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The aim of this thesis is to achieve a deep understanding of the working mechanism of polymer based solar cells and to improve the device performance. Two types of the polymer based solar cells are studied here: all-polymer solar cells comprising macromolecular donors and acceptors based on poly(p-phenylene vinylene) and hybrid cells comprising a PPV copolymer in combination with a novel small molecule electron acceptor. To understand the interplay between morphology and photovoltaic properties in all-polymer devices, I compared the photocurrent characteristics and excited state properties of bilayer and blend devices with different nano-morphology, which was fine tuned by using solvents with different boiling points. The main conclusion from these complementary measurements was that the performance-limiting step is the field-dependent generation of free charge carriers, while bimolecular recombination and charge extraction do not compromise device performance. These findings imply that the proper design of the donor-acceptor heterojunction is of major importance towards the goal of high photovoltaic efficiencies. Regarding polymer-small molecular hybrid solar cells I combined the hole-transporting polymer M3EH-PPV with a novel Vinazene-based electron acceptor. This molecule can be either deposited from solution or by thermal evaporation, allowing for a large variety of layer architectures to be realized. I then demonstrated that the layer architecture has a large influence on the photovoltaic properties. Solar cells with very high fill factors of up to 57 % and an open circuit voltage of 1V could be achieved by realizing a sharp and well-defined donor-acceptor heterojunction. In the past, fill factors exceeding 50 % have only been observed for polymers in combination with soluble fullerene-derivatives or nanocrystalline inorganic semiconductors as the electron-accepting component. The finding that proper processing of polymer-vinazene devices leads to similar high values is a major step towards the design of efficient polymer-based solar cells.
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.
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.
In this Thesis, the properties of aqueous hemicellulose polysaccharides are investigated using computer simulations. The high swelling capacity of materials composed of these molecules allows the generation of directed motion in plant materials entirely controlled by water uptake.
To explore the molecular origin of this swelling capacity, a computational model with atomistic resolution for hemicellulose polysaccharides is build and validated in comparison with experiments. Using this model, simulations of small polysaccharides are employed to gain an understanding of the interactions of these molecules with water, the influence of water on their conformational freedom, and the swelling capacity quantified in terms of osmotic pressure. It is revealed that the branched hemicellulose polysaccharides show different hydration characteristics compared to linear polysaccharides.
To study swelling properties on length and time scales that exceed the limitations imposed by atomistic simulations, a procedure to obtain transferable coarse-grain models is developed. The transferability of the coarse-grain models over both different degrees of polymerization as well as different solute concentrations is demonstrated. Therefore, the procedure allows the construction of large coarse-grained systems based on small atomistic reference systems. Finally, the coarse-grain model is applied to demonstrate that linear and branched polysaccharides show a different swelling behavior when coupled to a water bath.
The cytoskeleton is an essential component of living cells. It is composed of different types of protein filaments that form complex, dynamically rearranging, and interconnected networks. The cytoskeleton serves a multitude of cellular functions which further depend on the cell context. In animal cells, the cytoskeleton prominently shapes the cell's mechanical properties and movement. In plant cells, in contrast, the presence of a rigid cell wall as well as their larger sizes highlight the role of the cytoskeleton in long-distance intracellular transport. As it provides the basis for cell growth and biomass production, cytoskeletal transport in plant cells is of direct environmental and economical relevance. However, while knowledge about the molecular details of the cytoskeletal transport is growing rapidly, the organizational principles that shape these processes on a whole-cell level remain elusive.
This thesis is devoted to the following question: How does the complex architecture of the plant cytoskeleton relate to its transport functionality? The answer requires a systems level perspective of plant cytoskeletal structure and transport. To this end, I combined state-of-the-art confocal microscopy, quantitative digital image analysis, and mathematically powerful, intuitively accessible graph-theoretical approaches.
This thesis summarizes five of my publications that shed light on the plant cytoskeleton as a transportation network: (1) I developed network-based frameworks for accurate, automated quantification of cytoskeletal structures, applicable in, e.g., genetic or chemical screens; (2) I showed that the actin cytoskeleton displays properties of efficient transport networks, hinting at its biological design principles; (3) Using multi-objective optimization, I demonstrated that different plant cell types sustain cytoskeletal networks with cell-type specific and near-optimal organization; (4) By investigating actual transport of organelles through the cell, I showed that properties of the actin cytoskeleton are predictive of organelle flow and provided quantitative evidence for a coordination of transport at a cellular level; (5) I devised a robust, optimization-based method to identify individual cytoskeletal filaments from a given network representation, allowing the investigation of single filament properties in the network context. The developed methods were made publicly available as open-source software tools.
