530 Physik
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Institute
- Institut für Physik und Astronomie (254)
- Extern (26)
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- Potsdam Institute for Climate Impact Research (PIK) e. V. (1)
Laser induced switching offers an attractive possibility to manipulate small magnetic domains for prospective memory and logic devices on ultrashort time scales. Moreover, optical control of magnetization without high applied magnetic fields allows manipulation of magnetic domains individually and locally, without expensive heat dissipation. One of the major challenges for developing novel optically controlled magnetic memory and logic devices is reliable formation and annihilation of non-volatile magnetic domains that can serve as memory bits in ambient conditions. Magnetic skyrmions, topologically nontrivial spin textures, have been studied intensively since their discovery due to their stability and scalability in potential spintronic devices. However, skyrmion formation and, especially, annihilation processes are still not completely understood and further investigation on such mechanisms are needed. The aim of this thesis is to contribute to better understanding of the physical processes behind the optical control of magnetism in thin films, with the goal of optimizing material parameters and methods for their potential use in next generation memory and logic devices.
First part of the thesis is dedicated to investigation of all-optical helicity-dependent switching (AO-HDS) as a method for magnetization manipulation. AO-HDS in Co/Pt multilayer and CoFeB alloys with and without the presence of Dzyaloshinskii-Moriya interaction (DMI), which is a type of exchange interaction, have been investigated by magnetic imaging using photo-emission electron microscopy (PEEM) in combination with X-ray magnetic circular dichroism (XMCD). The results show that in a narrow range of the laser fluence, circularly polarized laser light induces a drag on domain walls. This enables a local deterministic transformation of the magnetic domain pattern from stripes to bubbles in out-of-plane magnetized Co/Pt multilayers, only controlled by the helicity of ultrashort laser pulses. The temperature and characteristic fields at which the stripe-bubble transformation occurs has been calculated using theory for isolated magnetic bubbles, using as parameters experimentally determined average size of stripe domains and the magnetic layer thickness.
The second part of the work aims at purely optical formation and annihilation of magnetic skyrmions by a single laser pulse. The presence of a skyrmion phase in the investigated CoFeB alloys was first confirmed using a Kerr microscope. Then the helicity-dependent skyrmion manipulation was studied using AO-HDS at different laser fluences. It was found that formation or annihilation individual skyrmions using AO-HDS is possible, but not always reliable, as fluctuations in the laser fluence or position can easily overwrite the helicity-dependent effect of AO-HDS. However, the experimental results and magnetic simulations showed that the threshold values for the laser fluence for the formation and annihilation of skyrmions are different. A higher fluence is required for skyrmion formation, and existing skyrmions can be annihilated by pulses with a slightly lower fluence. This provides a further option for controlling formation and annihilation of skyrmions using the laser fluence. Micromagnetic simulations provide additional insights into the formation and annihilation mechanism.
The ability to manipulate the magnetic state of individual skyrmions is of fundamental importance for magnetic data storage technologies. Our results show for the first time that the optical formation and annihilation of skyrmions is possible without changing the external field. These results enable further investigations to optimise the magnetic layer to maximise the energy gap between the formation and annihilation barrier. As a result, unwanted switching due to small laser fluctuations can be avoided and fully deterministic optical switching can be achieved.
Arctic climate change is marked by intensified warming compared to global trends and a significant reduction in Arctic sea ice which can intricately influence mid-latitude atmospheric circulation through tropo- and stratospheric pathways. Achieving accurate simulations of current and future climate demands a realistic representation of Arctic climate processes in numerical climate models, which remains challenging.
Model deficiencies in replicating observed Arctic climate processes often arise due to inadequacies in representing turbulent boundary layer interactions that determine the interactions between the atmosphere, sea ice, and ocean. Many current climate models rely on parameterizations developed for mid-latitude conditions to handle Arctic turbulent boundary layer processes.
This thesis focuses on modified representation of the Arctic atmospheric processes and understanding their resulting impact on large-scale mid-latitude atmospheric circulation within climate models. The improved turbulence parameterizations, recently developed based on Arctic measurements, were implemented in the global atmospheric circulation model ECHAM6. This involved modifying the stability functions over sea ice and ocean for stable stratification and changing the roughness length over sea ice for all stratification conditions. Comprehensive analyses are conducted to assess the impacts of these modifications on ECHAM6's simulations of the Arctic boundary layer, overall atmospheric circulation, and the dynamical pathways between the Arctic and mid-latitudes.
Through a step-wise implementation of the mentioned parameterizations into ECHAM6, a series of sensitivity experiments revealed that the combined impacts of the reduced roughness length and the modified stability functions are non-linear. Nevertheless, it is evident that both modifications consistently lead to a general decrease in the heat transfer coefficient, being in close agreement with the observations.
Additionally, compared to the reference observations, the ECHAM6 model falls short in accurately representing unstable and strongly stable conditions.
The less frequent occurrence of strong stability restricts the influence of the modified stability functions by reducing the affected sample size. However, when focusing solely on the specific instances of a strongly stable atmosphere, the sensible heat flux approaches near-zero values, which is in line with the observations. Models employing commonly used surface turbulence parameterizations were shown to have difficulties replicating the near-zero sensible heat flux in strongly stable stratification.
I also found that these limited changes in surface layer turbulence parameterizations have a statistically significant impact on the temperature and wind patterns across multiple pressure levels, including the stratosphere, in both the Arctic and mid-latitudes. These significant signals vary in strength, extent, and direction depending on the specific month or year, indicating a strong reliance on the background state.
Furthermore, this research investigates how the modified surface turbulence parameterizations may influence the response of both stratospheric and tropospheric circulation to Arctic sea ice loss.
The most suitable parameterizations for accurately representing Arctic boundary layer turbulence were identified from the sensitivity experiments. Subsequently, the model's response to sea ice loss is evaluated through extended ECHAM6 simulations with different prescribed sea ice conditions.
The simulation with adjusted surface turbulence parameterizations better reproduced the observed Arctic tropospheric warming in vertical extent, demonstrating improved alignment with the reanalysis data. Additionally, unlike the control experiments, this simulation successfully reproduced specific circulation patterns linked to the stratospheric pathway for Arctic-mid-latitude linkages. Specifically, an increased occurrence of the Scandinavian-Ural blocking regime (negative phase of the North Atlantic Oscillation) in early (late) winter is observed. Overall, it can be inferred that improving turbulence parameterizations at the surface layer can improve the ECHAM6's response to sea ice loss.
Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments
(2024)
The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics.
The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources.
The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments.
The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions.
Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics.
In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.
The mobile-immobile model (MIM) has been established in geoscience in the context of contaminant transport in groundwater. Here the tracer particles effectively immobilise, e.g., due to diffusion into dead-end pores or sorption. The main idea of the MIM is to split the total particle density into a mobile and an immobile density. Individual tracers switch between the mobile and immobile state following a two-state telegraph process, i.e., the residence times in each state are distributed exponentially. In geoscience the focus lies on the breakthrough curve (BTC), which is the concentration at a fixed location over time. We apply the MIM to biological experiments with a special focus on anomalous scaling regimes of the mean squared displacement (MSD) and non-Gaussian displacement distributions. As an exemplary system, we have analysed the motion of tau proteins, that diffuse freely inside axons of neurons. Their free diffusion thereby corresponds to the mobile state of the MIM. Tau proteins stochastically bind to microtubules, which effectively immobilises the tau proteins until they unbind and continue diffusing. Long immobilisation durations compared to the mobile durations give rise to distinct non-Gaussian Laplace shaped distributions. It is accompanied by a plateau in the MSD for initially mobile tracer particles at relevant intermediate timescales. An equilibrium fraction of initially mobile tracers gives rise to non-Gaussian displacements at intermediate timescales, while the MSD remains linear at all times. In another setting bio molecules diffuse in a biosensor and transiently bind to specific receptors, where advection becomes relevant in the mobile state. The plateau in the MSD observed for the advection-free setting and long immobilisation durations persists also for the case with advection. We find a new clear regime of anomalous diffusion with non-Gaussian distributions and a cubic scaling of the MSD. This regime emerges for initially mobile and for initially immobile tracers. For an equilibrium fraction of initially mobile tracers we observe an intermittent ballistic scaling of the MSD. The long-time effective diffusion coefficient is enhanced by advection, which we physically explain with the variance of mobile durations. Finally, we generalize the MIM to incorporate arbitrary immobilisation time distributions and focus on a Mittag-Leffler immobilisation time distribution with power-law tail ~ t^(-1-mu) with 0<mu<1 and diverging mean immobilisation durations. A fit of our model to the BTC of experimental data from tracer particles in aquifers matches the BTC including the power-law tail. We use the fit parameters for plotting the displacement distributions and the MSD. We find Gaussian normal diffusion at short times and long-time power-law decay of mobile mass accompanied by anomalous diffusion at long times. The long-time diffusion is subdiffusive in the advection-free setting, while it is either subdiffusive for 0<mu<1/2 or superdiffusive for 1/2<mu<1 when advection is present. In the long-time limit we show equivalence of our model to a bi-fractional diffusion equation.
The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt.
The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm.
Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas.
For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season.
Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
Additive manufacturing (AM) processes enable the production of metal structures with exceptional design freedom, of which laser powder bed fusion (PBF-LB) is one of the most common. In this process, a laser melts a bed of loose feedstock powder particles layer-by-layer to build a structure with the desired geometry. During fabrication, the repeated melting and rapid, directional solidification create large temperature gradients that generate large thermal stress. This thermal stress can itself lead to cracking or delamination during fabrication. More often, large residual stresses remain in the final part as a footprint of the thermal stress. This residual stress can cause premature distortion or even failure of the part in service. Hence, knowledge of the residual stress field is critical for both process optimization and structural integrity.
Diffraction-based techniques allow the non-destructive characterization of the residual stress fields. However, such methods require a good knowledge of the material of interest, as certain assumptions must be made to accurately determine residual stress. First, the measured lattice plane spacings must be converted to lattice strains with the knowledge of a strain-free material state. Second, the measured lattice strains must be related to the macroscopic stress using Hooke's law, which requires knowledge of the stiffness of the material. Since most crystal structures exhibit anisotropic material behavior, the elastic behavior is specific to each lattice plane of the single crystal. Thus, the use of individual lattice planes in monochromatic diffraction residual stress analysis requires knowledge of the lattice plane-specific elastic properties. In addition, knowledge of the microstructure of the material is required for a reliable assessment of residual stress.
This work presents a toolbox for reliable diffraction-based residual stress analysis. This is presented for a nickel-based superalloy produced by PBF-LB. First, this work reviews the existing literature in the field of residual stress analysis of laser-based AM using diffraction-based techniques. Second, the elastic and plastic anisotropy of the nickel-based superalloy Inconel 718 produced by PBF-LB is studied using in situ energy dispersive synchrotron X-ray and neutron diffraction techniques. These experiments are complemented by ex situ material characterization techniques. These methods establish the relationship between the microstructure and texture of the material and its elastic and plastic anisotropy. Finally, surface, sub-surface, and bulk residual stress are determined using a texture-based approach. Uncertainties of different methods for obtaining stress-free reference values are discussed.
The tensile behavior in the as-built condition is shown to be controlled by texture and cellular sub-grain structure, while in the heat-treated condition the precipitation of strengthening phases and grain morphology dictate the behavior. In fact, the results of this thesis show that the diffraction elastic constants depend on the underlying microstructure, including texture and grain morphology. For columnar microstructures in both as-built and heat-treated conditions, the diffraction elastic constants are best described by the Reuss iso-stress model. Furthermore, the low accumulation of intergranular strains during deformation demonstrates the robustness of using the 311 reflection for the diffraction-based residual stress analysis with columnar textured microstructures. The differences between texture-based and quasi-isotropic approaches for the residual stress analysis are shown to be insignificant in the observed case. However, the analysis of the sub-surface residual stress distributions show, that different scanning strategies result in a change in the orientation of the residual stress tensor. Furthermore, the location of the critical sub-surface tensile residual stress is related to the surface roughness and the microstructure. Finally, recommendations are given for the diffraction-based determination and evaluation of residual stress in textured additively manufactured alloys.
The origin and structure of magnetic fields in the Galaxy are largely unknown. What is known is that they are essential for several astrophysical processes, in particular the propagation of cosmic rays. Our ability to describe the propagation of cosmic rays through the Galaxy is severely limited by the lack of observational data needed to probe the structure of the Galactic magnetic field on many different length scales. This is particularly true for modelling the propagation of cosmic rays into the Galactic halo, where our knowledge of the magnetic field is particularly poor.
In the last decade, observations of the Galactic halo in different frequency regimes have revealed the existence of out-of-plane bubble emission in the Galactic halo. In gamma rays these bubbles have been termed Fermi bubbles with a radial extent of ≈ 3 kpc and an azimuthal height of ≈ 6 kpc. The radio counterparts of the Fermi bubbles were seen by both the S-PASS telescopes and the Planck satellite, and showed a clear spatial overlap. The X-ray counterparts of the Fermi bubbles were named eROSITA bubbles after the eROSITA satellite, with a radial width of ≈ 7 kpc and an azimuthal height of ≈ 14 kpc. Taken together, these observations suggest the presence of large extended Galactic Halo Bubbles (GHB) and have stimulated interest in exploring the less explored Galactic halo.
In this thesis, a new toy model (GHB model) for the magnetic field and non-thermal electron distribution in the Galactic halo has been proposed. The new toy model has been used to produce polarised synchrotron emission sky maps. Chi-square analysis was used to compare the synthetic skymaps with the Planck 30 GHz polarised skymaps. The obtained constraints on the strength and azimuthal height were found to be in agreement with the S-PASS radio observations.
The upper, lower and best-fit values obtained from the above chi-squared analysis were used to generate three separate toy models. These three models were used to propagate ultra-high energy cosmic rays. This study was carried out for two potential sources, Centaurus A and NGC 253, to produce magnification maps and arrival direction skymaps. The simulated arrival direction skymaps were found to be consistent with the hotspots of Centaurus A and NGC 253 as seen in the observed arrival direction skymaps provided by the Pierre Auger Observatory (PAO).
The turbulent magnetic field component of the GHB model was also used to investigate the extragalactic dipole suppression seen by PAO. UHECRs with an extragalactic dipole were forward-tracked through the turbulent GHB model at different field strengths. The suppression in the dipole due to the varying diffusion coefficient from the simulations was noted. The results could also be compared with an analytical analogy of electrostatics. The simulations of the extragalactic dipole suppression were in agreement with similar studies carried out for galactic cosmic rays.
Organic solar cells (OSCs) represent a new generation of solar cells with a range of captivating attributes including low-cost, light-weight, aesthetically pleasing appearance, and flexibility. Different from traditional silicon solar cells, the photon-electron conversion in OSCs is usually accomplished in an active layer formed by blending two kinds of organic molecules (donor and acceptor) with different energy levels together.
The first part of this thesis focuses on a better understanding of the role of the energetic offset and each recombination channel on the performance of these low-offset OSCs. By combining advanced experimental techniques with optical and electrical simulation, the energetic offsets between CT and excitons, several important insights were achieved: 1. The short circuit current density and fill-factor of low-offset systems are largely determined by field-dependent charge generation in such low-offset OSCs. Interestingly, it is strongly evident that such field-dependent charge generation originates from a field-dependent exciton dissociation yield. 2. The reduced energetic offset was found to be accompanied by strongly enhanced bimolecular recombination coefficient, which cannot be explained solely by exciton repopulation from CT states. This implies the existence of another dark decay channel apart from CT.
The second focus of the thesis was on the technical perspective. In this thesis, the influence of optical artifacts in differential absorption spectroscopy upon the change of sample configuration and active layer thickness was studied. It is exemplified and discussed thoroughly and systematically in terms of optical simulations and experiments, how optical artifacts originated from non-uniform carrier profile and interference can manipulate not only the measured spectra, but also the decay dynamics in various measurement conditions. In the end of this study, a generalized methodology based on an inverse optical transfer matrix formalism was provided to correct the spectra and decay dynamics manipulated by optical artifacts.
Overall, this thesis paves the way for a deeper understanding of the keys toward higher PCEs in low-offset OSC devices, from the perspectives of both device physics and characterization techniques.
Supernova remnants are considered to be the primary sources of galactic cosmic rays. These cosmic rays are assumed to be accelerated by the diffusive shock acceleration mechanism, specifically at shocks in the remnants. Particularly in the core-collapse scenario, these supernova remnant shocks expand inside the wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, the complex environment of wind bubbles can influence the particle acceleration and radiation from the remnants. Further, the evolution of massive stars depends on their Zero Age Main Sequence mass, rotation, and metallicity. Consequently, the structures of the wind bubbles generated during the lifetime of massive stars should be considerably different. Hence, the particle acceleration in the core-collapse supernova remnants should vary, not only from the remnants evolving in the uniform environment but also from one another, depending on their progenitor stars.
A core-collapse supernova remnant with a very massive 60 𝑀 ⊙ progenitor star has been considered to study the particle acceleration at the shock considering Bohm-like diffusion. This dissertation demonstrates the modification in particle acceleration and radiation while the remnant propagates through different regions of the wind bubble by impacts from the profiles of gas density, the temperature of the bubble and the magnetic field structure. Subsequently, in this thesis, I discuss the impacts of the non-identical ambient environment of core-collapse supernova remnants on particle spectra and the non-thermal emissions, considering 20 𝑀 ⊙ and 60 𝑀⊙ massive progenitors having different evolutionary tracks. Additionally, I also analyse the effect of cosmic ray streaming instabilities on particle spectra.
To model the particle acceleration in the remnants, I have performed simulations in one-dimensional spherical symmetry using RATPaC code. The transport equation for cosmic rays and magnetic turbulence in test-particle approximation, along with the induction equation for the evolution of the large-scale magnetic field, have been solved simultaneously with the hydrodynamic equations for the expansion of remnants inside the pre-supernova circumstellar medium.
The results from simulations describe that the spectra of accelerated particles in supernova remnants are regulated by density fluctuations, temperature variations, the large-scale magnetic field configuration and scattering turbulence. Although the diffusive shock acceleration mechanism at supernova remnant shock predicts the spectral index of 2 for the accelerated non-thermal particles, I have obtained the particle spectra that deviate from this prediction, in the core-collapse scenario. I have found that the particle spectral index reaches 2.5 for the supernova remnant with 60 𝑀 ⊙ progenitor when the remnant resides inside the shocked wind region of the wind bubble, and this softness persists at later evolutionary stages even with Bohm-like diffusion for accelerated particles. However, the supernova remnant with 20 𝑀 ⊙ progenitor does not demonstrate persistent softness in particle spectra from the influence of the hydrodynamics of the corresponding wind bubble. At later stages of evolution, the particle spectra illustrate softness at higher energies for both remnants as the consequence of the escape of high-energy particles from the remnants while considering the cosmic ray streaming instabilities. Finally, I have probed the emission morphology of remnants that varies depending on the progenitors, particularly in earlier evolutionary stages. This dissertation provides insight into different core-collapse remnants expanding inside wind bubbles, for instance, the calculated gamma-ray spectral index from the supernova remnant with 60 𝑀 ⊙ progenitor at later evolutionary stages is consistent with that of the observed supernova remnants expanding in dense molecular clouds.
The Lyman-𝛼 (Ly𝛼) line commonly assists in the detection of high-redshift galaxies, the so-called Lyman-alpha emitters (LAEs). LAEs are useful tools to study the baryonic matter distribution of the high-redshift universe. Exploring their spatial distribution not only reveals the large-scale structure of the universe at early epochs, but it also provides an insight into the early formation and evolution of the galaxies we observe today. Because dark matter halos (DMHs) serve as sites of galaxy formation, the LAE distribution also traces that of the underlying dark matter. However, the details of this relation and their co-evolution over time remain unclear. Moreover, theoretical studies predict that the spatial distribution of LAEs also impacts their own circumgalactic medium (CGM) by influencing their extended Ly𝛼 gaseous halos (LAHs), whose origin is still under investigation. In this thesis, I make several contributions to improve the knowledge on these fields using samples of LAEs observed with the Multi Unit Spectroscopic Explorer (MUSE) at redshifts of 3 < 𝑧 < 6.
The near-Earth space environment is a highly complex system comprised of several regions and particle populations hazardous to satellite operations. The trapped particles in the radiation belts and ring current can cause significant damage to satellites during space weather events, due to deep dielectric and surface charging. Closer to Earth is another important region, the ionosphere, which delays the propagation of radio signals and can adversely affect navigation and positioning. In response to fluctuations in solar and geomagnetic activity, both the inner-magnetospheric and ionospheric populations can undergo drastic and sudden changes within minutes to hours, which creates a challenge for predicting their behavior. Given the increasing reliance of our society on satellite technology, improving our understanding and modeling of these populations is a matter of paramount importance.
In recent years, numerous spacecraft have been launched to study the dynamics of particle populations in the near-Earth space, transforming it into a data-rich environment. To extract valuable insights from the abundance of available observations, it is crucial to employ advanced modeling techniques, and machine learning methods are among the most powerful approaches available. This dissertation employs long-term satellite observations to analyze the processes that drive particle dynamics, and builds interdisciplinary links between space physics and machine learning by developing new state-of-the-art models of the inner-magnetospheric and ionospheric particle dynamics.
The first aim of this thesis is to investigate the behavior of electrons in Earth's radiation belts and ring current. Using ~18 years of electron flux observations from the Global Positioning System (GPS), we developed the first machine learning model of hundreds-of-keV electron flux at Medium Earth Orbit (MEO) that is driven solely by solar wind and geomagnetic indices and does not require auxiliary flux measurements as inputs. We then proceeded to analyze the directional distributions of electrons, and for the first time, used Fourier sine series to fit electron pitch angle distributions (PADs) in Earth's inner magnetosphere. We performed a superposed epoch analysis of 129 geomagnetic storms during the Van Allen Probes era and demonstrated that electron PADs have a strong energy-dependent response to geomagnetic activity. Additionally, we showed that the solar wind dynamic pressure could be used as a good predictor of the PAD dynamics. Using the observed dependencies, we created the first PAD model with a continuous dependence on L, magnetic local time (MLT) and activity, and developed two techniques to reconstruct near-equatorial electron flux observations from low-PA data using this model.
The second objective of this thesis is to develop a novel model of the topside ionosphere. To achieve this goal, we collected observations from five of the most widely used ionospheric missions and intercalibrated these data sets. This allowed us to use these data jointly for model development, validation, and comparison with other existing empirical models. We demonstrated, for the first time, that ion density observations by Swarm Langmuir Probes exhibit overestimation (up to ~40-50%) at low and mid-latitudes on the night side, and suggested that the influence of light ions could be a potential cause of this overestimation. To develop the topside model, we used 19 years of radio occultation (RO) electron density profiles, which were fitted with a Chapman function with a linear dependence of scale height on altitude. This approximation yields 4 parameters, namely the peak density and height of the F2-layer and the slope and intercept of the linear scale height trend, which were modeled using feedforward neural networks (NNs). The model was extensively validated against both RO and in-situ observations and was found to outperform the International Reference Ionosphere (IRI) model by up to an order of magnitude. Our analysis showed that the most substantial deviations of the IRI model from the data occur at altitudes of 100-200 km above the F2-layer peak. The developed NN-based ionospheric model reproduces the effects of various physical mechanisms observed in the topside ionosphere and provides highly accurate electron density predictions.
This dissertation provides an extensive study of geospace dynamics, and the main results of this work contribute to the improvement of models of plasma populations in the near-Earth space environment.
This thesis discusses heat and charge transport phenomena in single-crystalline Silicon penetrated by nanometer-sized pores, known as mesoporous Silicon (pSi). Despite the extensive attention given to it as a thermoelectric material of interest, studies on microscopic thermal and electronic transport beyond its macroscopic characterizations are rarely reported. In contrast, this work reports the interplay of both.
PSi samples synthesized by electrochemical anodization display a temperature dependence of specific heat 𝐶𝑝 that deviates from the characteristic 𝑇^3 behaviour (at 𝑇<50𝐾). A thorough analysis reveals that both 3D and 2D Einstein and Debye modes contribute to this specific heat. Additional 2D Einstein modes (~3 𝑚𝑒𝑉) agree reasonably well with the boson peak of SiO2 in pSi pore walls. 2D Debye modes are proposed to account for surface acoustic modes causing a significant deviation from the well-known 𝑇^3 dependence of 𝐶𝑝 at 𝑇<50𝐾.
A novel theoretical model gives insights into the thermal conductivity of pSi in terms of porosity and phonon scattering on the nanoscale. The thermal conductivity analysis utilizes the peculiarities of the pSi phonon dispersion probed by the inelastic neutron scattering experiments. A phonon mean-free path of around 10 𝑛𝑚 extracted from the presented model is proposed to cause the reduced thermal conductivity of pSi by two orders of magnitude compared to p-doped bulk Silicon. Detailed analysis indicates that compound averaging may cause a further 10-50% reduction. The percolation threshold of 65% for thermal conductivity of pSi samples is subsequently determined by employing theoretical effective medium models.
Temperature-dependent electrical conductivity measurements reveal a thermally activated transport process. A detailed analysis of the activation energy 𝐸𝐴𝜎 in the thermally activated transport exhibits a Meyer Neldel compensation rule between different samples that originates in multi-phonon absorption upon carrier transport. Activation energies 𝐸𝐴𝑆 obtained from temperature-dependent thermopower measurements provide further evidence for multi-phonon assisted hopping between localized states as a dominant charge transport mechanism in pSi, as they systematically differ from the determined 𝐸𝐴𝜎 values.
Control over spin and electronic structure of MoS₂ monolayer via interactions with substrates
(2023)
The molybdenum disulfide (MoS2) monolayer is a semiconductor with a direct bandgap while it is a robust and affordable material.
It is a candidate for applications in optoelectronics and field-effect transistors.
MoS2 features a strong spin-orbit coupling which makes its spin structure promising for acquiring the Kane-Mele topological concept with corresponding applications in spintronics and valleytronics.
From the optical point of view, the MoS2 monolayer features two valleys in the regions of K and K' points. These valleys are differentiated by opposite spins and a related valley-selective circular dichroism.
In this study we aim to manipulate the MoS2 monolayer spin structure in the vicinity of the K and K' points to explore the possibility of getting control over the optical and electronic properties.
We focus on two different substrates to demonstrate two distinct routes: a gold substrate to introduce a Rashba effect and a graphene/cobalt substrate to introduce a magnetic proximity effect in MoS2.
The Rashba effect is proportional to the out-of-plane projection of the electric field gradient. Such a strong change of the electric field occurs at the surfaces of a high atomic number materials and effectively influence conduction electrons as an in-plane magnetic field. A molybdenum and a sulfur are relatively light atoms, thus, similar to many other 2D materials, intrinsic Rashba effect in MoS2 monolayer is vanishing small. However, proximity of a high atomic number substrate may enhance Rashba effect in a 2D material as it was demonstrated for graphene previously.
Another way to modify the spin structure is to apply an external magnetic field of high magnitude (several Tesla), and cause a Zeeman splitting, the conduction electrons.
However, a similar effect can be reached via magnetic proximity which allows us to reduce external magnetic fields significantly or even to zero. The graphene on cobalt interface is ferromagnetic and stable for MoS2 monolayer synthesis. Cobalt is not the strongest magnet; therefore, stronger magnets may lead to more significant results.
Nowadays most experimental studies on the dichalcogenides (MoS2 included) are performed on encapsulated heterostructures that are produced by mechanical exfoliation.
While mechanical exfoliation (or scotch-tape method) allows to produce a huge variety of structures, the shape and the size of the samples as well as distance between layers in heterostructures are impossible to control reproducibly.
In our study we used molecular beam epitaxy (MBE) methods to synthesise both MoS2/Au(111) and MoS2/graphene/Co systems.
We chose to use MBE, as it is a scalable and reproducible approach, so later industry may adapt it and take over.
We used graphene/cobalt instead of just a cobalt substrate because direct contact of MoS2\ monolayer and a metallic substrate may lead to photoluminescence (PL) quenching in the metallic substrate. Graphene and hexagonal boron nitride monolayer are considered building blocks of a new generation of electronics also commonly used as encapsulating materials for PL studies. Moreover graphene is proved to be a suitable substrate for the MBE growth of transitional metal dichalcogenides (TMDCs).
In chapter 1,
we start with an introduction to TMDCs. Then we focus on MoS2 monolayer state of the art research in the fields of application scenario; synthesis approaches; electronic, spin, and optical properties; and interactions with magnetic fields and magnetic materials.
We briefly touch the basics of magnetism in solids and move on to discuss various magnetic exchange interactions and magnetic proximity effect.
Then we describe MoS2 optical properties in more detail. We start from basic exciton physics and its manifestation in the MoS2 monolayer. We consider optical selection rules in the MoS2 monolayer and such properties as chirality, spin-valley locking, and coexistence of bright and dark excitons.
Chapter 2 contains an overview of the employed surface science methods: angle-integrated, angle-resolved, and spin-resolved photoemission; low energy electron diffraction and scanning tunneling microscopy.
In chapter 3, we describe MoS2 monolayer synthesis details for two substrates: gold monocrystal with (111) surface and graphene on cobalt thin film with Co(111) surface orientation.
The synthesis descriptions are followed by a detailed characterisation of the obtained structures: fingerprints of MoS2 monolayer formation; MoS2 monolayer symmetry and its relation to the substrate below; characterisation of MoS2 monolayer coverage, domain distribution, sizes and shapes, and moire structures.
