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Research on novel and advanced biomaterials is an indispensable step towards their applications in desirable fields such as tissue engineering, regenerative medicine, cell culture, or biotechnology. The work presented here focuses on such a promising material: polyelectrolyte multilayer (PEM) composed of hyaluronic acid (HA) and poly(L-lysine) (PLL). This gel-like polymer surface coating is able to accumulate (bio-)molecules such as proteins or drugs and release them in a controlled manner. It serves as a mimic of the extracellular matrix (ECM) in composition and intrinsic properties. These qualities make the HA/PLL multilayers a promising candidate for multiple bio-applications such as those mentioned above. The work presented aims at the development of a straightforward approach for assessment of multi-fractional diffusion in multilayers (first part) and at control of local molecular transport into or from the multilayers by laser light trigger (second part).
The mechanism of the loading and release is governed by the interaction of bioactives with the multilayer constituents and by the diffusion phenomenon overall. The diffusion of a molecule in HA/PLL multilayers shows multiple fractions of different diffusion rate. Approaches, that are able to assess the mobility of molecules in such a complex system, are limited. This shortcoming motivated the design of a novel evaluation tool presented here.
The tool employs a simulation-based approach for evaluation of the data acquired by fluorescence recovery after photobleaching (FRAP) method. In this approach, possible fluorescence recovery scenarios are primarily simulated and afterwards compared with the data acquired while optimizing parameters of a model until a sufficient match is achieved. Fluorescent latex particles of different sizes and fluorescein in an aqueous medium are utilized as test samples validating the analysis results. The diffusion of protein cytochrome c in HA/PLL multilayers is evaluated as well.
This tool significantly broadens the possibilities of analysis of spatiotemporal FRAP data, which originate from multi-fractional diffusion, while striving to be widely applicable. This tool has the potential to elucidate the mechanisms of molecular transport and empower rational engineering of the drug release systems.
The second part of the work focuses on the fabrication of such a spatiotemporarily-controlled drug release system employing the HA/PLL multilayer. This release system comprises different layers of various functionalities that together form a sandwich structure. The bottom layer, which serves as a reservoir, is formed by HA/PLL PEM deposited on a planar glass substrate. On top of the PEM, a layer of so-called hybrids is deposited. The hybrids consist of thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) -based hydrogel microparticles with surface-attached gold nanorods. The layer of hybrids is intended to serve as a gate that controls the local molecular transport through the PEM–solution-interface. The possibility of stimulating the molecular transport by near-infrared (NIR) laser irradiation is being explored.
From several tested approaches for the deposition of hybrids onto the PEM surface, the drying-based approach was identified as optimal. Experiments, that examine the functionality of the fabricated sandwich at elevated temperature, document the reversible volume phase transition of the PEM-attached hybrids while sustaining the sandwich stability. Further, the gold nanorods were shown to effectively absorb light radiation in the tissue- and cell-friendly NIR spectral region while transducing the energy of light into heat. The rapid and reversible shrinkage of the PEM-attached hybrids was thereby achieved. Finally, dextran was employed as a model transport molecule. It loads into the PEM reservoir in a few seconds with the partition constant of 2.4, while it spontaneously releases in a slower, sustained manner. The local laser irradiation of the sandwich, which contains the fluorescein isothiocyanate tagged dextran, leads to a gradual reduction of fluorescence intensity in the irradiated region.
The release system fabricated employs renowned photoresponsivity of the hybrids in an innovative setting. The results of the research are a step towards a spatially-controlled on-demand drug release system that paves the way to spatiotemporally controlled drug release.
The approaches developed in this work have the potential to elucidate the molecular dynamics in ECM and to foster engineering of multilayers with properties tuned to mimic the ECM. The work aims at spatiotemporal control over the diffusion of bioactives and their presentation to the cells.
Lava domes are severely hazardous, mound-shaped extrusions of highly viscous lava and commonly erupt at many active stratovolcanoes around the world. Due to gradual growth and flank oversteepening, such lava domes regularly experience partial or full collapses, resulting in destructive and far-reaching pyroclastic density currents. They are also associated with cyclic explosive activity as the complex interplay of cooling, degassing, and solidification of dome lavas regularly causes gas pressurizations on the dome or the underlying volcano conduit. Lava dome extrusions can last from days to decades, further highlighting the need for accurate and reliable monitoring data.
This thesis aims to improve our understanding of lava dome processes and to contribute to the monitoring and prediction of hazards posed by these domes. The recent rise and sophistication of photogrammetric techniques allows for the extraction of observational data in unprecedented detail and creates ideal tools for accomplishing this purpose. Here, I study natural lava dome extrusions as well as laboratory-based analogue models of lava dome extrusions and employ photogrammetric monitoring by Structure-from-Motion (SfM) and Particle-Image-Velocimetry (PIV) techniques. I primarily use aerial photography data obtained by helicopter, airplanes, Unoccupied Aircraft Systems (UAS) or ground-based timelapse cameras. Firstly, by combining a long time-series of overflight data at Volcán de Colima, México, with seismic and satellite radar data, I construct a detailed timeline of lava dome and crater evolution. Using numerical model, the impact of the extrusion on dome morphology and loading stress is further evaluated and an impact on the growth direction is identified, bearing important implications for the location of collapse hazards. Secondly, sequential overflight surveys at the Santiaguito lava dome, Guatemala, reveal surface motion data in high detail. I quantify the growth of the lava dome and the movement of a lava flow, showing complex motions that occur on different timescales and I provide insight into rock properties relevant for hazard assessment inferred purely by photogrammetric processing of remote sensing data. Lastly, I recreate artificial lava dome and spine growth using analogue modelling under controlled conditions, providing new insights into lava extrusion processes and structures as well as the conditions in which they form.
These findings demonstrate the capabilities of photogrammetric data analyses to successfully monitor lava dome growth and evolution while highlighting the advantages of complementary modelling methods to explain the observed phenomena. The results presented herein further bear important new insights and implications for the hazards posed by lava domes.
The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions.
First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set.
We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data.
The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions.
Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers.
Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.
Completely water-based systems are of interest for the development of novel material for various reasons: On one hand, they provide benign environment for biological systems and on the other hand they facilitate effective molecular transport in a membrane-free environment. In order to investigate the general potential of aqueous two-phase systems (ATPSs) for biomaterials and compartmentalized systems, various solid particles were applied to stabilize all-aqueous emulsion droplets. The target ATPS to be investigated should be prepared via mixing of two aqueous solutions of water-soluble polymers, which turn biphasic when exceeding a critical polymer concentration. Hydrophilic polymers with a wide range of molar mass such as dextran/poly(ethylene glycol) (PEG) can therefore be applied. Solid particles adsorbed at the interfaces can be exceptionally efficient stabilizers forming so-called Pickering emulsions, and nanoparticles can bridge the correlation length of polymer solutions and are thereby the best option for water-in-water emulsions.
