Theoretical investigation of the interaction of a polymer film with a nanoparticle

The fundamental aim in our investigation of the interaction of a polymer film with a nanoparticle is the extraction of information on the dynamics of the liquid using a single tracking particle. In this work two theoretical methods were used: one passive, where the motion of the particle measures the dynamics of the liquid, one active, where perturbations in the system are introduced through the particle. In the first part of this investigation a thin polymeric film on a substrate is studied using molecular dynamics simulations. The polymer is modeled via a 'bead spring' model. The particle is spheric and non structured and is able to interact with the monomers via a Lennard Jones potential. The system is micro-canonical and simulations were performed for average temperatures between the glass transition temperature of the film and its dewetting temperature. It is shown that the stability of the nanoparticle on the polymer film in the absence of gravity depends strongly on the form of the chosen interaction potential between nanoparticle and polymer. The relative position of the tracking particle to the liquid vapor interface of the polymer film shows the glass transition of the latter. The velocity correlation function and the mean square displacement of the particle has shown that it is caged when the temperature is close to the glass transition temperature. The analysis of the dynamics at long times shows the coupling of the nanoparticle to the center of mass of the polymer chains. The use of the Stokes-Einstein formula, which relates the diffusion coefficient to the viscosity, permits to use the nanoparticle as a probe for the determination of the bulk viscosity of the melt, the so called 'microrheology'. It is shown that for low frequencies the result obtained using microrheology coincides with the results of the Rouse model applied to the polymer dynamics. In the second part of this investigation the equations of Linear Hydrodynamics are solved for a nanoparticle oscillating above the film. It is shown that compressible liquids have mechanical response to external perturbations induced with the nanoparticle. These solutions show strong velocity and pressure profiles of the liquid near the interface, as well as a mechanical response of the liquid-vapor interface. The results obtained with this calculations can be employed for the interpretation of experimental results of non contact AFM microscopy

Mechanics and dynamics of liposomes and cells studied by QCM and ECIS

The present thesis introduces a novel sensitive technique based on TSM resonators that provides quantitative information about the dynamic properties of biological cells and artificial lipid systems. In order to support and complement results obtained by this method supplementary measurements based on ECIS technique were carried out. The first part (chapters 3 and 4) deals with artificial lipid systems. In chapter 3 ECIS measurements were used to monitor the adsorption of giant unilamellar vesicles as well as their thermal fluctuations. From dynamic Monte Carlo Simulations the rate constant of vesicle adsorption was determined. Furthermore, analysis of fluctuation measurements reveals Brownian motion reflecting membrane undulations of the adherent liposomes. In chapter 4 QCM-based fluctuation measurements were applied to quantify nanoscopically small deformations of giant unilamellar vesicles with an external electrical field applied simultaneously. The response of liposomes to an external voltage with shape changes was monitored as a function of cholesterol content and adhesion force. In the second part (chapters 5 - 8) attention was given to cell motility. It was shown for the first time, that QCM can be applied to monitor the dynamics of living adherent cells in real time. QCM turned out to be a highly sensitive tool to detect the vertical motility of adherent cells with a time resolution in the millisecond regime. The response of cells to environmental changes such as temperature or osmotic stress could be quantified. Furthermore, the impact of cytochalasin D (inhibits actin polymerization) and taxol (facilitate polymerization of microtubules) as well as nocodazole (depolymerizes microtubules) on the dynamic properties of cells was scrutinized. Each drug provoked a significant reduction of the monitored cell shape fluctuations as expected from their biochemical potential. However, not only the abolition of fluctuations was observed but also an increase of motility due to integrin-induced transmembrane signals. These signals were activated by peptides containing the RGD sequence, which is known to be an integrin recognition motif. Ultimately, two pancreatic carcinoma cell lines, derived from the same original tumor, but known to possess different metastatic potential were studied. Different dynamic behavior of the two cell lines was observed which was attributed to cell-cell as well as cell-substrate interactions rather than motility. Thus one may envision that it might be possible to characterize the motility of different cell types as a function of many variables by this new highly sensitive technique based on TSM resonators. Finally the origin of the broad cell resonance was investigated. Improvement of the time resolution reveals the "real" frequency of cell shape fluctuations. Several broad resonances around 3-5 Hz, 15-17 Hz and 25-29 Hz were observed and that could unequivocally be assigned to biological activity of living cells. However, the kind of biological process that provokes this synchronized collective and periodic behavior of the cells remains to be elucidated.

