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Structural and spectroscopical study of crystals of 1,3,4-oxadiazole derivatives at high pressure
(2002)
In recent years the search for new materials of technological interest has given new impulses to the study of organic compounds. Organic substances possess a great number of advantages such as the possibility to adjust their properties for a given purpose by different chemical and physical techniques in the preparation process. Oxadiazole derivatives are interesting due to their use as material for light emitting diodes (LED) as well as scintillators. The physical properties of a solid depend on its structure. Different structures induce different intra- and intermolecular interactions. An advantageous method to modify the intra- as well as the intermolecular interactions of a given substance is the application of high pressure. Furthermore, using this method the chemical features of the compound are not influenced. We have investigated the influence of high pressure and high temperature on the super-molecular structure of several oxadiazole derivatives in crystalline state. From the results of this investigation an equation of state for these crystals was determined. Furthermore, the spectroscopical features of these materials under high pressure were characterized.
The interaction between surfaces displaying end-grafted hydrophilic polymer brushes plays important roles in biology and in many wet-technological applications. The outer surfaces of Gram-negative bacteria, for example, are composed of lipopolysaccharide (LPS) molecules exposing oligo- and polysaccharides to the aqueous environment. This unique, structurally complex biological interface is of great scientific interest as it mediates the interaction of bacteria with neighboring bacteria in colonies and biofilms. The interaction between polymer-decorated surfaces is generally coupled to the distance-dependent conformation of the polymer chains. Therefore, structural insight into the interacting surfaces is a prerequisite to understand the interaction characteristics as well as the underlying physical mechanisms. This problem has been addressed by theory, but accurate experimental data on polymer conformations under confinement are rare, because obtaining perturbation-free structural insight into buried soft interfaces is inherently difficult.
In this thesis, lipid membrane surfaces decorated with hydrophilic polymers of technological and biological relevance are investigated under controlled interaction conditions, i.e., at defined surface separations. For this purpose, dedicated sample architectures and experimental tools are developed. Via ellipsometry and neutron reflectometry pressure-distance curves and distance-dependent polymer conformations in terms of brush compression and reciprocative interpenetration are determined. Additional element-specific structural insight into the end-point distribution of interacting brushes is obtained by standing-wave x-ray fluorescence (SWXF).
The methodology is first established for poly[ethylene glycol] (PEG) brushes of defined length and grafting density. For this system, neutron reflectometry revealed pronounced brush interpenetration, which is not captured in common brush theories and therefore motivates rigorous simulation-based treatments. In the second step the same approach is applied to realistic mimics of the outer surfaces of Gram-negative bacteria: monolayers of wild type LPSs extracted from E. Coli O55:B5 displaying strain-specific O-side chains. The neutron reflectometry experiments yield unprecedented structural insight into bacterial interactions, which are of great relevance for the properties of biofilms.
Structural dynamics of photoexcited nanolayered perovskites studied by ultrafast x-ray diffraction
(2012)
This publication-based thesis represents a contribution to the active research field of ultrafast structural dynamics in laser-excited nanostructures. The investigation of such dynamics is mandatory for the understanding of the various physical processes on microscopic scales in complex materials which have great potentials for advances in many technological applications. I theoretically and experimentally examine the coherent, incoherent and anharmonic lattice dynamics of epitaxial metal-insulator heterostructures on timescales ranging from femtoseconds up to nanoseconds. To infer information on the transient dynamics in the photoexcited crystal lattices experimental techniques using ultrashort optical and x-ray pulses are employed. The experimental setups include table-top sources as well as large-scale facilities such as synchrotron sources. At the core of my work lies the development of a linear-chain model to simulate and analyze the photoexcited atomic-scale dynamics. The calculated strain fields are then used to simulate the optical and x-ray response of the considered thin films and multilayers in order to relate the experimental signatures to particular structural processes. This way one obtains insight into the rich lattice dynamics exhibiting coherent transport of vibrational energy from local excitations via delocalized phonon modes of the samples. The complex deformations in tailored multilayers are identified to give rise to highly nonlinear x-ray diffraction responses due to transient interference effects. The understanding of such effects and the ability to precisely calculate those are exploited for the design of novel ultrafast x-ray optics. In particular, I present several Phonon Bragg Switch concepts to efficiently generate ultrashort x-ray pulses for time-resolved structural investigations. By extension of the numerical models to include incoherent phonon propagation and anharmonic lattice potentials I present a new view on the fundamental research topics of nanoscale thermal transport and anharmonic phonon-phonon interactions such as nonlinear sound propagation and phonon damping. The former issue is exemplified by the time-resolved heat conduction from thin SrRuO3 films into a SrTiO3 substrate which exhibits an unexpectedly slow heat conductivity. Furthermore, I discuss various experiments which can be well reproduced by the versatile numerical models and thus evidence strong lattice anharmonicities in the perovskite oxide SrTiO3. The thesis also presents several advances of experimental techniques such as time-resolved phonon spectroscopy with optical and x-ray photons as well as concepts for the implementation of x-ray diffraction setups at standard synchrotron beamlines with largely improved time-resolution for investigations of ultrafast structural processes. This work forms the basis for ongoing research topics in complex oxide materials including electronic correlations and phase transitions related to the elastic, magnetic and polarization degrees of freedom.