The first approach towards the investigation of ATPS was conducted with all aqueous dextran-PEG emulsions in the presence of poly(dopamine) particles (PDP) in Chapter 4. The water-in-water emulsions were formed with a PEG/dextran system via utilizing PDP as stabilizers. Studies of the formed emulsions were performed via laser scanning confocal microscope (CLSM), optical microscope (OM), cryo-scanning electron microscope (SEM) and tensiometry. The stable emulsions (at least 16 weeks) were demulsified easily via dilution or surfactant addition. Furthermore, the solid PDP at the water-water interface were crosslinked in order to inhibit demulsification of the Pickering emulsion. Transmission electron microscope (TEM) and scanning electron microscope (SEM) were used to visualize the morphology of PDP before and after crosslinking. PDP stabilized water-in-water emulsions were utilized in the following Chapter 5 to form supramolecular compartmentalized hydrogels. Here, hydrogels were prepared in pre-formed water-in-water emulsions and gelled via α-cyclodextrin-PEG (α-CD-PEG) inclusion complex formation. Studies of the formed complexes were performed via X-ray powder diffraction (XRD) and the mechanical properties of the hydrogels were measured with oscillatory shear rheology. In order to verify the compartmentalized state and its triggered decomposition, hydrogels and emulsions were assessed via OM, SEM and CLSM. The last chapter broadens the investigations from the previous two systems by utilizing various carbon nitrides (CN) as different stabilizers in ATPS. CN introduces another way to trigger demulsification, namely irradiation with visible light. Therefore, emulsification and demulsification with various triggers were probed. The investigated all aqueous multi-phase systems will act as model for future fabrication of biocompatible materials, cell micropatterning as well as separation of compartmentalized systems.
Seismological and seismotectonic analysis of the northwestern Argentine Central Andean foreland
(2020)
After a severe M W 5.7 earthquake on October 17, 2015 in El Galpón in the province of Salta NW Argentina, I installed a local seismological network around the estimated epicenter. The network covered an area characterized by inherited Cretaceous normal faults and neotectonic faults with unknown recurrence intervals, some of which may have been reactivated normal faults. The 13 three-component seismic stations recorded data continuously for 15 months.
The 2015 earthquake took place in the Santa Bárbara System of the Andean foreland, at about 17km depth. This region is the easternmost morphostructural region of the central Andes. As a part of the broken foreland, it is bounded to the north by the Subandes fold-and-thrust belt and the Sierras Pampeanas to the south; to the east lies the Chaco-Paraná basin.
A multi-stage morphotectonic evolution with thick-skinned basement uplift and coeval thin-skinned deformation in the intermontane basins is suggested for the study area. The release of stresses associated with the foreland deformation can result in strong earthquakes, as the study area is known for recurrent and historical, destructive earthquakes. The available continuous record reaches back in time, when the strongest event in 1692 (magnitude 7 or intensity IX) destroyed the city of Esteco. Destructive earthquakes and surface deformation are thus a hallmark of this part of the Andean foreland.
With state-of-the-art Python packages (e.g. pyrocko, ObsPy), a semi-automatic approach is followed to analyze the collected continuous data of the seismological network. The resulting 1435 hypocenter locations consist of three different groups: 1.) local crustal earthquakes (nearly half of the events belong to this group), 2.) interplate activity, of regional distance in the slab of the Nazca-plate, and 3.) very deep earthquakes at about 600km depth. My major interest focused on the first event class. Those crustal events are partly aftershock events of the El Galpón earthquake and a second earthquake, in the south of the same fault. Further events can be considered as background seismicity of other faults within the study area. Strikingly, the seismogenic zone encompass the whole crust and propagates brittle deformation down, close to the Moho.
From the collected seismological data, a local seismic velocity model is estimated, using VELEST. After the execution of various stability tests, the robust minimum 1D-velocity model implies guiding values for the composition of the local, subsurface structure of the crust. Afterwards, performing a hypocenter relocation enables the assignment of individual earthquakes to aftershock clusters or extended seismotectonic structures. This allows the mapping of previously unknown seismogenic faults.
Finally, focal mechanisms are modeled for events with acurately located hypocenters, using the newly derived local velocity model. A compressive regime is attested by the majority of focal mechanisms, while the strike direction of the individual seismogenic structures is in agreement with the overall north – south orientation of the Central Andes, its mountain front, and individual mountain ranges in the southern Santa-Bárbara-System.
The Milky Way is a spiral galaxy consisting of a disc of gas, dust and stars embedded in a halo of dark matter. Within this dark matter halo there is also a diffuse population of stars called the stellar halo, that has been accreting stars for billions of years from smaller galaxies that get pulled in and disrupted by the large gravitational potential of the Milky Way. As they are disrupted, these galaxies leave behind long streams of stars that can take billions of years to mix with the rest of the stars in the halo. Furthermore, the amount of heavy elements (metallicity) of the stars in these galaxies reflects the rate of chemical enrichment that occurred in them, since the Universe has been slowly enriched in heavy elements (e.g. iron) through successive generations of stars which produce them in their cores and supernovae explosions. Therefore, stars that contain small amounts of heavy elements (metal-poor stars) either formed at early times before the Universe was significantly enriched, or in isolated environments. The aim of this thesis is to develop a better understanding of the substructure content and chemistry of the Galactic stellar halo, in order to gain further insight into the formation and evolution of the Milky Way.
The Pristine survey uses a narrow-band filter which specifically targets the Ca II H & K spectral absorption lines to provide photometric metallicities for a large number of stars down to the extremely metal-poor (EMP) regime, making it a very powerful data set for Galactic archaeology studies. In Chapter 2, we quantify the efficiency of the survey using a preliminary spectroscopic follow-up sample of ~ 200 stars. We also use this sample to establish a set of selection criteria to improve the success rate of selecting EMP candidates for follow-up spectroscopy. In Chapter 3, we extend this work and present the full catalogue of ~ 1000 stars from a three year long medium resolution spectroscopic follow-up effort conducted as part of the Pristine survey. From this sample, we compute success rates of 56% and 23% for recovering stars with [Fe/H] < -2.5 and [Fe/H] < -3.0, respectively. This demonstrates a high efficiency for finding EMP stars as compared to previous searches with success rates of 3-4%.
In Chapter 4, we select a sample of ~ 80000 halo stars using colour and magnitude cuts to select a main sequence turnoff population in the distance range 6 < dʘ < 20 kpc. We then use the spectroscopic follow-up sample presented in Chapter 3 to statistically rescale the Pristine photometric metallicities of this sample, and present the resulting corrected metallicity distribution function (MDF) of the halo. The slope at the metal-poor end is significantly shallower than previous spectroscopic efforts have shown, suggesting that there may be more metal-poor stars with [Fe/H] < -2.5 in the halo than previously thought. This sample also shows evidence that the MDF of the halo may not be bimodal as was proposed by previous works, and that the lack of globular clusters in the Milky Way may be the result of a physical truncation of the MDF rather than just statistical under-sampling.
Chapter 5 showcases the unexpected capability of the Pristine filter for separating blue horizontal branch (BHB) stars from Blue Straggler (BS) stars. We demonstrate a purity of 93% and completeness of 91% for identifying BHB stars, a substantial improvement over previous works. We then use this highly pure and complete sample of BHB stars to trace the halo density profile out to d > 100 kpc, and the Sagittarius stream substructure out to ~ 130 kpc.
