Refine
Year of publication
- 2018 (28) (remove)
Document Type
- Doctoral Thesis (28) (remove)
Language
- English (28) (remove)
Is part of the Bibliography
- yes (28)
Keywords
- Magnetismus (3)
- magnetism (3)
- Bakterien (2)
- Ferroelektrika (2)
- bacteria (2)
- ferroelectrics (2)
- mode stability (2)
- Antarctica (1)
- Antarktis (1)
- Astronomie (1)
Institute
- Institut für Physik und Astronomie (28) (remove)
Future magnetic recording industry needs a high-density data storage technology. However, switching the magnetization of small bits requires high magnetic fields that cause excessive heat dissipation. Therefore, controlling magnetism without applying external magnetic field is an important research topic for potential applications in data storage devices with low power consumption. Among the different approaches being investigated, two of them stand out, namely i) all-optical helicity dependent switching (AO-HDS) and ii) ferroelectric control of magnetism. This thesis aims to contribute towards a better understanding of the physical processes behinds these effects as well as reporting new and exciting possibility for the optical and/or electric control of magnetic properties. Hence, the thesis contains two differentiated chapters of results; the first devoted to AO-HDS on TbFe alloys and the second to the electric field control of magnetism in an archetypal Fe/BaTiO3 system.
In the first part, the scalability of the AO-HDS to small laser spot-sizes of few microns in the ferrimagnetic TbFe alloy is investigated by spatially resolving the magnetic contrast with photo-emission electron microscopy (PEEM) and X-ray magnetic circular dichroism (XMCD). The results show that the AO-HDS is a local effect within the laser spot size that occurs in the ring-shaped region in the vicinity of thermal demagnetization. Within the ring region, the helicity dependent switching occurs via thermally activated domain wall motion. Further, the thesis reports on a novel effect of thickness dependent inversion of the switching orientation. It addresses some of the important questions like the role of laser heating and the microscopic mechanism driving AO-HDS.
The second part of the thesis focuses on the electric field control of magnetism in an artificial multiferroic heterostructure. The sample consists of an Fe wedge with thickness varying between 0:5 nm and 3 nm, deposited on top of a ferroelectric and ferroelastic BaTiO3 [001]-oriented single crystal substrate. Here, the magnetic contrast is imaged via PEEM and XMCD as a function of out-of-plane voltage. The results show the evidence of the electric field control of superparamagnetism mediated by a ferroelastic modification of the magnetic anisotropy. The changes in the magnetoelastic anisotropy drive the transition from the superparamagnetic to superferromagnetic state at localized sample positions.
Microswimmers, i.e. swimmers of micron size experiencing low Reynolds numbers, have received a great deal of attention in the last years, since many applications are envisioned in medicine and bioremediation. A promising field is the one of magnetic swimmers, since magnetism is biocom-patible and could be used to direct or actuate the swimmers. This thesis studies two examples of magnetic microswimmers from a physics point of view.
The first system to be studied are magnetic cells, which can be magnetic biohybrids (a swimming cell coupled with a magnetic synthetic component) or magnetotactic bacteria (naturally occurring bacteria that produce an intracellular chain of magnetic crystals). A magnetic cell can passively interact with external magnetic fields, which can be used for direction. The aim of the thesis is to understand how magnetic cells couple this magnetic interaction to their swimming strategies, mainly how they combine it with chemotaxis (the ability to sense external gradient of chemical species and to bias their walk on these gradients). In particular, one open question addresses the advantage given by these magnetic interactions for the magnetotactic bacteria in a natural environment, such as porous sediments. In the thesis, a modified Active Brownian Particle model is used to perform simulations and to reproduce experimental data for different systems such as bacteria swimming in the bulk, in a capillary or in confined geometries. I will show that magnetic fields speed up chemotaxis under special conditions, depending on parameters such as their swimming strategy (run-and-tumble or run-and-reverse), aerotactic strategy (axial or polar), and magnetic fields (intensities and orientations), but it can also hinder bacterial chemotaxis depending on the system.
