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Institute
- Institut für Physik und Astronomie (279) (remove)
Synchrotron-based angle-resolved time-of-flight electron spectroscopy for dynamics in dichalogenides
(2018)
Spectroscopy at the limit
(2018)
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).
Modeling and data analysis of large-scale atmosphere dynamics associated with extreme weather
(2018)
In the last decades the frequency and intensity of extreme weather events like heat waves and heavy rainfall have increased and are at least partly linked to global warming. These events can have a strong impact on agricultural and economic production and, thereby, on society. Thus, it is important to improve our understanding of the physical processes leading to those extreme events in order to provide accurate near-term and long-term forecasts. Thermodynamic drivers associated with global warming are well understood, but dynamical aspects of the atmosphere much less so. The dynamical aspects, while less important than the thermodynamic drivers in regards to large-scale and long-time averaged effects, play a critical role in the formation of extremes.
The overall aim of this thesis is to improve our understanding of patterns, variability and trends in the global atmospheric circulation under a changing climate. In particular, in this dissertation I developed two new data-driven methods to quantitatively describe the dynamics of jet streams, Hadley cells and storm tracks. In addition, I introduce and validate a new statistical-dynamical atmosphere model that can be used to efficiently model the large-scale circulation.
First, I developed a scheme based on the Dijkstra ‘shortest-path’ algorithm to identify jet stream cores. Using reanalysis data, I found a significant change in jet stream strength and position over the last decades: Specifically, a decrease in wind speeds and a spatial shift toward the poles. This work also shows that the splitting or merging of the polar front jet stream and the subtropical jet stream depends on the season and longitudinal position. In a follow-up study, I analyzed trends in the latitudinal position of the poleward edge of the Hadley cell and subtropical jet stream core for all longitudes. These trends depend strongly on longitude and thus the impacts of tropical expansion might be pronounced in some regions and absent in others.
The second approach was to develop an empirical forecast method for European and Mediterranean winter precipitation. This prediction algorithm innovatively incorporates the spatial patterns of predictors in autumn using clustering analyses. I identified the most important precursors (snow cover in Eurasia, Barents and Kara sea ice concentrations as well as sea surface temperature in the Atlantic and Mediterranean region) for the precipitation prediction. This forecast algorithm had higher forecast skills than conventionally employed methods such as Canonical Correlation Analysis or operational systems using climate models.
The last approach was to examine the atmospheric circulation using the novel statisticaldynamical atmosphere model Aeolus. First, I validated the model’s depiction of the largescale circulation in terms of Hadley circulation, jet streams, storm tracks and planetary waves. To do so, I performed a parameter optimization using simulated annealing. Next, I investigated the sensitivity of the large-scale circulation to three different temperature components: global mean temperature, meridional temperature gradient and zonal temperature gradient. The model experiment showed that the strength of the Hadley cell, storm tracks and jet streams depend almost linearly on both the global mean temperature and the meridional temperature gradient, whereas the zonal temperature gradient is shown to have little or no influence. The magnitude of planetary waves is clearly affected by all three temperature components. Finally, the width of the Hadley cell behaves nonlinearly with respect to all three temperature components.
These findings might have profound consequences for climate modeling of the Mediterranean region. The latitudinal poleward trend of the Hadley cell edge position might become stronger under climate change according to the results with Aeolus. These changes would lead to a substantial reduction of the winter precipitation in the Mediterranean region. In this case seasonal empirical forecast methods, like the clustering-based prediction scheme, will play an important role for forecasting seasonal droughts in advance such that water managers and politicians can mitigate impacts.
A considerable number of systems have recently been reported in which
Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential(Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.
Recent advances in single particle tracking and supercomputing techniques demonstrate the emergence of normal or anomalous, viscoelastic diffusion in conjunction with non-Gaussian distributions in soft, biological, and active matter systems. We here formulate a stochastic model based on a generalised Langevin equation in which non-Gaussian shapes of the probability density function and normal or anomalous diffusion have a common origin, namely a random parametrisation of the stochastic force. We perform a detailed analysis demonstrating how various types of parameter distributions for the memory kernel result in exponential, power law, or power-log law tails of the memory functions. The studied system is also shown to exhibit a further unusual property: the velocity has a Gaussian one point probability density but non-Gaussian joint distributions. This behaviour is reflected in the relaxation from a Gaussian to a non-Gaussian distribution observed for the position variable. We show that our theoretical results are in excellent agreement with stochastic simulations.