In Chapter 6 we use the photometric metallicities from the Pristine survey to perform a clustering analysis of the halo as a function of metallicity. Separating the Pristine sample into four metallicity bins of [Fe/H] < -2, -2 < [Fe/H] < -1.5, -1.5 < [Fe/H] < -1 and -0.9 < [Fe/H] < -0.8, we compute the two-point correlation function to measure the amount of clustering on scales of < 5 deg. For a smooth comparison sample we make a mock Pristine data set generated using the Galaxia code based on the Besançon model of the Galaxy. We find enhanced clustering on small scales (< 0.5 deg) for some regions of the Galaxy for the most metal-poor bin ([Fe/H] < -2), while in others we see large scale signals that correspond to known substructures in those directions. This confirms that the substructure content of the halo is highly anisotropic and diverse in different Galactic environments. We discuss the difficulties of removing systematic clustering signals from the data and the limitations of disentangling weak clustering signals from real substructures and residual systematic structure in the data.
Taken together, the work presented in this thesis approaches the problem of better understanding the halo of our Galaxy from multiple angles. Firstly, presenting a sizeable sample of EMP stars and improving the selection efficiency of EMP stars for the Pristine survey, paving the way for the further discovery of metal-poor stars to be used as probes to early chemical evolution. Secondly, improving the selection of BHB distance tracers to map out the halo to large distances, and finally, using the large samples of metal-poor stars to derive the MDF of the inner halo and analyse the substructure content at different metallicities. The results of this thesis therefore expand our understanding of the physical and chemical properties of the Milky Way stellar halo, and provide insight into the processes involved in its formation and evolution.
Water quality in river systems is of growing concern due to rising anthropogenic pressures and climate change. Mitigation efforts have been placed under the guidelines of different governance conventions during last decades (e.g., the Water Framework Directive in Europe). Despite significant improvement through relatively straightforward measures, the environmental status has likely reached a plateau. A higher spatiotemporal accuracy of catchment nitrate modeling is, therefore, needed to identify critical source areas of diffuse nutrient pollution (especially for nitrate) and to further guide implementation of spatially differentiated, cost-effective mitigation measures. On the other hand, the emerging high-frequency sensor monitoring upgrades the monitoring resolution to the time scales of biogeochemical processes and enables more flexible monitoring deployments under varying conditions. The newly available information offers new prospects in understanding nitrate spatiotemporal dynamics. Formulating such advanced process understanding into catchment models is critical for model further development and environmental status evaluation. This dissertation is targeting on a comprehensive analysis of catchment and in-stream nitrate dynamics and is aiming to derive new insights into their spatial and temporal variabilities through the new fully distributed model development and the new high-frequency data.
Firstly, a new fully distributed, process-based catchment nitrate model (the mHM-Nitrate model) is developed based on the mesoscale Hydrological Model (mHM) platform. Nitrate process descriptions are adopted from the Hydrological Predictions for the Environment (HYPE), with considerable improved implementations. With the multiscale grid-based discretization, mHM-Nitrate balances the spatial representation and the modeling complexity. The model has been thoughtfully evaluated in the Selke catchment (456 km2), central Germany, which is characterized by heterogeneous physiographic conditions. Results show that the model captures well the long-term discharge and nitrate dynamics at three nested gauging stations. Using daily nitrate-N observations, the model is also validated in capturing short-term fluctuations due to changes in runoff partitioning and spatial contribution during flooding events. By comparing the model simulations with the values reported in the literature, the model is capable of providing detailed and reliable spatial information of nitrate concentrations and fluxes. Therefore, the model can be taken as a promising tool for environmental scientists in advancing environmental modeling research, as well as for stakeholders in supporting their decision-making, especially for spatially differentiated mitigation measures.
Secondly, a parsimonious approach of regionalizing the in-stream autotrophic nitrate uptake is proposed using high-frequency data and further integrated into the new mHM-Nitrate model. The new regionalization approach considers the potential uptake rate (as a general parameter) and effects of above-canopy light and riparian shading (represented by global radiation and leaf area index data, respectively). Multi-parameter sensors have been continuously deployed in a forest upstream reach and an agricultural downstream reach of the Selke River. Using the continuous high-frequency data in both streams, daily autotrophic uptake rates (2011-2015) are calculated and used to validate the regionalization approach. The performance and spatial transferability of the approach is validated in terms of well-capturing the distinct seasonal patterns and value ranges in both forest and agricultural streams. Integrating the approach into the mHM-Nitrate model allows spatiotemporal variability of in-stream nitrate transport and uptake to be investigated throughout the river network.
Thirdly, to further assess the spatial variability of catchment nitrate dynamics, for the first time the fully distributed parameterization is investigated through sensitivity analysis. Sensitivity results show that parameters of soil denitrification, in-stream denitrification and in-stream uptake processes are the most sensitive parameters throughout the Selke catchment, while they all show high spatial variability, where hot-spots of parameter sensitivity can be explicitly identified. The Spearman rank correlation is further analyzed between sensitivity indices and multiple catchment factors. The correlation identifies that the controlling factors vary spatially, reflecting heterogeneous catchment responses in the Selke catchment. These insights are, therefore, informative in informing future parameter regionalization schemes for catchment water quality models. In addition, the spatial distributions of parameter sensitivity are also influenced by the gauging information that is being used for sensitivity evaluation. Therefore, an appropriate monitoring scheme is highly recommended to truly reflect the catchment responses.
Perovskite solar cells have become one of the most studied systems in the quest for new, cheap and efficient solar cell materials. Within a decade device efficiencies have risen to >25% in single-junction and >29% in tandem devices on top of silicon. This rapid improvement was in many ways fortunate, as e. g. the energy levels of commonly used halide perovskites are compatible with already existing materials from other photovoltaic technologies such as dye-sensitized or organic solar cells. Despite this rapid success, fundamental working principles must be understood to allow concerted further improvements. This thesis focuses on a comprehensive understanding of recombination processes in functioning devices.
