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- Institut für Physik und Astronomie (1480) (remove)
Using time-resolved x-ray diffraction, we demonstrate the manipulation of the picosecond strain response of a metallic heterostructure consisting of a dysprosium (Dy) transducer and a niobium (Nb) detection layer by an external magnetic field. We utilize the first-order ferromagnetic–antiferromagnetic phase transition of the Dy layer, which provides an additional large contractive stress upon laser excitation compared to its zerofield response. This enhances the laser-induced contraction of the transducer and changes the shape of the picosecond strain pulses driven in Dy and detected within the buried Nb layer. Based on our experiment with rare-earth metals we discuss required properties for functional transducers, which may allow for novel field-control of the emitted picosecond strain pulses.
Porous ceramic diesel particulate filters (DPFs) are extruded products that possess macroscopic anisotropic mechanical and thermal properties. This anisotropy is caused by both morphological features (mostly the orientation of porosity) and crystallographic texture. We systematically studied those two aspects in two aluminum titanate ceramic materials of different porosity using mercury porosimetry, gas adsorption, electron microscopy, X-ray diffraction, and X-ray refraction radiography. We found that a lower porosity content implies a larger isotropy of both the crystal texture and the porosity orientation. We also found that, analogous to cordierite, crystallites do align with their axis of negative thermal expansion along the extrusion direction. However, unlike what found for cordierite, the aluminium titanate crystallite form is such that a more pronounced (0 0 2) texture along the extrusion direction implies porosity aligned perpendicular to it.
In this paper, we introduce the phenomenon of light driven diffusioosmotic long-range attraction and repulsion of porous particles under irradiation with UV light. The change in the inter-particle interaction potential is governed by flow patterns generated around single colloids and results in reversible aggregation or separation of the mesoporous silica particles that are trapped at a solid surface. The range of the interaction potential extends to several times the diameter of the particle and can be adjusted by varying the light intensity. The "fuel" of the process is a photosensitive surfactant undergoing photo-isomerization from a more hydrophobic trans-state to a rather hydrophilic cis-state. The surfactant has different adsorption affinities to the particles depending on the isomerization state. The trans-isomer, for example, tends to accumulate in the negatively charged pores of the particles, while the cis-isomer prefers to remain in the solution. This implies that when under UV irradiation cis-isomers are being formed within the pores, they tend to diffuse out readily and generate an excess concentration near the colloid's outer surface, ultimately resulting in the initiation of diffusioosmotic flow. The direction of the flow depends strongly on the dynamic redistribution of the fraction of trans- and cis-isomers near the colloids due to different kinetics of photo-isomerization within the pores as compared to the bulk. The unique feature of the mechanism discussed in the paper is that the long-range mutual repulsion but also the attraction can be tuned by convenient external optical stimuli such as intensity so that a broad variety of experimental situations for manipulation of a particle ensemble can be realized.
Low donor content solar cells are an intriguing class of photovoltaic device about which there is still considerable discussion with respect to their mode of operation. We have synthesized a series of triphenylamine-based materials for use in low donor content devices with the electron accepting [6,6]-phenyl-C71-butyric acid methyl ester (PC(7)0BM). The triphenylamine-based materials absorb light in the near UV enabling the PC(7)0BM to be be the main light absorbing organic semiconducting material in the solar cell. It was found that the devices did not operate as classical Schottky junctions but rather photocurrent was generated by hole transfer from the photo-excited PC(7)0BM to the triphenylamine-based donors. We found that replacing the methoxy surface groups with methyl groups on the donor material led to a decrease in hole mobility for the neat films, which was due to the methyl substituted materials having the propensity to aggregate. The thermodynamic drive to aggregate was advantageous for the performance of the low donor content (6 wt%) films. It was found that the 6 wt% donor devices generally gave higher performance than devices containing 50 wt% of the donor.