Mutually catalytic branching at infinite rate

The purpose of this doctoral thesis is to prove existence for a mutually catalytic random walk with infinite branching rate on countably many sites. The process is defined as a weak limit of an approximating family of processes. An approximating process is constructed by adding jumps to a deterministic migration on an equidistant time grid. As law of jumps we need to choose the invariant probability measure of the mutually catalytic random walk with a finite branching rate in the recurrent regime. This model was introduced by Dawson and Perkins (1998) and this thesis relies heavily on their work. Due to the properties of this invariant distribution, which is in fact the exit distribution of planar Brownian motion from the first quadrant, it is possible to establish a martingale problem for the weak limit of any convergent sequence of approximating processes. We can prove a duality relation for the solution to the mentioned martingale problem, which goes back to Mytnik (1996) in the case of finite rate branching, and this duality gives rise to weak uniqueness for the solution to the martingale problem. Using standard arguments we can show that this solution is in fact a Feller process and it has the strong Markov property. For the case of only one site we prove that the model we have constructed is the limit of finite rate mutually catalytic branching processes as the branching rate approaches infinity. Therefore, it seems naturalto refer to the above model as an infinite rate branching process. However, a result for convergence on infinitely many sites remains open.

Thermal fluctuations and boundary conditions in the lattice Boltzmann method

The lattice Boltzmann method is a popular approach for simulating hydrodynamic interactions in soft matter and complex fluids. The solvent is represented on a discrete lattice whose nodes are populated by particle distributions that propagate on the discrete links between the nodes and undergo local collisions. On large length and time scales, the microdynamics leads to a hydrodynamic flow field that satisfies the Navier-Stokes equation. In this thesis, several extensions to the lattice Boltzmann method are developed. In complex fluids, for example suspensions, Brownian motion of the solutes is of paramount importance. However, it can not be simulated with the original lattice Boltzmann method because the dynamics is completely deterministic. It is possible, though, to introduce thermal fluctuations in order to reproduce the equations of fluctuating hydrodynamics. In this work, a generalized lattice gas model is used to systematically derive the fluctuating lattice Boltzmann equation from statistical mechanics principles. The stochastic part of the dynamics is interpreted as a Monte Carlo process, which is then required to satisfy the condition of detailed balance. This leads to an expression for the thermal fluctuations which implies that it is essential to thermalize all degrees of freedom of the system, including the kinetic modes. The new formalism guarantees that the fluctuating lattice Boltzmann equation is simultaneously consistent with both fluctuating hydrodynamics and statistical mechanics. This establishes a foundation for future extensions, such as the treatment of multi-phase and thermal flows. An important range of applications for the lattice Boltzmann method is formed by microfluidics. Fostered by the "lab-on-a-chip" paradigm, there is an increasing need for computer simulations which are able to complement the achievements of theory and experiment. Microfluidic systems are characterized by a large surface-to-volume ratio and, therefore, boundary conditions are of special relevance. On the microscale, the standard no-slip boundary condition used in hydrodynamics has to be replaced by a slip boundary condition. In this work, a boundary condition for lattice Boltzmann is constructed that allows the slip length to be tuned by a single model parameter. Furthermore, a conceptually new approach for constructing boundary conditions is explored, where the reduced symmetry at the boundary is explicitly incorporated into the lattice model. The lattice Boltzmann method is systematically extended to the reduced symmetry model. In the case of a Poiseuille flow in a plane channel, it is shown that a special choice of the collision operator is required to reproduce the correct flow profile. This systematic approach sheds light on the consequences of the reduced symmetry at the boundary and leads to a deeper understanding of boundary conditions in the lattice Boltzmann method. This can help to develop improved boundary conditions that lead to more accurate simulation results.