First the impact the energy level alignment between the perovskite and the electron transport layer based on fullerenes is investigated. This controversial topic is comprehensively addressed and recombination is mitigated through reducing the energy difference between the perovskite conduction band minimum and the LUMO of the fullerene. Additionally, an insulating blocking layer is introduced, which is even more effective in reducing this recombination, without compromising carrier collection and thus efficiency. With the rapid efficiency development (certified efficiencies have broken through the 20% ceiling) and thousands of researchers working on perovskite-based optoelectronic devices, reliable protocols on how to reach these efficiencies are lacking. Having established robust methods for >20% devices, while keeping track of possible pitfalls, a detailed description of the fabrication of perovskite solar cells at the highest efficiency level (>20%) is provided. The fabrication of low-temperature p-i-n structured devices is described, commenting on important factors such as practical experience, processing atmosphere & temperature, material purity and solution age. Analogous to reliable fabrication methods, a method to identify recombination losses is needed to further improve efficiencies. Thus, absolute photoluminescence is identified as a direct way to quantify the Quasi-Fermi level splitting of the perovskite absorber (1.21eV) and interfacial recombination losses the transport layers impose, reducing the latter to ~1.1eV. Implementing very thin interlayers at both the p- and n-interface (PFN-P2 and LiF, respectively), these losses are suppressed, enabling a VOC of up to 1.17eV. Optimizing the device dimensions and the bandgap, 20% devices with 1cm2 active area are demonstrated. Another important consideration is the solar cells’ stability if subjected to field-relevant stressors during operation. In particular these are heat, light, bias or a combination thereof. Perovskite layers – especially those incorporating organic cations – have been shown to degrade if subjected to these stressors. Keeping in mind that several interlayers have been successfully used to mitigate recombination losses, a family of perfluorinated self-assembled monolayers (X-PFCn, where X denotes I/Br and n = 7-12) are introduced as interlayers at the n-interface. Indeed, they reduce interfacial recombination losses enabling device efficiencies up to 21.3%. Even more importantly they improve the stability of the devices. The solar cells with IPFC10 are stable over 3000h stored in the ambient and withstand a harsh 250h of MPP at 85◦C without appreciable efficiency losses. To advance further and improve device efficiencies, a sound understanding of the photophysics of a device is imperative. Many experimental observations in recent years have however drawn an inconclusive picture, often suffering from technical of physical impediments, disguising e. g. capacitive discharge as recombination dynamics. To circumvent these obstacles, fully operational, highly efficient perovskites solar cells are investigated by a combination of multiple optical and optoelectronic probes, allowing to draw a conclusive picture of the recombination dynamics in operation. Supported by drift-diffusion simulations, the device recombination dynamics can be fully described by a combination of first-, second- and third-order recombination and JV curves as well as luminescence efficiencies over multiple illumination intensities are well described within the model. On this basis steady state carrier densities, effective recombination constants, densities-of-states and effective masses are calculated, putting the devices at the brink of the radiative regime. Moreover, a comprehensive review of recombination in state-of-the-art devices is given, highlighting the importance of interfaces in nonradiative recombination. Different strategies to assess these are discussed, before emphasizing successful strategies to reduce interfacial recombination and pointing towards the necessary steps to further improve device efficiency and stability. Overall, the main findings represent an advancement in understanding loss mechanisms in highly efficient solar cells. Different reliable optoelectronic techniques are used and interfacial losses are found to be of grave importance for both efficiency and stability. Addressing the interfaces, several interlayers are introduced, which mitigate recombination losses and degradation.
To meet the demands of a growing world population while reducing carbon dioxide (CO2) emissions, it is necessary to capture CO2 and convert it into value-added compounds. In recent years, metabolic engineering of microbes has gained strong momentum as a strategy for the production of valuable chemicals. As common microbial feedstocks like glucose directly compete with human consumption, the one carbon (C1) compound formate was suggested as an alternative feedstock. Formate can be easily produced by various means including electrochemical reduction of CO2 and could serve as a feedstock for microbial production, hence presenting a novel entry point for CO2 to the biosphere and a storage option for excess electricity. Compared to the gaseous molecule CO2, formate is a highly soluble compound that can be easily handled and stored. It can serve as a carbon and energy source for natural formatotrophs, but these microbes are difficult to cultivate and engineer. In this work, I present the results of several projects that aim to establish efficient formatotrophic growth of E. coli – which cannot naturally grow on formate – via synthetic formate assimilation pathways. In the first study, I establish a workflow for growth-coupled metabolic engineering of E. coli. I demonstrate this approach by presenting an engineering scheme for the PFL-threonine cycle, a synthetic pathway for anaerobic formate assimilation in E. coli. The described methods are intended to create a standardized toolbox for engineers that aim to establish novel metabolic routes in E. coli and related organisms. The second chapter presents a study on the catalytic efficiency of C1-oxidizing enzymes in vivo. As formatotrophic growth requires generation of both energy and biomass from formate, the engineered E. coli strains need to be equipped with a highly efficient formate dehydrogenase, which provides reduction equivalents and ATP for formate assimilation. I engineered a strain that cannot generate reducing power and energy for cellular growth, when fed on acetate. Under this condition, the strain depends on the introduction of an enzymatic system for NADH regeneration, which could further produce ATP via oxidative phosphorylation. I show that the strain presents a valuable testing platform for C1-oxidizing enzymes by testing different NAD-dependent formate and methanol dehydrogenases in the energy auxotroph strain. Using this platform, several candidate enzymes with high in vivo activity, were identified and characterized as potential energy-generating systems for synthetic formatotrophic or methylotrophic growth in E. coli. In the third chapter, I present the establishment of the serine threonine cycle (STC) – a synthetic formate assimilation pathway – in E. coli. In this pathway, formate is assimilated via formate tetrahydrofolate ligase (FtfL) from Methylobacterium extorquens (M. extorquens). The carbon from formate is attached to glycine to produce serine, which is converted into pyruvate entering central metabolism. Via the natural threonine synthesis and cleavage route, glycine is regenerated and acetyl-CoA is produced as the pathway product. I engineered several selection strains that depend on different STC modules for growth and determined key enzymes that enable high flux through threonine synthesis and cleavage. I could show that expression of an auxiliary formate dehydrogenase was required to achieve growth via threonine synthesis and cleavage on pyruvate. By overexpressing most of the pathway enzymes from the genome, and applying adaptive laboratory evolution, growth on glycine and formate was achieved, indicating the activity of the complete cycle. The fourth chapter shows the establishment of the reductive glycine pathway (rGP) – a short, linear formate assimilation route – in E. coli. As in the STC, formate is assimilated via M. extorquens FtfL. The C1 from formate is condensed with CO2 via the reverse reaction of the glycine cleavage system to produce glycine. Another carbon from formate is attached to glycine to form serine, which is assimilated into central metabolism via pyruvate. The engineered E. coli strain, expressing most of the pathway genes from the genome, can grow via the rGP with formate or methanol as a sole carbon and energy source.
Methane is an important greenhouse gas contributing to global climate change. Natural environments and restored wetlands contribute a large proportion to the global methane budget. Methanogenic archaea (methanogens) and methane oxidizing bacteria (methanotrophs), the biogenic producers and consumers of methane, play key roles in the methane cycle in those environments. A large number of studies revealed the distribution, diversity and composition of these microorganisms in individual habitats. However, uncertainties exist in predicting the response and feedback of methane-cycling microorganisms to future climate changes and related environmental changes due to the limited spatial scales considered so far, and due to a poor recognition of the biogeography of these important microorganisms combining global and local scales.