Diffusion of antibiotics through a biofilm in the presence of diffusion and absorption barriers
(2020)
We propose a model of antibiotic diffusion through a bacterial biofilm when diffusion and/or absorption barriers develop in the biofilm. The idea of this model is: We deduce details of the diffusion process in a medium in which direct experimental study is difficult, based on probing diffusion in external regions. Since a biofilm has a gel-like consistency, we suppose that subdiffusion of particles in the biofilm may occur. To describe this process we use a fractional subdiffusion-absorption equation with an adjustable anomalous diffusion exponent. The boundary conditions at the boundaries of the biofilm are derived by means of a particle random walk model on a discrete lattice leading to an expression involving a fractional time derivative. We show that the temporal evolution of the total amount of substance that has diffused through the biofilm explicitly depends on whether there is antibiotic absorption in the biofilm. This fact is used to experimentally check for antibiotic absorption in the biofilm and if subdiffusion and absorption parameters of the biofilm change over time. We propose a four-stage model of antibiotic diffusion in biofilm based on the following physical characteristics: whether there is absorption of the antibiotic in the biofilm and whether all biofilm parameters remain unchanged over time. The biological interpretation of the stages, in particular their relation with the bacterial defense mechanisms, is discussed. Theoretical results are compared with empirical results of ciprofloxacin diffusion through Pseudomonas aeruginosa biofilm, and ciprofloxacin and gentamicin diffusion through Proteus mirabilis biofilm.
Alone but not lonely
(2020)
Context. Hot subdwarfs are core-helium burning stars that show lower masses and higher temperatures than canonical horizontal branch stars. They are believed to be formed when a red giant suffers an extreme mass-loss episode. Binary interaction is suggested to be the main formation channel, but the high fraction of apparently single hot subdwarfs (up to 30%) has prompted single star formation scenarios to be proposed.Aims. We investigate the possibility that hot subdwarfs could form without interaction by studying wide binary systems. If single formation scenarios were possible, there should be hot subdwarfs in wide binaries that have undergone no interaction.Methods. Angular momentum accretion during interaction is predicted to cause the hot subdwarf companion to spin up to the critical velocity. The effect of this should still be observable given the timescales of the hot subdwarf phase. To study the rotation rates of companions, we have analysed light curves from the Transiting Exoplanet Survey Satellite for all known hot subdwarfs showing composite spectral energy distributions indicating the presence of a main sequence wide binary companion. If formation without interaction were possible, that would also imply the existence of hot subdwarfs in very wide binaries that are not predicted to interact. To identify such systems, we have searched for common proper motion companions with projected orbital distances of up to 0.1 pc to all known spectroscopically confirmed hot subdwarfs using Gaia DR2 astrometry.Results. We find that the companions in composite hot subdwarfs show short rotation periods when compared to field main sequence stars. They display a triangular-shaped distribution with a peak around 2.5 days, similar to what is observed for young open clusters. We also report a shortage of hot subdwarfs with candidate common proper motion companions. We identify only 16 candidates after probing 2938 hot subdwarfs with good astrometry. Out of those, at least six seem to be hierarchical triple systems, in which the hot subdwarf is part of an inner binary.Conclusions. The observed distribution of rotation rates for the companions in known wide hot subdwarf binaries provides evidence of previous interaction causing spin-up. Additionally, there is a shortage of hot subdwarfs in common proper motion pairs, considering the frequency of such systems among progenitors. These results suggest that binary interaction is always required for the formation of hot subdwarfs.
A conducting Taylor-Couette flow with quasi-Keplerian rotation law containing a toroidal magnetic field serves as a mean-field dynamo model of the Tayler-Spruit type. The flows are unstable against non-axisymmetric perturbations which form electromotive forces defining a effect and eddy diffusivity. If both degenerated modes with m = +/- 1 are excited with the same power then the global a effect vanishes and a dynamo cannot work. It is shown, however, that the Tayler instability produces finite alpha effects if only an isolated mode is considered but this intrinsic helicity of the single-mode is too low for an alpha(2) dynamo. Moreover, an alpha Omega dynamo model with quasi-Keplerian rotation requires a minimum magnetic Reynolds number of rotation of Rm similar or equal to 2000 to work. Whether it really works depends on assumptions about the turbulence energy. For a steeper-than-quadratic dependence of the turbulence intensity on the magnetic field, however, dynamos are only excited if the resulting magnetic eddy diffusivity approximates its microscopic value, eta(T) similar or equal to eta. By basically lower or larger eddy diffusivities the dynamo instability is suppressed.
We consider a ring network of theta neurons with non-local homogeneous coupling. We analyse the corresponding continuum evolution equation, analytically describing all possible steady states and their stability. By considering a number of different parameter sets, we determine the typical bifurcation scenarios of the network, and put on a rigorous footing some previously observed numerical results.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
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.