Nowadays, colloidal rods can be synthesized in large amounts. The rods are typically cylindrically and their length ranges from several nanometers to a few micrometers. In solution, systems of colloidal rodlike molecules or aggregates can form liquid-crystalline phases with long-range orientational and spatial order. In the present work, we investigate structure formation and fractionation in systems of rodlike colloids with the help of Monte Carlo simulations in the NPT ensemble. Repulsive interactions can successfully be mimicked by the hard rod model, which has been studied extensively in the past. In many cases, attractive interactions like van der Waals or depletion forces cannot be neglected, however. In the first part of this work, the phase behavior of monodisperse attractive rods is characterized for different interaction strengths. Phase diagrams as a function of rod length and pressure are presented. Most systems of synthesized mesoscopic rods have a polydisperse length distribution as a consequence of the longitudinal growth process of the rods. For many technical and research applications, a rather small polydispersity is desired in order to have well defined material properties. The polydispersity can be reduced by a spatial demixing (fractionation) of long and short rods. Fractionation and structure formation is studied in a tridisperse and a polydisperse bulk suspension of rods. We observe that the resulting structures depend distinctly on the interaction strength. The fractionation in the system is strongly enhanced with increasing interaction strength. Suspensions are typically confined in a container. We also examine the influence of adjacent substrates in systems of tridisperse and polydisperse rod suspensions. Three different substrate types are studied in detail: a planar wall, a corrugated substrate, and a substrate with rectangular cavities. We analyze the fluid structure close to the substrate and substrate controlled fractionation. The spatial arrangement of long and short rods in front of the substrate depends sensitively on the substrate structure and the pressure. Rods with a predefined length are segregated at substrates with rectangular cavities.
The mammalian brain is, with its numerous neural elements and structured complex connectivity, one of the most complex systems in nature. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex networks. Here, we try to shed some light on the relationship between structural and functional connectivities by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the cortical areas by a subnetwork of interacting excitable neurons (multilevel model) and by a neural mass model (population model). With weak couplings, the multilevel model displays biologically plausible dynamics and the synchronization patterns reveal a hierarchical cluster organization in the network structure. We can identify a group of brain areas involved in multifunctional tasks by comparing the dynamical clusters to the topological communities of the network. With strong couplings of multilevel model and by using neural mass model, the dynamics are characterized by well-defined oscillations. The synchronization patterns are mainly determined by the node intensity (total input strengths of a node); the detailed network topology is of secondary importance. The biologically improved multilevel model exhibits similar dynamical patterns in the two regimes. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.
In the present work, we use symbolic regression for automated modeling of dynamical systems. Symbolic regression is a powerful and general method suitable for data-driven identification of mathematical expressions. In particular, the structure and parameters of those expressions are identified simultaneously.
We consider two main variants of symbolic regression: sparse regression-based and genetic programming-based symbolic regression. Both are applied to identification, prediction and control of dynamical systems.
We introduce a new methodology for the data-driven identification of nonlinear dynamics for systems undergoing abrupt changes. Building on a sparse regression algorithm derived earlier, the model after the change is defined as a minimum update with respect to a reference model of the system identified prior to the change. The technique is successfully exemplified on the chaotic Lorenz system and the van der Pol oscillator. Issues such as computational complexity, robustness against noise and requirements with respect to data volume are investigated.