The second example of magnetic microswimmer are rigid magnetic propellers such as helices or random-shaped propellers. These propellers are actuated and directed by an external rotating magnetic field. One open question is how shape and magnetic properties influence the propeller behavior; the goal of this research field is to design the best propeller for a given situation. The aim of the thesis is to propose a simulation method to reproduce the behavior of experimentally-realized propellers and to determine their magnetic properties. The hydrodynamic simulations are based on the use of the mobility matrix. As main result, I propose a method to match the experimental data, while showing that not only shape but also the magnetic properties influence the propellers swimming characteristics.
The topic of this thesis is the experimental investigation of evaporating thin films on planar solid substrates and the enrichment, the crystal growth and Marangoni flows near the three phase line in the case of partially wetting mixtures of volatile and non volatile liquids. In short, it deals with the properties of planar liquid films and with those of thin liquid sections near the three phase contact line. In both cases the liquid looses continuously one component by evaporation. One topic is the rupture behavior of ultra-thin films of binary mixtures of a volatile solvent and a nonvolatile solute. It is studied how the thickness at which the film ruptures is related to the solute crystallization at the liquid/ substrate interface as soon as the solute reaches supersaturation. A universal relation between the rupture thickness and the saturation behaviour is presented. The second research subject are individual nanoparticles embedded in molecularly thin films at planar substrates. It is found that the nanoparticles cause an unexpectedly large film surface distortion (meniscus). This distortion can be measured quantitatively by conventional reflective microscopy although the nanoparticles are much smaller than the Rayleigh diffraction limit. Investigations with binary mixtures of volatile solvents and non-volatile solutes (polymers) aim at a better understanding/prediction of the final solute coverage, the timeresolved film thinning, the time-resolved solvent evaporation, and the evolution of the solute concentration within the thinning film. A quantiative theoretical description of the experimental findings is derived. Experiments of completely miscible binary mixtures of volatile liquids, which individually form continuous planar films show unexpectedly that films of mixtures are not necessarily continuous and planar. Rather, they may form surface
undulations or even rupture. This is explained with surface Marangoni flows. A new method for the exceptionally fast fabrication (mm/min) of ultralong aligned diphenylalanin single crystals via dip casting is presented. It is shown how the specific evaporation conditions at the three phase line can be used for a controlled peptide crystal growth process. It is further demonstrated how the confinement inside a smalll capillary affects the peptide crystallization and how this can be understood (and used).
Light-driven diffusioosmosis
(2018)
The emergence of microfluidics created the need for precise and remote control of micron-sized objects. I demonstrate how light-sensitive motion can be induced at the micrometer scale by a simple addition of a photosensitive surfactant, which makes it possible to trigger hydrophobicity with light. With point-like laser irradiation, radial inward and outward hydrodynamic surface flows are remotely switched on and off. In this way, ensembles of microparticles can be moved toward or away from the irradiation center. Particle motion is analyzed according to varying parameters, such as surfactant and salt concentration, illumination condition, surface hydrophobicity, and surface structure.
The physical origin of this process is the so-called light-driven diffusioosmosis (LDDO), a phenomenon that was discovered in the framework of this thesis and is described experimentally and theoretically in this work. To give a brief explanation, a focused light irradiation induces a local photoisomerization that creates a concentration gradient at the solid-liquid interface. To compensate for the change in osmotic pressure near the surface, a hydrodynamic flow along the surface is generated. Surface-surfactant interaction largely governs LDDO. It is shown that surfactant adsorption depends on the isomerization state of the surfactant. Photoisomerization, therefore, triggers a surfactant attachment or detachment from the surface. This change is considered to be one of the reasons for the formation of LDDO flow.