Altogether, my findings and proposed frameworks provide quantitative, system-level insights into intracellular transport in living cells. Despite my focus on the plant cytoskeleton, the established combination of experimental and theoretical approaches is readily applicable to different organisms. Despite the necessity of detailed molecular studies, only a complementary, systemic perspective, as presented here, enables both understanding of cytoskeletal function in its evolutionary context as well as its future technological control and utilization.
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.
When Galactic microlensing events of stars are observed, one usually measures a symmetric light curve corresponding to a single lens, or an asymmetric light curve, often with caustic crossings, in the case of a binary lens system. In principle, the fraction of binary stars at a certain separation range can be estimated based on the number of measured microlensing events. However, a binary system may produce a light curve which can be fitted well as a single lens light curve, in particullary if the data sampling is poor and the errorbars are large. We investigate what fraction of microlensing events produced by binary stars for different separations may be well fitted by and hence misinterpreted as single lens events for various observational conditions. We find that this fraction strongly depends on the separation of the binary components, reaching its minimum at between 0.6 and 1.0 Einstein radius, where it is still of the order of 5% The Einstein radius is corresponding to few A.U. for typical Galactic microlensing scenarios. The rate for misinterpretation is higher for short microlensing events lasting up to few months and events with smaller maximum amplification. For fixed separation it increases for binaries with more extreme mass ratios. Problem of degeneracy in photometric light curve solution between binary lens and binary source microlensing events was studied on simulated data, and data observed by the PLANET collaboration. The fitting code BISCO using the PIKAIA genetic algorithm optimizing routine was written for optimizing binary-source microlensing light curves observed at different sites, in I, R and V photometric bands. Tests on simulated microlensing light curves show that BISCO is successful in finding the solution to a binary-source event in a very wide parameter space. Flux ratio method is suggested in this work for breaking degeneracy between binary-lens and binary-source photometric light curves. Models show that only a few additional data points in photometric V band, together with a full light curve in I band, will enable breaking the degeneracy. Very good data quality and dense data sampling, combined with accurate binary lens and binary source modeling, yielded the discovery of the lowest-mass planet discovered outside of the Solar System so far, OGLE-2005-BLG-390Lb, having only 5.5 Earth masses. This was the first observed microlensing event in which the degeneracy between a planetary binary-lens and an extreme flux ratio binary-source model has been successfully broken. For events OGLE-2003-BLG-222 and OGLE-2004-BLG-347, the degeneracy was encountered despite of very dense data sampling. From light curve modeling and stellar evolution theory, there was a slight preference to explain OGLE-2003-BLG-222 as a binary source event, and OGLE-2004-BLG-347 as a binary lens event. However, without spectra, this degeneracy cannot be fully broken. No planet was found so far around a white dwarf, though it is believed that Jovian planets should survive the late stages of stellar evolution, and that white dwarfs will retain planetary systems in wide orbits. We want to perform high precision astrometric observations of nearby white dwarfs in wide binary systems with red dwarfs in order to find planets around white dwarfs. We selected a sample of observing targets (WD-RD binary systems, not published yet), which can possibly have planets around the WD component, and modeled synthetic astrometric orbits which can be observed for these targets using existing and future astrometric facilities. Modeling was performed for the astrometric accuracy of 0.01, 0.1, and 1.0 mas, separation between WD and planet of 3 and 5 A.U., binary system separation of 30 A.U., planet masses of 10 Earth masses, 1 and 10 Jupiter masses, WD mass of 0.5M and 1.0 Solar masses, and distances to the system of 10, 20 and 30 pc. It was found that the PRIMA facility at the VLTI will be able to detect planets around white dwarfs once it is operating, by measuring the astrometric wobble of the WD due to a planet companion, down to 1 Jupiter mass. We show for the simulated observations that it is possible to model the orbits and find the parameters describing the potential planetary systems.