In chapter~4, we start our discussion with MoS2/Au(111) electronic and spin structure. Combining density functional theory computations (DFT) and spin-resolved photoemission studies, we demonstrate that the MoS2 monolayer band structure features an in-plane Rashba spin splitting. This confirms the possibility of MoS2 monolayer spin structure manipulation via a substrate.
Then we investigate the influence of a magnetic proximity in the MoS2/graphene/Co system on the MoS2 monolayer spin structure.
We focus our investigation on MoS2 high symmetry points: G and K.
First, using spin-resolved measurements, we confirm that electronic states are spin-split at the G point via a magnetic proximity effect. Second, combining spin-resolved measurements and DFT computations for MoS2 monolayer in the K point region, we demonstrate the appearance of a small in-plane spin polarisation in the valence band top and predict a full in-plane spin polarisation for the conduction band bottom.
We move forward discussing how these findings are related to the MoS2 monolayer optical properties, in particular the possibility of dark exciton observation. Additionally, we speculate on the control of the MoS2 valley energy via magnetic proximity from cobalt.
As graphene is spatially buffering the MoS2 monolayer from the Co thin film, we speculate on the role of graphene in the magnetic proximity transfer by replacing graphene with vacuum and other 2D materials in our computations.
We finish our discussion by investigating the K-doped MoS2/graphene/Co system and the influence of this doping on the electronic and spin structure as well as on the magnetic proximity effect.
In summary, using a scalable MBE approach we synthesised
MoS2/Au(111) and MoS2/graphene/Co systems. We found a Rashba effect taking place in MoS2/Au(111) which proves that the MoS2 monolayer in-plane spin structure can be modified. In MoS2/graphene/Co the in-plane magnetic proximity effect indeed takes place which rises the possibility of fine tuning the MoS2 optical properties via manipulation of the the substrate magnetisation.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
The Antarctic ice sheet is the largest freshwater reservoir worldwide. If it were to melt completely, global sea levels would rise by about 58 m. Calculation of projections of the Antarctic contribution to sea level rise under global warming conditions is an ongoing effort which
yields large ranges in predictions. Among the reasons for this are uncertainties related to the physics of ice sheet modeling. These
uncertainties include two processes that could lead to runaway ice retreat: the Marine Ice Sheet Instability (MISI), which causes rapid grounding line retreat on retrograde bedrock, and the Marine Ice Cliff Instability (MICI), in which tall ice cliffs become unstable and calve off, exposing even taller ice cliffs.
In my thesis, I investigated both marine instabilities (MISI and MICI) using the Parallel Ice Sheet Model (PISM), with a focus on MICI.
Search for light primordial black holes with VERITAS using gamma γ-ray and optical observations
(2023)
The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is an array of four imaging atmospheric Cherenkov telescopes (IACTs). VERITAS is sensitive to very-high-energy gamma-rays in the range of 100 GeV to >30 TeV. Hypothesized primordial black holes (PBHs) are attractive targets for IACTs. If they exist, their potential cosmological impact reaches beyond the candidacy for constituents of dark matter. The sublunar mass window is the largest unconstrained range of PBH masses. This thesis aims to develop novel concepts searching for light PBHs with VERITAS. PBHs below the sublunar window lose mass due to Hawking radiation. They would evaporate at the end of their lifetime, leading to a short burst of gamma-rays. If PBHs formed at about 10^15 g, the evaporation would occur nowadays. Detecting these signals might not only confirm the existence of PBHs but also prove the theory of Hawking radiation. This thesis probes archival VERITAS data recorded between 2012 and 2021 for possible PBH signals. This work presents a new automatic approach to assess the quality of the VERITAS data. The array-trigger rate and far infrared temperature are well suited to identify periods with poor data quality. These are masked by time cuts to obtain a consistent and clean dataset which contains about 4222 hours. The PBH evaporations could occur at any location in the field of view or time within this data. Only a blind search can be performed to identify these short signals. This thesis implements a data-driven deep learning based method to search for short transient signals with VERITAS. It does not depend on the modelling of the effective area and radial acceptance. This work presents the first application of this method to actual observational IACT data. This thesis develops new concepts dealing with the specifics of the data and the transient detection method. These are reflected in the developed data preparation pipeline and search strategies. After correction for trial factors, no candidate PBH evaporation is found in the data. Thus, new constraints of the local rate of PBH evaporations are derived. At the 99% confidence limit it is below <1.07 * 10^5 pc^-3 yr^-1. This constraint with the new, independent analysis approach is in the range of existing limits for the evaporation rate.
This thesis also investigates an alternative novel approach to searching for PBHs with IACTs. Above the sublunar window, the PBH abundance is constrained by optical microlensing studies. The sampling speed, which is of order of minutes to hours for traditional optical telescopes, is a limiting factor in expanding the limits to lower masses. IACTs are also powerful instruments for fast transient optical astronomy with up to O(ns) sampling. This thesis investigates whether IACTs might constrain the sublunar window with optical microlensing observations. This study confirms that, in principle, the fast sampling speed might allow extending microlensing searches into the sublunar mass window. However, the limiting factor for IACTs is the modest sensitivity to detect changes in optical fluxes. This thesis presents the expected rate of detectable events for VERITAS as well as prospects of possible future next-generation IACTs. For VERITAS, the rate of detectable microlensing events in the sublunar range is ~10^-6 per year of observation time. The future prospects for a 100 times more sensitive instrument are at ~0.05 events per year.
The evolution of a galaxy is pivotally governed by its pattern of star formation over a given period of time. The star formation rate at any given time is strongly dependent on the amount of cold gas available in the galaxy. Accretion of pristine gas from the Intergalactic medium (IGM) is thought to be one of the primary sources for star-forming gas. This gas first passes through the virial regions of the galaxy before reaching the Interstellar medium (ISM), the hub of star formation. On the other hand, owing to the evolutionary course of young and massive stars, energetic winds are ejected from the ISM to the virial regions of the galaxy. A bunch of interlinked, complex astrophysical processes, arising from the concurrent presence of both infalling as well as outbound gas, play out over a range of timescales in the halo region or the Circumgalactic medium (CGM) of a galaxy. It would not be incorrect to say that the CGM has a stronghold over the gas reserves of a galaxy and thus, plays a backhand, yet, rather pivotal role in shaping many galactic properties, some of which are also readily observable. Observing the multi-phase CGM (via spectral-line ion measurements), however, remains a non-trivial effort even today. Low particle densities as well as the CGM’s vast spatial extent, coupled with likely deviations from a spherical distribution, marr the possibility of obtaining complete, unbiased, high-quality spectral information tracing the full extent of the gaseous halo. This often incomplete information leads to multiple inferences about the CGM properties that give rise to multiple contradicting models. In this regard, computer simulations offer a neat solution towards testing and, subsequently, falsifying many of these existing CGM models. Thanks to their controlled environments, simulations are able to not only effortlessly transcend several orders of magnitude in time and space, but also get around many of the observational limitations and provide some unique views on many CGM properties. In this thesis, I focus on effectively using different computer simulations to understand the role of CGM in various astrophysical contexts, namely, the effect of Local Group (LG) environment, major merger events and satellite galaxies. In Chapter 2, I discuss the approach used for modeling various phases of the simulated z = 0 LG CGM in Hestia constrained simulations. Each of the three realizations contain a Milky Way (MW)–Andromeda (M31) galaxy pair, along with their corresponding sets of satellite galaxies, all embedded within the larger cosmological context. For characterizing the different temperature–density phases within the CGM, I model five tracer ions with cloudy ionization modeling. The cold and cool–ionized CGM (H i and Si iii respectively) in Hestia is very clumpy and distributed close to the galactic centers, while the warm-hot and hot CGM (O vi, O vii and O viii) is tenuous and volume-filling. On comparing the H i and Si iii column densities for the simulated M31 with observational measurements from Project AMIGA survey and other low-z galaxies, I found that Hestia galaxies produced less gas in the outer CGM, unlike observations. My carefully designed observational bias model subsequently revealed the possibility that some MW gas clouds might be incorrectly associated with the M31 CGM in observations, and hence, may be partly responsible for giving rise to the detected mismatch between simulated data and observations. In Chapter 3, I present results from four zoom–in, major merger, gas–rich simulations and the subsequent role of the gas, originally situated in the CGM, in influencing some of the galactic observables. The progenitor parameters are selected such that the post–merger remnants are MW–mass galaxies. We generally see a very clear gas bridge joining the merging galaxies in case of multiple passage mergers while such a bridge is mostly absent when a direct collision occurs. On the basis of particle–to–galaxy distance computations and tracer particle analysis, I found that about 33–48 percent of the cold gas contributing to the merger–induced star formation in the bridge originated from the CGM regions. In Chapter 4, I used a sample of 234 MW-mass, L* galaxies from the TNG50 cosmological simulations, with an aim of characterizing the impact of their global satellite populations on the extended cold CGM properties of their host L* halos. On the basis of halo mass and number of satellite galaxies (N_sats ), I categorized the sample into low and high mass bins, and subsequently into bottom, inter and top quartiles respectively. After confirming that satellites indeed influence the extended cold halo gas density profiles of the host galaxies, I investigated the effects of different satellite population parameters on the host halo cold CGMs. My analysis showed that there is hardly any cold gas associated with the satellite population of the lowest mass halos. The stellar mass of the most massive satellite (M_*mms ) impacted the cold gas in low mass bin halos the most, while N_sats (followed by M_*mms ) was the most influential factor for the high mass halos. In any case, how easily cold gas was stripped off the most massive satellite did not play much role. The number of massive (Stellar mass, M* > 10^8 M_solar) satellites as well as the M_*mms associated with a galaxy are two of the most crucial parameters determining how much cold gas ultimately finds its way from the satellites to the host halo. Low mass galaxies are found rather lacking on both these fronts unlike their high mass counterparts. This work highlights some aspects of the complex gas physics that constitute the basic essence of a low-z CGM. My analysis proved the importance of a cosmological environment, local surroundings and merger history in defining some key observable properties of a galactic CGM. Furthermore, I found that different satellite properties were responsible for affecting the cold–dense CGM of the low and high-mass parent galaxies. Finally, the LG emerged as an exciting prospect for testing and pinning down several intricate details about the CGM.
The first part of the thesis studies the properties of fast mode in magneto hydro-dynamic (MHD) turbulence. 1D and 3D numerical simulations are carried out to generate decaying fast mode MHD turbulence. The injection of waves are carried out in a collinear and isotropic fashion to generate fast mode turbulence. The properties of fast mode turbulence are analyzed by studying their energy spectral density, 2D structure functions and energy decay/cascade time. The injection wave vector is varied to study the dependence of the above properties on the injection wave vectors. The 1D energy spectrum obtained for the velocity and magnetic fields has 𝐸 (𝑘) ∝ 𝑘−2. The 2D energy spectrum and 2D structure functions in parallel and perpendicular directions shows that fast mode turbulence generated is isotropic in nature. The cascade/decay rate of fast mode MHD turbulence is proportional to 𝑘−0.5 for different kinds of wave vector injection. Simulations are also carried out in 1D and 3D to compare balanced and imbalanced turbulence. The results obtained shows that while 1D imbalanced turbulence decays faster than 1D balanced turbulence, there is no difference in the decay of 3D balanced and imbalanced turbulence for the current resolution of 512 grid points.
"The second part of the thesis studies cosmic ray (CR) transport in driven MHD turbulence and is strongly dependent on it’s properties. Test particle simulations are carried out to study CR interaction with both total MHD turbulence and decomposed MHD modes. The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence. The results confirms that the fast modes dominate the CR propagation, whereas Alfvén, slow modes are much less efficient with similar pitch angle scattering rates. The cross field transport on large and small scales are investigated next. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by 𝑀𝜁𝐴 compared to the parallel diffusion coefficients, with 𝜁 closer to 4 in Alfvén modes than that in total turbulence as theoretically expected. For the CR transport on scales smaller than the turbulence injection scale 𝐿, both the local and global magnetic reference frames are adopted. Super diffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfvén modes show clear Richardson diffusion in the local reference frame. The diffusion transition smoothly from the Richardson’s one with index 1.5 to normal diffusion as particle’s mean free path decreases from 𝜆∥ ≫ 𝐿 to 𝜆∥ ≪ 𝐿. These results have broad applications to CRs in various astrophysical environments".
With the implementation of intense, short pulsed light sources throughout the last years, the powerful technique of resonant inelastic X-ray scattering (RIXS) became feasible for a wide range of experiments within femtosecond dynamics in correlated materials and molecules.
In this thesis I investigate the potential to bring RIXS into the fluence regime of nonlinear X-ray-matter interactions, especially focusing on the impact of stimulated scattering on RIXS in transition metal systems in a transmission spectroscopy geometry around transition metal L-edges.
After presenting the RIXS toolbox and the capabilities of free electron laser light sources for ultrafast intense X-ray experiments, the thesis explores an experiment designed to understand the impact of stimulated scattering on diffraction and direct beam transmission spectroscopy on a CoPd multilayer system. The experiments require short X-ray pulses that can only be generated at free electron lasers (FEL). Here the pulses are not only short, but also very intense, which opens the door to nonlinear X-ray-matter interactions. In the second part of this thesis, we investigate observations in the nonlinear interaction regime, look at potential difficulties for classic spectroscopy and investigate possibilities to enhance the RIXS through stimulated scattering. Here, a study on stimulated RIXS is presented, where we investigate the light field intensity dependent CoPd demagnetization in transmission as well as scattering geometry. Thereby we show the first direct observation of stimulated RIXS as well as light field induced nonlinear effects,
namely the breakdown of scattering intensity and the increase in sample transmittance. The topic is of ongoing interest and will just increase in relevance as more free electron lasers are planned and the number of experiments at such light sources will continue to increase in the near future.
Finally we present a discussion on the accessibility of small DOS shifts in the absorption-band of transition metal complexes through stimulated resonant X-ray scattering. As these shifts occur for example in surface states this finding could expand the experimental selectivity of NEXAFS and RIXS to the detectability of surface states. We show how stimulation can indeed enhance the visibility of DOS shifts through the detection of stimulated spectral shifts and enhancements in this theoretical study. We also forecast the observation of stimulated enhancements in resonant excitation experiments at FEL sources in systems with a high density of states just below the Fermi edge and in systems with an occupied to unoccupied DOS ratio in the valence band above 1.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
International migration has been an increasing phenomenon during the past decades and has involved all the regions of the globe. Together with fertility and mortality rates, net migration rates represent the components that fully define the demographic evolution of the population in a country. Therefore, being able to capture the patterns of international migration flows and to produce projections of how they might change in the future is of relevant importance for demographic studies and for designing policies informed on the potential scenarios. Existing forecasting methods do not account explicitly for the main drivers and processes shaping international migration flows: existing migrant communities at the destination country, termed diasporas, would reduce the costs of migration and facilitate the settling for new migrants, ultimately producing a positive feedback; accounting for the heterogeneity in the type of migration flows, e.g. return and transit Ćows, becomes critical in some specific bilateral migration channels; in low- to middle- income countries economic development could relax poverty constraint and result in an increase of emigration rates.
Economic conditions at both origin and destination are identified as major drivers of international migration. At the same time, climate change impacts have already appeared on natural and human-made systems such as the economic productivity. These economic impacts might have already produced a measurable effect on international migration flows. Studies that provide a quantification of the number of migration moves that might have been affected by climate change are usually specific to small regions, do not provide a mechanistic understanding of the pathway leading from climate change to migration and restrict their focus to the effective induced flows, disregarding the impact that climate change might have had in inhibiting other flows.
Global climate change is likely to produce impacts on the economic development of the countries during the next decades too. Understanding how these impacts might alter future global migration patterns is relevant for preparing future societies and understanding whether the response in migration flows would reduce or increase population's exposure to climate change impacts.
This doctoral research aims at investigating these questions and fill the research gaps outlined above. First, I have built a global bilateral international migration model which accounts explicitly for the diaspora feedback, distinguishes between transit and return flows, and accounts for the observed non-linear effects that link emigration rates to income levels in the country of origin. I have used this migration model within a population dynamic model where I account also for fertility and mortality rates, producing hindcasts and future projections of international migration flows, covering more than 170 countries. Results show that the model reproduces past patterns and trends well. Future projections highlight the fact that,depending on the assumptions regarding future evolution of income levels and between-country inequality, migration at the end of the century might approach net zero or be still high in many countries. The model, parsimonious in the explanatory variables that includes, represents a versatile tool for assessing the impacts of different socioeconomic scenarios on international migration.
I consider then a counterfactual past without climate change impacts on the economic productivity. By prescribing these counterfactual economic conditions to the migration model I produce counterfactual migration flows for the past 30 years. I compare the counterfactual migration flows to factual ones, where historical economic conditions are used to produce migration flows. This provides an estimation of the recent international migration flows attributed to climate change impacts. Results show that a counterfactual world without climate change would have seen less migration globally. This effect becomes larger if I consider separately the increase and decrease in migration moves: a Ągure of net change in the migration flows is not representative of the effective magnitude of the climate change impact on migration. Indeed, in my results climate change produces a divergent effect on richer and poorer countries: by slowing down the economic development, climate change might have reduced international mobility from and to countries of the Global South, and increased it from and to richer countries in the Global North.
I apply the same methodology to a scenario of future 3℃ global warming above pre-industrial conditions. I Ąnd that climate change impacts, acting by reorganizing the relative economic attractiveness of destination countries or by affecting the economic growth in the origin, might produce a substantial effect in international migration flows, inhibiting some moves and inducing others.
Overall my results suggest that climate change might have had and might have in the future a significant effect on global patterns of international migration. It also emerges clearly that, for a comprehensive understanding of the effects of climate change on international migration, we need to go beyond net effects and consider separately induced and inhibited flows.
In this work, binding interactions between biomolecules were analyzed by a technique that is based on electrically controllable DNA nanolevers. The technique was applied to virus-receptor interactions for the first time. As receptors, primarily peptides on DNA nanostructures and antibodies were utilized. The DNA nanostructures were integrated into the measurement technique and enabled the presentation of the peptides in a controllable geometrical order. The number of peptides could be varied to be compatible to the binding sites of the viral surface proteins.
Influenza A virus served as a model system, on which the general measurability was demonstrated. Variations of the receptor peptide, the surface ligand density, the measurement temperature and the virus subtypes showed the sensitivity and applicability of the technology. Additionally, the immobilization of virus particles enabled the measurement of differences in oligovalent binding of DNA-peptide nanostructures to the viral proteins in their native environment.
When the coronavirus pandemic broke out in 2020, work on binding interactions of a peptide from the hACE2 receptor and the spike protein of the SARS-CoV-2 virus revealed that oligovalent binding can be quantified in the switchSENSE technology. It could also be shown that small changes in the amino acid sequence of the spike protein resulted in complete loss of binding. Interactions of the peptide and inactivated virus material as well as pseudo virus particles could be measured. Additionally, the switchSENSE technology was utilized to rank six antibodies for their binding affinity towards the nucleocapsid protein of SARS-CoV-2 for the development of a rapid antigen test device.
The technique was furthermore employed to show binding of a non-enveloped virus (adenovirus) and a virus-like particle (norovirus-like particle) to antibodies. Apart from binding interactions, the use of DNA origami levers with a length of around 50 nm enabled the switching of virus material. This proved that the technology is also able to size objects with a hydrodynamic diameter larger than 14 nm.
A theoretical work on diffusion and reaction-limited binding interactions revealed that the technique and the chosen parameters enable the determination of binding rate constants in the reaction-limited regime.
Overall, the applicability of the switchSENSE technique to virus-receptor binding interactions could be demonstrated on multiple examples. While there are challenges that remain, the setup enables the determination of affinities between viruses and receptors in their native environment. Especially the possibilities regarding the quantification of oligo- and multivalent binding interactions could be presented.
In this thesis, I present my contributions to the field of ultrafast molecular spectroscopy. Using the molecule 2-thiouracil as an example, I use ultrashort x-ray pulses from free- electron lasers to study the relaxation dynamics of gas-phase molecular samples. Taking advantage of the x-ray typical element- and site-selectivity, I investigate the charge flow and geometrical changes in the excited states of 2-thiouracil.
In order to understand the photoinduced dynamics of molecules, knowledge about the ground-state structure and the relaxation after photoexcitation is crucial. Therefore, a part of this thesis covers the electronic ground-state spectroscopy of mainly 2-thiouracil to provide the basis for the time-resolved experiments. Many of the previously published studies that focused on the gas-phase time-resolved dynamics of thionated uracils after UV excitation relied on information from solution phase spectroscopy to determine the excitation energies. This is not an optimal strategy as solvents alter the absorption spec- trum and, hence, there is no guarantee that liquid-phase spectra resemble the gas-phase spectra. Therefore, I measured the UV-absorption spectra of all three thionated uracils to provide a gas-phase reference and, in combination with calculations, we determined the excited states involved in the transitions.
In contrast to the UV absorption, the literature on the x-ray spectroscopy of thionated uracil is sparse. Thus, we measured static photoelectron, Auger-Meitner and x-ray absorption spectra on the sulfur L edge before or parallel to the time-resolved experiments we performed at FLASH (DESY, Hamburg). In addition, (so far unpublished) measurements were performed at the synchrotron SOLEIL (France) which have been included in this thesis and show the spin-orbit splitting of the S 2p photoline and its satellite which was not observed at the free-electron laser.
The relaxation of 2-thiouracil has been studied extensively in recent years with ultrafast visible and ultraviolet methods showing the ultrafast nature of the molecular process after photoexcitation. Ultrafast spectroscopy probing the core-level electrons provides a complementary approach to common optical ultrafast techniques. The method inherits its local sensitivity from the strongly localised core electrons. The core energies and core-valence transitions are strongly affected by local valence charge and geometry changes, and past studies have utilised this sensitivity to investigate the molecular process reflected by the ultrafast dynamics. We have built an apparatus that provides the requirements to perform time-resolved x-ray spectroscopy on molecules in the gas phase. With the apparatus, we performed UV-pump x-ray-probe electron spectroscopy on the S 2p edge of 2-thiouracil using the free-electron laser FLASH2. While the UV triggers the relaxation dynamics, the x-ray probes the single sulfur atom inside the molecule. I implemented photoline self-referencing for the photoelectron spectral analysis. This minimises the spectral jitter of the FEL, which is due to the underlying self-amplified spontaneous emission (SASE) process. With this approach, we were not only able to study dynamical changes in the binding energy of the electrons but also to detect an oscillatory behaviour in the shift of the observed photoline, which we associate with non-adiabatic dynamics involving several electronic states. Moreover, we were able to link the UV-induced shift in binding energy to the local charge flow at the sulfur which is directly connected to the electronic state. Furthermore, the analysis of the Auger-Meitner electrons shows that energy shifts observed at early stages of the photoinduced relaxation are related to the geometry change in the molecule. More specifically, the observed increase in kinetic energy of the Auger-Meitner electrons correlates with a previously predicted C=S bond stretch.
Gravitational-wave (GW) astrophysics is a field in full blossom. Since the landmark detection of GWs from a binary black hole on September 14th 2015, fifty-two compact-object binaries have been reported by the LIGO-Virgo collaboration. Such events carry astrophysical and cosmological information ranging from an understanding of how black holes and neutron stars are formed, what neutron stars are composed of, how the Universe expands, and allow testing general relativity in the highly-dynamical strong-field regime. It is the goal of GW astrophysics to extract such information as accurately as possible. Yet, this is only possible if the tools and technology used to detect and analyze GWs are advanced enough. A key aspect of GW searches are waveform models, which encapsulate our best predictions for the gravitational radiation under a certain set of parameters, and that need to be cross-correlated with data to extract GW signals. Waveforms must be very accurate to avoid missing important physics in the data, which might be the key to answer the fundamental questions of GW astrophysics. The continuous improvements of the current LIGO-Virgo detectors, the development of next-generation ground-based detectors such as the Einstein Telescope or the Cosmic Explorer, as well as the development of the Laser Interferometer Space Antenna (LISA), demand accurate waveform models. While available models are enough to capture the low spins, comparable-mass binaries routinely detected in LIGO-Virgo searches, those for sources from both current and next-generation ground-based and spaceborne detectors must be accurate enough to detect binaries with large spins and asymmetry in the masses. Moreover, the thousands of sources that we expect to detect with future detectors demand accurate waveforms to mitigate biases in the estimation of signals’ parameters due to the presence of a foreground of many sources that overlap in the frequency band. This is recognized as one of the biggest challenges for the analysis of future-detectors’ data, since biases might hinder the extraction of important astrophysical and cosmological information from future detectors’ data. In the first part of this thesis, we discuss how to improve waveform models for binaries with high spins and asymmetry in the masses. In the second, we present the first generic metrics that have been proposed to predict biases in the presence of a foreground of many overlapping signals in GW data.
For the first task, we will focus on several classes of analytical techniques. Current models for LIGO and Virgo studies are based on the post-Newtonian (PN, weak-field, small velocities) approximation that is most natural for the bound orbits that are routinely detected in GW searches. However, two other approximations have risen in prominence, the post-Minkowskian (PM, weak- field only) approximation natural for unbound (scattering) orbits and the small-mass-ratio (SMR) approximation typical of binaries in which the mass of one body is much bigger than the other. These are most appropriate to binaries with high asymmetry in the masses that challenge current waveform models. Moreover, they allow one to “cover” regions of the parameter space of coalescing binaries, thereby improving the interpolation (and faithfulness) of waveform models. The analytical approximations to the relativistic two-body problem can synergically be included within the effective-one-body (EOB) formalism, in which the two-body information from each approximation can be recast into an effective problem of a mass orbiting a deformed Schwarzschild (or Kerr) black hole. The hope is that the resultant models can cover both the low-spin comparable-mass binaries that are routinely detected, and the ones that challenge current models. The first part of this thesis is dedicated to a study about how to best incorporate information from the PN, PM, SMR and EOB approaches in a synergistic way. We also discuss how accurate the resulting waveforms are, as compared against numerical-relativity (NR) simulations. We begin by comparing PM models, whether alone or recast in the EOB framework, against PN models and NR simulations. We will show that PM information has the potential to improve currently-employed models for LIGO and Virgo, especially if recast within the EOB formalism. This is very important, as the PM approximation comes with a host of new computational techniques from particle physics to exploit. Then, we show how a combination of PM and SMR approximations can be employed to access previously-unknown PN orders, deriving the third subleading PN dynamics for spin-orbit and (aligned) spin1-spin2 couplings. Such new results can then be included in the EOB models currently used in GW searches and parameter estimation studies, thereby improving them when the binaries have high spins. Finally, we build an EOB model for quasi-circular nonspinning binaries based on the SMR approximation (rather than the PN one as usually done). We show how this is done in detail without incurring in the divergences that had affected previous attempts, and compare the resultant model against NR simulations. We find that the SMR approximation is an excellent approximation for all (quasi-circular nonspinning) binaries, including both the equal-mass binaries that are routinely detected in GW searches and the ones with highly asymmetric masses. In particular, the SMR-based models compare much better than the PN models, suggesting that SMR-informed EOB models might be the key to model binaries in the future. In the second task of this thesis, we work within the linear-signal ap- proximation and describe generic metrics to predict inference biases on the parameters of a GW source of interest in the presence of confusion noise from unfitted foregrounds and from residuals of other signals that have been incorrectly fitted out. We illustrate the formalism with simple (yet realistic) LISA sources, and demonstrate its validity against Monte-Carlo simulations. The metrics we describe pave the way for more realistic studies to quantify the biases with future ground-based and spaceborne detectors.
In X-ray computed tomography (XCT), an X-ray beam of intensity I0 is transmitted through an object and its attenuated intensity I is measured when it exits the object. The attenuation of the beam depends on the attenuation coefficients along its path. The attenuation coefficients provide information about the structure and composition of the object and can be determined through mathematical operations that are referred to as reconstruction.
The standard reconstruction algorithms are based on the filtered backprojection (FBP) of the measured data. While these algorithms are fast and relatively simple, they do not always succeed in computing a precise reconstruction, especially from under-sampled data.
Alternatively, an image or volume can be reconstructed by solving a system of linear equations. Typically, the system of equations is too large to be solved but its solution can be approximated by iterative methods, such as the Simultaneous Iterative Reconstruction Technique (SIRT) and the Conjugate Gradient Least Squares (CGLS).
This dissertation focuses on the development of a novel iterative algorithm, the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT). After its reconstruction principle is explained, its performance is assessed for real parallel- and cone-beam CT (including under-sampled) data and compared to that of other established algorithms. Finally, it is demonstrated how the shape of the measured object can be modelled into DIRECTT to achieve even better reconstruction results.
The Greenland Ice Sheet is the second-largest mass of ice on Earth. Being almost 2000 km long, more than 700 km wide, and more than 3 km thick at the summit, it holds enough ice to raise global sea levels by 7m if melted completely. Despite its massive size, it is particularly vulnerable to anthropogenic climate change: temperatures over the Greenland Ice Sheet have increased by more than 2.7◦C in the past 30 years, twice as much as the global mean temperature. Consequently, the ice sheet has been significantly losing mass since the 1980s and the rate of loss has increased sixfold since then. Moreover, it is one of the potential tipping elements of the Earth System, which might undergo irreversible change once a warming threshold is exceeded. This thesis aims at extending the understanding of the resilience of the Greenland Ice Sheet against global warming by analyzing processes and feedbacks relevant to its centennial to multi-millennial stability using ice sheet modeling.