These flows are introduced not only by a focused laser source but also by global irradiation. Porous particles show reversible repulsive and attractive interactions when dispersed in the solution of photosensitive surfactant. Repulsion and attraction is controlled by the irradiation wavelength. Illumination with red light leads to formation of aggregates, while illumination with blue light leads to the formation of a well-separated grid with equal interparticle distances, between 2µm and 80µm, depending on the particle surface density. These long-range interactions are considered to be a result of an increase or decrease of surfactant concentration around each particle, depending on the irradiation wavelength. Surfactant molecules adsorb inside the pores of the particles. A light-induced photoisomerization changes adsorption to the pores and drives surfactant molecules to the outside. The concentration gradients generate symmetric flows around each single particle resulting in local LDDO. With a break of the symmetry (i.e., by closing one side of the particle with a metal cap), one can achieve active self-propelled particle motion.
Spectroscopy at the limit
(2018)
Movement and navigation are essential for many organisms during some parts of their lives. This is also true for bacteria, which can move along surfaces and swim though liquid environments. They are able to sense their environment, and move towards environmental cues in a directed fashion.
These abilities enable microbial lifecyles in biofilms, improved food uptake, host infection, and many more. In this thesis we study aspects of the swimming movement - or motility - of the soil bacterium (P. putida). Like most bacteria, P. putida swims by rotating its helical flagella, but their arrangement differs from the main model organism in bacterial motility research: (E. coli). P. putida is known for its intriguing motility strategy, where fast and slow episodes can occur after each other. Up until now, it was not known how these two speeds can be produced, and what advantages they might confer to this bacterium.
Normally the flagella, the main component of thrust generation in bacteria, are not observable by ordinary light microscopy. In order to elucidate this behavior, we therefore used a fluorescent staining technique on a mutant strain of this species to specifically label the flagella, while leaving the cell body only faintly stained. This allowed us to image the flagella of the swimming bacteria with high spacial and temporal resolution with a customized high speed fluorescence microscopy setup. Our observations show that P. putida can swim in three different modes. First, It can swim with the flagella pushing the cell body, which is the main mode of swimming motility previously known from other bacteria. Second, it can swim with the flagella pulling the cell body, which was thought not to be possible in situations with multiple flagella. Lastly, it can wrap its flagellar bundle around the cell body, which results in a speed wich is slower by a factor of two. In this mode, the flagella are in a different physical conformation with a larger radius so the cell body can fit inside. These three swimming modes explain the previous observation of two speeds, as well as the non strict alternation of the different speeds.
Because most bacterial swimming in nature does not occur in smoothly walled glass enclosures under a microscope, we used an artificial, microfluidic, structured system of obstacles to study the motion of our model organism in a structured environment. Bacteria were observed in microchannels with cylindrical obstacles of different sizes and with different distances with video microscopy and cell tracking. We analyzed turning angles, run times, and run length, which we compared to a minimal model for movement in structured geometries. Our findings show that hydrodynamic interactions with the walls lead to a guiding of the bacteria along obstacles. When comparing the observed behavior with the statics of a particle that is deflected with every obstacle contact, we find that cells run for longer distances than that model.
Navigation in chemical gradients is one of the main applications of motility in bacteria. We studied the swimming response of P. putida cells to chemical stimuli (chemotaxis) of the common food preservative sodium benzoate. Using a microfluidic gradient generation device, we created gradients of varying strength, and observed the motion of cells with a video microscope and subsequent cell tracking. Analysis of different motility parameters like run lengths and times, shows that P. putida employs the classical chemotaxis strategy of E. coli: runs up the gradient are biased to be longer than those down the gradient. Using the two different run speeds we observed due to the different swimming modes, we classify runs into `fast' and `slow' modes with a Gaussian mixture model (GMM). We find no evidence that P. putida's uses its swimming modes to perform chemotaxis.
In most studies of bacterial motility, cell tracking is used to gather trajectories of individual swimming cells. These trajectories then have to be decomposed into run sections and tumble sections. Several algorithms have been developed to this end, but most require manual tuning of a number of parameters, or extensive measurements with chemotaxis mutant strains. Together with our collaborators, we developed a novel motility analysis scheme, based on generalized Kramers-Moyal-coefficients. From the underlying stochastic model, many parameters like run length etc., can be inferred by an optimization procedure without the need for explicit run and tumble classification. The method can, however, be extended to a fully fledged tumble classifier. Using this method, we analyze E. coli chemotaxis measurements in an aspartate analog, and find evidence for a chemotactic bias in the tumble angles.