Theory of mRNA degradation
(2012)
One of the central themes of biology is to understand how individual cells achieve a high fidelity in gene expression. Each cell needs to ensure accurate protein levels for its proper functioning and its capability to proliferate. Therefore, complex regulatory mechanisms have evolved in order to render the expression of each gene dependent on the expression level of (all) other genes. Regulation can occur at different stages within the framework of the central dogma of molecular biology. One very effective and relatively direct mechanism concerns the regulation of the stability of mRNAs. All organisms have evolved diverse and powerful mechanisms to achieve this. In order to better comprehend the regulation in living cells, biochemists have studied specific degradation mechanisms in detail. In addition to that, modern high-throughput techniques allow to obtain quantitative data on a global scale by parallel analysis of the decay patterns of many different mRNAs from different genes. In previous studies, the interpretation of these mRNA decay experiments relied on a simple theoretical description based on an exponential decay. However, this does not account for the complexity of the responsible mechanisms and, as a consequence, the exponential decay is often not in agreement with the experimental decay patterns. We have developed an improved and more general theory of mRNA degradation which provides a general framework of mRNA expression and allows describing specific degradation mechanisms. We have made an attempt to provide detailed models for the regulation in different organisms. In the yeast S. cerevisiae, different degradation pathways are known to compete and furthermore most of them rely on the biochemical modification of mRNA molecules. In bacteria such as E. coli, degradation proceeds primarily endonucleolytically, i.e. it is governed by the initial cleavage within the coding region. In addition, it is often coupled to the level of maturity and the size of the polysome of an mRNA. Both for S. cerevisiae and E. coli, our descriptions lead to a considerable improvement of the interpretation of experimental data. The general outcome is that the degradation of mRNA must be described by an age-dependent degradation rate, which can be interpreted as a consequence of molecular aging of mRNAs. Within our theory, we find adequate ways to address this much debated topic from a theoretical perspective. The improvements of the understanding of mRNA degradation can be readily applied to further comprehend the mRNA expression under different internal or environmental conditions such as after the induction of transcription or stress application. Also, the role of mRNA decay can be assessed in the context of translation and protein synthesis. The ultimate goal in understanding gene regulation mediated by mRNA stability will be to identify the relevance and biological function of different mechanisms. Once more quantitative data will become available, our description allows to elaborate the role of each mechanism by devising a suitable model.
Thermophony in real gases
(2016)
A thermophone is an electrical device for sound generation. The advantages of thermophones over conventional sound transducers such as electromagnetic, electrostatic or piezoelectric transducers are their operational principle which does not require any moving parts, their resonance-free behavior, their simple construction and their low production costs.
In this PhD thesis, a novel theoretical model of thermophonic sound generation in real gases has been developed. The model is experimentally validated in a frequency range from 2 kHz to 1 MHz by testing more then fifty thermophones of different materials, including Carbon nano-wires, Titanium, Indium-Tin-Oxide, different sizes and shapes for sound generation in gases such as air, argon, helium, oxygen, nitrogen and sulfur hexafluoride.
Unlike previous approaches, the presented model can be applied to different kinds of thermophones and various gases, taking into account the thermodynamic properties of thermophone materials and of adjacent gases, degrees of freedom and the volume occupied by the gas atoms and molecules, as well as sound attenuation effects, the shape and size of the thermophone surface and the reduction of the generated acoustic power due to photonic emission. As a result, the model features better prediction accuracy than the existing models by a factor up to 100. Moreover, the new model explains previous experimental findings on thermophones which can not be explained with the existing models.
The acoustic properties of the thermophones have been tested in several gases using unique, highly precise experimental setups comprising a Laser-Doppler-Vibrometer combined with a thin polyethylene film which acts as a broadband and resonance-free sound-pressure detector. Several outstanding properties of the thermophones have been demonstrated for the first time, including the ability to generate arbitrarily shaped acoustic signals, a greater acoustic efficiency compared to conventional piezoelectric and electrostatic airborne ultrasound transducers, and applicability as powerful and tunable sound sources with a bandwidth up to the megahertz range and beyond.
Additionally, new applications of thermophones such as the study of physical properties of gases, the thermo-acoustic gas spectroscopy, broad-band characterization of transfer functions of sound and ultrasound detection systems, and applications in non-destructive materials testing are discussed and experimentally demonstrated.
A key non-destructive technique for analysis, optimization and developing of new functional materials such as sensors, transducers, electro-optical and memory devices is presented. The Thermal-Pulse Tomography (TPT) provides high-resolution three-dimensional images of electric field and polarization distribution in a material. This thermal technique use a pulsed heating by means of focused laser light which is absorbed by opaque electrodes. The diffusion of the heat causes changes in the sample geometry, generating a short-circuit current or change in surface potential, which contains information about the spatial distribution of electric dipoles or space charges. Afterwards, a reconstruction of the internal electric field and polarization distribution in the material is possible via Scale Transformation or Regularization methods. In this way, the TPT was used for the first time to image the inhomogeneous ferroelectric switching in polymer ferroelectric films (candidates to memory devices). The results shows the typical pinning of electric dipoles in the ferroelectric polymer under study and support the previous hypotheses of a ferroelectric reversal at a grain level via nucleation and growth. In order to obtain more information about the impact of the lateral and depth resolution of the thermal techniques, the TPT and its counterpart called Focused Laser Intensity Modulation Method (FLIMM) were implemented in ferroelectric films with grid-shaped electrodes. The results from both techniques, after the data analysis with different regularization and scale methods, are in total agreement. It was also revealed a possible overestimated lateral resolution of the FLIMM and highlights the TPT method as the most efficient and reliable thermal technique. After an improvement in the optics, the Thermal-Pulse Tomography method was implemented in polymer-dispersed liquid crystals (PDLCs) films, which are used in electro-optical applications. The results indicated a possible electrostatic interaction between the COH group in the liquid crystals and the fluorinate atoms of the used ferroelectric matrix. The geometrical parameters of the LC droplets were partially reproduced as they were compared with Scanning Electron Microscopy (SEM) images. For further applications, it is suggested the use of a non-strong-ferroelectric polymer matrix. In an effort to develop new polymerferroelectrets and for optimizing their properties, new multilayer systems were inspected. The results of the TPT method showed the non-uniformity of the internal electric-field distribution in the shaped-macrodipoles and thus suggested the instability of the sample. Further investigation on multilayers ferroelectrets was suggested and the implementation of less conductive polymers layers too.
