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- Röntgenspektroskopie (3)
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Institute
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.
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.
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.
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.
Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy
(2022)
The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model. This allows us to invert TR-XPS spectra to the dynamic charge at a specific atom. We demonstrate the power of TR-XPS by using sulphur 2p-core-electron-emission probing to study the UV-excited dynamics of 2-thiouracil. The method allows us to discover that a major part of the population relaxes to the molecular ground state within 220–250 fs. In addition, a 250-fs oscillation, visible in the kinetic energy of the TR-XPS, reveals a coherent exchange of population among electronic states.
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.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
Isoflux tension propagation (IFTP) theory and Langevin dynamics (LD) simulations are employed to study the dynamics of channel-driven polymer translocation in which a polymer translocates into a narrow channel and the monomers in the channel experience a driving force fc. In the high driving force limit, regardless of the channel width, IFTP theory predicts τ ∝ f βc for the translocation time, where β = −1 is the force scaling exponent. Moreover, LD data show that for a very narrow channel fitting only a single file of monomers, the entropic force due to the subchain inside the channel does not play a significant role in the translocation dynamics and the force exponent β = −1 regardless of the force magnitude. As the channel width increases the number of possible spatial configurations of the subchain inside the channel becomes significant and the resulting entropic force causes the force exponent to drop below unity.
We consider a one-dimensional oscillatory medium with a coupling through a diffusive linear field. In the limit of fast diffusion this setup reduces to the classical Kuramoto–Battogtokh model. We demonstrate that for a finite diffusion stable chimera solitons, namely localized synchronous domain in an infinite asynchronous environment, are possible. The solitons are stable also for finite density of oscillators, but in this case they sway with a nearly constant speed. This finite-density-induced motility disappears in the continuum limit, as the velocity of the solitons is inverse proportional to the density. A long-wave instability of the homogeneous asynchronous state causes soliton turbulence, which appears as a sequence of soliton mergings and creations. As the instability of the asynchronous state becomes stronger, this turbulence develops into a spatio-temporal intermittency.
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.
Beim Resonanzenergietransfer werden Fotonen von einem angeregten Donator über einen Wechselwirkungsabstand auf einen Akzeptor übertragen. Nach der quantenmechanischen Theorie von FÖRSTER kann dieser Abstand mit Hilfe des Überlappungsintegrals von Fluoreszenzspektrum des Donators und Absorp-tionsspektrum des Akzeptors berechnet werden.
Eine andere Möglichkeit der Bestimmung erhält man mit Hilfe von statistischen Modellen, die in einem Überblick zusammengestellt sind. Dabei kann der Abstand durch Auswertung der Löschkurve bestimmt werden.
In dieser Arbeit wird dazu eine weitere statistische Variante der Bestimmung des Wechselwirkungsradius hinzugefügt und an einem Beispiel ausführlich demonstriert.
Beim Resonanzenergietransfer werden Fotonen von einem angeregten Donator über einen Wechselwirkungsabstand auf einen Akzeptor übertragen. Nach der quantenmechanischen Theorie von FÖRSTER kann dieser Abstand mit Hilfe des Überlappungsintegrals von Fluoreszenzspektrum des Donators und Absorp-tionsspektrum des Akzeptors berechnet werden.
Eine andere Möglichkeit der Bestimmung erhält man mit Hilfe von statistischen Modellen, die in einem Überblick zusammengestellt sind. Dabei kann der Abstand durch Auswertung der Löschkurve bestimmt werden.
In dieser Arbeit wird dazu eine weitere statistische Variante der Bestimmung des Wechselwirkungsradius hinzugefügt und an einem Beispiel ausführlich demonstriert.
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.
How do different reset protocols affect ergodicity of a diffusion process in single-particle-tracking experiments? We here address the problem of resetting of an arbitrary stochastic anomalous-diffusion process (ADP) from the general mathematical points of view and assess ergodicity of such reset ADPs for an arbitrary resetting protocol. The process of stochastic resetting describes the events of the instantaneous restart of a particle’s motion via randomly distributed returns to a preset initial position (or a set of those). The waiting times of such resetting events obey the Poissonian, Gamma, or more generic distributions with specified conditions regarding the existence of moments. Within these general approaches, we derive general analytical results and support them by computer simulations for the behavior of the reset mean-squared displacement (MSD), the new reset increment-MSD (iMSD), and the mean reset time-averaged MSD (TAMSD). For parental nonreset ADPs with the MSD(t)∝ tμ we find a generic behavior and a switch of the short-time growth of the reset iMSD and mean reset TAMSDs from ∝ _μ for subdiffusive to ∝ _1 for superdiffusive reset ADPs. The critical condition for a reset ADP that recovers its ergodicity is found to be more general than that for the nonequilibrium stationary state, where obviously the iMSD and the mean TAMSD are equal. The consideration of the new statistical quantifier, the iMSD—as compared to the standard MSD—restores the ergodicity of an arbitrary reset ADP in all situations when the μth moment of the waiting-time distribution of resetting events is finite. Potential applications of these new resetting results are, inter alia, in the area of biophysical and soft-matter systems.
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.
There is a large variety of goals instructors have for laboratory courses, with different courses focusing on different subsets of goals. An often implicit, but crucial, goal is to develop students’ attitudes, views, and expectations about experimental physics to align with practicing experimental physicists. The assessment of laboratory courses upon this one dimension of learning has been intensively studied in U.S. institutions using the Colorado Learning Attitudes about Science Survey for Experimental Physics (E-CLASS). However, there is no such an instrument available to use in Germany, and the influence of laboratory courses on students views about the nature of experimental physics is still unexplored at German-speaking institutions. Motivated by the lack of an assessment tool to investigate this goal in laboratory courses at German-speaking institutions, we present a translated version of the E-CLASS adapted to the context at German-speaking institutions. We call the German version of the E-CLASS, the GE-CLASS. We describe the translation process and the creation of an automated web-based system for instructors to assess their laboratory courses. We also present first results using GE-CLASS obtained at the University of Potsdam. A first comparison between E-CLASS and GE-CLASS results shows clear differences between University of Potsdam and U.S. students’ views and beliefs about experimental physics.
We introduce and study a Lévy walk (LW) model of particle spreading with a finite propagation speed combined with soft resets, stochastically occurring periods in which an harmonic external potential is switched on and forces the particle towards a specific position. Soft resets avoid instantaneous relocation of particles that in certain physical settings may be considered unphysical. Moreover, soft resets do not have a specific resetting point but lead the particle towards a resetting point by a restoring Hookean force. Depending on the exact choice for the LW waiting time density and the probability density of the periods when the harmonic potential is switched on, we demonstrate a rich emerging response behaviour including ballistic motion and superdiffusion. When the confinement periods of the soft-reset events are dominant, we observe a particle localisation with an associated non-equilibrium steady state. In this case the stationary particle probability density function turns out to acquire multimodal states. Our derivations are based on Markov chain ideas and LWs with multiple internal states, an approach that may be useful and flexible for the investigation of other generalised random walks with soft and hard resets. The spreading efficiency of soft-rest LWs is characterised by the first-passage time statistic.