With the aim of improving our understanding about whether and how methane-cycling microbial communities will be affected by a series of dynamic environmental factors in response to climate change, this PhD thesis investigates the biogeographic patterns of methane-cycling communities, and the driving factors which define these patterns at different spatial scales. At the global scale, a meta-analysis was performed by implementing 94 globally distributed public datasets together with environmental data from various natural environments including soils, lake sediments, estuaries, marine sediments, hydrothermal sediments and mud volcanos. In combination with a global biogeographic map of methanogenic archaea from multiple natural environments, this thesis revealed that biogeographic patterns of methanogens exist. The terrestrial habitats showed higher alpha diversities than marine environments. Methanoculleus and Methanosaeta (Methanothrix) are the most frequently detected taxa in marine habitats, while Methanoregula prevails in terrestrial habitats. Estuary ecosystems, the transition zones between marine and terrestrial/limnic ecosystems, have the highest methanogenic richness but comparably low methane emission rates. At the local scale, this study compared two rewetted fens with known high methane emissions in northeastern Germany, a coastal brackish fen (Hütelmoor) and a freshwater riparian fen (Polder Zarnekow). Consistent with different geochemical conditions and land-use history, the two rewetted fens exhibit dissimilar methanogenic and, especially, methanotrophic community compositions. The methanotrophic community was generally under-represented among the prokaryotic communities and both fens show similarly low ratios of methanotrophic to methanogenic abundances. Since few studies have characterized methane-cycling microorganisms in rewetted fens, this study provides first evidence that the rapid and well re-established methanogenic community in combination with the low and incomplete re-establishment of the methanotrophic community after rewetting contributes to elevated sustained methane fluxes following rewetting.
Finally, this thesis demonstrates that dispersal limitation only slightly regulates the biogeographic distribution patterns of methanogenic microorganisms in natural environments and restored wetlands. Instead, their existence, adaption and establishment are more associated with the selective pressures under different environmental conditions. Salinity, pH and temperature are identified as the most important factors in shaping microbial community structure at different spatial scales (global versus terrestrial environments). Predicted changes in climate, such as increasing temperature, changes in precipitation patterns and increasing frequency of flooding events, are likely to induce a series of environmental alterations, which will either directly or indirectly affect the driving environmental forces of methanogenic communities, leading to changes in their community composition and thus potentially also in methane emission patterns in the future.
Largescale patterns of global land use change are very frequently accompanied by natural habitat loss. To assess the consequences of habitat loss for the remaining natural and semi-natural biotopes, inclusion of cumulative effects at the landscape level is required. The interdisciplinary concept of vulnerability constitutes an appropriate assessment framework at the landscape level, though with few examples of its application for ecological assessments. A comprehensive biotope vulnerability analysis allows identification of areas most affected by landscape change and at the same time with the lowest chances of regeneration.
To this end, a series of ecological indicators were reviewed and developed. They measured spatial attributes of individual biotopes as well as some ecological and conservation characteristics of the respective resident species community. The final vulnerability index combined seven largely independent indicators, which covered exposure, sensitivity and adaptive capacity of biotopes to landscape changes. Results for biotope vulnerability were provided at the regional level. This seems to be an appropriate extent with relevance for spatial planning and designing the distribution of nature reserves.
Using the vulnerability scores calculated for the German federal state of Brandenburg, hot spots and clusters within and across the distinguished types of biotopes were analysed. Biotope types with high dependence on water availability, as well as biotopes of the open landscape containing woody plants (e.g., orchard meadows) are particularly vulnerable to landscape changes. In contrast, the majority of forest biotopes appear to be less vulnerable. Despite the appeal of such generalised statements for some biotope types, the distribution of values suggests that conservation measures for the majority of biotopes should be designed specifically for individual sites. Taken together, size, shape and spatial context of individual biotopes often had a dominant influence on the vulnerability score.
The implementation of biotope vulnerability analysis at the regional level indicated that large biotope datasets can be evaluated with high level of detail using geoinformatics. Drawing on previous work in landscape spatial analysis, the reproducible approach relies on transparent calculations of quantitative and qualitative indicators. At the same time, it provides a synoptic overview and information on the individual biotopes. It is expected to be most useful for nature conservation in combination with an understanding of population, species, and community attributes known for specific sites. The biotope vulnerability analysis facilitates a foresighted assessment of different land uses, aiding in identifying options to slow habitat loss to sustainable levels. It can also be incorporated into planning of restoration measures, guiding efforts to remedy ecological damage. Restoration of any specific site could yield synergies with the conservation objectives of other sites, through enhancing the habitat network or buffering against future landscape change.
Biotope vulnerability analysis could be developed in line with other important ecological concepts, such as resilience and adaptability, further extending the broad thematic scope of the vulnerability concept. Vulnerability can increasingly serve as a common framework for the interdisciplinary research necessary to solve major societal challenges.
To find out the future of nowadays reef ecosystem turnover under the environmental stresses such as global warming and ocean acidification, analogue studies from the geologic past are needed. As a critical time of reef ecosystem innovation, the Permian-Triassic transition witnessed the most severe demise of Phanerozoic reef builders, and the establishment of modern style symbiotic relationships within the reef-building organisms. Being the initial stage of this transition, the Middle Permian (Capitanian) mass extinction coursed a reef eclipse in the early Late Permian, which lead to a gap of understanding in the post-extinction Wuchiapingian reef ecosystem, shortly before the radiation of Changhsingian reefs. Here, this thesis presents detailed biostratigraphic, sedimentological, and palaeoecological studies of the Wuchiapingian reef recovery following the Middle Permian (Capitanian) mass extinction, on the only recorded Wuchiapingian reef setting, outcropping in South China at the Tieqiao section.
Conodont biostratigraphic zonations were revised from the Early Permian Artinskian to the Late Permian Wuchiapingian in the Tieqiao section. Twenty main and seven subordinate conodont zones are determined at Tieqiao section including two conodont zone below and above the Tieqiao reef complex. The age of Tieqiao reef was constrained as early to middle Wuchiapingian.
After constraining the reef age, detailed two-dimensional outcrop mapping combined with lithofacies study were carried out on the Wuchiapingian Tieqiao Section to investigate the reef growth pattern stratigraphically as well as the lateral changes of reef geometry on the outcrop scale. Semi-quantitative studies of the reef-building organisms were used to find out their evolution pattern within the reef recovery. Six reef growth cycles were determined within six transgressive-regressive cycles in the Tieqiao section. The reefs developed within the upper part of each regressive phase and were dominated by different biotas. The timing of initial reef recovery after the Middle Permian (Capitanian) mass extinction was updated to the Clarkina leveni conodont zone, which is earlier than previous understanding. Metazoans such as sponges were not the major components of the Wuchiapingian reefs until the 5th and 6th cycles. So, the recovery of metazoan reef ecosystem after the Middle Permian (Capitanian) mass extinction was obviously delayed. In addition, although the importance of metazoan reef builders such as sponges did increase following the recovery process, encrusting organisms such as Archaeolithoporella and Tubiphytes, combined with microbial carbonate precipitation, still played significant roles to the reef building process and reef recovery after the mass extinction.
Based on the results from outcrop mapping and sedimentological studies, quantitative composition analysis of the Tieqiao reef complex were applied on selected thin sections to further investigate the functioning of reef building components and the reef evolution after the Middle Permian (Capitanian) mass extinction. Data sets of skeletal grains and whole rock components were analyzed. The results show eleven biocommunity clusters/eight rock composition clusters dominated by different skeletal grains/rock components. Sponges, Archaeolithoporella and Tubiphytes were the most ecologically important components within the Wuchiapingian Tieqiao reef, while the clotted micrites and syndepositional cements are the additional important rock components for reef cores. The sponges were important within the whole reef recovery. Tubiphytes were broadly distributed in different environments and played a key-role in the initial reef communities. Archaeolithoporella concentrated in the shallower part of reef cycles (i.e., the upper part of reef core) and was functionally significant for the enlargement of reef volume.