One of these feedbacks, the melt-elevation-feedback is driven by the temperature rise with decreasing altitudes: As the ice sheet melts, its thickness and surface elevation decrease, exposing the ice surface to warmer air and thus increasing the melt rates even further. The glacial isostatic adjustment (GIA) can partly mitigate this melt-elevation feedback as the bedrock lifts in response to an ice load decrease, forming the negative GIA feedback. In my thesis, I show that the interaction between these two competing feedbacks can lead to qualitatively different dynamical responses of the Greenland Ice Sheet to warming – from permanent loss to incomplete recovery, depending on the feedback parameters. My research shows that the interaction of those feedbacks can initiate self-sustained oscillations of the ice volume while the climate forcing remains constant.
Furthermore, the increased surface melt changes the optical properties of the snow or ice surface, e.g. by lowering their albedo, which in turn enhances melt rates – a process known as the melt-albedo feedback. Process-based ice sheet models often neglect this melt-albedo feedback. To close this gap, I implemented a simplified version of the diurnal Energy Balance Model, a computationally efficient approach that can capture the first-order effects of the melt-albedo feedback, into the Parallel Ice Sheet Model (PISM). Using the coupled model, I show in warming experiments that the melt-albedo feedback almost doubles the ice loss until the year 2300 under the low greenhouse gas emission scenario RCP2.6, compared to simulations where the melt-albedo feedback is neglected,
and adds up to 58% additional ice loss under the high emission scenario RCP8.5. Moreover, I find that the melt-albedo feedback dominates the ice loss until 2300, compared to the melt-elevation feedback.
Another process that could influence the resilience of the Greenland Ice Sheet is the warming induced softening of the ice and the resulting increase in flow. In my thesis, I show with PISM how the uncertainty in Glen’s flow law impacts the simulated response to warming. In a flow line setup at fixed climatic mass balance, the uncertainty in flow parameters leads to a range of ice loss comparable to the range caused by different warming levels.
While I focus on fundamental processes, feedbacks, and their interactions in the first three projects of my thesis, I also explore the impact of specific climate scenarios on the sea level rise contribution of the Greenland Ice Sheet. To increase the carbon budget flexibility, some warming scenarios – while still staying within the limits of the Paris Agreement – include a temporal overshoot of global warming. I show that an overshoot by 0.4◦C increases the short-term and long-term ice loss from Greenland by several centimeters. The long-term increase is driven by the warming at high latitudes, which persists even when global warming is reversed. This leads to a substantial long-term commitment of the sea level rise contribution from the Greenland Ice Sheet.
Overall, in my thesis I show that the melt-albedo feedback is most relevant for the ice loss of the Greenland Ice Sheet on centennial timescales. In contrast, the melt-elevation feedback and its interplay with the GIA feedback become increasingly relevant on millennial timescales. All of these influence the resilience of the Greenland Ice Sheet against global warming, in the near future and on the long term.
A task-based parallel elliptic solver for numerical relativity with discontinuous Galerkin methods
(2022)
Elliptic partial differential equations are ubiquitous in physics. In numerical relativity---the study of computational solutions to the Einstein field equations of general relativity---elliptic equations govern the initial data that seed every simulation of merging black holes and neutron stars. In the quest to produce detailed numerical simulations of these most cataclysmic astrophysical events in our Universe, numerical relativists resort to the vast computing power offered by current and future supercomputers. To leverage these computational resources, numerical codes for the time evolution of general-relativistic initial value problems are being developed with a renewed focus on parallelization and computational efficiency. Their capability to solve elliptic problems for accurate initial data must keep pace with the increasing detail of the simulations, but elliptic problems are traditionally hard to parallelize effectively.
In this thesis, I develop new numerical methods to solve elliptic partial differential equations on computing clusters, with a focus on initial data for orbiting black holes and neutron stars. I develop a discontinuous Galerkin scheme for a wide range of elliptic equations, and a stack of task-based parallel algorithms for their iterative solution. The resulting multigrid-Schwarz preconditioned Newton-Krylov elliptic solver proves capable of parallelizing over 200 million degrees of freedom to at least a few thousand cores, and already solves initial data for a black hole binary about ten times faster than the numerical relativity code SpEC. I also demonstrate the applicability of the new elliptic solver across physical disciplines, simulating the thermal noise in thin mirror coatings of interferometric gravitational-wave detectors to unprecedented accuracy. The elliptic solver is implemented in the new open-source SpECTRE numerical relativity code, and set up to support simulations of astrophysical scenarios for the emerging era of gravitational-wave and multimessenger astronomy.
The complex hierarchical structure of bone undergoes a lifelong remodeling process, where it adapts to mechanical needs. Hereby, bone resorption by osteoclasts and bone formation by osteoblasts have to be balanced to sustain a healthy and stable organ. Osteocytes orchestrate this interplay by sensing mechanical strains and translating them into biochemical signals. The osteocytes are located in lacunae and are connected to one another and other bone cells via cell processes through small channels, the canaliculi. Lacunae and canaliculi form a network (LCN) of extracellular spaces that is able to transport ions and enables cell-to-cell communication. Osteocytes might also contribute to mineral homeostasis by direct interactions with the surrounding matrix. If the LCN is acting as a transport system, this should be reflected in the mineralization pattern. The central hypothesis of this thesis is that osteocytes are actively changing their material environment. Characterization methods of material science are used to achieve the aim of detecting traces of this interaction between osteocytes and the extracellular matrix. First, healthy murine bones were characterized. The properties analyzed were then compared with three murine model systems: 1) a loading model, where a bone of the mouse was loaded during its life time; 2) a healing model, where a bone of the mouse was cut to induce a healing response; and 3) a disease model, where the Fbn1 gene is dysfunctional causing defects in the formation of the extracellular tissue.
The measurement strategy included routines that make it possible to analyze the organization of the LCN and the material components (i.e., the organic collagen matrix and the mineral particles) in the same bone volumes and compare the spatial distribution of different data sets. The three-dimensional network architecture of the LCN is visualized by confocal laser scanning microscopy (CLSM) after rhodamine staining and is then subsequently quantified. The calcium content is determined via quantitative backscattered electron imaging (qBEI), while small- and wide-angle X-ray scattering (SAXS and WAXS) are employed to determine the thickness and length of local mineral particles.
First, tibiae cortices of healthy mice were characterized to investigate how changes in LCN architecture can be attributed to interactions of osteocytes with the surrounding bone matrix. The tibial mid-shaft cross-sections showed two main regions, consisting of a band with unordered LCN surrounded by a region with ordered LCN. The unordered region is a remnant of early bone formation and exhibited short and thin mineral particles. The surrounding, more aligned bone showed ordered and dense LCN as well as thicker and longer mineral particles. The calcium content was unchanged between the two regions.
In the mouse loading model, the left tibia underwent two weeks of mechanical stimulation, which results in increased bone formation and decreased resorption in skeletally mature mice. Here the specific research question addressed was how do bone material characteristics change at (re)modeling sites? The new bone formed in response to mechanical stimulation showed similar properties in terms of the mineral particles, like the ordered calcium region but lower calcium content compared to the right, non-loaded control bone of the same mice. There was a clear, recognizable border between mature and newly formed bone. Nevertheless, some canaliculi went through this border connecting the LCN of mature and newly formed bone.
Additionally, the question should be answered whether the LCN topology and the bone matrix material properties adapt to loading. Although, mechanically stimulated bones did not show differences in calcium content compared to controls, different correlations were found between the local LCN density and the local Ca content depending on whether the bone was loaded or not. These results suggest that the LCN may serve as a mineral reservoir.
For the healing model, the femurs of mice underwent an osteotomy, stabilized with an external fixator and were allowed to heal for 21 days. Thus, the spatial variations in the LCN topology with mineral properties within different tissue types and their interfaces, namely calcified cartilage, bony callus and cortex, could be simultaneously visualized and compared in this model. All tissue types showed structural differences across multiple length scales. Calcium content increased and became more homogeneous from calcified cartilage to bony callus to lamellar cortical bone. The degree of LCN organization increased as well, while the lacunae became smaller, as did the lacunar density between these different tissue types that make up the callus. In the calcified cartilage, the mineral particles were short and thin. The newly formed callus exhibited thicker mineral particles, which still had a low degree of orientation. While most of the callus had a woven-like structure, it also served as a scaffold for more lamellar tissue at the edges. The lamelar bone callus showed thinner mineral particles, but a higher degree of alignment in both, mineral particles and the LCN. The cortex showed the highest values for mineral length, thickness and degree of orientation. At the same time, the lacunae number density was 34% lower and the lacunar volume 40% smaller compared to bony callus. The transition zone between cortical and callus regions showed a continuous convergence of bone mineral properties and lacunae shape. Although only a few canaliculi connected callus and the cortical region, this indicates that communication between osteocytes of both tissues should be possible. The presented correlations between LCN architecture and mineral properties across tissue types may suggest that osteocytes have an active role in mineralization processes of healing.
A mouse model for the disease marfan syndrome, which includes a genetic defect in the fibrillin-1 gene, was investigated. In humans, Marfan syndrome is characterized by a range of clinical symptoms such as long bone overgrowth, loose joints, reduced bone mineral density, compromised bone microarchitecture, and increased fracture rates. Thus, fibrillin-1 seems to play a role in the skeletal homeostasis. Therefore, the present work studied how marfan syndrome alters LCN architecture and the surrounding bone matrix. The mice with marfan syndrome showed longer tibiae than their healthy littermates from an age of seven weeks onwards. In contrast, the cortical development appeared retarded, which was observed across all measured characteristics, i. e. lower endocortical bone formation, looser and less organized lacuno-canalicular network, less collagen orientation, thinner and shorter mineral particles.
In each of the three model systems, this study found that changes in the LCN architecture spatially correlated with bone matrix material parameters. While not knowing the exact mechanism, these results provide indications that osteocytes can actively manipulate a mineral reservoir located around the canaliculi to make a quickly accessible contribution to mineral homeostasis. However, this interaction is most likely not one-sided, but could be understood as an interplay between osteocytes and extra-cellular matrix, since the bone matrix contains biochemical signaling molecules (e.g. non-collagenous proteins) that can change osteocyte behavior. Bone (re)modeling can therefore not only be understood as a method for removing defects or adapting to external mechanical stimuli, but also for increasing the efficiency of possible osteocyte-mineral interactions during bone homeostasis. With these findings, it seems reasonable to consider osteocytes as a target for drug development related to bone diseases that cause changes in bone composition and mechanical properties. It will most likely require the combined effort of materials scientists, cell biologists, and molecular biologists to gain a deeper understanding of how bone cells respond to their material environment.
In the present thesis I investigate the lattice dynamics of thin film hetero structures of magnetically ordered materials upon femtosecond laser excitation as a probing and manipulation scheme for the spin system. The quantitative assessment of laser induced thermal dynamics as well as generated picosecond acoustic pulses and their respective impact on the magnetization dynamics of thin films is a challenging endeavor. All the more, the development and implementation of effective experimental tools and comprehensive models are paramount to propel future academic and technological progress.
In all experiments in the scope of this cumulative dissertation, I examine the crystal lattice of nanoscale thin films upon the excitation with femtosecond laser pulses. The relative change of the lattice constant due to thermal expansion or picosecond strain pulses is directly monitored by an ultrafast X-ray diffraction (UXRD) setup with a femtosecond laser-driven plasma X-ray source (PXS). Phonons and spins alike exert stress on the lattice, which responds according to the elastic properties of the material, rendering the lattice a versatile sensor for all sorts of ultrafast interactions. On the one hand, I investigate materials with strong magneto-elastic properties; The highly magnetostrictive rare-earth compound TbFe2, elemental Dysprosium or the technological relevant Invar material FePt. On the other hand I conduct a comprehensive study on the lattice dynamics of Bi1Y2Fe5O12 (Bi:YIG), which exhibits high-frequency coherent spin dynamics upon femtosecond laser excitation according to the literature. Higher order standing spinwaves (SSWs) are triggered by coherent and incoherent motion of atoms, in other words phonons, which I quantified with UXRD. We are able to unite the experimental observations of the lattice and magnetization dynamics qualitatively and quantitatively. This is done with a combination of multi-temperature, elastic, magneto-elastic, anisotropy and micro-magnetic modeling.
The collective data from UXRD, to probe the lattice, and time-resolved magneto-optical Kerr effect (tr-MOKE) measurements, to monitor the magnetization, were previously collected at different experimental setups. To improve the precision of the quantitative assessment of lattice and magnetization dynamics alike, our group implemented a combination of UXRD and tr-MOKE in a singular experimental setup, which is to my knowledge, the first of its kind. I helped with the conception and commissioning of this novel experimental station, which allows the simultaneous observation of lattice and magnetization dynamics on an ultrafast timescale under identical excitation conditions. Furthermore, I developed a new X-ray diffraction measurement routine which significantly reduces the measurement time of UXRD experiments by up to an order of magnitude. It is called reciprocal space slicing (RSS) and utilizes an area detector to monitor the angular motion of X-ray diffraction peaks, which is associated with lattice constant changes, without a time-consuming scan of the diffraction angles with the goniometer. RSS is particularly useful for ultrafast diffraction experiments, since measurement time at large scale facilities like synchrotrons and free electron lasers is a scarce and expensive resource. However, RSS is not limited to ultrafast experiments and can even be extended to other diffraction techniques with neutrons or electrons.
Elementary particle physics is a contemporary topic in science that is slowly being integrated into high-school education. These new implementations are challenging teachers’ professional knowledge worldwide. Therefore, physics education research is faced with two important questions, namely, how can particle physics be integrated in high-school physics curricula and how best to support teachers in enhancing their professional knowledge on particle physics. This doctoral research project set up to provide better guidelines for answering these two questions by conducting three studies on high-school particle physics education.
First, an expert concept mapping study was conducted to elicit experts’ expectations on what high-school students should learn about particle physics. Overall, 13 experts in particle physics, computing, and physics education participated in 9 concept mapping rounds. The broad knowledge base of the experts ensured that the final expert concept map covers all major particle physics aspects. Specifically, the final expert concept map includes 180 concepts and examples, connected with 266 links and crosslinks. Among them are also several links to students’ prior knowledge in topics such as mechanics and thermodynamics. The high interconnectedness of the concepts shows possible opportunities for including particle physics as a context for other curricular topics. As such, the resulting expert concept map is showcased as a well-suited tool for teachers to scaffold their instructional practice.
Second, a review of 27 high-school physics curricula was conducted. The review uncovered which concepts related to particle physics can be identified in most curricula. Each curriculum was reviewed by two reviewers that followed a codebook with 60 concepts related to particle physics. The analysis showed that most curricula mention cosmology, elementary particles, and charges, all of which are considered theoretical particle physics concepts. None of the experimental particle physics concepts appeared in more than half of the reviewed curricula. Additional analysis was done on two curricular subsets, namely curricula with and curricula without an explicit particle physics chapter. Curricula with an explicit particle physics chapter mention several additional explicit particle physics concepts, namely the Standard Model of particle physics, fundamental interactions, antimatter research, and particle accelerators. The latter is an example of experimental particle physics concepts. Additionally, the analysis revealed that, overall, most curricula include Nature of Science and history of physics, albeit both are typically used as context or as a tool for teaching, respectively.
Third, a Delphi study was conducted to investigate stakeholders’ expectations regarding what teachers should learn in particle physics professional development programmes. Over 100 stakeholders from 41 countries represented four stakeholder groups, namely physics education researchers, research scientists, government representatives, and high-school teachers. The study resulted in a ranked list of the 13 most important topics to be included in particle physics professional development programmes. The highest-ranked topics are cosmology, the Standard Model, and real-life applications of particle physics. All stakeholder groups agreed on the overall ranking of the topics. While the highest-ranked topics are again more theoretical, stakeholders also expect teachers to learn about experimental particle physics topics, which are ranked as medium importance topics.
The three studies addressed two research aims of this doctoral project. The first research aim was to explore to what extent particle physics is featured in high-school physics curricula. The comparison of the outcomes of the curricular review and the expert concept map showed that curricula cover significantly less than what experts expect high-school students to learn about particle physics. For example, most curricula do not include concepts that could be classified as experimental particle physics. However, the strong connections between the different concept show that experimental particle physics can be used as context for theoretical particle physics concepts, Nature of Science, and other curricular topics. In doing so, particle physics can be introduced in classrooms even though it is not (yet) explicitly mentioned in the respective curriculum.
The second research aim was to identify which aspects of content knowledge teachers are expected to learn about particle physics. The comparison of the Delphi study results to the outcomes of the curricular review and the expert concept map showed that stakeholders generally expect teachers to enhance their school knowledge as defined by the curricula. Furthermore, teachers are also expected to enhance their deeper school knowledge by learning how to connect concepts from their school knowledge to other concepts in particle physics and beyond. As such, professional development programmes that focus on enhancing teachers’ school knowledge and deeper school knowledge best support teachers in building relevant context in their instruction.
Overall, this doctoral research project reviewed the current state of high-school particle physics education and provided guidelines for future enhancements of the particle physics content in high-school student and teacher education. The outcomes of the project support further implementations of particle physics in high-school education both as explicit content and as context for other curricular topics. Furthermore, the mixed-methods approach and the outcomes of this research project lead to several implications for professional development programmes and science education research, that are discussed in the final chapters of this dissertation.
Over the past decades, there has been a growing interest in ‘extreme events’ owing to the increasing threats that climate-related extremes such as floods, heatwaves, droughts, etc., pose to society. While extreme events have diverse definitions across various disciplines, ranging from earth science to neuroscience, they are characterized mainly as dynamic occurrences within a limited time frame that impedes the normal functioning of a system. Although extreme events are rare in occurrence, it has been found in various hydro-meteorological and physiological time series (e.g., river flows, temperatures, heartbeat intervals) that they may exhibit recurrent behavior, i.e., do not end the lifetime of the system. The aim of this thesis to develop some
sophisticated methods to study various properties of extreme events.
One of the main challenges in analyzing such extreme event-like time series is that they have large temporal gaps due to the paucity of the number of observations of extreme events. As a result, existing time series analysis tools are usually not helpful to decode the underlying
information. I use the edit distance (ED) method to analyze extreme event-like time series in their unaltered form. ED is a specific distance metric, mainly designed to measure the similarity/dissimilarity between point process-like data. I combine ED with recurrence plot techniques to identify the recurrence property of flood events in the Mississippi River in the United States. I also use recurrence quantification analysis to show the deterministic properties
and serial dependency in flood events.
After that, I use this non-linear similarity measure (ED) to compute the pairwise dependency in extreme precipitation event series. I incorporate the similarity measure within the framework of complex network theory to study the collective behavior of climate extremes. Under this architecture, the nodes are defined by the spatial grid points of the given spatio-temporal climate dataset. Each node is associated with a time series corresponding to the temporal evolution
of the climate observation at that grid point. Finally, the network links are functions of the pairwise statistical interdependence between the nodes. Various network measures, such as degree, betweenness centrality, clustering coefficient, etc., can be used to quantify the network’s topology. We apply the methodology mentioned above to study the spatio-temporal coherence pattern of extreme rainfall events in the United States and the Ganga River basin, which reveals its relation to various climate processes and the orography of the region.
The identification of precursors associated with the occurrence of extreme events in the near future is extremely important to prepare the masses for an upcoming disaster and mitigate the potential risks associated with such events. Under this motivation, I propose an in-data prediction recipe for predicting the data structures that typically occur prior to extreme events using the Echo state network, a type of Recurrent Neural Network which is a part of the reservoir
computing framework. However, unlike previous works that identify precursory structures in the same variable in which extreme events are manifested (active variable), I try to predict these structures by using data from another dynamic variable (passive variable) which does not show large excursions from the nominal condition but carries imprints of these extreme events. Furthermore, my results demonstrate that the quality of prediction depends on the magnitude
of events, i.e., the higher the magnitude of the extreme, the better is its predictability skill. I show quantitatively that this is because the input signals collectively form a more coherent pattern for an extreme event of higher magnitude, which enhances the efficiency of the machine to predict the forthcoming extreme events.
Stellar interferometry is the only method in observational astronomy for obtaining the highest resolution images of astronomical targets. This method is based on combining light from two or more separate telescopes to obtain the complex visibility that contains information about the brightness distribution of an astronomical source. The applications of stellar interferometry have made significant contributions in the exciting research areas of astronomy and astrophysics, including the precise measurement of stellar diameters, imaging of stellar surfaces, observations of circumstellar disks around young stellar objects, predictions of Einstein's General relativity at the galactic center, and the direct search for exoplanets to name a few. One important related technique is aperture masking interferometry, pioneered in the 1960s, which uses a mask with holes at the re-imaged pupil of the telescope, where the light from the holes is combined using the principle of stellar interferometry. While this can increase the resolution, it comes with a disadvantage. Due to the finite size of the holes, the majority of the starlight (typically > 80 %) is lost at the mask, thus limiting the signal-to-noise ratio (SNR) of the output images. This restriction of aperture masking only to the bright targets can be avoided using pupil remapping interferometry - a technique combining aperture masking interferometry and advances in photonic technologies using single-mode fibers. Due to the inherent spatial filtering properties, the single-mode fibers can be placed at the focal plane of the re-imaged pupil, allowing the utilization of the whole pupil of the telescope to produce a high-dynamic range along with high-resolution images. Thus, pupil remapping interferometry is one of the most promising application areas in the emerging field of astrophotonics.
At the heart of an interferometric facility, a beam combiner exists whose primary function is to combine light to obtain high-contrast fringes. A beam combiner can be as simple as a beam splitter or an anamorphic lens to combine light from 2 apertures (or telescopes) or as complex as a cascade of beam splitters and lenses to combine light for > 2 apertures. However, with the field of astrophotonics, interferometric facilities across the globe are increasingly employing some form of photonics technologies by using single-mode fibers or integrated optics (IO) chips as an efficient way to combine light from several apertures. The state-of-the-art instrument - GRAVITY at the very large telescope interferometer (VLTI) facility uses an IO-based beam combiner device reaching visibilities accuracy of better than < 0.25 %, which is roughly 50× as precise as a few decades back.
Therefore, in the context of IO-based components for applications in stellar interferometry, this Thesis describes the work towards the development of a 3-dimensional (3-D) IO device - a monolithic astrophotonics component containing both the pupil remappers and a discrete beam combiner (DBC). In this work, the pupil remappers are 3-D single-mode waveguides in a glass substrate collecting light from the re-imaged pupil of the telescope and feeding the light to a DBC, where the combination takes place. The DBC is a lattice of 3-D single-mode waveguides, which interact through evanescent coupling. By observing the output power of single-mode waveguides of the DBC, the visibilities are retrieved by using a calibrated transfer matrix ({U}) of the device.
The feasibility of the DBC in retrieving the visibilities theoretically and experimentally had already been studied in the literature but was only limited to laboratory tests with monochromatic light sources. Thus, a part of this work extends these studies by investigating the response of a 4-input DBC to a broad-band light source. Hence, the objectives of this Thesis are the following: 1) Design an IO device for broad-band light operation such that accurate and precise visibilities could be retrieved experimentally at astronomical H-band (1.5-1.65 μm), and 2) Validation of the DBC as a possible beam combination scheme for future interferometric facilities through on-sky testing at the William Herschel Telescope (WHT).
This work consisted of designing three different 3-D IO devices. One of the popular methods for fabricating 3-D photonic components in a glass substrate is ultra-fast laser inscription (ULI). Thus, manufacturing of the designed devices was outsourced to Politecnico di Milano as part of an iterative fabrication process using their state-of-the-art ULI facility. The devices were then characterized using a 2-beam Michelson interferometric setup obtaining both the monochromatic and polychromatic visibilities. The retrieved visibilities for all devices were in good agreement as predicted by the simulation results of a DBC, which confirms both the repeatability of the ULI process and the stability of the Michelson setup, thus fulfilling the first objective.
The best-performing device was then selected for the pupil-remapping of the WHT using a different optical setup consisting of a deformable mirror and a microlens array. The device successfully collected stellar photons from Vega and Altair. The visibilities were retrieved using a previously calibrated {U} but showed significant deviations from the expected results. Based on the analysis of comparable simulations, it was found that such deviations were primarily caused by the limited SNR of the stellar observations, thus constituting a first step towards the fulfillment of the second objective.
Understanding the changes that follow UV-excitation in thionucleobases is of great importance for the study of light-induced DNA lesions and, in a broader context, for their applications in medicine and biochemistry. Their ultrafast photophysical reactions can alter the chemical structure of DNA - leading to damages to the genetic code - as proven by the increased skin cancer risk observed for patients treated with thiouracil for its immunosuppressant properties.
In this thesis, I present four research papers that result from an investigation of the ultrafast dynamics of 2-thiouracil by means of ultrafast x-ray probing combined with electron spectroscopy. A molecular jet in the gas phase is excited with a uv pulse and then ionized with x-ray radiation from a Free Electron Laser. The kinetic energy of the emitted electrons is measured in a magnetic bottle spectrometer. The spectra of the measured photo and Auger electrons are used to derive a picture of the changes in the geometrical and electronic configurations. The results allow us to look at the dynamical processes from a new perspective, thanks to the element- and site- sensitivity of x-rays. The custom-built URSA-PQ apparatus used in the experiment is described. It has been commissioned and used at the FL24 beamline of the FLASH2 FEL, showing an electron kinetic energy resolution of ∆E/E ~ 40 and a pump-probe timing resolution of 190 f s. X-ray only photoelectron and Auger spectra of 2-thiouracil are extracted from the data and used as reference. Photoelectrons following the formation a 2p core hole are identified, as well as resonant and non-resonant Auger electrons. At the L 1 edge, Coster-Kronig decay is observed from the 2s core hole.
The UV-induced changes in the 2p photoline allow the study the electronic-state dynamics. With the use of an Excited-State Chemical Shift (ESCS) model, we observe a ultrafast ground-state relaxation within 250 f s. Furthermore, an oscillation with a 250 f s period is observed in the 2p binding energy, showing a coherent population exchange between electronic states. Auger electrons from the 2p core hole are analyzed and used to deduce a ultrafast C −S bond expansion on a sub 100 f s scale. A simple Coulomb-model, coupled to quantum chemical calculations, can be used to infer the geometrical changes in the molecular structure.
Organic solar cells offer an efficient and cost-effective alternative for solar energy harvesting. This type of photovoltaic cell typically consists of a blend of two organic semiconductors, an electron donating polymer and a low molecular weight electron acceptor to create what is known as a bulk heterojunction (BHJ) morphology. Traditionally, fullerene-based acceptors have been used for this purpose. In recent years, the development of new acceptor molecules, so-called non-fullerene acceptors (NFA), has breathed new life into organic solar cell research, enabling record efficiencies close to 19%. Today, NFA-based solar cells are approaching their inorganic competitors in terms of photocurrent generation, but lag in terms of open circuit voltage (V_OC). Interestingly, the V_OC of these cells benefits from small offsets of orbital energies at the donor-NFA interface, although previous knowledge considered large energy offsets to be critical for efficient charge carrier generation. In addition, there are several other electronic and structural features that distinguish NFAs from fullerenes.
My thesis focuses on understanding the interplay between the unique attributes of NFAs and the physical processes occurring in solar cells. By combining various experimental techniques with drift-diffusion simulations, the generation of free charge carriers as well as their recombination in state-of-the-art NFA-based solar cells is characterized. For this purpose, solar cells based on the donor polymer PM6 and the NFA Y6 have been investigated. The generation of free charge carriers in PM6:Y6 is efficient and independent of electric field and excitation energy. Temperature-dependent measurements show a very low activation energy for photocurrent generation (about 6 meV), indicating barrierless charge carrier separation. Theoretical modeling suggests that Y6 molecules have large quadrupole moments, leading to band bending at the donor-acceptor interface and thereby reducing the electrostatic Coulomb dissociation barrier. In this regard, this work identifies poor extraction of free charges in competition with nongeminate recombination as a dominant loss process in PM6:Y6 devices. Subsequently, the spectral characteristics of PM6:Y6 solar cells were investigated with respect to the dominant process of charge carrier recombination. It was found that the photon emission under open-circuit conditions can be almost entirely attributed to the occupation and recombination of Y6 singlet excitons. Nevertheless, the recombination pathway via the singlet state contributes only 1% to the total recombination, which is dominated by the charge transfer state (CT-state) at the donor-acceptor interface. Further V_OC gains can therefore only be expected if the density and/or recombination rate of these CT-states can be significantly reduced. Finally, the role of energetic disorder in NFA solar cells is investigated by comparing Y6 with a structurally related derivative, named N4. Layer morphology studies combined with temperature-dependent charge transport experiments show significantly lower structural and energetic disorder in the case of the PM6:Y6 blend. For both PM6:Y6 and PM6:N4, disorder determines the maximum achievable V_OC, with PM6:Y6 benefiting from improved morphological order. Overall, the obtained findings point to avenues for the realization of NFA-based solar cells with even smaller V_OC losses. Further reduction of nongeminate recombination and energetic disorder should result in organic solar cells with efficiencies above 20% in the future.
Weather extremes pose a persistent threat to society on multiple layers. Besides an average of ~37,000 deaths per year, climate-related disasters cause destroyed properties and impaired economic activities, eroding people's livelihoods and prosperity. While global temperature rises – caused by anthropogenic greenhouse gas emissions – the direct impacts of climatic extreme events increase and will further intensify without proper adaptation measures. Additionally, weather extremes do not only have local direct effects. Resulting economic repercussions can propagate either upstream or downstream along trade chains causing indirect effects. One approach to analyze these indirect effects within the complex global supply network is the agent-based model Acclimate. Using and extending this loss-propagation model, I focus in this thesis on three aspects of the relation between weather extremes and economic repercussions.