Samarium hexaboride
(2018)
Gamma-ray astronomy has proven to provide unique insights into cosmic-ray accelerators in the past few decades. By combining information at the highest photon energies with the entire electromagnetic spectrum in multi-wavelength studies, detailed knowledge of non-thermal particle populations in astronomical objects and systems has been gained: Many individual classes of gamma-ray sources could be identified inside our galaxy and outside of it. Different sources were found to exhibit a wide range of temporal evolution, ranging from seconds to stable behaviours over many years of observations. With the dawn of both neutrino- and gravitational wave astronomy, additional messengers have come into play over the last years. This development presents the advent of multi-messenger astronomy: a novel approach not only to search for sources of cosmic rays, but for astronomy in general.
In this thesis, both traditional multi-wavelength studies and multi-messenger studies will be presented. They were carried out with the H.E.S.S. experiment, an imaging air Cherenkov telescope array located in the Khomas Highland of Namibia. H.E.S.S. has entered its second phase in 2012 with the addition of a large, fifth telescope. While the initial array was limited to the study of gamma-rays with energies above 100 GeV, the new instrument allows to access gamma-rays with energies down to a few tens of GeV. Strengths of the multi-wavelength approach will be demonstrated at the example of the galaxy NGC253, which is undergoing an episode of enhanced star-formation. The gamma-ray emission will be discussed in light of all the information on this system available from radio, infrared and X-rays. These wavelengths reveal detailed information on the population of supernova remnants, which are suspected cosmic-ray accelerators. A broad-band gamma-ray spectrum is derived from H.E.S.S. and Fermi-LAT data. The improved analysis of H.E.S.S. data provides a measurement which is no longer dominated by systematic uncertainties. The long-term behaviour of cosmic rays in the starburst galaxy NGC253 is finally characterised.
In contrast to the long time-scale evolution of a starburst galaxy, multi-messenger studies are especially intriguing when shorter time-scales are being probed. A prime example of a short time-scale transient are Gamma Ray Bursts. The efforts to understand this phenomenon effectively founded the branch of gamma-ray astronomy. The multi-messenger approach allows for the study of illusive phenomena such as Gamma Ray Bursts and other transients using electromagnetic radiation, neutrinos, cosmic rays and gravitational waves contemporaneously. With contemporaneous observations getting more important just recently, the execution of such observation campaigns still presents a big challenge due to the different limitations and strengths of the infrastructures.
An alert system for transient phenomena has been developed over the course of this thesis for H.E.S.S. It aims to address many follow-up challenges in order to maximise the science return of the new large telescope, which is able to repoint much faster than the initial four telescopes. The system allows for fully automated observations based on scientific alerts from any wavelength or messenger and allows H.E.S.S. to participate in multi-messenger campaigns. Utilising this new system, many interesting multi-messenger observation campaigns have been performed. Several highlight observations with H.E.S.S. are analysed, presented and discussed in this work. Among them are observations of Gamma Ray Bursts with low latency and low energy threshold, the follow-up of a neutrino candidate in spatial coincidence with a flaring active galactic nucleus and of the merger of two neutron stars, which was revealed by the coincidence of gravitational waves and a Gamma-Ray Burst.
In this thesis we provide a construction of the operator framework starting from the functional formulation of group field theory (GFT). We define operator algebras on Hilbert spaces whose expectation values in specific states provide correlation functions of the functional formulation. Our construction allows us to give a direct relation between the ingredients of the functional GFT and its operator formulation in a perturbative regime. Using this construction we provide an example of GFT states that can not be formulated as states in a Fock space and lead to math- ematically inequivalent representations of the operator algebra. We show that such inequivalent representations can be grouped together by their symmetry properties and sometimes break the left translation symmetry of the GFT action. We interpret these groups of inequivalent representations as phases of GFT, similar to the classification of phases that we use in QFT’s on space-time.