In general, the reef recovery after the Middle Permian (Capitanian) mass extinction has some similarities with the reef recovery following the end-Permian mass extinction. It shows a delayed recovery of metazoan reefs and a stepwise recovery pattern that was controlled by both ecological and environmental factors. The importance of encrusting organisms and microbial carbonates are also similar to most of the other post-extinction reef ecosystems. These findings can be instructive to extend our understanding of the reef ecosystem evolution under environmental perturbation or stresses.
Bank filtration is an effective water treatment technique and is widely adopted in Europe along major rivers. It is the process where surface water penetrates the riverbed, flows through the aquifer, and then is extracted by near-bank production wells. By flowing in the subsurface flow passage, the water quality can be improved by a series of beneficial processes. Long-term riverbank filtration also produces colmation layers on the riverbed. The colmation layer may act as a bioactive zone that is governed by biochemical and physical processes owing to its enrichment of microbes and organic matter. Low permeability may strongly limit the surface water infiltration and further lead to a decreasing recoverable ratio of production wells.The removal of the colmation layer is therefore a trade-off between the treatment capacity and treatment efficiency. The goal of this Ph.D. thesis is to focus on the temporal and spatial change of the water quality and quantity along the flow path of a hydrogeological heterogeneous riverbank filtration site adjacent to an artificial-reconstructed (bottom excavation and bank reconstruction) canal in Potsdam, Germany.
To quantify the change of the infiltration rate, travel time distribution, and the thermal field brought by the canal reconstruction, a three-dimensional flow and heat transport model was created. This model has two scenarios, 1) ‘with’ canal reconstruction, and 2) ‘without’ canal reconstruction. Overall, the model calibration results of both water heads and temperatures matched those observed in the field study. In comparison to the model without reconstruction, the reconstruction model led to more water being infiltrated into the aquifer on that section, on average 521 m3/d, which corresponded to around 9% of the total pumping rate. Subsurface travel-time distribution substantially shifted towards shorter travel times. Flow paths with travel times <200 days increased by ~10% and those with <300 days by 15%. Furthermore, the thermal distribution in the aquifer showed that the seasonal variation in the scenario with reconstruction reaches deeper and laterally propagates further.
By scatter plotting of δ18O versus δ 2H, the infiltrated river water could be differentiated from water flowing in the deep aquifer, which may contain remnant landside groundwater from further north. In contrast, the increase of river water contribution due to decolmation could be shown by piper plot. Geological heterogeneity caused a substantial spatial difference in redox zonation among different flow paths, both horizontally and vertically. Using the Wilcoxon rank test, the reconstruction changed the redox potential differently in observation wells. However, taking the small absolute concentration level, the change is also relatively minor. The treatment efficiency for both organic matter and inorganic matter is consistent after the reconstruction, except for ammonium. The inconsistent results for ammonium could be explained by changes in the Cation Exchange Capacity (CEC) in the newly paved riverbed. Because the bed is new, it was not yet capable of keeping the newly produced ammonium by sorption and further led to the breakthrough of the ammonium plume. By estimation, the peak of the ammonium plume would reach the most distant observation well before February 2024, while the peaking concentration could be further dampened by sorption and diluted by the afterward low ammonium flow. The consistent DOC and SUVA level suggests that there was no clear preference for the organic matter removal along the flow path.
As one of the most-produced commodity polymers, polypropylene draws considerable scientific and commercial interest as an electret material. In the present thesis, the influence of the surface chemical modification and crystalline reconstruction on the electret properties of the polypropylene thin films will be discussed. The chemical treatment with orthophosphoric acid can significantly improve the surface charge stability of the polypropylene electrets by introducing phosphorus- and oxygen-containing structures onto the modified surface. The thermally stimulated discharge measurement and charge profiling by means of piezoelectrically generated pressure steps are used to investigate the electret behaviour. It is concluded that deep traps of limited number density are created during the treatment with inorganic chemicals. Hence, the improvement dramatically decreases when the surface-charge density is substantially higher than ±1.2×10^(-3) C·m^(-2). The newly formed traps also show a higher trapping energy for negative charges. The energetic distributions of the traps in the non-treated and chemically treated samples offer an insight regarding the surface and foreign-chemical dominance on the charge storage and transport in the polypropylene electrets.
Additionally, different electret properties are observed on the polypropylene films with the spherulitic and transcrystalline structures. It indicates the dependence of the charge storage and transport on the crystallite and molecular orientations in the crystalline phase. In general, a more diverse crystalline growth in the spherulitic samples can result in a more complex energetic trap distribution, in comparison to that in a transcrystalline polypropylene. The double-layer transcrystalline polypropylene film with a crystalline interface in the middle can be obtained by crystallising the film in contact with rough moulding surfaces on both sides. A layer of heterocharges appears on each side of the interface in the double-layer transcrystalline polypropylene electrets after the thermal poling. However, there is no charge captured within the transcrystalline layers. The phenomenon reveals the importance of the crystalline interface in terms of creating traps with the higher activation energy in polypropylene. The present studies highlight the fact that even slight variations in the polypropylene film may lead to dramatic differences in its electret properties.
It has frequently been observed that single emotional events are not only more efficiently processed, but also better remembered, and form longer-lasting memory traces than neutral material. However, when emotional information is perceived as a part of a complex event, such as in the context of or in relation to other events and/or source details, the modulatory effects of emotion are less clear. The present work aims to investigate how emotional, contextual source information modulates the initial encoding and subsequent long-term retrieval of associated neutral material (item memory) and contextual source details (contextual source memory). To do so, a two-task experiment was used, consisting of an incidental encoding task in which neutral objects were displayed over different contextual background scenes which varied in emotional content (unpleasant, pleasant, and neutral), and a delayed retrieval task (1 week), in which previously-encoded objects and new ones were presented. In a series of studies, behavioral indices (Studies 2, 3, and 5), event-related potentials (ERPs; Studies 1-4), and functional magnetic resonance imaging (Study 5) were used to investigate whether emotional contexts can rapidly tune the visual processing of associated neutral information (Study 1) and modulate long-term item memory (Study 2), how different recognition memory processes (familiarity vs. recollection) contribute to these emotion effects on item and contextual source memory (Study 3), whether the emotional effects of item memory can also be observed during spontaneous retrieval (Sstudy 4), and which brain regions underpin the modulatory effects of emotional contexts on item and contextual source memory (Study 5). In Study 1, it was observed that emotional contexts by means of emotional associative learning, can rapidly alter the processing of associated neutral information. Neutral items associated with emotional contexts (i.e. emotional associates) compared to neutral ones, showed enhanced perceptual and more elaborate processing after one single pairing, as indexed by larger amplitudes in the P100 and LPP components, respectively. Study 2 showed that emotional contexts produce longer-lasting memory effects, as evidenced by better item memory performance and larger ERP Old/New differences for emotional associates. In Study 3, a mnemonic differentiation was observed between item and contextual source memory which was modulated by emotion. Item memory was driven by familiarity, independently of emotional contexts during encoding, whereas contextual source memory was driven by recollection, and better for emotional material. As in Study 2, enhancing effects of emotional contexts for item memory were observed in ERPs associated with recollection processes. Likewise, for contextual source memory, a pronounced recollection-related ERP enhancement was observed for exclusively emotional contexts. Study 4 showed that the long-term recollection enhancement of emotional contexts on item memory can be observed even when retrieval is not explicitly attempted, as measured with ERPs, suggesting that the emotion enhancing effects on memory are not related to the task embedded during recognition, but to the motivational relevance of the triggering event. In Study 5, it was observed that enhancing effects of emotional contexts on item and contextual source memory involve stronger engagement of the brain's regions which are associated with memory recollection, including areas of the medial temporal lobe, posterior parietal cortex, and prefrontal cortex.