First, extreme weather events cause direct impacts on local economic performance. I compute daily local direct output loss time series of heat stress, river floods, tropical cyclones, and their consecutive occurrence using (near-future) climate projection ensembles. These regional impacts are estimated based on physical drivers and local productivity distribution. Direct effects of the aforementioned disaster categories are widely heterogeneous concerning regional and temporal distribution. As well, their intensity changes differently under future warming. Focusing on the hurricane-impacted capital, I find that long-term growth losses increase with higher heterogeneity of a shock ensemble.
Second, repercussions are sectorally and regionally distributed via economic ripples within the trading network, causing higher-order effects. I use Acclimate to identify three phases of those economic ripples. Furthermore, I compute indirect impacts and analyze overall regional and global production and consumption changes. Regarding heat stress, global consumer losses double while direct output losses increase by a factor 1.5 between 2000 – 2039. In my research I identify the effect of economic ripple resonance and introduce it to climate impact research. This effect occurs if economic ripples of consecutive disasters overlap, which increases economic responses such as an enhancement of consumption losses. These loss enhancements can even be more amplified with increasing direct output losses, e.g. caused by climate crises.
Transport disruptions can cause economic repercussions as well. For this, I extend the model Acclimate with a geographical transportation route and expand the decision horizon of economic agents. Using this, I show that policy-induced sudden trade restrictions (e.g. a no-deal Brexit) can significantly reduce the longer-term economic prosperity of affected regions. Analyses of transportation disruptions in typhoon seasons indicate that severely affected regions must reduce production as demand falls during a storm. Substituting suppliers may compensate for fluctuations at the beginning of the storm, which fails for prolonged disruptions.
Third, possible coping mechanisms and adaptation strategies arise from direct and indirect economic responses to weather extremes. Analyzing annual trade changes due to typhoon-induced transport disruptions depict that overall exports rise. This trade resilience increases with higher network node diversification. Further, my research shows that a basic insurance scheme may diminish hurricane-induced long-term growth losses due to faster reconstruction in disasters aftermaths. I find that insurance coverage could be an economically reasonable coping scheme towards higher losses caused by the climate crisis. Indirect effects within the global economic network from weather extremes indicate further adaptation possibilities. For one, diversifying linkages reduce the hazard of sharp price increases. Next to this, close economic interconnections with regions that do not share the same extreme weather season can be economically beneficial in the medium run. Furthermore, economic ripple resonance effects should be considered while computing costs. Overall, an increase in local adaptation measures reduces economic ripples within the trade network and possible losses elsewhere. In conclusion, adaptation measures are necessary and potential present, but it seems rather not possible to avoid all direct or indirect losses.
As I show in this thesis, dynamical modeling gives valuable insights into how direct and indirect economic impacts arise from different categories of weather extremes. Further, it highlights the importance of resolving individual extremes and reflecting amplifying effects caused by incomplete recovery or consecutive disasters.
In this thesis, the dependencies of charge localization and itinerance in two classes of aromatic molecules are accessed: pyridones and porphyrins. The focus lies on the effects of isomerism, complexation, solvation, and optical excitation, which are concomitant with different crucial biological applications of specific members of these groups of compounds. Several porphyrins play key roles in the metabolism of plants and animals. The nucleobases, which store the genetic information in the DNA and RNA are pyridone derivatives. Additionally, a number of vitamins are based on these two groups of substances.
This thesis aims to answer the question of how the electronic structure of these classes of molecules is modified, enabling the versatile natural functionality. The resulting insights into the effect of constitutional and external factors are expected to facilitate the design of new processes for medicine, light-harvesting, catalysis, and environmental remediation.
The common denominator of pyridones and porphyrins is their aromatic character. As aromaticity was an early-on topic in chemical physics, the overview of relevant theoretical models in this work also mirrors the development of this scientific field in the 20th century. The spectroscopic investigation of these compounds has long been centered on their global, optical transition between frontier orbitals.
The utilization and advancement of X-ray spectroscopic methods characterizing the local electronic structure of molecular samples form the core of this thesis. The element selectivity of the near-edge X-ray absorption fine structure (NEXAFS) is employed to probe the unoccupied density of states at the nitrogen site, which is key for the chemical reactivity of pyridones and porphyrins. The results contribute to the growing database of NEXAFS features and their interpretation, e.g., by advancing the debate on the porphyrin N K-edge through systematic experimental and theoretical arguments. Further, a state-of-the-art laser pump – NEXAFS probe scheme is used to characterize the relaxation pathway of a photoexcited porphyrin on the atomic level.
Resonant inelastic X-ray scattering (RIXS) provides complementary results by accessing the highest occupied valence levels including symmetry information. It is shown that RIXS is an effective experimental tool to gain detailed information on charge densities of individual species in tautomeric mixtures. Additionally, the hRIXS and METRIXS high-resolution RIXS spectrometers, which have been in part commissioned in the course of this thesis, will gain access to the ultra-fast and thermal chemistry of pyridones, porphyrins, and many other compounds.
With respect to both classes of bio-inspired aromatic molecules, this thesis establishes that even though pyridones and porphyrins differ largely by their optical absorption bands and hydrogen bonding abilities, they all share a global stabilization of local constitutional changes and relevant external perturbation. It is because of this wide-ranging response that pyridones and porphyrins can be applied in a manifold of biological and technical processes.
Poly(vinylidene fluoride) (PVDF)-based homo-, co- and ter-polymers are well-known for their ferroelectric and relaxor-ferroelectric properties. Their semi-crystalline morphology consists of crystalline and amorphous phases, plus interface regions in between, and governs the relevant electro-active properties. In this work, the influence of chemical, thermal and mechanical treatments on the structure and morphology of PVDF-based polymers and on the related ferroelectric/relaxor-ferroelectric properties is investigated. Polymer films were prepared in different ways and subjected to various treatments such as annealing, quenching and stretching. The resulting changes in the transitions and relaxations of the polymer samples were studied by means of dielectric, thermal, mechanical and optical techniques. In particular, the origin(s) behind the mysterious mid-temperature transition (T_{mid}) that is observed in all PVDF-based polymers was assessed. A new hypothesis is proposed to describe the T_{mid} transition as a result of multiple processes taking place within the temperature range of the transition. The contribution of the individual processes to the observed overall transition depends on both the chemical structure of the monomer units and the processing conditions which also affect the melting transition. Quenching results in a decrease of the overall crystallinity and in smaller crystallites. On samples quenched after annealing, notable differences in the fractions of different crystalline phases have been observed when compared to samples that had been slowly cooled. Stretching of poly(vinylidene fluoride-tetrafluoroethylene) (P(VDF-TFE)) films causes an increase in the fraction of the ferroelectric β-phase with simultaneous increments in the melting point (T_m) and the crystallinity (\chi_c) of the copolymer. While an increase in the stretching temperature does not have a profound effect on the amount of the ferroelectric phase, its stability appears to improve.
Measurements of the non-linear dielectric permittivity \varepsilon_2^\prime in a poly(vinylidenefluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE- CFE)) relaxor-ferroelectric (R-F) terpolymer reveal peaks at 30 and 80 °C that cannot be identified in conventional dielectric spectroscopy. The former peak is associated with T_{mid}\ and may help to understand the non-zero \varepsilon_2^\prime values that are found for the paraelectric terpolymer phase. The latter peak can also be observed during cooling of P(VDF-TrFE) copolymer samples at 100 °C and is due to conduction processes and space-charge polarization as a result of the accumulation of real charges at the electrode-sample interface. Annealing lowers the Curie-transition temperature of the terpolymer as a consequence of its smaller ferroelectric-phase fraction, which by default exists even in terpolymers with relatively high CFE content. Changes in the transition temperatures are in turn related to the behavior of the hysteresis curves observed on differently heat-treated samples. Upon heating, the hysteresis curves evolve from those known for a ferroelectric to those of a typical relaxor-ferroelectric material. Comparing dielectric-hysteresis loops obtained at various temperatures, we find that annealed terpolymer films show higher electric-displacement values and lower coercive fields than the non-annealed samples − irrespective of the measurement temperature − and also exhibit ideal relaxor-ferroelectric behavior at ambient temperatures, which makes them excellent candidates for related applications at or near room temperature. However, non-annealed films − by virtue of their higher ferroelectric activity − show a larger and more stable remanent polarization at room temperature, while annealed samples need to be poled below 0 °C to induce a well-defined polarization. Overall, by modifying the three phases in PVDF-based polymers, it has been demonstrated how the preparation steps and processing conditions can be tailored to achieve the desired properties that are optimal for specific applications.
The current generation of ground-based instruments has rapidly extended the limits of the range accessible to us with very-high-energy (VHE) gamma-rays, and more than a hundred sources have now been detected in the Milky Way. These sources represent only the tip of the iceberg, but their number has reached a level that allows population studies. In this work, a model of the global population of VHE gamma-ray sources based on the most comprehensive census of Galactic sources in this energy regime, the H.E.S.S. Galactic plane survey (HGPS), will be presented. A population synthesis approach was followed in the construction of the model. Particular attention was paid to correcting for the strong observational bias inherent in the sample of detected sources. The methods developed for estimating the model parameters have been validated with extensive Monte Carlo simulations and will be shown to provide unbiased estimates of the model parameters. With these methods, five models for different spatial distributions of sources have been constructed. To test the validity of these models, their predictions for the composition of sources within the sensitivity range of the HGPS are compared with the observed sample. With one exception, similar results are obtained for all spatial distributions, showing that the observed longitude profile and the source distribution over photon flux are in fair agreement with observation. Regarding the latitude profile and the source distribution over angular extent, it becomes apparent that the model needs to be further adjusted to bring its predictions in agreement with observation. Based on the model, predictions of the global properties of the Galactic population of VHE gamma-ray sources and the prospects of the Cherenkov Telescope Array (CTA) will be presented.
CTA will significantly increase our knowledge of VHE gamma-ray sources by lowering the threshold for source detection, primarily through a larger detection area compared to current-generation instruments. In ground-based gamma-ray astronomy, the sensitivity of an instrument depends strongly, in addition to the detection area, on the ability to distinguish images of air showers produced by gamma-rays from those produced by cosmic rays, which are a strong background. This means that the number of detectable sources depends on the background rejection algorithm used and therefore may also be increased by improving the performance of such algorithms. In this context, in addition to the population model, this work presents a study on the application of deep-learning techniques to the task of gamma-hadron separation in the analysis of data from ground-based gamma-ray instruments. Based on a systematic survey of different neural-network architectures, it is shown that robust classifiers can be constructed with competitive performance compared to the best existing algorithms. Despite the broad coverage of neural-network architectures discussed, only part of the potential offered by the
application of deep-learning techniques to the analysis of gamma-ray data is exploited in the context of this study. Nevertheless, it provides an important basis for further research on this topic.
In the frame of a world fighting a dramatic global warming caused by human-related activities, research towards the development of renewable energies plays a crucial role. Solar energy is one of the most important clean energy sources and its role in the satisfaction of the global energy demand is set to increase. In this context, a particular class of materials captured the attention of the scientific community for its attractive properties: halide perovskites. Devices with perovskite as light-absorber saw an impressive development within the last decade, reaching nowadays efficiencies comparable to mature photovoltaic technologies like silicon solar cells. Yet, there are still several roadblocks to overcome before a wide-spread commercialization of this kind of devices is enabled. One of the critical points lies at the interfaces: perovskite solar cells (PSCs) are made of several layers with different chemical and physical features. In order for the device to function properly, these properties have to be well-matched.
This dissertation deals with some of the challenges related to interfaces in PSCs, with a focus on the interface between the perovskite material itself and the subsequent charge transport layer. In particular, molecular assemblies with specific properties are deposited on the perovskite surface to functionalize it. The functionalization results in energy level alignment adjustment, interfacial losses reduction, and stability improvement.
First, a strategy to tune the perovskite’s energy levels is introduced: self-assembled monolayers of dipolar molecules are used to functionalize the surface, obtaining simultaneously a shift in the vacuum level position and a saturation of the dangling bonds at the surface. A shift in the vacuum level corresponds to an equal change in work function, ionization energy, and electron affinity. The direction of the shift depends on the direction of the collective interfacial dipole. The magnitude of the shift can be tailored by controlling the deposition parameters, such as the concentration of the solution used for the deposition. The shift for different molecules is characterized by several non-invasive techniques, including in particular Kelvin probe. Overall, it is shown that it is possible to shift the perovskite energy levels in both directions by several hundreds of meV. Moreover, interesting insights on the molecules deposition dynamics are revealed.
Secondly, the application of this strategy in perovskite solar cells is explored. Devices with different perovskite compositions (“triple cation perovskite” and MAPbBr3) are prepared. The two resulting model systems present different energetic offsets at the perovskite/hole-transport layer interface. Upon tailored perovskite surface functionalization, the devices show a stabilized open circuit voltage (Voc) enhancement of approximately 60 meV on average for devices with MAPbBr3, while the impact is limited on triple-cation solar cells. This suggests that the proposed energy level tuning method is valid, but its effectiveness depends on factors such as the significance of the energetic offset compared to the other losses in the devices.
Finally, the above presented method is further developed by incorporating the ability to interact with the perovskite surface directly into a novel hole-transport material (HTM), named PFI. The HTM can anchor to the perovskite halide ions via halogen bonding (XB). Its behaviour is compared to that of another HTM (PF) with same chemical structure and properties, except for the ability of forming XB. The interaction of perovskite with PFI and PF is characterized through UV-Vis, atomic force microscopy and Kelvin probe measurements combined with simulations. Compared to PF, PFI exhibits enhanced resilience against solvent exposure and improved energy level alignment with the perovskite layer. As a consequence, devices comprising PFI show enhanced Voc and operational stability during maximum-power-point tracking, in addition to hysteresis reduction. XB promotes the formation of a high-quality interface by anchoring to the halide ions and forming a stable and ordered interfacial layer, showing to be a particularly interesting candidate for the development of tailored charge transport materials in PSCs.
Overall, the results exposed in this dissertation introduce and discuss a versatile tool to functionalize the perovskite surface and tune its energy levels. The application of this method in devices is explored and insights on its challenges and advantages are given. Within this frame, the results shed light on XB as ideal interaction for enhancing stability and efficiency in perovskite-based devices.
Organic solar cells (OSCs), in recent years, have shown high efficiencies through the development of novel non-fullerene acceptors (NFAs). Fullerene derivatives have been the centerpiece of the accepting materials used throughout organic photovoltaic (OPV) research. However, since 2015 novel NFAs have been a game-changer and have overtaken fullerenes. However, the current understanding of the properties of NFAs for OPV is still relatively limited and critical mechanisms defining the performance of OPVs are still topics of debate.
In this thesis, attention is paid to understanding reduced-Langevin recombination with respect to the device physics properties of fullerene and non-fullerene systems. The work is comprised of four closely linked studies. The first is a detailed exploration of the fill factor (FF) expressed in terms of transport and recombination properties in a comparison of fullerene and non-fullerene acceptors. We investigated the key reason behind the reduced FF in the NFA (ITIC-based) devices which is faster non-geminate recombination relative to the fullerene (PCBM[70]-based) devices. This is then followed by a consideration of a newly synthesized NFA Y-series derivative which exhibits the highest power conversion efficiency for OSC at the time. Such that in the second study, we illustrated the role of disorder on the non-geminate recombination and charge extraction of thick NFA (Y6-based) devices. As a result, we enhanced the FF of thick PM6:Y6 by reducing the disorder which leads to suppressing the non-geminate recombination toward non-Langevin system. In the third work, we revealed the reason behind thickness independence of the short circuit current of PM6:Y6 devices, caused by the extraordinarily long diffusion length of Y6. The fourth study entails a broad comparison of a selection of fullerene and non-fullerene blends with respect to charge generation efficiency and recombination to unveil the importance of efficient charge generation for achieving reduced recombination.
I employed transient measurements such as Time Delayed Collection Field (TDCF), Resistance dependent Photovoltage (RPV), and steady-state techniques such as Bias Assisted Charge Extraction (BACE), Temperature-Dependent Space Charge Limited Current (T-SCLC), Capacitance-Voltage (CV), and Photo-Induce Absorption (PIA), to analyze the OSCs.
The outcomes in this thesis together draw a complex picture of multiple factors that affect reduced-Langevin recombination and thereby the FF and overall performance. This provides a suitable platform for identifying important parameters when designing new blend systems. As a result, we succeeded to improve the overall performance through enhancing the FF of thick NFA device by adjustment of the amount of the solvent additive in the active blend solution. It also highlights potentially critical gaps in the current experimental understanding of fundamental charge interaction and recombination dynamics.
Extending synchrotron X-ray refraction techniques to the quantitative analysis of metallic materials
(2022)
In this work, two X-ray refraction based imaging methods, namely, synchrotron X-ray refraction radiography (SXRR) and synchrotron X-ray refraction computed tomography (SXRCT), are applied to analyze quantitatively cracks and porosity in metallic materials. SXRR and SXRCT make use of the refraction of X-rays at inner surfaces of the material, e.g., the surfaces of cracks and pores, for image contrast. Both methods are, therefore, sensitive to smaller defects than their absorption based counterparts X-ray radiography and computed tomography. They can detect defects of nanometric size. So far the methods have been applied to the analysis of ceramic materials and fiber reinforced plastics. The analysis of metallic materials requires higher photon energies to achieve sufficient X-ray transmission due to their higher density. This causes smaller refraction angles and, thus, lower image contrast because the refraction index depends on the photon energy. Here, for the first time, a conclusive study is presented exploring the possibility to apply SXRR and SXRCT to metallic materials. It is shown that both methods can be optimized to overcome the reduced contrast due to smaller refraction angles. Hence, the only remaining limitation is the achievable X-ray transmission which is common to all X-ray imaging methods. Further, a model for the quantitative analysis of the inner surfaces is presented and verified.
For this purpose four case studies are conducted each posing a specific challenge to the imaging task. Case study A investigates cracks in a coupon taken from an aluminum weld seam. This case study primarily serves to verify the model for quantitative analysis and prove the sensitivity to sub-resolution features. In case study B, the damage evolution in an aluminum-based particle reinforced metal-matrix composite is analyzed. Here, the accuracy and repeatability of subsequent SXRR measurements is investigated showing that measurement errors of less than 3 % can be achieved. Further, case study B marks the fist application of SXRR in combination with in-situ tensile loading. Case study C is out of the highly topical field of additive manufacturing. Here, porosity in additively manufactured Ti-Al6-V4 is analyzed with a special interest in the pore morphology. A classification scheme based on SXRR measurements is devised which allows to distinguish binding defects from keyhole pores even if the defects cannot be spatially resolved. In case study D, SXRCT is applied to the analysis of hydrogen assisted cracking in steel. Due to the high X-ray attenuation of steel a comparatively high photonenergy of 50 keV is required here. This causes increased noise and lower contrast in the data compared to the other case studies. However, despite the lower data quality a quantitative analysis of the occurance of cracks in dependence of hydrogen content and applied mechanical load is possible.
In our daily life, recurrence plays an important role on many spatial and temporal scales and in different contexts. It is the foundation of learning, be it in an evolutionary or in a neural context. It therefore seems natural that recurrence is also a fundamental concept in theoretical dynamical systems science. The way in which states of a system recur or develop in a similar way from similar initial states makes it possible to infer information about the underlying dynamics of the system. The mathematical space in which we define the state of a system (state space) is often high dimensional, especially in complex systems that can also exhibit chaotic dynamics. The recurrence plot (RP) enables us to visualize the recurrences of any high-dimensional systems in a two-dimensional, binary representation. Certain patterns in RPs can be related to physical properties of the underlying system, making the qualitative and quantitative analysis of RPs an integral part of nonlinear systems science. The presented work has a methodological focus and further develops recurrence analysis (RA) by addressing current research questions related to an increasing amount of available data and advances in machine learning techniques. By automatizing a central step in RA, namely the reconstruction of the state space from measured experimental time series, and by investigating the impact of important free parameters this thesis aims to make RA more accessible to researchers outside of physics.
The first part of this dissertation is concerned with the reconstruction of the state space from time series. To this end, a novel idea is proposed which automates the reconstruction problem in the sense that there is no need to preprocesse the data or estimate parameters a priori. The key idea is that the goodness of a reconstruction can be evaluated by a suitable objective function and that this function is minimized in the embedding process. In addition, the new method can process multivariate time series input data. This is particularly important because multi-channel sensor-based observations are ubiquitous in many research areas and continue to increase. Building on this, the described minimization problem of the objective function is then processed using a machine learning approach.
In the second part technical and methodological aspects of RA are discussed. First, we mathematically justify the idea of setting the most influential free parameter in RA, the recurrence threshold ε, in relation to the distribution of all pairwise distances in the data. This is especially important when comparing different RPs and their quantification statistics and is fundamental to any comparative study. Second, some aspects of recurrence quantification analysis (RQA) are examined. As correction schemes for biased RQA statistics, which are based on diagonal lines, we propose a simple method for dealing with border effects of an RP in RQA and a skeletonization algorithm for RPs. This results in less biased (diagonal line based) RQA statistics for flow-like data. Third, a novel type of RQA characteristic is developed, which can be viewed as a generalized non-linear powerspectrum of high dimensional systems. The spike powerspectrum transforms a spike-train like signal into its frequency domain. When transforming the diagonal line-dependent recurrence rate (τ-RR) of a RP in this way, characteristic periods, which can be seen in the state space representation of the system can be unraveled. This is not the case, when Fourier transforming τ-RR.
Finally, RA and RQA are applied to climate science in the third part and neuroscience in the fourth part. To the best of our knowledge, this is the first time RPs and RQA have been used to analyze lake sediment data in a paleoclimate context. Therefore, we first elaborate on the basic formalism and the interpretation of visually visible patterns in RPs in relation to the underlying proxy data. We show that these patterns can be used to classify certain types of variability and transitions in the Potassium record from six short (< 17m) sediment cores collected during the Chew Bahir Drilling Project. Building on this, the long core (∼ m composite) from the same site is analyzed and two types of variability and transitions are
identified and compared with ODP Site wetness index from the eastern Mediterranean. Type variability likely reflects the influence of precessional forcing in the lower latitudes at times of maximum values of the long eccentricity cycle ( kyr) of the earth’s orbit around the sun, with a tendency towards extreme events. Type variability appears to be related to the minimum values of this cycle and corresponds to fairly rapid transitions between relatively dry and relatively wet conditions.
In contrast, RQA has been applied in the neuroscientific context for almost two decades. In the final part, RQA statistics are used to quantify the complexity in a specific frequency band of multivariate EEG (electroencephalography) data. By analyzing experimental data, it can be shown that the complexity of the signal measured in this way across the sensorimotor cortex decreases as motor tasks are performed. The results are consistent with and comple- ment the well known concepts of motor-related brain processes. We assume that the thus discovered features of neuronal dynamics in the sensorimotor cortex together with the robust RQA methods for identifying and classifying these contribute to the non-invasive EEG-based development of brain-computer interfaces (BCI) for motor control and rehabilitation.
The present work is an important step towards a robust analysis of complex systems based on recurrence.
Magnetic strain contributions in laser-excited metals studied by time-resolved X-ray diffraction
(2021)
In this work I explore the impact of magnetic order on the laser-induced ultrafast strain response of metals. Few experiments with femto- or picosecond time-resolution have so far investigated magnetic stresses. This is contrasted by the industrial usage of magnetic invar materials or magnetostrictive transducers for ultrasound generation, which already utilize magnetostrictive stresses in the low frequency regime.
In the reported experiments I investigate how the energy deposition by the absorption of femtosecond laser pulses in thin metal films leads to an ultrafast stress generation. I utilize that this stress drives an expansion that emits nanoscopic strain pulses, so called hypersound, into adjacent layers. Both the expansion and the strain pulses change the average inter-atomic distance in the sample, which can be tracked with sub-picosecond time resolution using an X-ray diffraction setup at a laser-driven Plasma X-ray source. Ultrafast X-ray diffraction can also be applied to buried layers within heterostructures that cannot be accessed by optical methods, which exhibit a limited penetration into metals. The reconstruction of the initial energy transfer processes from the shape of the strain pulse in buried detection layers represents a contribution of this work to the field of picosecond ultrasonics.
A central point for the analysis of the experiments is the direct link between the deposited energy density in the nano-structures and the resulting stress on the crystal lattice. The underlying thermodynamical concept of a Grüneisen parameter provides the theoretical framework for my work. I demonstrate how the Grüneisen principle can be used for the interpretation of the strain response on ultrafast timescales in various materials and that it can be extended to describe magnetic stresses. The class of heavy rare-earth elements exhibits especially large magnetostriction effects, which can even lead to an unconventional contraction of the laser-excited transducer material. Such a dominant contribution of the magnetic stress to the motion of atoms has not been demonstrated previously. The observed rise time of the magnetic stress contribution in Dysprosium is identical to the decrease in the helical spin-order, that has been found previously using time-resolved resonant X-ray diffraction. This indicates that the strength of the magnetic stress can be used as a proxy of the underlying magnetic order. Such magnetostriction measurements are applicable even in case of antiparallel or non-collinear alignment of the magnetic moments and a vanishing magnetization.
The strain response of metal films is usually determined by the pressure of electrons and lattice vibrations. I have developed a versatile two-pulse excitation routine that can be used to extract the magnetic contribution to the strain response even if systematic measurements above and below the magnetic ordering temperature are not feasible. A first laser pulse leads to a partial ultrafast demagnetization so that the amplitude and shape of the strain response triggered by the second pulse depends on the remaining magnetic order. With this method I could identify a strongly anisotropic magnetic stress contribution in the magnetic data storage material iron-platinum and identify the recovery of the magnetic order by the variation of the pulse-to-pulse delay. The stark contrast of the expansion of iron-platinum nanograins and thin films shows that the different constraints for the in-plane expansion have a strong influence on the out-of-plane expansion, due to the Poisson effect. I show how such transverse strain contributions need to be accounted for when interpreting the ultrafast out-of-plane strain response using thermal expansion coefficients obtained in near equilibrium conditions.
This work contributes an investigation of magnetostriction on ultrafast timescales to the literature of magnetic effects in materials. It develops a method to extract spatial and temporal varying stress contributions based on a model for the amplitude and shape of the emitted strain pulses. Energy transfer processes result in a change of the stress profile with respect to the initial absorption of the laser pulses. One interesting example occurs in nanoscopic gold-nickel heterostructures, where excited electrons rapidly transport energy into a distant nickel layer, that takes up much more energy and expands faster and stronger than the laser-excited gold capping layer. Magnetic excitations in rare earth materials represent a large energy reservoir that delays the energy transfer into adjacent layers. Such magneto-caloric effects are known in thermodynamics but not extensively covered on ultrafast timescales. The combination of ultrafast X-ray diffraction and time-resolved techniques with direct access to the magnetization has a large potential to uncover and quantify such energy transfer processes.
The evolution of life on Earth has been driven by disturbances of different types and magnitudes over the 4.6 million years of Earth’s history (Raup, 1994, Alroy, 2008). One example for such disturbances are mass extinctions which are characterized by an exceptional increase in the extinction rate affecting a great number of taxa in a short interval of geologic time (Sepkoski, 1986). During the 541 million years of the Phanerozoic, life on Earth suffered five exceptionally severe mass extinctions named the “Big Five Extinctions”. Many mass extinctions are linked to changes in climate
(Feulner, 2009). Hence, the study of past mass extinctions is not only intriguing, but can also provide insights into the complex nature of the Earth system. This thesis aims at deepening our understanding of the triggers of mass extinctions and how they affected life. To accomplish this, I investigate changes in climate during two of the Big Five extinctions using a coupled climate model.
During the Devonian (419.2–358.9 million years ago) the first vascular plants and vertebrates evolved on land while extinction events occurred in the ocean (Algeo et al., 1995). The causes of these formative changes, their interactions and their links to changes in climate are still poorly understood. Therefore, we explore the sensitivity of the Devonian climate to various boundary conditions using an intermediate-complexity climate model (Brugger et al., 2019). In contrast to Le Hir et al. (2011), we find only a minor biogeophysical effect of changes in vegetation cover due to unrealistically high soil albedo values used in the earlier study. In addition, our results cannot support the strong influence of orbital parameters on the Devonian climate, as simulated with a climate model with a strongly simplified ocean model (De Vleeschouwer et al., 2013, 2014, 2017). We can only reproduce the changes in Devonian climate suggested by proxy data by decreasing atmospheric CO2. Still, finding agreement between the evolution of sea surface temperatures reconstructed from proxy data (Joachimski et al., 2009) and our simulations remains challenging and suggests a lower δ18O ratio of Devonian seawater. Furthermore, our study of the sensitivity of the Devonian climate reveals a prevailing mode of climate variability on a timescale of decades to centuries. The quasi-periodic ocean temperature fluctuations are linked to a physical mechanism of changing sea-ice cover, ocean convection and overturning in high northern latitudes.
In the second study of this thesis (Dahl et al., under review) a new reconstruction of atmospheric CO2 for the Devonian, which is based on CO2-sensitive carbon isotope fractionation in the earliest vascular plant fossils, suggests a much earlier drop of atmo- spheric CO2 concentration than previously reconstructed, followed by nearly constant CO2 concentrations during the Middle and Late Devonian. Our simulations for the Early Devonian with identical boundary conditions as in our Devonian sensitivity study (Brugger et al., 2019), but with a low atmospheric CO2 concentration of 500 ppm, show no direct conflict with available proxy and paleobotanical data and confirm that under the simulated climatic conditions carbon isotope fractionation represents a robust proxy for atmospheric CO2. To explain the earlier CO2 drop we suggest that early forms of vascular land plants have already strongly influenced weathering. This new perspective on the Devonian questions previous ideas about the climatic conditions and earlier explanations for the Devonian mass extinctions.