Statistical problems related to excitation threshold and reset value of membrane potentials

Die vorliegende Arbeit ist motiviert durch biologische Fragestellungen bezüglich des Verhaltens von Membranpotentialen in Neuronen. Ein vielfach betrachtetes Modell für spikende Neuronen ist das Folgende. Zwischen den Spikes verhält sich das Membranpotential wie ein Diffusionsprozess X der durch die SDGL dX_t= beta(X_t) dt+ sigma(X_t) dB_t gegeben ist, wobei (B_t) eine Standard-Brown'sche Bewegung bezeichnet. Spikes erklärt man wie folgt. Sobald das Potential X eine gewisse Exzitationsschwelle S überschreitet entsteht ein Spike. Danach wird das Potential wieder auf einen bestimmten Wert x_0 zurückgesetzt. In Anwendungen ist es manchmal möglich, einen Diffusionsprozess X zwischen den Spikes zu beobachten und die Koeffizienten der SDGL beta() und sigma() zu schätzen. Dennoch ist es nötig, die Schwellen x_0 und S zu bestimmen um das Modell festzulegen. Eine Möglichkeit, dieses Problem anzugehen, ist x_0 und S als Parameter eines statistischen Modells aufzufassen und diese zu schätzen. In der vorliegenden Arbeit werden vier verschiedene Fälle diskutiert, in denen wir jeweils annehmen, dass das Membranpotential X zwischen den Spikes eine Brown'sche Bewegung mit Drift, eine geometrische Brown'sche Bewegung, ein Ornstein-Uhlenbeck Prozess oder ein Cox-Ingersoll-Ross Prozess ist. Darüber hinaus beobachten wir die Zeiten zwischen aufeinander folgenden Spikes, die wir als iid Treffzeiten der Schwelle S von X gestartet in x_0 auffassen. Die ersten beiden Fälle ähneln sich sehr und man kann jeweils den Maximum-Likelihood-Schätzer explizit angeben. Darüber hinaus wird, unter Verwendung der LAN-Theorie, die Optimalität dieser Schätzer gezeigt. In den Fällen OU- und CIR-Prozess wählen wir eine Minimum-Distanz-Methode, die auf dem Vergleich von empirischer und wahrer Laplace-Transformation bezüglich einer Hilbertraumnorm beruht. Wir werden beweisen, dass alle Schätzer stark konsistent und asymptotisch normalverteilt sind. Im letzten Kapitel werden wir die Effizienz der Minimum-Distanz-Schätzer anhand simulierter Daten überprüfen. Ferner, werden Anwendungen auf reale Datensätze und deren Resultate ausführlich diskutiert.

Ausbreitung einer Infektion durch ein System Brownscher Bewegungen

In dieser Arbeit werden wir ein Modell untersuchen, welches die Ausbreitung einer Infektion beschreibt. Bei diesem Modell werden zunächst Partikel gemäß eines Poissonschen Punktprozesses auf der reellen Achse verteilt. Bis zu einem gewissen Punkt auf der reellen Achse sind alle Partikel von einer Infektion befallen. Während sich nicht infizierte Partikel nicht bewegen, folgen die infizierten Partikel den Pfaden von voneinander unabhängigen Brownschen Bewegungen und verbreitet die Infektion dabei an den Orten, welche sie betreten. Wenn sie dabei auf ein nicht infiziertes Partikel treffen, ist dieses von diesem Moment an auch infiziert und beginnt ebenfalls, dem Pfad einer Brownschen Bewegung zu folgen und die Infektion auszubreiten. Auf diese Art verschiebt sich nun der am weitesten rechts liegende Ort R_t, an dem die Infektion bereits verbreitet wurde. Wir werden mit Hilfe des subadditiven Ergodensatzes zeigen, dass sich dieser Ort mit linearer Geschwindigkeit fortbewegt. Ferner werden wir eine obere und eine untere Schranke für die Ausbreitungsgeschwindkeit angeben. Danach werden wir zeigen, dass der Prozess Regenerationszeiten hat, nämlich solche zufällige Zeiten, zu denen er eine Art Neustart unter speziellen Startbedingungen durchführt. Wir werden diese für eine weitere Charakterisierung der Ausbreitungsgeschwingkeit nutzen. Ferner erhalten wir durch die Regenerationszeiten auch einen Zentralen Grenzwertsatz für R_t und können zeigen, dass die Verteilung der infizierten Partikel aus Sicht des am weitesten rechts liegenden infizierten Ortes gegen eine invariante Verteilung konvergiert.