Taken together, these findings suggest that emotional contexts rapidly modulate the initial processing of associated neutral information and the subsequent, long-term item and contextual source memories. The enhanced memory effects of emotional contexts are strongly supported by recollection rather than familiarity processes, and are shown to be triggered when retrieval is both explicitly and spontaneously attempted. These results provide new insights into the modulatory role of emotional information on the visual processing and the long-term recognition memory of complex events. The present findings are integrated into the current theoretical models and future ventures are discussed.
This thesis offers new insights on the effects of Start-Up Subsidies (SUS) for unemployed individuals as a special kind of active labor market program (ALMP) that aims to re-integrate individuals into the labor market via the route of self-employment. Moreover, this thesis contributes to the literature on methods for causal inference when the treatment variable is continuous rather than binary. For example, this is the case when individuals differ in their degree of exposure to a common treatment.
The analysis of the effects of SUS focuses on the main current German program called “Gründungszuschuss” (New Start-Up Subsidy, NSUS) after its reform in 2011. Average Effects on participants' labor market outcomes - as measured by employment and earnings - as well as subjective well-being are estimated mainly based on propensity score matching (PSM) techniques. PSM aims to achieve balance in terms of observed characteristics by matching participants with at least one comparable non-participant in terms of their probability to receive the treatment. This estimation strategy is valid as long as all relevant characteristics that explain selection patterns into treatment are observed and included in the estimation of the propensity score. To make our analysis as credible as possible, we control for a large vector of characteristics as observed through the combination of rich administrative data from the Federal Employment Agency as well as through survey data.
Chapters two to four of this thesis puts special emphasis on aspects regarding (the evaluation of) SUS programs that have received no or only limited attention thus far. The first aspect relates to the interplay of institutional details of the program and its effectiveness. So far, relatively little is known about the importance of SUS program features such as the duration of support. Second, there is no experimental benchmark evaluation of SUS available and thus, the reliability of non-experimental estimation techniques such as PSM is of crucial importance as estimates are biased when relevant confounders are omitted from the analysis. Third, there may be potentially detrimental effects of transitioning into (relatively risky) self-employment on subjective well-being among subsidized founders out of unemployment. These were to remain undetected if the analysis would focus exclusively on labor market outcomes of participants. The results indicate positive long-term effects of SUS participation on employment and earnings among participants. These effects are substantially larger than what estimated before the reform, indicating room for improvement in program design via changes in institutional details. Moreover, non-experimental estimates of treatment effects are remarkably robust to hidden confounding. Regarding subjective well-being, this thesis finds a positive long-run impact on job satisfaction and a detrimental effect on satisfaction with social security. The latter appears to be driven by adverse effects on social insurance contributions.
In chapter five, a novel automated covariate balancing technique for the estimation of causal effects in the context of continuous treatments is derived and assessed regarding its performance compared to other (automated) balancing techniques. Although binary research designs that only differentiate between participants and non-participants of some treatment remain the most-common case in empirical practice, many applications can be adapted to include continuous treatments as well. Often, this will allow for more meaningful estimates of causal effects in order to further improve the design of programs. In the context of SUS, one may further investigate the effects of the size of monetary support or its duration on participants' labor market outcomes. Both Monte-Carlo investigations and analysis of two well-known datasets suggests superior performance of the proposed Entropy Balancing for continuous treatments (EBCT) compared to other existing estimation strategies.
The development of bioinspired self-assembling materials, such as hydrogels, with promising applications in cell culture, tissue engineering and drug delivery is a current focus in material science. Biogenic or bioinspired proteins and peptides are frequently used as versatile building blocks for extracellular matrix (ECM) mimicking hydrogels. However, precisely controlling and reversibly tuning the properties of these building blocks and the resulting hydrogels remains challenging. Precise control over the viscoelastic properties and self-healing abilities of hydrogels are key factors for developing intelligent materials to investigate cell matrix interactions. Thus, there is a need to develop building blocks that are self-healing, tunable and self-reporting. This thesis aims at the development of α-helical peptide building blocks, called coiled coils (CCs), which integrate these desired properties. Self-healing is a direct result of the fast self-assembly of these building blocks when used as material cross-links. Tunability is realized by means of reversible histidine (His)-metal coordination bonds. Lastly, implementing a fluorescent readout, which indicates the CC assembly state, self-reporting hydrogels are obtained.
Coiled coils are abundant protein folding motifs in Nature, which often have mechanical function, such as in myosin or fibrin. Coiled coils are superhelices made up of two or more α-helices wound around each other. The assembly of CCs is based on their repetitive sequence of seven amino acids, so-called heptads (abcdefg). Hydrophobic amino acids in the a and d position of each heptad form the core of the CC, while charged amino acids in the e and g position form ionic interactions. The solvent-exposed positions b, c and f are excellent targets for modifications since they are more variable. His-metal coordination bonds are strong, yet reversible interactions formed between the amino acid histidine and transition metal ions (e.g. Ni2+, Cu2+ or Zn2+). His-metal coordination bonds essentially contribute to the mechanical stability of various high-performance proteinaceous materials, such as spider fangs, Nereis worm jaws and mussel byssal threads. Therefore, I bioengineered reversible His-metal coordination sites into a well-characterized heterodimeric CC that served as tunable material cross-link. Specifically, I took two distinct approaches facilitating either intramolecular (Chapter 4.2) and/or intermolecular (Chapter 4.3) His-metal coordination.
Previous research suggested that force-induced CC unfolding in shear geometry starts from the points of force application. In order to tune the stability of a heterodimeric CC in shear geometry, I inserted His in the b and f position at the termini of force application (Chapter 4.2). The spacing of His is such that intra-CC His-metal coordination bonds can form to bridge one helical turn within the same helix, but also inter-CC coordination bonds are not generally excluded. Starting with Ni2+ ions, Raman spectroscopy showed that the CC maintained its helical structure and the His residues were able to coordinate Ni2+. Circular dichroism (CD) spectroscopy revealed that the melting temperature of the CC increased by 4 °C in the presence of Ni2+. Using atomic force microscope (AFM)-based single molecule force spectroscopy, the energy landscape parameters of the CC were characterized in the absence and the presence of Ni2+. His-Ni2+ coordination increased the rupture force by ~10 pN, accompanied by a decrease of the dissociation rate constant. To test if this stabilizing effect can be transferred from the single molecule level to the bulk viscoelastic material properties, the CC building block was used as a non-covalent cross-link for star-shaped poly(ethylene glycol) (star-PEG) hydrogels. Shear rheology revealed a 3-fold higher relaxation time in His-Ni2+ coordinating hydrogels compared to the hydrogel without metal ions. This stabilizing effect was fully reversible when using an excess of the metal chelator ethylenediaminetetraacetate (EDTA). The hydrogel properties were further investigated using different metal ions, i.e. Cu2+, Co2+ and Zn2+. Overall, these results suggest that Ni2+, Cu2+ and Co2+ primarily form intra-CC coordination bonds while Zn2+ also participates in inter-CC coordination bonds. This may be a direct result of its different coordination geometry.