The second mass extinction investigated in this thesis is the end-Cretaceous mass extinction (66 million years ago) which differs from the Devonian mass extinctions in terms of the processes involved and the timescale on which the extinctions occurred. In the two studies presented here (Brugger et al., 2017, 2021), we model the climatic effects of the Chicxulub impact, one of the proposed causes of the end-Cretaceous extinction, for the first millennium after the impact. The light-dimming effect of stratospheric sulfate aerosols causes severe cooling, with a decrease of global annual mean surface air temperature of at least 26◦C and a recovery to pre-impact temperatures after more than 30 years. The sudden surface cooling of the ocean induces deep convection which brings nutrients from the deep ocean via upwelling to the surface ocean. Using an ocean biogeochemistry model we explore the combined effect of ocean mixing and iron-rich dust originating from the impactor on the marine biosphere. As soon as light levels have recovered, we find a short, but prominent peak in marine net primary productivity. This newly discovered mechanism could result in toxic effects for marine near-surface ecosystems. Comparison of our model results to proxy data (Vellekoop et al., 2014, 2016, Hull et al., 2020) suggests that carbon release from the terrestrial biosphere is required in addition to the carbon dioxide which can be attributed to the target material. Surface ocean acidification caused by the addition of carbon dioxide and sulfur is only moderate. Taken together, the results indicate a significant contribution of the Chicxulub impact to the end-Cretaceous mass extinction by triggering multiple stressors for the Earth system.
Although the sixth extinction we face today is characterized by human intervention in nature, this thesis shows that we can gain many insights into future extinctions from studying past mass extinctions, such as the importance of the rate of change (Rothman, 2017), the interplay of multiple stressors (Gunderson et al., 2016), and changes in the carbon cycle (Rothman, 2017, Tierney et al., 2020).
Halide perovskites are a class of novel photovoltaic materials that have recently attracted much attention in the photovoltaics research community due to their highly promising optoelectronic properties, including large absorption coefficients and long carrier lifetimes. The charge carrier mobility of halide perovskites is investigated in this thesis by THz spectroscopy, which is a contact-free technique that yields the intra-grain sum mobility of electrons and holes
in a thin film.
The polycrystalline halide perovskite thin films, provided from Potsdam University, show moderate mobilities in the range from 21.5 to 33.5 cm2V-1s-1. It is shown in this work that the room temperature mobility is limited by charge carrier scattering at polar optical phonons. The mobility at low temperature is likely to be limited by scattering at charged and neutral impurities at impurity concentration N=1017-1018 cm-3. Furthermore, it is shown that exciton formation
may decrease the mobility at low temperatures. Scattering at acoustic phonons can be neglected at both low and room temperatures. The analysis of mobility spectra over a broad range of temperatures for perovskites with various cation compounds shows that cations have a minor impact on charge carrier mobility.
The low-dimensional thin films of quasi-2D perovskite with different numbers of [PbI6]4−sheets (n=2-4) alternating with long organic spacer molecules were provided by S. Zhang from Potsdam University. They exhibit mobilities in the range from 3.7 to 8 cm2V-1s-1. A clear
decrease of mobility is observed with decrease in number of metal-halide sheets n, which likely arises from charge carrier confinement within metal-halide layers. Modelling the measured THz mobility with the modified Drude-Smith model yields localization length from 0.9 to 3.7 nm, which agrees well on the thicknesses of the metal-halide layers. Additionally, the mobilities are found to be dependent on the orientation of the layers. The charge carrier dynamics is also
dependent on the number of metal-halide sheets n. For the thin films with n =3-4 the dynamics is similar to the 3D MHPs. However, the thin film with n = 2 shows clearly different dynamics, where the signs of exciton formation are observed within 390 fs timeframe after
photoexcitation.
Also, the charge carrier dynamics of CsPbI3 perovskite nanocrystals was investigated, in particular the effect of post treatments on the charge carrier transport.
Filaments are omnipresent features in the solar chromosphere, one of the atmospheric layers of the Sun, which is located above the photosphere, the visible surface of the Sun. They are clouds of plasma reaching from the photosphere to the chromosphere, and even to the outer-most atmospheric layer, the corona. They are stabalized by the magnetic field. If the magnetic field is disturbed, filaments can erupt as coronal mass ejections (CME), releasing plasma into space, which can also hit the Earth. A special type of filaments are polar crown filaments, which form at the interface of the unipolar field of the poles and flux of opposite magnetic polarity, which was transported towards the poles. This flux transport is related to the global dynamo of the Sun and can therefore be analyzed indirectly with polar crown filaments. The main objective of this thesis is to better understand the physical properties and environment of high-latitude and polar crown filaments, which can be approached from two perspectives: (1) analyzing the large-scale properties of high-latitude and polar crown filaments with full-disk Hα observations from the Chromospheric Telescope (ChroTel) and (2) determining the relation of polar crown and high-latitude filaments from the chromosphere to the lower-lying photosphere with high-spatial resolution observations of the Vacuum Tower Telescope (VTT), which reveal the smallest details.
The Chromospheric Telescope (ChroTel) is a small 10-cm robotic telescope at Observatorio del Teide on Tenerife (Spain), which observes the entire Sun in Hα, Ca IIK, and He I 10830 Å. We present a new calibration method that includes limb-darkening correction, removal of non-uniform filter transmission, and determination of He I Doppler velocities. Chromospheric full-disk filtergrams are often obtained with Lyot filters, which may display non-uniform transmission causing large-scale intensity variations across the solar disk. Removal of a 2D symmetric limb-darkening function from full-disk images results in a flat background. However, transmission artifacts remain and are even more distinct in these contrast-enhanced images. Zernike polynomials are uniquely appropriate to fit these large-scale intensity variations of the background. The Zernike coefficients show a distinct temporal evolution for ChroTel data, which is likely related to the telescope’s alt-azimuth mount that introduces image rotation. In addition, applying this calibration to sets of seven filtergrams that cover the He I triplet facilitates determining chromospheric Doppler velocities. To validate the method, we use three datasets with varying levels of solar activity. The Doppler velocities are benchmarked with respect to co-temporal high-resolution spectroscopic data of the GREGOR Infrared Spectrograph (GRIS). Furthermore, this technique can be applied to ChroTel Hα and Ca IIK data. The calibration method for ChroTel filtergrams can be easily adapted to other full-disk data exhibiting unwanted large-scale variations. The spectral region of the He I triplet is a primary choice for high-resolution near-infrared spectropolarimetry. Here, the improved calibration of ChroTel data will provide valuable context data.
Polar crown filaments form above the polarity inversion line between the old magnetic flux of the previous cycle and the new magnetic flux of the current cycle. Studying their appearance and their properties can lead to a better understanding of the solar cycle. We use full-disk data of the ChroTel at Observatorio del Teide, Tenerife, Spain, which were taken in three different chromospheric absorption lines (Hα 6563 Å, Ca IIK 3933 Å, and He I 10830 Å), and we create synoptic maps. In addition, the spectroscopic He I data allow us to compute Doppler velocities and to create synoptic Doppler maps. ChroTel data cover the rising and decaying phase of Solar Cycle 24 on about 1000 days between 2012 and 2018. Based on these data, we automatically extract polar crown filaments with image-processing tools and study their properties. We compare contrast maps of polar crown filaments with those of quiet-Sun filaments. Furthermore, we present a super-synoptic map summarizing the entire ChroTel database. In summary, we provide statistical properties, i.e. number and location of filaments, area, and tilt angle for both the maximum and declining phase of Solar Cycle 24. This demonstrates that ChroTel provides a
promising dataset to study the solar cycle.
The cyclic behavior of polar crown filaments can be monitored by regular full-disk Hα observations. ChroTel provides such regular observations of the Sun in three chromospheric wavelengths. To analyze the cyclic behavior and the statistical properties of polar crown filaments, we have to extract the filaments from the images. Manual extraction is tedious, and extraction with morphological image processing tools produces a large number of false positive detections and the manual extraction of these takes too much time. Automatic object detection and extraction in a reliable manner allows us to process more data in a shorter time. We will present an overview of the ChroTel database and a proof of concept of a machine learning application, which allows us a unified extraction of, for example, filaments from ChroTel data.
The chromospheric Hα spectral line dominates the spectrum of the Sun and other stars. In the stellar regime, this spectral line is already used as a powerful tracer of magnetic activity. For the Sun, other tracers are typically used to monitor solar activity. Nonetheless, the Sun is observed constantly in Hα with globally distributed ground-based full-disk imagers. The aim of this study is to introduce Hα as a tracer of solar activity and compare it to other established indicators. We discuss the newly created imaging Hα excess in the perspective of possible application for modelling of stellar atmospheres. In particular, we try to determine how constant is the mean intensity of the Hα excess and number density of low-activity regions between solar maximum and minimum. Furthermore, we investigate whether the active region coverage fraction or the changing emission strength in the active regions dominates time variability in solar Hα observations. We use ChroTel observations of full-disk Hα filtergrams and morphological image processing techniques to extract the positive and negative imaging Hα excess, for bright features (plage regions) and dark absorption features (filaments and sunspots), respectively. We describe the evolution of the Hα excess during Solar Cycle 24 and compare it to other well established tracers: the relative sunspot number, the F10.7 cm radio flux, and the Mg II index. Moreover, we discuss possible applications of the Hα excess for stellar activity diagnostics and the contamination of exoplanet transmission spectra. The positive and negative Hα excess follow the behavior of the solar activity over the course of the cycle. Thereby, positive Hα excess is closely correlated to the chromospheric Mg II index. On the other hand, the negative Hα excess, created from dark features like filaments and sunspots, is introduced as a tracer of solar activity for the first time. We investigated the mean intensity distribution for active regions for solar minimum and maximum and found that the shape of both distributions is very similar but with different amplitudes. This might be related with the relatively stable coronal temperature component during the solar cycle. Furthermore, we found that the coverage fraction of Hα excess and the Hα excess of bright features are strongly correlated, which will influence modelling of stellar and exoplanet atmospheres.
High-resolution observations of polar crown and high-latitude filaments are scarce. We present a unique sample of such filaments observed in high-resolution Hα narrow-band filtergrams and broad-band images, which were obtained with a new fast camera system at the VTT. ChroTel provided full-disk context observations in Hα, Ca IIK, and He I 10830 Å. The Helioseismic and Magnetic Imager (HMI) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) provided line-of-sight magnetograms and ultraviolet (UV) 1700 Å filtergrams, respectively. We study filigree in the vicinity of polar crown and high-latitude filaments and relate their locations to magnetic concentrations at the filaments’ footpoints. Bright points are a well studied phenomenon in the photosphere at low latitudes, but they were not yet studied in the quiet network close to the poles. We examine size, area, and eccentricity of bright points and find that their morphology is very similar to their counterparts at lower latitudes, but their sizes and areas are larger. Bright points at the footpoints of polar crown filaments are preferentially located at stronger magnetic flux concentrations, which are related to bright regions at the border of supergranules as observed in UV filtergrams. Examining the evolution of bright points on three consecutive days reveals that their amount increases while the filament decays, which indicates they impact the equilibrium of the cool plasma contained in filaments.
Selfsustained oscillations are some of the most commonly observed phenomena in biological systems. They emanate from non-linear systems in a heterogeneous environment and can be described by the theory of dynamical systems. Part of this theory considers reduced models of the oscillator dynamics by means of amplitudes and a phase variable. Such variables are highly attractive for theoretical and experimental studies. Theoretically these variables correspond to an integrable linearization of the generally non-linear system. Experimentally, there exist well established approaches to extract phases from oscillator signals. Notably, one can define phase models also for networks of oscillators. One highly active field examines effects of non-local coupling among oscillators, which is thought to play a key role in networks with strong coupling. The dissertation introduces and expands the knowledge about high-order phase coupling in networks of oscillators. Mathematical calculations consider the Stuart-Landau oscillator. A novel phase estimation scheme for direct observations of an oscillator dynamics is introduced based on numerics. A numerical study of high-order phase coupling applies a Fourier fit for the Stuart-Landau and for the van-der-Pol oscillator. The numerical approach is finally tested on observation-based phase estimates of the Morris-Lecar neuron. A popular approach for the construction of phases from signals is based on phase demodulation by means of the Hilbert transform. Generally, observations of oscillations contain a small and generic variation of their amplitude. The work presents a way to quantify how much the variations of signal amplitude spoil a phase demodulation procedure. For the ideal case of phase modulated signals, amplitude modulations vanish. However, the Hilbert transform produces artificial variations of the reconstructed amplitude even in this case. The work proposes a novel procedure called Iterative Hilbert Transform Embedding to obtain an optimal demodulation of signals. The text presents numerous examples and tests of application for the method, covering multicomponent signals, observables of highly stable limit cycle oscillations and noisy phase dynamics. The numerical results are supported by a spectral theory of convergence for weak phase modulations.
Noise is ubiquitous in nature and usually results in rich dynamics in stochastic systems such as oscillatory systems, which exist in such various fields as physics, biology and complex networks. The correlation and synchronization of two or many oscillators are widely studied topics in recent years.
In this thesis, we mainly investigate two problems, i.e., the stochastic bursting phenomenon in noisy excitable systems and synchronization in a three-dimensional Kuramoto model with noise. Stochastic bursting here refers to a sequence of coherent spike train, where each spike has random number of followers due to the combined effects of both time delay and noise. Synchronization, as a universal phenomenon in nonlinear dynamical systems, is well illustrated in the Kuramoto model, a prominent model in the description of collective motion.
In the first part of this thesis, an idealized point process, valid if the characteristic timescales in the problem are well separated, is used to describe statistical properties such as the power spectral density and the interspike interval distribution. We show how the main parameters of the point process, the spontaneous excitation rate, and the probability to induce a spike during the delay action can be calculated from the solutions of a stationary and a forced Fokker-Planck equation. We extend it to the delay-coupled case and derive analytically the statistics of the spikes in each neuron, the pairwise correlations between any two neurons, and the spectrum of the total output from the network.
In the second part, we investigate the three-dimensional noisy Kuramoto model, which can be used to describe the synchronization in a swarming model with helical trajectory. In the case without natural frequency, the Kuramoto model can be connected with the Vicsek model, which is widely studied in collective motion and swarming of active matter. We analyze the linear stability of the incoherent state and derive the critical coupling strength above which the incoherent state loses stability. In the limit of no natural frequency, an exact self-consistent equation of the mean field is derived and extended straightforward to any high-dimensional case.
As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields, with high potential impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects, as biosensors and drug-releasing microparticles, towards specific target sites, a promising strategy is the use of living cells as smart biochemically-powered carriers, building the so-called bio-hybrid systems. Inspired by leukocytes, native cells of living organisms efficiently migrating to critical targets as tumor tissue, an emerging concept is to exploit the amoeboid crawling motility of such cells as mean of transport for drug delivery applications.
In the research work described in this thesis, I synergistically applied experimental, computational and theoretical modeling approaches to investigate the behaviour and transport mechanism of a novel kind of bio-hybrid system for active transport at the micro-scale, referred to as cellular truck. This system consists of an amoeboid crawling cell, the carrier, attached to a microparticle, the cargo, which may ideally be drug-loaded for specific therapeutic treatments.
For the purposes of experimental investigation, I employed the amoeba Dictyostelium discoideum as crawling cellular carrier, being a renowned model organism for leukocyte migration and, in general, for eukaryotic cell motility. The performed experiments revealed a complex recurrent cell-cargo relative motion, together with an intermittent motility of the cellular truck as a whole. The evidence suggests the presence of cargoes on amoeboid cells to act as mechanical stimulus leading cell polarization, thus promoting cell motility and giving rise to the observed intermittent dynamics of the truck. Particularly, bursts in cytoskeletal polarity along the cell-cargo axis have been
found to occur in time with a rate dependent on cargo geometrical features, as particle diameter. Overall, the collected experimental evidence pointed out a pivotal role of cell-cargo interactions in the emergent cellular truck motion dynamics. Especially, they can determine the transport capabilities of amoeboid cells, as the cargo size significantly impacts the cytoskeletal activity and repolarization dynamics along the cell-cargo axis, the latter responsible for truck displacement and reorientation.
Furthermore, I developed a modeling framework, built upon the experimental evidence on cellular truck behaviour, that connects the relative dynamics and interactions arising at the truck scale with the actual particle transport dynamics. In fact, numerical simulations of the proposed model successfully reproduced the phenomenology of the cell-cargo system, while enabling the prediction of the transport properties of cellular trucks over larger spatial and temporal scales. The theoretical analysis provided a deeper understanding of the role of cell-cargo interaction on mass transport, unveiling in particular how the long-time transport efficiency is governed by the interplay between the persistence time of cell polarity and time scales of the relative dynamics stemming from cell-cargo interaction. Interestingly, the model predicts the existence of an optimal cargo size, enhancing the diffusivity of cellular trucks; this is in line with previous independent experimental data, which appeared rather counterintuitive and had no explanation prior to this study.
In conclusion, my research work shed light on the importance of cargo-carrier interactions in the context of crawling cell-mediated particle transport, and provides a prototypical, multifaceted framework for the analysis and modelling of such complex bio-hybrid systems and their perspective optimization.
The two hallmark features of Brownian motion are the linear growth < x2(t)> = 2Ddt of the mean squared displacement (MSD) with diffusion coefficient D in d spatial dimensions, and the Gaussian distribution of displacements. With the increasing complexity of the studied systems deviations from these two central properties have been unveiled over the years. Recently, a large variety of systems have been reported in which the MSD exhibits the linear growth in time of Brownian (Fickian) transport, however, the distribution of displacements is pronouncedly non-Gaussian (Brownian yet non-Gaussian, BNG). A similar behaviour is also observed for viscoelastic-type motion where an anomalous trend of the MSD, i.e., <x2(t)> ~ ta, is combined with a priori unexpected non-Gaussian distributions (anomalous yet non-Gaussian, ANG). This kind of behaviour observed in BNG and ANG diffusions has been related to the presence of heterogeneities in the systems and a common approach has been established to address it, that is, the random diffusivity approach.
This dissertation explores extensively the field of random diffusivity models. Starting from a chronological description of all the main approaches used as an attempt of describing BNG and ANG diffusion, different mathematical methodologies are defined for the resolution and study of these models. The processes that are reported in this work can be classified in three subcategories, i) randomly-scaled Gaussian processes, ii) superstatistical models and iii) diffusing diffusivity models, all belonging to the more general class of random diffusivity models. Eventually, the study focuses more on BNG diffusion, which is by now well-established and relatively well-understood. Nevertheless, many examples are discussed for the description of ANG diffusion, in order to highlight the possible scenarios which are known so far for the study of this class of processes.
The second part of the dissertation deals with the statistical analysis of random diffusivity processes. A general description based on the concept of moment-generating function is initially provided to obtain standard statistical properties of the models. Then, the discussion moves to the study of the power spectral analysis and the first passage statistics for some particular random diffusivity models. A comparison between the results coming from the random diffusivity approach and the ones for standard Brownian motion is discussed. In this way, a deeper physical understanding of the systems described by random diffusivity models is also outlined.
To conclude, a discussion based on the possible origins of the heterogeneity is sketched, with the main goal of inferring which kind of systems can actually be described by the random diffusivity approach.
Towards seasonal prediction: stratosphere-troposphere coupling in the atmospheric model ICON-NWP
(2020)
Stratospheric variability is one of the main potential sources for sub-seasonal to seasonal predictability in mid-latitudes in winter. Stratospheric pathways play an important role for long-range teleconnections between tropical phenomena, such as the quasi-biennial oscillation (QBO) and El Niño-Southern Oscillation (ENSO), and the mid-latitudes on the one hand, and linkages between Arctic climate change and the mid-latitudes on the other hand. In order to move forward in the field of extratropical seasonal predictions, it is essential that an atmospheric model is able to realistically simulate the stratospheric circulation and variability. The numerical weather prediction (NWP) configuration of the ICOsahedral Non-hydrostatic atmosphere model ICON is currently being used by the German Meteorological Service for the regular weather forecast, and is intended to produce seasonal predictions in future. This thesis represents the first extensive evaluation of Northern Hemisphere stratospheric winter circulation in ICON-NWP by analysing a large set of seasonal ensemble experiments.
An ICON control climatology simulated with a default setup is able to reproduce the basic behaviour of the stratospheric polar vortex. However, stratospheric westerlies are significantly too weak and major stratospheric warmings too frequent, especially in January. The weak stratospheric polar vortex in ICON is furthermore connected to a mean sea level pressure (MSLP) bias pattern resembling the negative phase of the Arctic Oscillation (AO). Since a good representation of the drag exerted by gravity waves is crucial for a realistic simulation of the stratosphere, three sensitivity experiments with reduced gravity wave drag are performed. Both a reduction of the non-orographic and orographic gravity wave drag respectively, lead to a strengthening of the stratospheric vortex and thus a bias reduction in winter, in particular in January. However, the effect of the non-orographic gravity wave drag on the stratosphere is stronger. A third experiment, combining a reduced orographic and non-orographic drag, exhibits the largest stratospheric bias reductions. The analysis of stratosphere-troposphere coupling based on an index of the Northern Annular Mode demonstrates that ICON realistically represents downward coupling. This coupling is intensified and more realistic in experiments with a reduced gravity wave drag, in particular with reduced non-orographic drag. Tropospheric circulation is also affected by the reduced gravity wave drag, especially in January, when the strongly improved stratospheric circulation reduces biases in the MSLP patterns. Moreover, a retuning of the subgrid-scale orography parameterisations leads to a significant error reduction in the MSLP in all months. In conclusion, the combination of these adjusted parameterisations is recommended as a current optimal setup for seasonal simulations with ICON.
Additionally, this thesis discusses further possible influences on the stratospheric polar vortex, including the influence of tropical phenomena, such as QBO and ENSO, as well as the influence of a rapidly warming Arctic. ICON does not simulate the quasi-oscillatory behaviour of the QBO and favours weak easterlies in the tropical stratosphere. A comparison with a reanalysis composite of the easterly QBO phase reveals, that the shift towards the easterly QBO in ICON further weakens the stratospheric polar vortex. On the other hand, the stratospheric reaction to ENSO events in ICON is realistic. ICON and the reanalysis exhibit a weakened stratospheric vortex in warm ENSO years. Furthermore, in particular in winter, warm ENSO events favour the negative phase of the Arctic Oscillation, whereas cold events favour the positive phase. The ICON simulations also suggest a significant effect of ENSO on the Atlantic-European sector in late winter. To investigate the influence of Arctic climate change on mid-latitude circulation changes, two differing approaches with transient and fixed sea ice conditions are chosen. Neither ICON approach exhibits the mid-latitude tropospheric negative Arctic Oscillation circulation response to amplified Arctic warming, as it is discussed on the basis of observational evidence. Nevertheless, adding a new model to the current and active discussion on Arctic-midlatitude linkages, further contributes to the understanding of divergent conclusions between model and observational studies.
The current thesis is focused on the properties of graphene supported by metallic substrates and specifically on the behaviour of electrons in such systems. Methods of scanning tunneling microscopy, electron diffraction and photoemission spectroscopy were applied to study the structural and electronic properties of graphene. The purpose of the first part of this work is to introduce the most relevant aspects of graphene physics and the methodical background of experimental techniques used in the current thesis.
The scientific part of this work starts with the extensive study by means of scanning tunneling microscopy of the nanostructures that appear in Au intercalated graphene on Ni(111). This study was aimed to explore the possible structural explanations of the Rashba-type spin splitting of ~100 meV experimentally observed in this system — much larger than predicted by theory. It was demonstrated that gold can be intercalated under graphene not only as a dense monolayer, but also in the form of well-periodic arrays of nanoclusters, a structure previously not reported. Such nanocluster arrays are able to decouple graphene from the strongly interacting Ni substrate and render it quasi-free-standing, as demonstrated by our DFT study. At the same time calculations confirm strong enhancement of the proximity-induced SOI in graphene supported by such nanoclusters in comparison to monolayer gold. This effect, attributed to the reduced graphene-Au distance in the case of clusters, provides a large Rashba-type spin splitting of ~60 meV.
The obtained results not only provide a possible mechanism of SOI enhancement in this particular system, but they can be also generalized for graphene on other strongly interacting substrates intercalated by nanostructures of heavy noble d metals.
Even more intriguing is the proximity of graphene to heavy sp-metals that were predicted to induce an intrinsic SOI and realize a spin Hall effect in graphene. Bismuth is the heaviest stable sp-metal and its compounds demonstrate a plethora of exciting physical phenomena. This was the motivation behind the next part of the current thesis, where structural and electronic properties of a previously unreported phase of Bi-intercalated graphene on Ir(111) were studied by means of scanning tunneling microscopy, spin- and angle-resolved photoemission spectroscopy and electron diffraction. Photoemission experiments revealed a remarkable, nearly ideal graphene band structure with strongly suppressed signatures of interaction between graphene and the Ir(111) substrate, moreover, the characteristic moiré pattern observed in graphene on Ir(111) by electron diffraction and scanning tunneling microscopy was strongly suppressed after intercalation. The whole set of experimental data evidences that Bi forms a dense intercalated layer that efficiently decouples graphene from the substrate. The interaction manifests itself only in the n-type charge doping (~0.4 eV) and a relatively small band gap at the Dirac point (~190 meV). The origin of this minor band gap is quite intriguing and in this work it was possible to exclude a wide range of mechanisms that could be responsible for it, such as induced intrinsic spin-orbit interaction, hybridization with the substrate states and corrugation of the graphene lattice. The main origin of the band gap was attributed to the A-B symmetry breaking and this conclusion found support in the careful analysis of the interference effects in photoemission that provided the band gap estimate of ~140 meV.
While the previous chapters were focused on adjusting the properties of graphene by proximity to heavy metals, graphene on its own is a great object to study various physical effects at crystal surfaces. The final part of this work is devoted to a study of surface scattering resonances by means of photoemission spectroscopy, where this effect manifests itself as a distinct modulation of photoemission intensity. Though scattering resonances were widely studied in the past by means of electron diffraction, studies about their observation in photoemission experiments started to appear only recently and they are very scarce.
For a comprehensive study of scattering resonances graphene was selected as a versatile model system with adjustable properties. After the theoretical and historical introduction to the topic of scattering resonances follows a detailed description of the unusual features observed in the photoemission spectra obtained in this work and finally the equivalence between these features and scattering resonances is proven. The obtained photoemission results are in a good qualitative agreement with the existing theory, as verified by our calculations in the framework of the interference model. This simple model gives a suitable explanation for the general experimental observations.
The possibilities of engineering the scattering resonances were also explored. A systematic study of graphene on a wide range of substrates revealed that the energy position of the resonances is in a direct relation to the magnitude of charge transfer between graphene and the substrate. Moreover, it was demonstrated that the scattering resonances in graphene on Ir(111) can be suppressed by nanopatterning either by a superlattice of Ir nanoclusters or by atomic hydrogen. These effects were attributed to strong local variations of tork function and/or destruction of long-range order of thephene lattice. The tunability of scattering resonances can be applied for optoelectronic devices based on graphene. Moreover, the results of this study expand the general understanding of the phenomenon of scattering resonances and are applicable to many other materials besides graphene.
Perovskite solar cells have become one of the most studied systems in the quest for new, cheap and efficient solar cell materials. Within a decade device efficiencies have risen to >25% in single-junction and >29% in tandem devices on top of silicon. This rapid improvement was in many ways fortunate, as e. g. the energy levels of commonly used halide perovskites are compatible with already existing materials from other photovoltaic technologies such as dye-sensitized or organic solar cells. Despite this rapid success, fundamental working principles must be understood to allow concerted further improvements. This thesis focuses on a comprehensive understanding of recombination processes in functioning devices.
First the impact the energy level alignment between the perovskite and the electron transport layer based on fullerenes is investigated. This controversial topic is comprehensively addressed and recombination is mitigated through reducing the energy difference between the perovskite conduction band minimum and the LUMO of the fullerene. Additionally, an insulating blocking layer is introduced, which is even more effective in reducing this recombination, without compromising carrier collection and thus efficiency. With the rapid efficiency development (certified efficiencies have broken through the 20% ceiling) and thousands of researchers working on perovskite-based optoelectronic devices, reliable protocols on how to reach these efficiencies are lacking. Having established robust methods for >20% devices, while keeping track of possible pitfalls, a detailed description of the fabrication of perovskite solar cells at the highest efficiency level (>20%) is provided. The fabrication of low-temperature p-i-n structured devices is described, commenting on important factors such as practical experience, processing atmosphere & temperature, material purity and solution age. Analogous to reliable fabrication methods, a method to identify recombination losses is needed to further improve efficiencies. Thus, absolute photoluminescence is identified as a direct way to quantify the Quasi-Fermi level splitting of the perovskite absorber (1.21eV) and interfacial recombination losses the transport layers impose, reducing the latter to ~1.1eV. Implementing very thin interlayers at both the p- and n-interface (PFN-P2 and LiF, respectively), these losses are suppressed, enabling a VOC of up to 1.17eV. Optimizing the device dimensions and the bandgap, 20% devices with 1cm2 active area are demonstrated. Another important consideration is the solar cells’ stability if subjected to field-relevant stressors during operation. In particular these are heat, light, bias or a combination thereof. Perovskite layers – especially those incorporating organic cations – have been shown to degrade if subjected to these stressors. Keeping in mind that several interlayers have been successfully used to mitigate recombination losses, a family of perfluorinated self-assembled monolayers (X-PFCn, where X denotes I/Br and n = 7-12) are introduced as interlayers at the n-interface. Indeed, they reduce interfacial recombination losses enabling device efficiencies up to 21.3%. Even more importantly they improve the stability of the devices. The solar cells with IPFC10 are stable over 3000h stored in the ambient and withstand a harsh 250h of MPP at 85◦C without appreciable efficiency losses. To advance further and improve device efficiencies, a sound understanding of the photophysics of a device is imperative. Many experimental observations in recent years have however drawn an inconclusive picture, often suffering from technical of physical impediments, disguising e. g. capacitive discharge as recombination dynamics. To circumvent these obstacles, fully operational, highly efficient perovskites solar cells are investigated by a combination of multiple optical and optoelectronic probes, allowing to draw a conclusive picture of the recombination dynamics in operation. Supported by drift-diffusion simulations, the device recombination dynamics can be fully described by a combination of first-, second- and third-order recombination and JV curves as well as luminescence efficiencies over multiple illumination intensities are well described within the model. On this basis steady state carrier densities, effective recombination constants, densities-of-states and effective masses are calculated, putting the devices at the brink of the radiative regime. Moreover, a comprehensive review of recombination in state-of-the-art devices is given, highlighting the importance of interfaces in nonradiative recombination. Different strategies to assess these are discussed, before emphasizing successful strategies to reduce interfacial recombination and pointing towards the necessary steps to further improve device efficiency and stability. Overall, the main findings represent an advancement in understanding loss mechanisms in highly efficient solar cells. Different reliable optoelectronic techniques are used and interfacial losses are found to be of grave importance for both efficiency and stability. Addressing the interfaces, several interlayers are introduced, which mitigate recombination losses and degradation.