We show how symbolic regression can be used for time series prediction. Again, issues such as robustness against noise and convergence rate are investigated us- ing the harmonic oscillator as a toy problem. In combination with embedding, we demonstrate the prediction of a propagating front in coupled FitzHugh-Nagumo oscillators. Additionally, we show how we can enhance numerical weather predictions to commercially forecast power production of green energy power plants.
We employ symbolic regression for synchronization control in coupled van der Pol oscillators. Different coupling topologies are investigated. We address issues such as plausibility and stability of the control laws found. The toolkit has been made open source and is used in turbulence control applications.
Genetic programming based symbolic regression is very versatile and can be adapted to many optimization problems. The heuristic-based algorithm allows for cost efficient optimization of complex tasks.
We emphasize the ability of symbolic regression to yield white-box models. In contrast to black-box models, such models are accessible and interpretable which allows the usage of established tool chains.
This work deals with the connection between two basic phenomena in Nonlinear Dynamics: synchronization of chaotic systems and recurrences in phase space. Synchronization takes place when two or more systems adapt (synchronize) some characteristic of their respective motions, due to an interaction between the systems or to a common external forcing. The appearence of synchronized dynamics in chaotic systems is rather universal but not trivial. In some sense, the possibility that two chaotic systems synchronize is counterintuitive: chaotic systems are characterized by the sensitivity ti different initial conditions. Hence, two identical chaotic systems starting at two slightly different initial conditions evolve in a different manner, and after a certain time, they become uncorrelated. Therefore, at a first glance, it does not seem to be plausible that two chaotic systems are able to synchronize. But as we will see later, synchronization of chaotic systems has been demonstrated. On one hand it is important to investigate the conditions under which synchronization of chaotic systems occurs, and on the other hand, to develop tests for the detection of synchronization. In this work, I have concentrated on the second task for the cases of phase synchronization (PS) and generalized synchronization (GS). Several measures have been proposed so far for the detection of PS and GS. However, difficulties arise with the detection of synchronization in systems subjected to rather large amounts of noise and/or instationarities, which are common when analyzing experimental data. The new measures proposed in the course of this thesis are rather robust with respect to these effects. They hence allow to be applied to data, which have evaded synchronization analysis so far. The proposed tests for synchronization in this work are based on the fundamental property of recurrences in phase space.
In the present work synchronization phenomena in complex dynamical systems exhibiting multiple time scales have been analyzed. Multiple time scales can be active in different manners. Three different systems have been analyzed with different methods from data analysis. The first system studied is a large heterogenous network of bursting neurons, that is a system with two predominant time scales, the fast firing of action potentials (spikes) and the burst of repetitive spikes followed by a quiescent phase. This system has been integrated numerically and analyzed with methods based on recurrence in phase space. An interesting result are the different transitions to synchrony found in the two distinct time scales. Moreover, an anomalous synchronization effect can be observed in the fast time scale, i.e. there is range of the coupling strength where desynchronization occurs. The second system analyzed, numerically as well as experimentally, is a pair of coupled CO₂ lasers in a chaotic bursting regime. This system is interesting due to its similarity with epidemic models. We explain the bursts by different time scales generated from unstable periodic orbits embedded in the chaotic attractor and perform a synchronization analysis of these different orbits utilizing the continuous wavelet transform. We find a diverse route to synchrony of these different observed time scales. The last system studied is a small network motif of limit cycle oscillators. Precisely, we have studied a hub motif, which serves as elementary building block for scale-free networks, a type of network found in many real world applications. These hubs are of special importance for communication and information transfer in complex networks. Here, a detailed study on the mechanism of synchronization in oscillatory networks with a broad frequency distribution has been carried out. In particular, we find a remote synchronization of nodes in the network which are not directly coupled. We also explain the responsible mechanism and its limitations and constraints. Further we derive an analytic expression for it and show that information transmission in pure phase oscillators, such as the Kuramoto type, is limited. In addition to the numerical and analytic analysis an experiment consisting of electrical circuits has been designed. The obtained results confirm the former findings.
This thesis analyses synchronization phenomena occurring in large ensembles of interacting oscillatory units. In particular, the effects of nonisochronicity (frequency dependence on the oscillator's amplitude) on the macroscopic transition to synchronization are studied in detail. The new phenomena found (Anomalous Synchronization) are investigated in populations of oscillators as well as between oscillator's ensembles.