Intermolecular His-metal coordination bonds in the terminal regions of the protein building blocks of mussel byssal threads are primarily formed by Zn2+ and were found to be intimately linked to higher-order assembly and self-healing of the thread. In the above example, the contribution of intra-CC and inter-CC His-Zn2+ cannot be disentangled. In Chapter 4.3, I redesigned the CC to prohibit the formation of intra-CC His-Zn2+ coordination bonds, focusing only on inter-CC interactions. Specifically, I inserted His in the solvent-exposed f positions of the CC to focus on the effect of metal-induced higher-order assembly of CC cross-links. Raman and CD spectroscopy revealed that this CC building block forms α-helical Zn2+ cross-linked aggregates. Using this CC as a cross-link for star-PEG hydrogels, I showed that the material properties can be switched from viscoelastic in the absence of Zn2+ to elastic-like in the presence of Zn2+. Moreover, the relaxation time of the hydrogel was tunable over three orders of magnitude when using different Zn2+:His ratios. This tunability is attributed to a progressive transformation of single CC cross-links into His-Zn2+ cross-linked aggregates, with inter-CC His-Zn2+ coordination bonds serving as an additional, cross-linking mode.
Rheological characterization of the hydrogels with inter-CC His-Zn2+ coordination raised the question whether the His-Zn2+ coordination bonds between CCs or also the CCs themselves rupture when shear strain is applied. In general, the amount of CC cross-links initially formed in the hydrogel as well as the amount of CC cross-links breaking under force remains to be elucidated. In order to more deeply probe these questions and monitor the state of the CC cross-links when force is applied, a fluorescent reporter system based on Förster resonance energy transfer (FRET) was introduced into the CC (Chapter 4.4). For this purpose, the donor-acceptor pair carboxyfluorescein and tetramethylrhodamine was used. The resulting self-reporting CC showed a FRET efficiency of 77 % in solution. Using this fluorescently labeled CC as a self-reporting, reversible cross-link in an otherwise covalently cross-linked star-PEG hydrogel enabled the detection of the FRET efficiency change under compression force. This proof-of-principle result sets the stage for implementing the fluorescently labeled CCs as molecular force sensors in non-covalently cross-linked hydrogels.
In summary, this thesis highlights that rationally designed CCs are excellent reversibly tunable, self-healing and self-reporting hydrogel cross-links with high application potential in bioengineering and biomedicine. For the first time, I demonstrated that His-metal coordination-based stabilization can be transferred from the single CC level to the bulk material with clear viscoelastic consequences. Insertion of His in specific sequence positions was used to implement a second non-covalent cross-linking mode via intermolecular His-metal coordination. This His-metal binding induced aggregation of the CCs enabled for reversibly tuning the hydrogel properties from viscoelastic to elastic-like. As a proof-of-principle to establish self-reporting CCs as material cross-links, I labeled a CC with a FRET pair. The fluorescently labelled CC acts as a molecular force sensor and first preliminary results suggest that the CC enables the detection of hydrogel cross-link failure under compression force. In the future, fluorescently labeled CC force sensors will likely not only be used as intelligent cross-links to study the failure of hydrogels but also to investigate cell-matrix interactions in 3D down to the single molecule level.
The development of methods such as super-resolution microscopy (Nobel prize in Chemistry, 2014) and multi-scale computer modelling (Nobel prize in Chemistry, 2013) have provided scientists with powerful tools to study microscopic systems. Sub-micron particles or even fluorescently labelled single molecules can now be tracked for long times in a variety of systems such as living cells, biological membranes, colloidal solutions etc. at spatial and temporal resolutions previously inaccessible. Parallel to such single-particle tracking experiments, super-computing techniques enable simulations of large atomistic or coarse-grained systems such as biologically relevant membranes or proteins from picoseconds to seconds, generating large volume of data. These have led to an unprecedented rise in the number of reported cases of anomalous diffusion wherein the characteristic features of Brownian motion—namely linear growth of the mean squared displacement with time and the Gaussian form of the probability density function (PDF) to find a particle at a given position at some fixed time—are routinely violated. This presents a big challenge in identifying the underlying stochastic process and also estimating the corresponding parameters of the process to completely describe the observed behaviour. Finding the correct physical mechanism which leads to the observed dynamics is of paramount importance, for example, to understand the first-arrival time of transcription factors which govern gene regulation, or the survival probability of a pathogen in a biological cell post drug administration. Statistical Physics provides useful methods that can be applied to extract such vital information. This cumulative dissertation, based on five publications, focuses on the development, implementation and application of such tools with special emphasis on Bayesian inference and large deviation theory. Together with the implementation of Bayesian model comparison and parameter estimation methods for models of diffusion, complementary tools are developed based on different observables and large deviation theory to classify stochastic processes and gather pivotal information. Bayesian analysis of the data of micron-sized particles traced in mucin hydrogels at different pH conditions unveiled several interesting features and we gained insights into, for example, how in going from basic to acidic pH, the hydrogel becomes more heterogeneous and phase separation can set in, leading to observed non-ergodicity (non-equivalence of time and ensemble averages) and non-Gaussian PDF. With large deviation theory based analysis we could detect, for instance, non-Gaussianity in seeming Brownian diffusion of beads in aqueous solution, anisotropic motion of the beads in mucin at neutral pH conditions, and short-time correlations in climate data. Thus through the application of the developed methods to biological and meteorological datasets crucial information is garnered about the underlying stochastic processes and significant insights are obtained in understanding the physical nature of these systems.
‘The Territorialities of U.S. Imperialisms’ sets into relation U.S. imperial and Indigenous conceptions of territoriality as articulated in U.S. legal texts and Indigenous life writing in the 19th century. It analyzes the ways in which U.S. legal texts as “legal fictions” narratively press to affirm the United States’ territorial sovereignty and coherence in spite of its reliance on a variety of imperial practices that flexibly disconnect and (re)connect U.S. sovereignty, jurisdiction and territory.
At the same time, the book acknowledges Indigenous life writing as legal texts in their own right and with full juridical force, which aim to highlight the heterogeneity of U.S. national territory both from their individual perspectives and in conversation with these legal fictions. Through this, the book’s analysis contributes to a more nuanced understanding of the coloniality of U.S. legal fictions, while highlighting territoriality as a key concept in the fashioning of the narrative of U.S. imperialism.