The purpose of Probabilistic Seismic Hazard Assessment (PSHA) at a construction site is to provide the engineers with a probabilistic estimate of ground-motion level that could be equaled or exceeded at least once in the structure’s design lifetime. A certainty on the predicted ground-motion allows the engineers to confidently optimize structural design and mitigate the risk of extensive damage, or in worst case, a collapse. It is therefore in interest of engineering, insurance, disaster mitigation, and security of society at large, to reduce uncertainties in prediction of design ground-motion levels.
In this study, I am concerned with quantifying and reducing the prediction uncertainty of regression-based Ground-Motion Prediction Equations (GMPEs). Essentially, GMPEs are regressed best-fit formulae relating event, path, and site parameters (predictor variables) to observed ground-motion values at the site (prediction variable). GMPEs are characterized by a parametric median (μ) and a non-parametric variance (σ) of prediction. μ captures the known ground-motion physics i.e., scaling with earthquake rupture properties (event), attenuation with distance from source (region/path), and amplification due to local soil conditions (site); while σ quantifies the natural variability of data that eludes μ. In a broad sense, the GMPE prediction uncertainty is cumulative of 1) uncertainty on estimated regression coefficients (uncertainty on μ,σ_μ), and 2) the inherent natural randomness of data (σ). The extent of μ parametrization, the quantity, and quality of ground-motion data used in a regression, govern the size of its prediction uncertainty: σ_μ and σ.
In the first step, I present the impact of μ parametrization on the size of σ_μ and σ. Over-parametrization appears to increase the σ_μ, because of the large number of regression coefficients (in μ) to be estimated with insufficient data. Under-parametrization mitigates σ_μ, but the reduced explanatory strength of μ is reflected in inflated σ. For an optimally parametrized GMPE, a ~10% reduction in σ is attained by discarding the low-quality data from pan-European events with incorrect parametric values (of predictor variables).
In case of regions with scarce ground-motion recordings, without under-parametrization, the only way to mitigate σ_μ is to substitute long-term earthquake data at a location with short-term samples of data across several locations – the Ergodic Assumption. However, the price of ergodic assumption is an increased σ, due to the region-to-region and site-to-site differences in ground-motion physics. σ of an ergodic GMPE developed from generic ergodic dataset is much larger than that of non-ergodic GMPEs developed from region- and site-specific non-ergodic subsets - which were too sparse to produce their specific GMPEs. Fortunately, with the dramatic increase in recorded ground-motion data at several sites across Europe and Middle-East, I could quantify the region- and site-specific differences in ground-motion scaling and upgrade the GMPEs with 1) substantially more accurate region- and site-specific μ for sites in Italy and Turkey, and 2) significantly smaller prediction variance σ. The benefit of such enhancements to GMPEs is quite evident in my comparison of PSHA estimates from ergodic versus region- and site-specific GMPEs; where the differences in predicted design ground-motion levels, at several sites in Europe and Middle-Eastern regions, are as large as ~50%.
Resolving the ergodic assumption with mixed-effects regressions is feasible when the quantified region- and site-specific effects are physically meaningful, and the non-ergodic subsets (regions and sites) are defined a priori through expert knowledge. In absence of expert definitions, I demonstrate the potential of machine learning techniques in identifying efficient clusters of site-specific non-ergodic subsets, based on latent similarities in their ground-motion data. Clustered site-specific GMPEs bridge the gap between site-specific and fully ergodic GMPEs, with their partially non-ergodic μ and, σ ~15% smaller than the ergodic variance.
The methodological refinements to GMPE development produced in this study are applicable to new ground-motion datasets, to further enhance certainty of ground-motion prediction and thereby, seismic hazard assessment. Advanced statistical tools show great potential in improving the predictive capabilities of GMPEs, but the fundamental requirement remains: large quantity of high-quality ground-motion data from several sites for an extended time-period.