Giant unilamellar vesicles are an important tool in todays experimental efforts to understand the structure and behaviour of biological cells. Their simple structure allows the isolation of the physical elastic properties of the lipid membrane. A central physical
property is the bending energy of the membrane, since the many different shapes of giant vesicles can be obtained by finding the minimum of the bending energy. In the spontaneous curvature model the bending energy is a function of the bending rigidity as well as the mean curvature and an additional parameter called the spontaneous curvature, which describes an internal preference of the lipid-bilayer to bend towards one side or the other. The spontaneous and mean curvature are local properties of the membrane.
Additional constraints arise from the conservation of the membrane surface area and the enclosed volume, which are global properties.
In this thesis the spontaneous curvature model is used to explain the experimental observation of a periodic shape oscillation of a giant unilamellar vesicle that was filled with a protein complex that periodically binds to and unbinds from the membrane.
By assuming that the binding of the proteins to the membrane induces a change in the spontaneous curvature the experimentally observed shapes could successfully be explained. This involves the numerical solution of the differential equations as obtained from the minimization of the bending energy respecting the area and volume constraints, the so called shape equations. Vice versa this approach can be used to estimate the spontaneous curvature from experimentally measurable quantities.
The second topic of this thesis is the analysis of concentration gradients in rigid conic membrane compartments. Gradients of an ideal gas due to gravity and gradients generated by the directed stochastic movement of molecular motors along a microtubulus were considered. It was possible to calculate the free energy and the bending energy analytically for the ideal gas. In the case of the non-equilibrium system with molecular motors, the characteristic length of the density profile, the jam-length, and its dependency on the opening angle of the conic compartment have been calculated in the mean-field limit.
The mean field results agree qualitatively with stochastic particle simulations.
In the present study, we employ the angle-resolved photoemission spectroscopy (ARPES) technique to study the electronic structure of topological states of matter. In particular, the so-called topological crystalline insulators (TCIs) Pb1-xSnxSe and Pb1-xSnxTe, and the Mn-doped Z2 topological insulators (TIs) Bi2Te3 and Bi2Se3. The Z2 class of strong topological insulators is protected by time-reversal symmetry and is characterized by an odd number of metallic Dirac type surface states in the surface Brillouin zone. The topological crystalline insulators on the other hand are protected by the individual crystal symmetries and exhibit an even number of Dirac cones.
The topological properties of the lead tin chalcogenides topological crystalline insulators can be tuned by temperature and composition. Here, we demonstrate that Bi-doping of the Pb1-xSnxSe(111) epilayers induces a quantum phase transition from a topological crystalline insulator to a Z2 topological insulator. This occurs because Bi-doping lifts the fourfold valley degeneracy in the bulk. As a consequence a gap appears at ⌈¯, while the three Dirac cones at the M̅ points of the surface Brillouin zone remain intact. We interpret this new phase transition is caused by lattice distortion. Our findings extend the topological phase diagram enormously and make strong topological insulators switchable by distortions or electric field. In contrast, the bulk Bi doping of epitaxial Pb1-xSnxTe(111) films induces a giant Rashba splitting at the surface that can be tuned by the doping level. Tight binding calculations identify their origin as Fermi level pinning by trap states at the surface.
Magnetically doped topological insulators enable the quantum anomalous Hall effect (QAHE) which provide quantized edge states for lossless charge transport applications. The edge states are hosted by a magnetic energy gap at the Dirac point which has not been experimentally observed to date. Our low temperature ARPES studies unambiguously reveal the magnetic gap of Mn-doped Bi2Te3. Our analysis shows a five times larger gap size below the Tc than theoretically predicted. We assign this enhancement to a remarkable structure modification induced by Mn doping. Instead of a disordered impurity system, a self-organized alternating sequence of MnBi2Te4 septuple and Bi2Te3quintuple layers is formed. This enhances the wave-function overlap and gives rise to a large magnetic gap. Mn-doped Bi2Se3 forms similar heterostructure, but only a nonmagnetic gap is observed in this system. This correlates with the difference in magnetic anisotropy due to the much larger spin-orbit interaction in Bi2Te3 compared to Bi2Se3. These findings provide crucial insights for pushing lossless transport in topological insulators towards room-temperature applications.
The Earth's inner magnetosphere is a very dynamic system, mostly driven by the external solar wind forcing exerted upon the magnetic field of our planet. Disturbances in the solar wind, such as coronal mass ejections and co-rotating interaction regions, cause geomagnetic storms, which lead to prominent changes in charged particle populations of the inner magnetosphere - the plasmasphere, ring current, and radiation belts. Satellites operating in the regions of elevated energetic and relativistic electron fluxes can be damaged by deep dielectric or surface charging during severe space weather events. Predicting the dynamics of the charged particles and mitigating their effects on the infrastructure is of particular importance, due to our increasing reliance on space technologies.
The dynamics of particles in the plasmasphere, ring current, and radiation belts are strongly coupled by means of collisions and collisionless interactions with electromagnetic fields induced by the motion of charged particles. Multidimensional numerical models simplify the treatment of transport, acceleration, and loss processes of these particles, and allow us to predict how the near-Earth space environment responds to solar storms. The models inevitably rely on a number of simplifications and assumptions that affect model accuracy and complicate the interpretation of the results. In this dissertation, we quantify the processes that control electron dynamics in the inner magnetosphere, paying particular attention to the uncertainties of the employed numerical codes and tools.
We use a set of convenient analytical solutions for advection and diffusion equations to test the accuracy and stability of the four-dimensional Versatile Electron Radiation Belt (VERB-4D) code. We show that numerical schemes implemented in the code converge to the analytical solutions and that the VERB-4D code demonstrates stable behavior independent of the assumed time step. The order of the numerical scheme for the convection equation is demonstrated to affect results of ring current and radiation belt simulations, and it is crucially important to use high-order numerical schemes to decrease numerical errors in the model.
Using the thoroughly tested VERB-4D code, we model the dynamics of the ring current electrons during the 17 March 2013 storm. The discrepancies between the model and observations above 4.5 Earth's radii can be explained by uncertainties in the outer boundary conditions. Simulation results indicate that the electrons were transported from the geostationary orbit towards the Earth by the global-scale electric and magnetic fields.
We investigate how simulation results depend on the input models and parameters. The model is shown to be particularly sensitive to the global electric field and electron lifetimes below 4.5 Earth's radii. The effects of radial diffusion and subauroral polarization streams are also quantified.
We developed a data-assimilative code that blends together a convection model of energetic electron transport and loss and Van Allen Probes satellite data by means of the Kalman filter. We show that the Kalman filter can correct model uncertainties in the convection electric field, electron lifetimes, and boundary conditions. It is also demonstrated how the innovation vector - the difference between observations and model prediction - can be used to identify physical processes missing in the model of energetic electron dynamics.
We computed radial profiles of phase space density of ultrarelativistic electrons, using Van Allen Probes measurements. We analyze the shape of the profiles during geomagnetically quiet and disturbed times and show that the formation of new local minimums in the radial profiles coincides with the ground observations of electromagnetic ion-cyclotron (EMIC) waves. This correlation indicates that EMIC waves are responsible for the loss of ultrarelativistic electrons from the heart of the outer radiation belt into the Earth's atmosphere.
Percolation process, which is intrinsically a phase transition process near the critical point, is ubiquitous in nature. Many of its applications embrace a wide spectrum of natural phenomena ranging from the forest fires, spread of contagious diseases, social behaviour dynamics to mathematical finance, formation of bedrocks and biological systems. The topology generated by the percolation process near the critical point is a random (stochastic) fractal. It is fundamental to the percolation theory that near the critical point, a unique infinite fractal structure, namely the infinite cluster, would emerge. As de Gennes suggested, the properties of the infinite cluster could be deduced by studying the dynamical behaviour of the random walk process taking place on it. He coined the term the ant in the labyrinth. The random walk process on such an infinite fractal cluster exhibits a subdiffusive dynamics in the sense that the mean squared displacement grows as ~t2/dw, where dw, called the fractal dimension of the random walk path, is greater than 2. Thus, the random walk process on the infinite cluster is classified as a process exhibiting the properties of anomalous diffusions. Yet near the critical point, the infinite cluster is not the sole emergent topology, but it coexists with other clusters whose size is finite. Though finite, on specific length scales these finite clusters exhibit fractal properties as well. In this work, it is assumed that the random walk process could take place on these finite size objects as well. Bearing this assumption in mind requires one address the non-equilibrium initial condition. Due to the lack of knowledge on the propagator of the random walk process in stochastic random environments, a phenomenological correspondence between the renowned Ornstein-Uhlenbeck process and the random walk process on finite size clusters is established. It is elucidated that when an ensemble of these finite size clusters and the infinite cluster is considered, the anisotropy and size of these finite clusters effects the mean squared displacement and its time averaged counterpart to grow in time as ~t(d+df (t-2))/dw, where d is the embedding Euclidean dimension, df is the fractal dimension of the infinite cluster, and , called the Fisher exponent, is a critical exponent governing the power-law distribution of the finite size clusters. Moreover, it is demonstrated that, even though the random walk process on a specific finite size cluster is ergodic, it exhibits a persistent non-ergodic behaviour when an ensemble of finite size and the infinite clusters is considered.
The goal of this thesis was to thoroughly investigate the behavior of multimode fibres to aid the development of modern and forthcoming fibre-fed spectrograph systems. Based on the Eigenmode Expansion Method, a field propagation model was created that can emulate effects in fibres relevant for astronomical spectroscopy, such as modal noise, scrambling, and focal ratio degradation. These effects are of major concern for any fibre-coupled spectrograph used in astronomical research. Changes in the focal ratio, modal distribution of light or non-perfect scrambling limit the accuracy of measurements, e.g. the flux determination of the astronomical object, the sky-background subtraction and detection limit for faint galaxies, or the spectral line position accuracy used for the detection of extra-solar planets.
Usually, fibres used for astronomical instrumentation are characterized empirically through tests. The results of this work allow to predict the fibre behaviour under various conditions using sophisticated software tools to simulate the waveguide behaviour and mode transport of fibres.
The simulation environment works with two software interfaces. The first is the mode solver module FemSIM from Rsoft. It is used to calculate all the propagation modes and effective refractive indexes of a given system. The second interface consists of Python scripts which enable the simulation of the near- and far-field outputs of a given fibre. The characteristics of the input field can be manipulated to emulate real conditions. Focus variations, spatial translation, angular fluctuations, and disturbances through the mode coupling factor can also be simulated.
To date, complete coherent propagation or complete incoherent propagation can be simulated. Partial coherence was not addressed in this work. Another limitation of the simulations is that they work exclusively for the monochromatic case and that the loss coefficient of the fibres is not considered. Nevertheless, the simulations were able to match the results of realistic measurements.
To test the validity of the simulations, real fibre measurements were used for comparison. Two fibres with different cross-sections were characterized. The first fibre had a circular cross-section, and the second one had an octagonal cross-section. The utilized test-bench was originally developed for the prototype fibres of the 4MOST fibre feed characterization. It allowed for parallel laser beam measurements, light cone measurements, and scrambling measurements. Through the appropriate configuration, the acquisition of the near- and/or far-field was feasible.
By means of modal noise analysis, it was possible to compare the near-field speckle patterns of simulations and measurements as a function of the input angle. The spatial frequencies that originate from the modal interference could be analyzed by using the power spectral density analysis. Measurements and simulations yielded similar results. Measurements with induced modal scrambling were compared to simulations using incoherent propagation and once again similar results were achieved. Through both measurements and simulations, the enlargement of the near-field distribution could be observed and analyzed. The simulations made it possible to explain incoherent intensity fluctuations that appear in real measurements due to the field distribution of the active propagation modes.
By using the Voigt analysis in the far-field distribution, it was possible to separate the modal diffusion component in order to compare it with the simulations. Through an appropriate assessment, the modal diffusion component as a function of the input angle could be translated into angular divergence. The simulations gave the minimal angular divergence of the system. Through the mean of the difference between simulations and measurements, a figure of merit is given which can be used to characterize the angular divergence of real fibres using the simulations. Furthermore, it was possible to simulate light cone measurements. Due to the overall consistent results, it can be stated that the simulations represent a good tool to assist the fibre characterization process for fibre-fed spectrograph systems.
This work was possible through the BMBF Grant 05A14BA1 which was part of the phase A study of the fibre system for MOSAIC, a multi-object spectrograph for the Extremely Large Telescope (ELT-MOS).
This cumulative thesis is concerned with the evolution of geomagnetic activity since the beginning of the 20th century, that is, the time-dependent response of the geomagnetic field to solar forcing. The focus lies on the description of the magnetospheric response field at ground level, which is particularly sensitive to the ring current system, and an interpretation of its variability in terms of the solar wind driving. Thereby, this work contributes to a comprehensive understanding of long-term solar-terrestrial interactions.
The common basis of the presented publications is formed by a reanalysis of vector magnetic field measurements from geomagnetic observatories located at low and middle geomagnetic latitudes. In the first two studies, new ring current targeting geomagnetic activity indices are derived, the Annual and Hourly Magnetospheric Currents indices (A/HMC). Compared to existing indices (e.g., the Dst index), they do not only extend the covered period by at least three solar cycles but also constitute a qualitative improvement concerning the absolute index level and the ~11-year solar cycle variability. The analysis of A/HMC shows that (a) the annual geomagnetic activity experiences an interval-dependent trend with an overall linear decline during 1900–2010 of ~5 % (b) the average trend-free activity level amounts to ~28 nT (c) the solar cycle related variability shows amplitudes of ~15–45 nT (d) the activity level for geomagnetically quiet conditions (Kp<2) lies slightly below 20 nT. The plausibility of the last three points is ensured by comparison to independent estimations either based on magnetic field measurements from LEO satellite missions (since the 1990s) or the modeling of geomagnetic activity from solar wind input (since the 1960s). An independent validation of the longterm trend is problematic mainly because the sensitivity of the locally measured geomagnetic activity depends on geomagnetic latitude. Consequently, A/HMC is neither directly comparable to global geomagnetic activity indices (e.g., the aa index) nor to the partly reconstructed open solar magnetic flux, which requires a homogeneous response of the ground-based measurements to the interplanetary magnetic field and the solar wind speed.
The last study combines a consistent, HMC-based identification of geomagnetic storms from 1930–2015 with an analysis of the corresponding spatial (magnetic local time-dependent) disturbance patterns. Amongst others, the disturbances at dawn and dusk, particularly their evolution during the storm recovery phases, are shown to be indicative of the solar wind driving structure (Interplanetary Coronal Mass Ejections vs. Stream or Co-rotating Interaction Regions), which enables a backward-prediction of the storm driver classes. The results indicate that ICME-driven geomagnetic storms have decreased since 1930 which is consistent with the concurrent decrease of HMC. Out of the collection of compiled follow-up studies the inclusion of measurements from high-latitude geomagnetic observatories into the third study’s framework seems most promising at this point.
From dawn till dusk
(2020)
Supernova remnants are believed to be the source of cosmic rays with energies up to 10^15 eV that are produced within our Galaxy. The acceleration mechanism associated with the collision-less shocks in supernova remnants - diffusive shock acceleration - predicts a spectral index of the accelerated non-thermal particles of s = 2. However, measurements of non-thermal emission in radio, X-rays and gamma-rays reveal significant deviations of the particles spectral index from the canonical value of s = 2.
The youngest Galactic supernova remnant G1.9+0.3 is an interesting target for next-generation gamma-ray observatories. So far, the remnant is only detected in the radio and the X-ray bands, but its young age of ≈100 yrs and inferred shock speed of ≈ 14, 000 km/s could make it an efficient particle accelerator.
I performed spherical symmetric 1D simulations with the RATPaC code, in which I simultaneously solved the transport equation for cosmic rays, the transport equation for magnetic turbulence, and the hydro-dynamical equations for the gas flow. Separately computed distributions of the particles accelerated at the forward and the reverse shock were then used to calculate the spectra of synchrotron, inverse Compton, and Pion-decay radiation from the source.
The emission from G1.9+0.3 can be self-consistently explained within the test-particle limit. I find that the X-ray flux is dominated by emission from the forward shock while most of the radio emission originates near the reverse shock, which makes G1.9+0.3 the first remnant with non-thermal radiation detected from the reverse shock. The flux of very-high-energy gamma-ray emission from G1.9+0.3 is expected to be close to the sensitivity threshold of the Cherenkov Telescope Array. The limited time available to grow large-scale turbulence limits the maximum energy of particles to values below 100 TeV, hence G1.9+0.3 is not a PeVatron.
Although there are many models for the acceleration of cosmic rays in Supernova remnants, the escape of cosmic rays from these sources is yet understudied.
I use our time-dependent acceleration code RATPaC to study the acceleration of cosmic rays and their escape in post-adiabatic Supernova remnants and calculate the subsequent gamma-ray emission from inverse-Compton scattering and Pion decay. My simulations span 100,000 years, thus covering the free-expansion, the Sedov-Taylor, and the beginning of the post-adiabatic phase of the remnant’s evolution.
At later stages of the evolution cosmic rays over a wide range of energy can reside outside of the remnant, creating spectra that are softer than predicted by standard diffusive shock acceleration and feature breaks in the 10 - 100 GeV-range. The total spectrum of cosmic rays released into the interstellar medium has a spectral index of s ≈ 2.4 above roughly 10 GeV which is close to that required by Galactic propagation models. I further find the gamma-ray luminosity to peak around an age of 4,000 years for inverse-Compton-dominated high-energy emission. Remnants expanding in low-density media emit generally more inverse-Compton radiation matching the fact that the brightest known supernova remnants - RCW86, Vela Jr, HESSJ1721-347 and RXJ1713.7-3946 - are all expanding in low density environments.
The importance of feedback from the cosmic-rays on the hydrodynamical evolution of the remnants is debated as a possibility to obtain soft cosmic-ray spectra at low energies.
I performed spherically symmetric 1-D simulations with a modified version of the RATPaC code, in which I simultaneously solve the transport equation for cosmic rays and the hydrodynamical equations, including the back-reaction of the cosmic-ray pressure on the flow profiles.
Besides the known modification of the flow profiles and the consequently curved cosmic-ray spectra, steady-state models for non-linear diffusive shock acceleration overpredict the total compression ratio that can be reached with cosmic-ray feedback, as there is limited time for building these modifications. Further, I find modifications to the downstream flow structure that change the evolutionary behavior of the remnant and trigger a cosmic-ray-induced instability close to the contact discontinuity, if and when the cosmic-ray pressure becomes dominant there.
As one of the most-produced commodity polymers, polypropylene draws considerable scientific and commercial interest as an electret material. In the present thesis, the influence of the surface chemical modification and crystalline reconstruction on the electret properties of the polypropylene thin films will be discussed. The chemical treatment with orthophosphoric acid can significantly improve the surface charge stability of the polypropylene electrets by introducing phosphorus- and oxygen-containing structures onto the modified surface. The thermally stimulated discharge measurement and charge profiling by means of piezoelectrically generated pressure steps are used to investigate the electret behaviour. It is concluded that deep traps of limited number density are created during the treatment with inorganic chemicals. Hence, the improvement dramatically decreases when the surface-charge density is substantially higher than ±1.2×10^(-3) C·m^(-2). The newly formed traps also show a higher trapping energy for negative charges. The energetic distributions of the traps in the non-treated and chemically treated samples offer an insight regarding the surface and foreign-chemical dominance on the charge storage and transport in the polypropylene electrets.
Additionally, different electret properties are observed on the polypropylene films with the spherulitic and transcrystalline structures. It indicates the dependence of the charge storage and transport on the crystallite and molecular orientations in the crystalline phase. In general, a more diverse crystalline growth in the spherulitic samples can result in a more complex energetic trap distribution, in comparison to that in a transcrystalline polypropylene. The double-layer transcrystalline polypropylene film with a crystalline interface in the middle can be obtained by crystallising the film in contact with rough moulding surfaces on both sides. A layer of heterocharges appears on each side of the interface in the double-layer transcrystalline polypropylene electrets after the thermal poling. However, there is no charge captured within the transcrystalline layers. The phenomenon reveals the importance of the crystalline interface in terms of creating traps with the higher activation energy in polypropylene. The present studies highlight the fact that even slight variations in the polypropylene film may lead to dramatic differences in its electret properties.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
A workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established. Synchrotron computed tomography (CT) was used to correlate the packing density with the particle size and particle shape. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to find reliable principal stress directions.
Near-Earth space represents a significant scientific and technological challenge. Particularly at magnetic low-latitudes, the horizontal magnetic field geometry at the dip equator and its closed field-lines support the existence of a distinct electric current system, abrupt electric field variations and the development of plasma irregularities. Of particular interest are small-scale irregularities associated with equatorial plasma depletions (EPDs). They are responsible for the disruption of trans-ionospheric radio waves used for navigation, communication, and Earth observation. The fast increase of satellite missions makes it imperative to study the near-Earth space, especially the phenomena known to harm space technology or disrupt their signals. EPDs correspond to the large-scale structure (i.e., tens to hundreds of kilometers) of topside F region irregularities commonly known as Spread F. They are observed as depleted-plasma density channels aligned with the ambient magnetic field in the post-sunset low-latitude ionosphere. Although the climatological variability of their occurrence in terms of season, longitude, local time and solar flux is well-known, their day to day variability is not. The sparse observations from ground-based instruments like radars and the few simultaneous measurements of ionospheric parameters by space-based instruments have left gaps in the knowledge of EPDs essential to comprehend their variability.
In this dissertation, I profited from the unique observations of the ESA’s Swarm constellation mission launched in November 2013 to tackle three issues that revealed novel and significant results on the current knowledge of EPDs. I used Swarm’s measurements of the electron density, magnetic, and electric fields to answer, (1.) what is the direction of propagation of the electromagnetic energy associated with EPDs?, (2.) what are the spatial and temporal characteristics of the electric currents (field-aligned and diamagnetic currents) related to EPDs, i.e., seasonal/geographical, and local time dependencies?, and (3.) under what conditions does the balance between magnetic and plasma pressure across EPDs occur?
The results indicate that: (1.) The electromagnetic energy associated with EPDs presents a preference for interhemispheric flows; that is, the related Poynting flux directs from one magnetic hemisphere to the other and varies with longitude and season. (2.) The field-aligned currents at the edges of EPDs are interhemispheric. They generally close in the hemisphere with the highest Pedersen conductance. Such hemispherical preference presents a seasonal/longitudinal dependence. The diamagnetic currents increase or decrease the magnetic pressure inside EPDs. These two effects rely on variations of the plasma temperature inside the EPDs that depend on longitude and local time. (3.) EPDs present lower or higher plasma pressure than the ambient. For low-pressure EPDs the plasma pressure gradients are mostly dominated by variations of the plasma density so that variations of the temperature are negligible. High-pressure EPDs suggest significant temperature variations with magnitudes of approximately twice the ambient. Since their occurrence is more frequent in the vicinity of the South Atlantic magnetic anomaly, such high temperatures are suggested to be due to particle precipitation.
In a broader context, this dissertation shows how dedicated satellite missions with high-resolution capabilities improve the specification of the low-latitude ionospheric electrodynamics and expand knowledge on EPDs which is valuable for current and future communication, navigation, and Earth-observing missions. The contributions of this investigation represent several ’firsts’ in the study of EPDs: (1.) The first observational evidence of interhemispheric electromagnetic energy flux and field-aligned currents. (2.) The first spatial and temporal characterization of EPDs based on their associated field-aligned and diamagnetic currents. (3.) The first evidence of high plasma pressure in regions of depleted plasma density in the ionosphere. These findings provide new insights that promise to advance our current knowledge of not only EPDs but the low-latitude post-sunset ionosphere environment.
Over the last decades, the Arctic regions of the earth have warmed at a rate 2–3 times faster than the global average– a phenomenon called Arctic Amplification. A complex, non-linear interplay of physical processes and unique pecularities in the Arctic climate system is responsible for this, but the relative role of individual processes remains to be debated. This thesis focuses on the climate change and related processes on Svalbard, an archipelago in the North Atlantic sector of the Arctic, which is shown to be a "hotspot" for the amplified recent warming during winter. In this highly dynamical region, both oceanic and atmospheric large-scale transports of heat and moisture interfere with spatially inhomogenous surface conditions, and the corresponding energy exchange strongly shapes the atmospheric boundary layer. In the first part, Pan-Svalbard gradients in the surface air temperature (SAT) and sea ice extent (SIE) in the fjords are quantified and characterized. This analysis is based on observational data from meteorological stations, operational sea ice charts, and hydrographic observations from the adjacent ocean, which cover the 1980–2016 period. It is revealed that typical estimates of SIE during late winter range from 40–50% (80–90%) in the western (eastern) parts of Svalbard. However, strong SAT warming during winter of the order of 2–3K per decade dictates excessive ice loss, leaving fjords in the western parts essentially ice-free in recent winters. It is further demostrated that warm water currents on the west coast of Svalbard, as well as meridional winds contribute to regional differences in the SIE evolution. In particular, the proximity to warm water masses of the West Spitsbergen Current can explain 20–37% of SIE variability in fjords on west Svalbard, while meridional winds and associated ice drift may regionally explain 20–50% of SIE variability in the north and northeast. Strong SAT warming has overruled these impacts in recent years, though.
In the next part of the analysis, the contribution of large-scale atmospheric circulation changes to the Svalbard temperature development over the last 20 years is investigated. A study employing kinematic air-back trajectories for Ny-Ålesund reveals a shift in the source regions of lower-troposheric air over time for both the winter and the summer season. In winter, air in the recent decade is more often of lower-latitude Atlantic origin, and less frequent of Arctic origin. This affects heat- and moisture advection towards Svalbard, potentially manipulating clouds and longwave downward radiation in that region. A closer investigation indicates that this shift during winter is associated with a strengthened Ural blocking high and Icelandic low, and contributes about 25% to the observed winter warming on Svalbard over the last 20 years. Conversely, circulation changes during summer include a strengthened Greenland blocking high which leads to more frequent cold air advection from the central Arctic towards Svalbard, and less frequent air mass origins in the lower latitudes of the North Atlantic. Hence, circulation changes during winter are shown to have an amplifying effect on the recent warming on Svalbard, while summer circulation changes tend to mask warming.
An observational case study using upper air soundings from the AWIPEV research station in Ny-Ålesund during May–June 2017 underlines that such circulation changes during summer are associated with tropospheric anomalies in temperature, humidity and boundary layer height.
In the last part of the analysis, the regional representativeness of the above described changes around Svalbard for the broader Arctic is investigated. Therefore, the terms in the diagnostic temperature equation in the Arctic-wide lower troposphere are examined for the Era-Interim atmospheric reanalysis product. Significant positive trends in diabatic heating rates, consistent with latent heat transfer to the atmosphere over regions of increasing ice melt, are found for all seasons over the Barents/Kara Seas, and in individual months in the vicinity of Svalbard. The above introduced warm (cold) advection trends during winter (summer) on Svalbard are successfully reproduced. Regarding winter, they are regionally confined to the Barents Sea and Fram Strait, between 70°–80°N, resembling a unique feature in the whole Arctic. Summer cold advection trends are confined to the area between eastern Greenland and Franz Josef Land, enclosing Svalbard.
Interactions involving biological interfaces such as lipid-based membranes are of paramount importance for all life processes. The same also applies to artificial interfaces to which biological matter is exposed, for example the surfaces of drug delivery systems or implants. This thesis deals with the two main types of interface interactions, namely (i) interactions between a single interface and the molecular components of the surrounding aqueous medium and (ii) interactions between two interfaces. Each type is investigated with regard to an important scientific problem in the fields of biotechnology and biology:
1.) The adsorption of proteins to surfaces functionalized with hydrophilic polymer brushes; a process of great biomedical relevance in context with harmful foreign-body-response to implants and drug delivery systems.
2.) The influence of glycolipids on the interaction between lipid membranes; a hitherto largely unexplored phenomenon with potentially great biological relevance.
