive decay as the dominant source