Sprache
Englisch
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
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.
Fractional Brownian motion in superharmonic potentials and non-Boltzmann stationary distributions
(2021)
We study the stochastic motion of particles driven by long-range correlated fractional Gaussian noise (FGN) in a superharmonic external potential of the form U(x) proportional to x(2n) (n is an element of N). When the noise is considered to be external, the resulting overdamped motion is described by the non-Markovian Langevin equation for fractional Brownian motion. For this case we show the existence of long time, stationary probability density functions (PDFs) the shape of which strongly deviates from the naively expected Boltzmann PDF in the confining potential U(x). We analyse in detail the temporal approach to stationarity as well as the shape of the non-Boltzmann stationary PDF. A typical characteristic is that subdiffusive, antipersistent (with negative autocorrelation) motion tends to effect an accumulation of probability close to the origin as compared to the corresponding Boltzmann distribution while the opposite trend occurs for superdiffusive (persistent) motion. For this latter case this leads to distinct bimodal shapes of the PDF. This property is compared to a similar phenomenon observed for Markovian Levy flights in superharmonic potentials. We also demonstrate that the motion encoded in the fractional Langevin equation driven by FGN always relaxes to the Boltzmann distribution, as in this case the fluctuation-dissipation theorem is fulfilled.
The photosensitive azobenzene-containing surfactant C-4-Azo-OC(6)TMAB is a promising agent for reversible DNA packaging in a solution. The simulation of the trans-isomer surfactant organization into associates in a solution with and without salt as well as its binding to DNA at different NaCl concentrations was carried out by molecular dynamics. Experimental data obtained by spectral and hydrodynamic methods were used to verify the results of simulation. It was shown that head-to-tail aggregates with close to antiparallel orientation of surfactant molecules were formed at certain NaCl and surfactant concentrations (below critical micelle concentration). Such aggregates have two positively charged ends, and therefore, they can be attracted to negatively charged DNA phosphates far located along the chain, as well as those that belong to different molecules. This contributes to the formation of intermolecular DNA-DNA contacts, and this way, the experimentally observed precipitation of DNA can be explained.
We consider large networks of theta neurons on a ring, synaptically coupled with an asymmetric kernel. Such networks support stable "bumps" of activity, which move along the ring if the coupling kernel is asymmetric. We investigate the effects of the kernel asymmetry on the existence, stability, and speed of these moving bumps using continuum equations formally describing infinite networks. Depending on the level of heterogeneity within the network, we find complex sequences of bifurcations as the amount of asymmetry is varied, in strong contrast to the behavior of a classical neural field model.
A new variant of the Laser-Induced Pressure-Pulse (LIPP) method for repeatable, time-resolved space-charge profile measurements is proposed and demonstrated. Automated deposition of a fresh laser-target film before each illumination leads to good repeatability of the LIPP and thus allows for the detection of time-resolved changes in the space-charge distribution over many hours. We describe and discuss the experimental setup and its features, compare the repeatability of the LIPP measurements on the same sample without and with re-preparation of the test cell, and present the time-resolved evolution of the space-charge profile in a two-layer arrangement of a silicone-grease and a silicone-elastomer film as an example. Finally, the temperature dependence of the space-charge evolution during polarization under high voltage and during depolarization in short circuit is shown. Possible uses and future developments of the new LIPP approach are also discussed.
Perovskite semiconductors as the active materials in efficient solar cells exhibit free carrier diffusion lengths on the order of microns at low illumination fluxes and many hundreds of nanometers under 1 sun conditions. These lengthscales are significantly larger than typical junction thicknesses, and thus the carrier transport and charge collection should be expected to be diffusion controlled. A consensus along these lines is emerging in the field. However, the question as to whether the built-in potential plays any role is still of matter of some conjecture. This important question using phase-sensitive photocurrent measurements and theoretical device simulations based upon the drift-diffusion framework is addressed. In particular, the role of the built-in electric field and charge-selective transport layers in state-of-the-art p-i-n perovskite solar cells comparing experimental findings and simulation predictions is probed. It is found that while charge collection in the junction does not require a drift field per se, a built-in potential is still needed to avoid the formation of reverse electric fields inside the active layer, and to ensure efficient extraction through the charge transport layers.
Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian—or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.