Both problems are addressed with the help of (quasi-)planar, lipid-based model surfaces in combination with x-ray and neutron scattering techniques which yield detailed structural insights into the interaction processes. Regarding the adsorption of proteins to brush-functionalized surfaces, the first scenario considered is the exposure of the surfaces to human blood serum containing a multitude of protein species. Significant blood protein adsorption was observed despite the functionalization, which is commonly believed to act as a protein repellent. The adsorption consists of two distinct modes, namely strong adsorption to the brush grafting surface and weak adsorption to the brush itself. The second aspect investigated was the fate of the brush-functionalized surfaces when exposed to aqueous media containing immune proteins (antibodies) against the brush polymer, an emerging problem in current biomedical applications. To this end, it was found that antibody binding cannot be prevented by variation of the brush grafting density or the polymer length. This result motivates the search for alternative, strictly non-antigenic brush chemistries. With respect to the influence of glycolipids on the interaction between lipid membranes, this thesis focused on the glycolipids’ ability to crosslink and thereby to tightly attract adjacent membranes. This adherence is due to preferential saccharide-saccharide interactions occurring among the glycolipid headgroups. This phenomenon had previously been described for lipids with special oligo-saccharide motifs. Here, it was investigated how common this phenomenon is among glycolipids with a variety of more abundant saccharide-headgroups. It was found that glycolipid-induced membrane crosslinking is equally observed for some of these abundant glycolipid types, strongly suggesting that this under-explored phenomenon is potentially of great biological relevance.
Electrets are dielectrics with quasi-permanent electric charge and/or dipoles, sometimes can be regarded as an electric analogy to a magnet. Since the discovery of the excellent charge retention capacity of poly(tetrafluoro ethylene) and the invention of the electret microphone, electrets have grown out of a scientific curiosity to an important application both in science and technology. The history of electret research goes hand in hand with the quest for new materials with better capacity at charge and/or dipole retention. To be useful, electrets normally have to be charged/poled to render them electro-active. This process involves electric-charge deposition and/or electric dipole orientation within the dielectrics ` surfaces and bulk. Knowledge of the spatial distribution of electric charge and/or dipole polarization after their deposition and subsequent decay is crucial in the task to improve their stability in the dielectrics.
Likewise, for dielectrics used in electrical insulation applications, there are also needs for accumulated space-charge and polarization spatial profiling. Traditionally, space-charge accumulation and large dipole polarization within insulating dielectrics is considered undesirable and harmful to the insulating dielectrics as they might cause dielectric loss and could lead to internal electric field distortion and local field enhancement. High local electric field could trigger several aging processes and reduce the insulating dielectrics' lifetime. However, with the advent of high-voltage DC transmission and high-voltage capacitor for energy storage, these are no longer the case. There are some overlapped between the two fields of electrets and electric insulation. While quasi-permanently trapped electric-charge and/or large remanent dipole polarization are the requisites for electret operation, stably trapped electric charge in electric insulation helps reduce electric charge transport and overall reduced electric conductivity. Controlled charge trapping can help in preventing further charge injection and accumulation as well as serving as field grading purpose in insulating dielectrics whereas large dipole polarization can be utilized in energy storage applications.
In this thesis, the Piezoelectrically-generated Pressure Steps (PPSs) were employed as a nondestructive method to probe the electric-charge and dipole polarization distribution in a range of thin film (several hundred micron) polymer-based materials, namely polypropylene (PP), low-density polyethylene/magnesium oxide (LDPE/MgO) nanocomposites and poly(vinylidene fluoride-co- trifluoro ethylene) (P(VDF-TrFE)) copolymer. PP film surface-treated with phosphoric acid to introduce surfacial isolated nanostructures serves as example of 2-dimensional nano-composites whereas LDPE/MgO serves as the case of 3-dimensional nano-composites with MgO nano-particles dispersed in LDPE polymer matrix. It is evidenced that the nanoparticles on the surface of acid-treated PP and in the bulk of LDPE/MgO nanocomposites improve charge trapping capacity of the respective material and prevent further charge injection and transport and that the enhanced charge trapping capacity makes PP and LDPE/MgO nanocomposites potential materials for both electret and electrical insulation applications. As for PVDF and VDF-based copolymers, the remanent spatial polarization distribution depends critically on poling method as well as specific parameters used in the respective poling method. In this work, homogeneous polarization poling of P(VDF-TrFE) copolymers with different VDF-contents have been attempted with hysteresis cyclical poling. The behaviour of remanent polarization growth and spatial polarization distribution are reported and discussed. The Piezoelectrically-generated Pressure Steps (PPSs) method has proven as a powerful method for the charge storage and transport characterization of a wide range of polymer material from nonpolar, to polar, to polymer nanocomposites category.
Ultrafast magnetisation dynamics have been investigated intensely for two decades. The recovery process after demagnetisation, however, was rarely studied experimentally and discussed in detail. The focus of this work lies on the investigation of the magnetisation on long timescales after laser excitation. It combines two ultrafast time resolved methods to study the relaxation of the magnetic and lattice system after excitation with a high fluence ultrashort laser pulse. The magnetic system is investigated by time resolved measurements of the magneto-optical Kerr effect. The experimental setup has been implemented in the scope of this work. The lattice dynamics were obtained with ultrafast X-ray diffraction. The combination of both techniques leads to a better understanding of the mechanisms involved in magnetisation recovery from a non-equilibrium condition. Three different groups of samples are investigated in this work: Thin Nickel layers capped with nonmagnetic materials, a continuous sample of the ordered L10 phase of Iron Platinum and a sample consisting of Iron Platinum nanoparticles embedded in a carbon matrix. The study of the remagnetisation reveals a general trend for all of the samples: The remagnetisation process can be described by two time dependences. A first exponential recovery that slows down with an increasing amount of energy absorbed in the system until an approximately linear time dependence is observed. This is followed by a second exponential recovery. In case of low fluence excitation, the first recovery is faster than the second. With increasing fluence the first recovery is slowed down and can be described as a linear function. If the pump-induced temperature increase in the sample is sufficiently high, a phase transition to a paramagnetic state is observed. In the remagnetisation process, the transition into the ferromagnetic state is characterised by a distinct transition between the linear and exponential recovery. From the combination of the transient lattice temperature Tp(t) obtained from ultrafast X-ray measurements and magnetisation M(t) gained from magneto-optical measurements we construct the transient magnetisation versus temperature relations M(Tp). If the lattice temperature remains below the Curie temperature the remagnetisation curve M(Tp) is linear and stays below the M(T) curve in equilibrium in the continuous transition metal layers. When the sample is heated above phase transition, the remagnetisation converges towards the static temperature dependence. For the granular Iron Platinum sample the M(Tp) curves for different fluences coincide, i.e. the remagnetisation follows a similar path irrespective of the initial laser-induced temperature jump.
Due to advances in science and technology towards smaller and more powerful processing units, the fabrication of micrometer sized machines for different tasks becomes more and more possible. Such micro-robots could revolutionize medical treatment of diseases and shall support to work on other small machines. Nevertheless, scaling down robots and other devices is a challenging task and will probably remain limited in near future. Over the past decade the concept of bio-hybrid systems has proved to be a promising approach in order to advance the further development of micro-robots. Bio-hybrid systems combine biological cells with artificial components, thereby benefiting from the functionality of living biological cells. Cell-driven micro-transport is one of the most prominent applications in the emerging field of these systems. So far, micrometer sized cargo has been successfully transported by means of swimming bacterial cells. The potential of motile adherent cells as transport systems has largely remained unexplored.
This thesis concentrates on the social amoeba Dictyostelium discoideum as a potential candidate for an amoeboid bio-hybrid transport system. The use of this model organism comes with several advantages. Due to the unspecific properties of Dictyostelium adhesion, a wide range of different cargo materials can be used for transport. As amoeboid cells exceed bacterial cells in size by one order of magnitude, also the size of an object carried by a single cell can also be much larger for an amoeba. Finally it is possible to guide the cell-driven transport based on the chemotactic behavior of the amoeba. Since cells undergo a developmentally induced chemotactic aggregation, cargo could be assembled in a self-organized manner into a cluster. It is also possible to impose an external chemical gradient to guide the amoeboid transport system to a desired location.
To establish Dictyostelium discoideum as a possible candidate for bio-hybrid transport systems, this thesis will first investigate the movement of single cells. Secondly, the interaction of cargo and cells will be studied. Eventually, a conceptional proof will be conducted, that the cheomtactic behavior can be exploited either to transport a cargo self-organized or through an external chemical source.
Synchronization – the adjustment of rhythms among coupled self-oscillatory systems – is a fascinating dynamical phenomenon found in many biological, social, and technical systems.
The present thesis deals with synchronization in finite ensembles of weakly coupled self-sustained oscillators with distributed frequencies.
The standard model for the description of this collective phenomenon is the Kuramoto model – partly due to its analytical tractability in the thermodynamic limit of infinitely many oscillators. Similar to a phase transition in the thermodynamic limit, an order parameter indicates the transition from incoherence to a partially synchronized state. In the latter, a part of the oscillators rotates at a common frequency. In the finite case, fluctuations occur, originating from the quenched noise of the finite natural frequency sample.
We study intermediate ensembles of a few hundred oscillators in which fluctuations are comparably strong but which also allow for a comparison to frequency distributions in the infinite limit.
First, we define an alternative order parameter for the indication of a collective mode in the finite case. Then we test the dependence of the degree of synchronization and the mean rotation frequency of the collective mode on different characteristics for different coupling strengths.
We find, first numerically, that the degree of synchronization depends strongly on the form (quantified by kurtosis) of the natural frequency sample and the rotation frequency of the collective mode depends on the asymmetry (quantified by skewness) of the sample. Both findings are verified in the infinite limit.
With these findings, we better understand and generalize observations of other authors. A bit aside of the general line of thoughts, we find an analytical expression for the volume contraction in phase space.
The second part of this thesis concentrates on an ordering effect of the finite-size fluctuations. In the infinite limit, the oscillators are separated into coherent and incoherent thus ordered and disordered oscillators. In finite ensembles, finite-size fluctuations can generate additional order among the asynchronous oscillators. The basic principle – noise-induced synchronization – is known from several recent papers. Among coupled oscillators, phases are pushed together by the order parameter fluctuations, as we on the one hand show directly and on the other hand quantify with a synchronization measure from directed statistics between pairs of passive oscillators.
We determine the dependence of this synchronization measure from the ratio of pairwise natural frequency difference and variance of the order parameter fluctuations. We find a good agreement with a simple analytical model, in which we replace the deterministic fluctuations of the order parameter by white noise.
Organic semiconductors are a promising class of materials. Their special properties are the particularly good absorption, low weight and easy processing into thin films. Therefore, intense research has been devoted to the realization of thin film organic solar cells (OPVs). Because of the low dielectric constant of organic semiconductors, primary excitations (excitons) are strongly bound and a type II heterojunction needs to be introduced to split these excitations into free charges. Therefore, most organic solar cells consist of at least an electron donor and electron acceptor material. For such donor acceptor systems mainly three states are relevant; the photoexcited exciton on the donor or acceptor material, the charge transfer state at the donor-acceptor interface and the charge separated state of a free electron and hole. The interplay between these states significantly determines the efficiency of organic solar cells. Due to the high absorption and the low charge carrier mobilities, the active layers are usually thin but also, exciton dissociation and free charge formation proceeds rapidely, which makes the study of carrier dynamics highly challenging.
Therefore, the focus of this work was first to install new experimental setups for the investigation of the charge carrier dynamics in complete devices with superior sensitivity and time resolution and, second, to apply these methods to prototypical photovoltaic materials to address specific questions in the field of organic and hybrid photovoltaics.
Regarding the first goal, a new setup combining transient absorption spectroscopy (TAS) and time delayed collection field (TDCF) was designed and installed in Potsdam. An important part of this work concerned the improvement of the electronic components with respect to time resolution and sensitivity. To this end, a highly sensitive amplifier for driving and detecting the device response in TDCF was developed. This system was then applied to selected organic and hybrid model systems with a particular focus on the understanding of the loss mechanisms that limit the fill factor and short circuit current of organic solar cells.
The first model system was a hybrid photovoltaic material comprising inorganic quantum dots decorated with organic ligands. Measurements with TDCF revealed fast free carrier recombination, in part assisted by traps, while bias-assisted charge extraction measurements showed high mobility. The measured parameters then served as input for a successful description of the device performance with an analytical model.
With a further improvement of the instrumentation, a second topic was the detailed analysis of non-geminate recombination in a disordered polymer:fullerene blend where an important question was the effect of disorder on the carrier dynamics. The measurements revealed that early time highly mobile charges undergo fast non-geminate recombination at the contacts, causing an apparent field dependence of free charge generation in TDCF experiments if not conducted properly. On the other hand, recombination the later time scale was determined by dispersive recombination in the bulk of the active layer, showing the characteristics of carrier dynamics in an exponential density of state distribution. Importantly, the comparison with steady state recombination data suggested a very weak impact of non-thermalized carriers on the recombination properties of the solar cells under application relevant illumination conditions.
Finally, temperature and field dependent studies of free charge generation were performed on three donor-acceptor combinations, with two donor polymers of the same material family blended with two different fullerene acceptor molecules. These particular material combinations were chosen to analyze the influence of the energetic and morphology of the blend on the efficiency of charge generation. To this end, activation energies for photocurrent generation were accurately determined for a wide range of excitation energies. The results prove that the formation of free charge is via thermalized charge transfer states and does not involve hot exciton splitting. Surprisingly, activation energies were of the order of thermal energy at room temperature. This led to the important conclusion that organic solar cells perform well not because of predominate high energy pathways but because the thermalized CT states are weakly bound. In addition, a model is introduced to interconnect the dissociation efficiency of the charge transfer state with its recombination observable with photoluminescence, which rules out a previously proposed two-pool model for free charge formation and recombination. Finally, based on the results, proposals for the further development of organic solar cells are formulated.
Ferroic materials have attracted a lot of attention over the years due to their wide range of applications in sensors, actuators, and memory devices. Their technological applications originate from their unique properties such as ferroelectricity and piezoelectricity. In order to optimize these materials, it is necessary to understand the coupling between their nanoscale structure and transient response, which are related to the atomic structure of the unit cell.
In this thesis, synchrotron X-ray diffraction is used to investigate the structure of ferroelectric thin film capacitors during application of a periodic electric field. Combining electrical measurements with time-resolved X-ray diffraction on a working device allows for visualization of the interplay between charge flow and structural motion. This constitutes the core of this work. The first part of this thesis discusses the electrical and structural dynamics of a ferroelectric Pt/Pb(Zr0.2,Ti0.8)O3/SrRuO3 heterostructure during charging, discharging, and polarization reversal. After polarization reversal a non-linear piezoelectric response develops on a much longer time scale than the RC time constant of the device. The reversal process is inhomogeneous and induces a transient disordered domain state. The structural dynamics under sub-coercive field conditions show that this disordered domain state can be remanent and can be erased with an appropriate voltage pulse sequence. The frequency-dependent dynamic characterization of a Pb(Zr0.52,Ti0.48)O3 layer, at the morphotropic phase boundary, shows that at high frequency, the limited domain wall velocity causes a phase lag between the applied field and both the structural and electrical responses. An external modification of the RC time constant of the measurement delays the switching current and widens the electromechanical hysteresis loop while achieving a higher compressive piezoelectric strain within the crystal.
In the second part of this thesis, time-resolved reciprocal space maps of multiferroic BiFeO3 thin films were measured to identify the domain structure and investigate the development of an inhomogeneous piezoelectric response during the polarization reversal. The presence of 109° domains is evidenced by the splitting of the Bragg peak.
The last part of this work investigates the effect of an optically excited ultrafast strain or heat pulse propagating through a ferroelectric BaTiO3 layer, where we observed an additional current response due to the laser pulse excitation of the metallic bottom electrode of the heterostructure.
Membrane adhesion is a fundamental biological process in which membranes are attached to neighboring membranes or surfaces. Membrane adhesion emerges from a complex interplay between the binding of membrane-anchored receptors/ligands and the membrane properties. In this work, we study membrane adhesion mediated by lipid-anchored saccharides using microsecond-long full-atomistic molecular dynamics simulations. Motivated by neutron scattering experiments on membrane adhesion via lipid-anchored saccharides, we investigate the role of LeX, Lac1, and Lac2 saccharides and membrane fluctuations in membrane adhesion.
We study the binding of saccharides in three different systems: for saccharides in water, for saccharides anchored to essentially planar membranes at fixed separations, and for saccharides anchored to apposing fluctuating membranes. Our simulations of two saccharides in water indicate that the saccharides engage in weak interactions to form dimers. We find that the binding occurs in a continuum of bound states instead of a certain number of well-defined bound structures, which we term as "diffuse binding".
The binding of saccharides anchored to essentially planar membranes strongly depends on separation of the membranes, which is fixed in our simulation system. We show that the binding constants for trans-interactions of two lipid-anchored saccharides monotonically decrease with increasing separation. Saccharides anchored to the same membrane leaflet engage in cis-interactions with binding constants comparable to the trans-binding constants at the smallest membrane separations. The interplay of cis- and trans-binding can be investigated in simulation systems with many lipid-anchored saccharides. For Lac2, our simulation results indicate a positive cooperativity of trans- and cis-binding. In this cooperative binding the trans-binding constant is enhanced by the cis-interactions. For LeX, in contrast, we observe no cooperativity between trans- and cis-binding. In addition, we determine the forces generated by trans-binding of lipid-anchored saccharides in planar membranes from the binding-induced deviations of the lipid-anchors. We find that the forces acting on trans-bound saccharides increase with increasing membrane separation to values of the order of 10 pN.
The binding of saccharides anchored to the fluctuating membranes results from an interplay between the binding properties of the lipid-anchored saccharides and membrane fluctuations. Our simulations, which have the same average separation of the membranes as obtained from the neutron scattering experiments, yield a binding constant larger than in planar membranes with the same separation. This result demonstrates that membrane fluctuations play an important role at average membrane separations which are seemingly too large for effective binding. We further show that the probability distribution of the local separation can be well approximated by a Gaussian distribution. We calculate the relative membrane roughness and show that our results are in good agreement with the roughness values reported from the neutron scattering experiments.
In this work we investigated ultrafast demagnetization in a Heusler-alloy. This material belongs to the halfmetal and exists in a ferromagnetic phase. A special feature of investigated alloy is a structure of electronic bands. The last leads to the specific density of the states. Majority electrons form a metallic like structure while minority electrons form a gap near the Fermi-level, like in semiconductor. This particularity offers a good possibility to use this material as model-like structure and to make some proof of principles concerning demagnetization. Using pump-probe experiments we carried out time-resolved measurements to figure out the times of demagnetization. For the pumping we used ultrashort laser pulses with duration around 100 fs. Simultaneously we used two excitation regimes with two different wavelengths namely 400 nm and 1240 nm. Decreasing the energy of photons to the gap size of the minority electrons we explored the effect of the gap on the demagnetization dynamics. During this work we used for the first time OPA (Optical Parametrical Amplifier) for the generation of the laser irradiation in a long-wave regime. We tested it on the FETOSPEX-beamline in BASSYII electron storage ring. With this new technique we measured wavelength dependent demagnetization dynamics. We estimated that the demagnetization time is in a correlation with photon energy of the excitation pulse. Higher photon energy leads to the faster demagnetization in our material. We associate this result with the existence of the energy-gap for minority electrons and explained it with Elliot-Yaffet-scattering events. Additionally we applied new probe-method for magnetization state in this work and verified their effectivity. It is about the well-known XMCD (X-ray magnetic circular dichroism) which we adopted for the measurements in reflection geometry. Static experiments confirmed that the pure electronic dynamics can be separated from the magnetic one. We used photon energy fixed on the L3 of the corresponding elements with circular polarization. Appropriate incidence angel was estimated from static measurements. Using this probe method in dynamic measurements we explored electronic and magnetic dynamics in this alloy.
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.
Force plays a fundamental role in the regulation of biological processes. Cells can sense the mechanical properties of the extracellular matrix (ECM) by applying forces and transmitting mechanical signals. They further use mechanical information for regulating a wide range of cellular functions, including adhesion, migration, proliferation, as well as differentiation and apoptosis. Even though it is well understood that mechanical signals play a crucial role in directing cell fate, surprisingly little is known about the range of forces that define cell-ECM interactions at the molecular level.
Recently, synthetic molecular force sensor (MFS) designs have been established for measuring the molecular forces acting at the cell-ECM interface. MFSs detect the traction forces generated by cells and convert this mechanical input into an optical readout. They are composed of calibrated mechanoresponsive building blocks and are usually equipped with a fluorescence reporter system. Up to date, many different MFS designs have been introduced and successfully used for measuring forces involved in the adhesion of mammalian cells. These MFSs utilize different molecular building blocks, such as double-stranded deoxyribonucleic acid (dsDNA) molecules, DNA hairpins and synthetic polymers like polyethylene glycol (PEG). These currently available MFS designs lack ECM mimicking properties.
In this work, I introduce a new MFS building block for cell biology applications, derived from the natural ECM. It combines mechanical tunability with the ability to mimic the native cellular microenvironment. Inspired by structural ECM proteins with load bearing function, this new MFS design utilizes coiled coil (CC)-forming peptides. CCs are involved in structural and mechanical tasks in the cellular microenvironment and many of the key protein components of the cytoskeleton and the ECM contain CC structures. The well-known folding motif of CC structures, an easy synthesis via solid phase methods and the many roles CCs play in biological processes have inspired studies to use CCs as tunable model systems for protein design and assembly. All these properties make CCs ideal candidates as building blocks for MFSs. In this work, a series of heterodimeric CCs were designed, characterized and further used as molecular building blocks for establishing a novel, next-generation MFS prototype.
A mechanistic molecular understanding of their structural response to mechanical load is essential for revealing the sequence-structure-mechanics relationships of CCs. Here, synthetic heterodimeric CCs of different length were loaded in shear geometry and their mechanical response was investigated using a combination of atomic force microscope (AFM)-based single-molecule force spectroscopy (SMFS) and steered molecular dynamics (SMD) simulations. SMFS showed that the rupture forces of short heterodimeric CCs (3-5 heptads) lie in the range of 20-50 pN, depending on CC length, pulling geometry and the applied loading rate (dF/dt). Upon shearing, an initial rise in the force, followed by a force plateau and ultimately strand separation was observed in SMD simulations. A detailed structural analysis revealed that CC response to shear load depends on the loading rate and involves helix uncoiling, uncoiling-assisted sliding in the direction of the applied force and uncoiling-assisted dissociation perpendicular to the force axis.
The application potential of these mechanically characterized CCs as building blocks for MFSs has been tested in 2D cell culture applications with the goal of determining the threshold force for cell adhesion. Fully calibrated, 4- to 5-heptad long, CC motifs (CC-A4B4 and CC-A5B5) were used for functionalizing glass surfaces with MFSs. 3T3 fibroblasts and endothelial cells carrying mutations in a signaling pathway linked to cell adhesion and mechanotransduction processes were used as model systems for time-dependent adhesion experiments. A5B5-MFS efficiently supported cell attachment to the functionalized surfaces for both cell types, while A4B4-MFS failed to maintain attachment of 3T3 fibroblasts after the first 2 hours of initial cell adhesion. This difference in cell adhesion behavior demonstrates that the magnitude of cell-ECM forces varies depending on the cell type and further supports the application potential of CCs as mechanoresponsive and tunable molecular building blocks for the development of next-generation protein-based MFSs.This novel CC-based MFS design is expected to provide a powerful new tool for observing cellular mechanosensing processes at the molecular level and to deliver new insights into the mechanisms and forces involved. This MFS design, utilizing mechanically tunable CC building blocks, will not only allow for measuring the molecular forces acting at the cell-ECM interface, but also yield a new platform for the development of mechanically controlled materials for a large number of biological and medical applications.
A reliable inference of networks from data is of key interest in many scientific fields. Several methods have been suggested in the literature to reliably determine links in a network. These techniques rely on statistical methods, typically controlling the number of false positive links, but not considering false negative links. In this thesis new methodologies to improve network inference are suggested. Initial analyses demonstrate the impact of falsepositive and false negative conclusions about the presence or absence of links on the resulting inferred network. Consequently, revealing the importance of making well-considered choices leads to suggest new approaches to enhance existing network reconstruction methods.
A simulation study, presented in Chapter 3, shows that different values to balance false positive and false negative conclusions about links should be used in order to reliably estimate network characteristics. The existence of type I and type II errors in the reconstructed network, also called biased network, is accepted. Consequently, an analytic method that describes the influence of these two errors on the network structure is explored. As a result of this analysis, an analytic formula of the density of the biased vertex degree distribution is found (Chapter 4).
In the inverse problem, the vertex degree distribution of the true underlying network is analytically reconstructed, assuming the probabilities of type I and type II errors. Chapters 4-5 show that the method is robust to incorrect estimates of α and β within reasonable limits. In Chapter 6, an iterative procedure to enhance this method is presented in the case of large errors on the estimates of α and β.
The investigations presented so far focus on the influence of false positive and false negative links on the network characteristics. In Chapter 7, the analysis is reversed - the study focuses on the influence of network characteristics on the probability of type I and type II errors, in the case of networks of coupled oscillators. The probabilities of α and β are influenced by the shortest path length and the detour degree, respectively. These results have been used to improve the network reconstruction, when the true underlying network is not known a priori, introducing a novel and advanced concept of threshold.
Advancing charge selective contacts for efficient monolithic perovskite-silicon tandem solar cells
(2019)
Hybrid organic-inorganic perovskites are one of the most promising material classes for photovoltaic energy conversion. In solar cells, the perovskite absorber is sandwiched between n- and p-type contact layers which selectively transport electrons and holes to the cell’s cathode and anode, respectively. This thesis aims to advance contact layers in perovskite solar cells and unravel the impact of interface and contact properties on the device performance. Further, the contact materials are applied in monolithic perovskite-silicon heterojunction (SHJ) tandem solar cells, which can overcome the single junction efficiency limits and attract increasing attention. Therefore, all contact layers must be highly transparent to foster light harvesting in the tandem solar cell design. Besides, the SHJ device restricts processing temperatures for the selective contacts to below 200°C.
A comparative study of various electron selective contact materials, all processed below 180°C, in n-i-p type perovskite solar cells highlights that selective contacts and their interfaces to the absorber govern the overall device performance. Combining fullerenes and metal-oxides in a TiO2/PC60BM (phenyl-C60-butyric acid methyl ester) double-layer contact allows to merge good charge extraction with minimized interface recombination. The layer sequence thereby achieved high stabilized solar cell performances up to 18.0% and negligible current-voltage hysteresis, an otherwise pronounced phenomenon in this device design. Double-layer structures are therefore emphasized as a general concept to establish efficient and highly selective contacts.
Based on this success, the concept to combine desired properties of different materials is transferred to the p-type contact. Here, a mixture of the small molecule Spiro-OMeTAD [2,2’,7,7’-tetrakis(N,N-di-p-methoxyphenylamine)-9,9’-spirobifluoren] and the doped polymer PEDOT [poly(3,4-ethylenedioxythiophene)] is presented as a novel hole selective contact. PEDOT thereby remarkably suppresses charge recombination at the perovskite surface, allowing an increase of quasi-Fermi level splitting in the absorber. Further, the addition of Spiro-OMeTAD into the PEDOT layer is shown to enhance charge extraction at the interface and allow high efficiencies up to 16.8%.
Finally, the knowledge on contact properties is applied to monolithic perovskite-SHJ tandem solar cells. The main goal is to optimize the top contact stack of doped Spiro-OMeTAD/molybdenum oxide(MoOx)/ITO towards higher transparency by two different routes. First, fine-tuning of the ITO deposition to mitigate chemical reduction of MoOx and increase the transmittance of MoOx/ITO stacks by 25%. Second, replacing Spiro-OMeTAD with the alternative hole transport materials PEDOT/Spiro-OMeTAD mixtures, CuSCN or PTAA [poly(triaryl amine)]. Experimental results determine layer thickness constrains and validate optical simulations, which subsequently allow to realistically estimate the respective tandem device performances. As a result, PTAA represents the most promising replacement for Spiro-OMeTAD, with a projected increase of the optimum tandem device efficiency for the herein used architecture by 2.9% relative to 26.5% absolute. The results also reveal general guidelines for further performance gains of the technology.
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.
In this dissertation the lattice and the magnetic recovery dynamics of the two heavy rare-earth metals Dy and Gd after femtosecond photoexcitation are described. For the investigations, thin films of Dy and Gd were measured at low temperatures in the antiferromagnetic phase of Dy and close to room temperature in the ferromagnetic phase of Gd. Two different optical pump-x-ray probe techniques were employed: Ultrafast x-ray diffraction with hard x-rays (UXRD) yields the structural response of heavy rare-earth metals and resonant soft (elastic) x-ray diffraction (RSXD), which allows measuring directly changes in the helical antiferromagnetic order of Dy. The combination of both techniques enables to study the complex interaction between the magnetic and the phononic subsystems.
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.
Poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) ferroelectric thin films of different molar ratio have been studied with regard to data memory applications. Therefore, films with thicknesses of 200 nm and less have been spin coated from solution. Observations gained from single layers have been extended to multilayer capacitors and three terminal transistor devices.
Besides conventional hysteresis measurements, the measurement of dielectric non-linearities has been used as a main tool of characterisation. Being a very sensitive and non-destructive method, non-linearity measurements are well suited for polarisation readout and property studies. Samples have been excited using a high quality, single-frequency sinusoidal voltage with an amplitude significantly smaller than the coercive field of the samples. The response was then measured at the excitation frequency and its higher harmonics. Using the measurement results, the linear and non-linear dielectric permittivities ɛ₁, ɛ₂ and ɛ₃ have been determined. The permittivities have been used to derive the temperature-dependent polarisation behaviour as well as the polarisation state and the order of the phase transitions.