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.
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.
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.
Classical semiconductor physics has been continuously improving electronic components such as diodes, light-emitting diodes, solar cells and transistors based on highly purified inorganic crystals over the past decades. Organic semiconductors, notably polymeric, are a comparatively young field of research, the first light-emitting diode based on conjugated polymers having been demonstrated in 1990. Polymeric semiconductors are of tremendous interest for high-volume, low-cost manufacturing ("printed electronics"). Due to their rather simple device structure mostly comprising only one or two functional layers, polymeric diodes are much more difficult to optimize compared to small-molecular organic devices. Usually, functions such as charge injection and transport are handled by the same material which thus needs to be highly optimized. The present work contributes to expanding the knowledge on the physical mechanisms determining device performance by analyzing the role of charge injection and transport on device efficiency for blue and white-emitting devices, based on commercially relevant spiro-linked polyfluorene derivatives. It is shown that such polymers can act as very efficient electron conductors and that interface effects such as charge trapping play the key role in determining the overall device efficiency. This work contributes to the knowledge of how charges drift through the polymer layer to finally find neutral emissive trap states and thus allows a quantitative prediction of the emission color of multichromophoric systems, compatible with the observed color shifts upon driving voltage and temperature variation as well as with electrical conditioning effects. In a more methodically oriented part, it is demonstrated that the transient device emission observed upon terminating the driving voltage can be used to monitor the decay of geminately-bound species as well as to determine trapped charge densities. This enables direct comparisons with numerical simulations based on the known properties of charge injection, transport and recombination. The method of charge extraction under linear increasing voltages (CELIV) is investigated in some detail, correcting for errors in the published approach and highlighting the role of non-idealized conditions typically present in experiments. An improved method is suggested to determine the field dependence of charge mobility in a more accurate way. Finally, it is shown that the neglect of charge recombination has led to a misunderstanding of experimental results in terms of a time-dependent mobility relaxation.
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.
Wetting and phase transitions play a very important role our daily life. Molecularly thin films of long-chain alkanes at solid/vapour interfaces (e.g. C30H62 on silicon wafers) are very good model systems for studying the relation between wetting behaviour and (bulk) phase transitions. Immediately above the bulk melting temperature the alkanes wet partially the surface (drops). In this temperature range the substrate surface is covered with a molecularly thin ordered, solid-like alkane film ("surface freezing"). Thus, the alkane melt wets its own solid only partially which is a quite rare phenomenon in nature. The thesis treats about how the alkane melt wets its own solid surface above and below the bulk melting temperature and about the corresponding melting and solidification processes. Liquid alkane drops can be undercooled to few degrees below the bulk melting temperature without immediate solidification. This undercooling behaviour is quite frequent and theoretical quite well understood. In some cases, slightly undercooled drops start to build two-dimensional solid terraces without bulk solidification. The terraces grow radially from the liquid drops on the substrate surface. They consist of few molecular layers with the thickness multiple of all-trans length of the molecule. By analyzing the terrace growth process one can find that, both below and above the melting point, the entire substrate surface is covered with a thin film of mobile alkane molecules. The presence of this film explains how the solid terrace growth is feeded: the alkane molecules flow through it from the undercooled drops to the periphery of the terrace. The study shows for the first time the coexistence of a molecularly thin film ("precursor") with partially wetting bulk phase. The formation and growth of the terraces is observed only in a small temperature interval in which the 2D nucleation of terraces is more likely than the bulk solidification. The nucleation mechanisms for 2D solidification are also analyzed in this work. More surprising is the terrace behaviour above bulk the melting temperature. The terraces can be slightly overheated before they melt. The melting does not occur all over the surface as a single event; instead small drops form at the terrace edge. Subsequently these drops move on the surface "eating" the solid terraces on their way. By this they grow in size leaving behind paths from were the material was collected. Both overheating and droplet movement can be explained by the fact that the alkane melt wets only partially its own solid. For the first time, these results explicitly confirm the supposed connection between the absence of overheating in solid and "surface melting": the solids usually start to melt without an energetic barrier from the surface at temperatures below the bulk melting point. Accordingly, the surface freezing of alkanes give rise of an energetic barrier which leads to overheating.
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.