The coercive field in VDF-TrFE copolymers is high if compared to their ceramic competitors. Therefore, the film thickness had to be reduced significantly. Considering a switching voltage of 5 V and a coercive field of 50 MV/m, the film thickness has to be 100 nm and below. If the thickness becomes substantially smaller than the other dimensions, surface and interface layer effects become more pronounced. For thicker films of P(VDF-TrFE) with a molar fraction of 56/44 a second-order phase transition without a thermal hysteresis for an ɛ₁(T) temperature cycle has been predicted and observed. This however, could not be confirmed by the measurements of thinner films. A shift of transition temperatures as well as a temperature independent, non-switchable polarisation and a thermal hysteresis for P(VDF-TrFE) 56/44 have been observed. The impact of static electric fields on the polarisation and the phase transition has therefore been studied and simulated, showing that all aforementioned phenomena including a linear temperature dependence of the polarisation might originate from intrinsic electric fields.
In further experiments the knowledge gained from single layer capacitors has been extended to bilayer copolymer thin films of different molar composition. Bilayers have been deposited by succeeding cycles of spin coating from solution. Single layers and their bilayer combination have been studied individually in order to prove the layers stability. The individual layers have been found to be physically stable. But while the bilayers reproduced the main ɛ₁(T) properties of the single layers qualitatively, quantitative numbers could not be explained by a simple serial connection of capacitors. Furthermore, a linear behaviour of the polarisation throughout the measured temperature range has been observed. This was found to match the behaviour predicted considering a constant electric field.
Retention time is an important quantity for memory applications. Hence, the retention behaviour of VDF-TrFE copolymer thin films has been determined using dielectric non-linearities. The polarisation loss in P(VDF-TrFE) poled samples has been found to be less than 20% if recorded over several days. The loss increases significantly if the samples have been poled with lower amplitudes, causing an unsaturated polarisation. The main loss was attributed to injected charges. Additionally, measurements of dielectric non-linearities have been proven to be a sensitive and non-destructive tool to measure the retention behaviour.
Finally, a ferroelectric field effect transistor using mainly organic materials (FerrOFET) has been successfully studied. DiNaphtho[2,3-b:2',3'-f]Thieno[3,2-b]Thiophene (DNTT) has proven to be a stable, suitable organic semiconductor to build up ferroelectric memory devices. Furthermore, an oxidised aluminium bottom electrode and additional dielectric layers, i.e. parylene C, have proven to reduce the leakage current and therefore enhance the performance significantly.
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.
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.
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.
The Sun is the nearest star to the Earth. It consists of an interior and an atmosphere. The convection zone is the outermost layer of the solar interior. A flux rope may emerge as a coherent structure from the convection zone into the solar atmosphere or be formed by magnetic reconnection in the atmosphere. A flux rope is a bundle of magnetic field lines twisting around an axis field line, creating a helical shape by which dense filament material can be supported against gravity. The flux rope is also considered as the key structure of the most energetic phenomena in the solar system, such as coronal mass ejections (CMEs) and flares. These magnetic flux ropes can produce severe geomagnetic storms. In particular, to improve the ability to forecast space weather, it is important to enrich our knowledge about the dynamic formation of flux ropes and the underlying physical mechanisms that initiate their eruption, such as a CME.
A confined eruption consists of a filament eruption and usually an associated are, but does not evolve into a CME; rather, the moving plasma is halted in the solar corona and usually seen to fall back. The first detailed observations of a confined filament eruption were obtained on 2002 May 27by the TRACE satellite in the 195 A band. So, in the Chapter 3, we focus on a flux rope instability model. A twisted flux rope can become unstable by entering the kink instability regime. We show that the kink instability, which occurs if the twist of a flux rope exceeds a critical value, is capable of initiating of an eruption. This model is tested against the well observed confined eruption on 2002 May 27 in a parametric magnetohydrodynamic (MHD) simulation study that comprises all phases of the event. Very good agreement with the essential observed properties is obtained, only except for a relatively poor matching of the initial filament height.
Therefore, in Chapter 4, we submerge the center point of the flux rope deeper below the photosphere to obtain a flatter coronal rope section and a better matching with the initial height profile of the erupting filament. This implies a more realistic inclusion of the photospheric line tying. All basic assumptions and the other parameter settings are kept the same as in Chapter 3. This complement of the parametric study shows that the flux rope instability model can yield an even better match with the observational data. We also focus in Chapters 3 and 4 on the magnetic reconnection during the confined eruption, demonstrating that it occurs in two distinct locations and phases that correspond to the observed brightenings and changes of topology, and consider the fate of the erupting flux, which can reform a (less twisted) flux rope.
The Sun also produces series of homologous eruptions, i.e. eruptions which occur repetitively in the same active region and are of similar morphology. Therefore, in Chapter 5, we employ the reformed flux rope as a new initial condition, to investigate the possibility of subsequent homologous eruptions. Free magnetic energy is built up by imposing motions in the bottom boundary, such as converging motions, leading to flux cancellation. We apply converging motions in the sunspot area, such that a small part of the flux from the sunspots with different polarities is transported toward the polarity inversion line (PIL) and cancels with each other. The reconnection associated with the cancellation process forms more helical magnetic flux around the reformed flux rope, which leads to a second and a third eruption. In this study, we obtain the first MHD simulation results of a homologous sequence of eruptions that show a transition from a confined to two ejective eruptions, based on the reformation of a flux rope after each eruption.
This publication based thesis, which consists of seven published articles, summarizes my contributions to the research field of laser excited ultrafast structural dynamics. The coherent and incoherent lattice dynamics on microscopic length scales are detected by ultrashort optical and X-ray pulses. The understanding of the complex physical processes is essential for future improvements of technological applications. For this purpose, tabletop soruces and large scale facilities, e.g. synchrotrons, are employed to study structural dynamics of longitudinal acoustic strain waves and heat transport. The investigated effects cover timescales from hundreds of femtoseconds up to several microseconds.
The main part of this thesis is dedicated to the investigation of tailored phonon wave packets propagating in perovskite nanostructures. Tailoring is achieved either by laser excitation of nanostructured bilayer samples or by a temporal series of laser pulses. Due to the propagation of longitudinal acoustic phonons, the out-of-plane lattice spacing of a thin film insulator-metal bilayer sample is modulated on an ultrafast timescale. This leads to an ultrafast modulation of the X-ray diffraction efficiency which is employed as a phonon Bragg switch to shorten hard X-ray pulses emitted from a 3rd generation synchrotron.
In addition, we have observed nonlinear mixing of high amplitude phonon wave packets which originates from an anharmonic interatomic potential. A chirped optical pulse sequence excites a narrow band phonon wave packet with specific momentum and energy. The second harmonic generation of these phonon wave packets is followed by ultrafast X-ray diffraction. Phonon upconversion takes place because the high amplitude phonon wave packet modulates the acoustic properties of the crystal which leads to self steepening and to the successive generation of higher harmonics of the phonon wave packet.
Furthermore, we have demonstrated ultrafast strain in direction parallel to the sample surface. Two consecutive so-called transient grating excitations displaced in space and time are used to coherently control thermal gradients and surface acoustic modes. The amplitude of the coherent and incoherent surface excursion is disentangled by time resolved X-ray reflectivity measurements. We calibrate the absolute amplitude of thermal and acoustic surface excursion with measurements of longitudinal phonon propagation. In addition, we develop a diffraction model which allows for measuring the surface excursion on an absolute length scale with sub-Äangström precision. Finally, I demonstrate full coherent control of an excited surface deformation by amplifying and suppressing thermal and coherent excitations at the surface of a laser-excited Yttrium-manganite sample.
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.
In this thesis, we treat the extreme Newman-Penrose components of both the Maxwell field (s=±1) and the linearized gravitational perturbations (or "linearized gravity" for short) (s=±2) in the exterior of a slowly rotating Kerr black hole. Upon different rescalings, we can obtain spin s components which satisfy the separable Teukolsky master equation (TME). For each of these spin s components defined in Kinnersley tetrad, the resulting equations by performing some first-order differential operator on it once and twice (twice only for s=±2), together with the TME, are in the form of an "inhomogeneous spin-weighted wave equation" (ISWWE) with different potentials and constitute a linear spin-weighted wave system. We then prove energy and integrated local energy decay (Morawetz) estimates for this type of ISWWE, and utilize them to achieve both a uniform bound of a positive definite energy and a Morawetz estimate for the regular extreme Newman-Penrose components defined in the regular Hawking-Hartle tetrad.
We also present some brief discussions on mode stability for TME for the case of real frequencies. This says that in a fixed subextremal Kerr spacetime, there is no nontrivial separated mode solutions to TME which are purely ingoing at horizon and purely outgoing at infinity. This yields a representation formula for solutions to inhomogeneous Teukolsky equations, and will play a crucial role in generalizing the above energy and Morawetz estimates results to the full subextremal Kerr case.
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.
Earth's climate varies continuously across space and time, but humankind has witnessed only a small snapshot of its entire history, and instrumentally documented it for a mere 200 years. Our knowledge of past climate changes is therefore almost exclusively based on indirect proxy data, i.e. on indicators which are sensitive to changes in climatic variables and stored in environmental archives. Extracting the data from these archives allows retrieval of the information from earlier times. Obtaining accurate proxy information is a key means to test model predictions of the past climate, and only after such validation can the models be used to reliably forecast future changes in our warming world. The polar ice sheets of Greenland and Antarctica are one major climate archive, which record information about local air temperatures by means of the isotopic composition of the water molecules embedded in the ice. However, this temperature proxy is, as any indirect climate data, not a perfect recorder of past climatic variations. Apart from local air temperatures, a multitude of other processes affect the mean and variability of the isotopic data, which hinders their direct interpretation in terms of climate variations. This applies especially to regions with little annual accumulation of snow, such as the Antarctic Plateau. While these areas in principle allow for the extraction of isotope records reaching far back in time, a strong corruption of the temperature signal originally encoded in the isotopic data of the snow is expected. This dissertation uses observational isotope data from Antarctica, focussing especially on the East Antarctic low-accumulation area around the Kohnen Station ice-core drilling site, together with statistical and physical methods, to improve our understanding of the spatial and temporal isotope variability across different scales, and thus to enhance the applicability of the proxy for estimating past temperature variability. The presented results lead to a quantitative explanation of the local-scale (1–500 m) spatial variability in the form of a statistical noise model, and reveal the main source of the temporal variability to be the mixture of a climatic seasonal cycle in temperature and the effect of diffusional smoothing acting on temporally uncorrelated noise. These findings put significant limits on the representativity of single isotope records in terms of local air temperature, and impact the interpretation of apparent cyclicalities in the records. Furthermore, to extend the analyses to larger scales, the timescale-dependency of observed Holocene isotope variability is studied. This offers a deeper understanding of the nature of the variations, and is crucial for unravelling the embedded true temperature variability over a wide range of timescales.
In Germany more than 200.000 persons die of cancer every year, which makes it the second most common cause of death. Chemotherapy and radiation therapy are often combined to exploit a supra-additive effect, as some chemotherapeutic agents like halogenated nucleobases sensitize the cancerous tissue to radiation. The radiosensitizing action of certain therapeutic agents can be at least partly assigned to their interaction with secondary low energy electrons (LEEs) that are generated along the track of the ionizing radiation. In the therapy of cancer DNA is an important target, as severe DNA damage like double strand breaks induce the cell death. As there is only a limited number of radiosensitizing agents in clinical practice, which are often strongly cytotoxic, it would be beneficial to get a deeper understanding of the interaction of less toxic potential radiosensitizers with secondary reactive species like LEEs. Beyond that LEEs can be generated by laser illuminated nanoparticles that are applied in photothermal therapy (PTT) of cancer, which is an attempt to treat cancer by an increase of temperature in the cells. However, the application of halogenated nucleobases in PTT has not been taken into account so far. In this thesis the interaction of the potential radiosensitizer 8-bromoadenine (8BrA) with LEEs was studied. In a first step the dissociative electron attachment (DEA) in the gas phase was studied in a crossed electron-molecular beam setup. The main fragmentation pathway was revealed as the cleavage of the C-Br bond. The formation of a stable parent anion was observed for electron energies around 0 eV. Furthermore, DNA origami nanostructures were used as platformed to determine electron induced strand break cross sections of 8BrA sensitized oligonucleotides and the corresponding nonsensitized sequence as a function of the electron energy. In this way the influence of the DEA resonances observed for the free molecules on the DNA strand breaks was examined. As the surrounding medium influences the DEA, pulsed laser illuminated gold nanoparticles (AuNPs) were used as a nanoscale electron source in an aqueous environment. The dissociation of brominated and native nucleobases was tracked with UV-Vis absorption spectroscopy and the generated fragments were identified with surface enhanced Raman scattering (SERS). Beside the electron induced damage, nucleobase analogues are decomposed in the vicinity of the laser illuminatednanoparticles due to the high temperatures. In order to get a deeper understanding of the different dissociation mechanisms, the thermal decomposition of the nucleobases in these systems was studied and the influence of the adsorption kinetics of the molecules was elucidated. In addition to the pulsed laser experiments, a dissociative electron transfer from plasmonically generated ”hot electrons” to 8BrA was observed under low energy continuous wave laser illumination and tracked with SERS. The reaction was studied on AgNPs and AuNPs as a function of the laser intensity and wavelength. On dried samples the dissociation of the molecule was described by fractal like kinetics. In solution, the dissociative electron transfer was observed as well. It turned out that the timescale of the reaction rates were slightly below typical integration times of Raman spectra. In consequence such reactions need to be taken into account in the interpretation of SERS spectra of electrophilic molecules. The findings in this thesis help to understand the interaction of brominated nucleobases with plasmonically generated electrons and free electrons. This might help to evaluate the potential radiosensitizing action of such molecules in cancer radiation therapy and PTT.
We present electrical impedance measurements of amoeboid cells on microelectrodes. The model organism Dictyostelium discoideum shows under starvation conditions a transition to collective behavior when chemotactic cells collect in multicellular aggregates. We show how impedance recordings give a precise picture of the stages of aggregation by tracing the dynamics of cell-substrate adhesion. Furthermore, we present for the first time systematic single cell measurements of wild type cells and four mutant strains that differ in their substrate adhesion strength. We recorded the projected cell area by time lapse microscopy and found a correlation between quasi-periodic oscillations in the kinetics of the projected area - the cell shape oscillation - and the long-term trend in the impedance signal. Typically, amoeboid motility advances via a cycle of membrane protrusion, substrate adhesion, traction of the cell body and tail retraction. This motility cycle results in the quasi-periodic oscillations of the projected cell area and the impedance. In all cell lines measured, similar periods were observed for this cycle, despite the differences in attachment strength. We observed that cell-substrate attachment strength strongly affects the impedance in that the deviations from mean (the magnitude of fluctuations) are enhanced in cells that effectively transmit forces, generated by the cytoskeleton, to the substrate. For example, in talA- cells, which lack the actin anchoring protein talin, the fluctuations are strongly reduced. Single cell force spectroscopy and results from a detachment assay, where adhesion is measured by exposing cells to shear stress, confirm that the magnitude of impedance fluctuations is a correct measure for the strength of substrate adhesion. Finally, we also worked on the integration of cell-substrate impedance sensors into microfluidic devices. A chip-based electrical chemotaxis assay is designed which measures the speed of chemotactic cells migrating over microelectrodes along a chemical concentration gradient.
Proteins are molecules that are essential for life and carry out an enormous number of functions in organisms. To this end, they change their conformation and bind to other molecules. However, the interplay between conformational change and binding is not fully understood. In this work, this interplay is investigated with molecular dynamics (MD) simulations of the protein-peptide system Mdm2-PMI and by analysis of data from relaxation experiments.
The central task it to uncover the binding mechanism, which is described by the sequence of (partial) binding events and conformational change events including their probabilities. In the simplest case, the binding mechanism is described by a two-step model: binding followed by conformational change or conformational change followed by binding. In the general case, longer sequences with multiple conformational changes and partial binding events are possible as well as parallel pathways that differ in their sequences of events. The theory of Markov state models (MSMs) provides the theoretical framework in which all these cases can be modeled. For this purpose, MSMs are estimated in this work from MD data, and rate equation models, which are related to MSMs, are inferred from experimental relaxation data.
The MD simulation and Markov modeling of the PMI-Mdm2 system shows that PMI and Mdm2 can bind via multiple pathways. A main result of this work is a dissociation rate on the order of one event per second, which was calculated using Markov modeling and is in agreement with experiment. So far, dissociation rates and transition rates of this magnitude have only been calculated with methods that speed up transitions by acting with time-dependent, external forces on the binding partners. The simulation technique developed in this work, in contrast, allows the estimation of dissociation rates from the combination of free energy calculation and direct MD simulation of the fast binding process. Two new statistical estimators TRAM and TRAMMBAR are developed to estimate a MSM from the joint data of both simulation types.
In addition, a new analysis technique for time-series data from chemical relaxation experiments is developed in this work. It allows to identify one of the above-mentioned two-step mechanisms as the mechanism that underlays the data. The new method is valid for a broader range of concentrations than previous methods and therefore allows to choose the concentrations such that the mechanism can be uniquely identified. It is successfully tested with data for the binding of recoverin to a rhodopsin kinase peptide.
Approaching physical limits in speed and size of today's magnetic storage and processing technologies demands new concepts for controlling magnetization and moves researches on optically induced magnetic dynamics. Studies on photoinduced magnetization dynamics and their underlying mechanisms have been primarily performed on ferromagnetic metals. Ferromagnetic dynamics bases on transfer of the conserved angular momentum connected with atomic magnetic moments out of the parallel aligned magnetic system into other degrees of freedom.
In this thesis the so far rarely studied response of antiferromagnetic order to ultra-short optical laser pulses in a metal is investigated. The experiments were performed at the FemtoSpex slicing facility at the storage ring BESSY II, an unique source for ultra-short elliptically polarized x-ray pulses. Laser-induced changes of the 4f-magnetic order parameter in ferro- and antiferromagnetic dysprosium (Dy), were studied by x-ray methods, which yield directly comparable quantities. The discovered fundamental differences in the temporal and spatial behavior of ferro- and antiferrmagnetic dynamics are assinged to an additional channel for angular momentum transfer, which reduces the antiferromagnetic order by redistributing angular momentum within the non-parallel aligned magnetic system, and hence conserves the zero net magnetization. It is shown that antiferromagnetic dynamics proceeds considerably faster and more energy-efficient than demagnetization in ferromagnets. By probing antiferromagnetic order in time and space, it is found to be affected along the whole sample depth of an in situ grown 73 nm tick Dy film. Interatomic transfer of angular momentum via fast diffusion of laser-excited 5d electrons is held responsible for the out-most long-ranging effect. Ultrafast ferromagnetic dynamics can be expected to base on the same origin, which however leads to demagnetization only in regions close to interfaces caused by super-diffusive spin transport. Dynamics due to local scattering processes of excited but less mobile electrons, occur in both magnetic alignments only in directly excited regions of the sample and on slower pisosecond timescales. The thesis provides fundamental insights into photoinduced magnetic dynamics by directly comparing ferro- and antiferromagnetic dynamics in the same material and by consideration of the laser-induced magnetic depth profile.
The goal of this thesis is related to the question how to introduce and combine simultaneously plasmonic and photoswitching properties to different nano-objects. In this thesis I investigate the complexes between noble metal nanoparticles and cationic surfactants containing azobenzene units in their hydrophobic tail, employing absorption spectroscopy, surface zeta-potential, and electron microscopy.
In the first part of the thesis, the formation of complexes between negatively charged laser ablated spherical gold nanoparticles and cationic azobenzene surfactants in trans- conformation is explored. It is shown that the constitution of the complexes strongly depends on a surfactant-to-gold molar ratio. At certain molar ratios, particle self-assembly into nanochains and their aggregation have been registered. At higher surfactant concentrations, the surface charge of nanoparticles turned positive, attributed to the formation of the stabilizing double layer of azobenzene surfactants on gold nanoparticle surfaces. These gold-surfactant complexes remained colloidally stable. UV light induced trans-cis isomerization of azobenzene surfactant molecules and thus perturbed the stabilizing surfactant shell, causing nanoparticle aggregation. The results obtained with silver and silicon nanoparticles mimick those for the comprehensively studied gold nanoparticles, corroborating the proposed model of complex formation.
In the second part, the interaction between plasmonic metal nanoparticles (Au, Ag, Pd, alloy Au-Ag, Au-Pd), as well as silicon nanoparticles, and cis-isomers of azobenzene containing compounds is addressed. Cis-trans thermal isomerization of azobenzenes was enhanced in the presence of gold, palladium, and alloy gold-palladium nanoparticles. The influence of the surfactant structure and nanoparticle material on the azobenzene isomerization rate is expounded. Gold nanoparticles showed superior catalytic activity for thermal cis-trans isomerization of azobenzenes. In a joint project with theoretical chemists, we demonstrated that the possible physical origin of this phenomenon is the electron transfer between azobenzene moieties and nanoparticle surfaces.
In the third part, complexes between gold nanorods and azobenzene surfactants with different tail length were exposed to UV and blue light, inducing trans-cis and cis-trans isomerization of surfactant, respectively. At the same time, the position of longitudinal plasmonic absorption maximum of gold nanorods experienced reversible shift responding to the changes in local dielectric environment. Surface plasmon resonance condition allowed the estimation of the refractive index of azobenzene containing surfactants in solution.
In the current paradigm of cosmology, the formation of large-scale structures is mainly driven by non-radiating dark matter, making up the dominant part of the matter budget of the Universe. Cosmological observations however, rely on the detection of luminous galaxies, which are biased tracers of the underlying dark matter. In this thesis I present cosmological reconstructions of both, the dark matter density field that forms the cosmic web, and cosmic velocities, for which both aspects of my work are delved into, the theoretical formalism and the results of its applications to cosmological simulations and also to a galaxy redshift survey.The foundation of our method is relying on a statistical approach, in which a given galaxy catalogue is interpreted as a biased realization of the underlying dark matter density field. The inference is computationally performed on a mesh grid by sampling from a probability density function, which describes the joint posterior distribution of matter density and the three dimensional velocity field. The statistical background of our method is described in Chapter ”Implementation of argo”, where the introduction in sampling methods is given, paying special attention to Markov Chain Monte-Carlo techniques. In Chapter ”Phase-Space Reconstructions with N-body Simulations”, I introduce and implement a novel biasing scheme to relate the galaxy number density to the underlying dark matter, which I decompose into a deterministic part, described by a non-linear and scale-dependent analytic expression, and a stochastic part, by presenting a negative binomial (NB) likelihood function that models deviations from Poissonity. Both bias components had already been studied theoretically, but were so far never tested in a reconstruction algorithm. I test these new contributions againstN-body simulations to quantify improvements and show that, compared to state-of-the-art methods, the stochastic bias is inevitable at wave numbers of k≥0.15h Mpc^−1 in the power spectrum in order to obtain unbiased results from the reconstructions. In the second part of Chapter ”Phase-Space Reconstructions with N-body Simulations” I describe and validate our approach to infer the three dimensional cosmic velocity field jointly with the dark matter density. I use linear perturbation theory for the large-scale bulk flows and a dispersion term to model virialized galaxy motions, showing that our method is accurately recovering the real-space positions of the redshift-space distorted galaxies. I analyze the results with the isotropic and also the two-dimensional power spectrum.Finally, in Chapter ”Phase-space Reconstructions with Galaxy Redshift Surveys”, I show how I combine all findings and results and apply the method to the CMASS (for Constant (stellar) Mass) galaxy catalogue of the Baryon Oscillation Spectroscopic Survey (BOSS). I describe how our method is accounting for the observational selection effects inside our reconstruction algorithm. Also, I demonstrate that the renormalization of the prior distribution function is mandatory to account for higher order contributions in the structure formation model, and finally a redshift-dependent bias factor is theoretically motivated and implemented into our method. The various refinements yield unbiased results of the dark matter until scales of k≤0.2 h Mpc^−1in the power spectrum and isotropize the galaxy catalogue down to distances of r∼20h^−1 Mpc in the correlation function. We further test the results of our cosmic velocity field reconstruction by comparing them to a synthetic mock galaxy catalogue, finding a strong correlation between the mock and the reconstructed velocities. The applications of both, the density field without redshift-space distortions, and the velocity reconstructions, are very broad and can be used for improved analyses of the baryonic acoustic oscillations, environmental studies of the cosmic web, the kinematic Sunyaev-Zel’dovic or integrated Sachs-Wolfe effect.
Magnetotactic bacteria possess an intracellular structure called the magnetosome chain. Magnetosome chains contain nano−particles of iron crystals enclosed by a membrane and aligned on a cytoskeletal filament. Due to the presence of the magnetosome chains, magnetotactic bacteria are able to orient and swim along the magnetic field lines. A detailed study of structural properties of magnetosome chains in magnetotactic bacteria has primary scientific interests. It can provide more insight into the formation of the cytoskeleton in bacteria. In this thesis, we develop a new framework to study the structural properties of magnetosome chains in magnetotactic bacteria.
First, we address the bending stiffness of magnetosome chains resulting from two main contributions: the magnetic interactions of magnetosome particles and the bending stiffness of the cytoskeletal filament to which the magnetosomes are anchored. Our analysis indicates that the linear configuration of magnetosome particles without the stabilisation to the cytoskeleton may close to ring like structures, with no net magnetic moment, which thus can not perform as a compass in cellular navigation. As a result we think that one of the roles of the filament is to stabilize the linear configuration against ring closure.
We then investigate the equilibrium configurations of magnetosome particles including linear chain and closed−ring structures. We notably observe that for the formation of a stable linear structure on the cytoskeletal filament, presence of a binding energy is needed. In the presence of external stimuli the stability of the magnetosome chain is due to the internal dipole−dipole interactions, the stiffness and the binding energy of the protein structure connecting the magnetosome particles to the filament. Our observations, during and after the treatment of the magnetosome chain with the external magnetic field substantiates the stabilisation of magnetosome chains to the cytoskeletal filament by proteinous linkers and the dynamic feature of these structures.
Finally, we employ our model to study the FMR spectra of magnetosome chains in a single cell of magnetotactic bacteria. We explore the effect of magnetocrystalline anisotropy in three-fold symmetry observed in FMR spectra and the peculiarity of different spectra arisen from different mutants of these bacteria.
Tremendous progress in the development of thin film solar cell techniques has been made over the last decade. The field of organic solar cells is constantly developing, new material classes like Perowskite solar cells are emerging and different types of hybrid organic/inorganic material combinations are being investigated for their physical properties and their applicability in thin film electronics. Besides typical single-junction architectures for solar cells, multi-junction concepts are also being investigated as they enable the overcoming of theoretical limitations of a single-junction. In multi-junction devices each sub-cell operates in different wavelength regimes and should exhibit optimized band-gap energies. It is exactly this tunability of the band-gap energy that renders organic solar cell materials interesting candidates for multi-junction applications. Nevertheless, only few attempts have been made to combine inorganic and organic solar cells in series connected multi-junction architectures. Even though a great diversity of organic solar cells exists nowadays, their open circuit voltage is usually low compared to the band-gap of the active layer. Hence, organic low band-gap solar cells in particular show low open circuit voltages and the key factors that determine the voltage losses are not yet fully understood. Besides open circuit voltage losses the recombination of charges in organic solar cells is also a prevailing research topic, especially with respect to the influence of trap states.
The exploratory focus of this work is therefore set, on the one hand, on the development of hybrid organic/inorganic multi-junctions and, on the other hand, on gaining a deeper understanding of the open circuit voltage and the recombination processes of organic solar cells.
In the first part of this thesis, the development of a hybrid organic/inorganic triple-junction will be discussed which showed at that time (Jan. 2015) a record power conversion efficiency of 11.7%. The inorganic sub-cells of these devices consist of hydrogenated amorphous silicon and were delivered by the Competence Center Thin-Film and Nanotechnology for Photovoltaics in Berlin. Different recombination contacts and organic sub-cells were tested in conjunction with these inorganic sub-cells on the basis of optical modeling predictions for the optimal layer thicknesses to finally reach record efficiencies for this type of solar cells.
In the second part, organic model systems will be investigated to gain a better understanding of the fundamental loss mechanisms that limit the open circuit voltage of organic solar cells. First, bilayer systems with different orientation of the donor and acceptor molecules were investigated to study the influence of the donor/acceptor orientation on non-radiative voltage loss. Secondly, three different bulk heterojunction solar cells all comprising the same amount of fluorination and the same polymer backbone in the donor component were examined to study the influence of long range electrostatics on the open circuit voltage. Thirdly, the device performance of two bulk heterojunction solar cells was compared which consisted of the same donor polymer but used different fullerene acceptor molecules. By this means, the influence of changing the energetics of the acceptor component on the open circuit voltage was investigated and a full analysis of the charge carrier dynamics was presented to unravel the reasons for the worse performance of the solar cell with the higher open circuit voltage. In the third part, a new recombination model for organic solar cells will be introduced and its applicability shown for a typical low band-gap cell. This model sheds new light on the recombination process in organic solar cells in a broader context as it re-evaluates the recombination pathway of charge carriers in devices which show the presence of trap states. Thereby it addresses a current research topic and helps to resolve alleged discrepancies which can arise from the interpretation of data derived by different measurement techniques.