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The concept of hydrologic connectivity summarizes all flow processes that link separate regions of a landscape. As such, it is a central theme in the field of catchment hydrology, with influence on neighboring disciplines such as ecology and geomorphology. It is widely acknowledged to be an important key in understanding the response behavior of a catchment and has at the same time inspired research on internal processes over a broad range of scales. From this process-hydrological point of view, hydrological connectivity is the conceptual framework to link local observations across space and scales.
This is the context in which the four studies this thesis comprises of were conducted. The focus was on structures and their spatial organization as important control on preferential subsurface flow. Each experiment covered a part of the conceptualized flow path from hillslopes to the stream: soil profile, hillslope, riparian zone, and stream.
For each study site, the most characteristic structures of the investigated domain and scale, such as slope deposits and peat layers were identified based on preliminary or previous investigations or literature reviews. Additionally, further structural data was collected and topographical analyses were carried out. Flow processes were observed either based on response observations (soil moisture changes or discharge patterns) or direct measurement (advective heat transport). Based on these data, the flow-relevance of the characteristic structures was evaluated, especially with regard to hillslope to stream connectivity.
Results of the four studies revealed a clear relationship between characteristic spatial structures and the hydrological behavior of the catchment. Especially the spatial distribution of structures throughout the study domain and their interconnectedness were crucial for the establishment of preferential flow paths and their relevance for large-scale processes. Plot and hillslope-scale irrigation experiments showed that the macropores of a heterogeneous, skeletal soil enabled preferential flow paths at the scale of centimeters through the otherwise unsaturated soil. These flow paths connected throughout the soil column and across the hillslope and facilitated substantial amounts of vertical and lateral flow through periglacial slope deposits.
In the riparian zone of the same headwater catchment, the connectivity between hillslopes and stream was controlled by topography and the dualism between characteristic subsurface structures and the geomorphological heterogeneity of the stream channel. At the small scale (1 m to 10 m) highest gains always occurred at steps along the longitudinal streambed profile, which also controlled discharge patterns at the large scale (100 m) during base flow conditions (number of steps per section). During medium and high flow conditions, however, the impact of topography and parafluvial flow through riparian zone structures prevailed and dominated the large-scale response patterns.
In the streambed of a lowland river, low permeability peat layers affected the connectivity between surface water and groundwater, but also between surface water and the hyporheic zone. The crucial factor was not the permeability of the streambed itself, but rather the spatial arrangement of flow-impeding peat layers, causing increased vertical flow through narrow “windows” in contrast to predominantly lateral flow in extended areas of high hydraulic conductivity sediments.
These results show that the spatial organization of structures was an important control for hydrological processes at all scales and study areas. In a final step, the observations from different scales and catchment elements were put in relation and compared. The main focus was on the theoretical analysis of the scale hierarchies of structures and processes and the direction of causal dependencies in this context. Based on the resulting hierarchical structure, a conceptual framework was developed which is capable of representing the system’s complexity while allowing for adequate simplifications.
The resulting concept of the parabolic scale series is based on the insight that flow processes in the terrestrial part of the catchment (soil and hillslopes) converge. This means that small-scale processes assemble and form large-scale processes and responses. Processes in the riparian zone and the streambed, however, are not well represented by the idea of convergence. Here, the large-scale catchment signal arrives and is modified by structures in the riparian zone, stream morphology, and the small-scale interactions between surface water and groundwater. Flow paths diverge and processes can better be represented by proceeding from large scales to smaller ones. The catchment-scale representation of processes and structures is thus the conceptual link between terrestrial hillslope processes and processes in the riparian corridor.
Anton Schindling (1947–2020)
(2020)
Thermoresponsive Zellkultursubstrate für zeitlich-räumlich gesteuertes Auswachsen neuronaler Zellen
(2019)
Ein wichtiges Ziel der Neurowissenschaften ist das Verständnis der komplexen und zugleich faszinierenden, hochgeordneten Vernetzung der Neurone im Gehirn, welche neuronalen Prozessen, wie zum Beispiel dem Wahrnehmen oder Lernen wie auch Neuropathologien zu Grunde liegt. Für verbesserte neuronale Zellkulturmodelle zur detaillierten Untersuchung dieser Prozesse ist daher die Rekonstruktion von geordneten neuronalen Verbindungen dringend erforderlich. Mit Oberflächenstrukturen aus zellattraktiven und zellabweisenden Beschichtungen können neuronale Zellen und ihre Neuriten in vitro strukturiert werden. Zur Kontrolle der neuronalen Verbindungsrichtung muss das Auswachsen der Axone zu benachbarten Zellen dynamisch gesteuert werden, zum Beispiel über eine veränderliche Zugänglichkeit der Oberfläche.
In dieser Arbeit wurde untersucht, ob mit thermoresponsiven Polymeren (TRP) beschichtete Zellkultursubstrate für eine dynamische Kontrolle des Auswachsens neuronaler Zellen geeignet sind. TRP können über die Temperatur von einem zellabweisenden in einen zellattraktiven Zustand geschaltet werden, womit die Zugänglichkeit der Oberfläche für Zellen dynamisch gesteuert werden kann. Die TRP-Beschichtung wurde mikrostrukturiert, um einzelne oder wenige neuronale Zellen zunächst auf der Oberfläche anzuordnen und das Auswachsen der Zellen und Neuriten über definierte TRP-Bereiche in Abhängigkeit der Temperatur zeitlich und räumlich zu kontrollieren. Das Protokoll wurde mit der neuronalen Zelllinie SH-SY5Y etabliert und auf humane induzierte Neurone übertragen. Die Anordnung der Zellen konnte bei Kultivierung im zellabweisenden Zustand des TRPs für bis zu 7 Tage aufrecht erhalten werden. Durch Schalten des TRPs in den zellattraktiven Zustand konnte das Auswachsen der Neuriten und Zellen zeitlich und räumlich induziert werden. Immunozytochemische Färbungen und Patch-Clamp-Ableitungen der Neurone demonstrierten die einfache Anwendbarkeit und Zellkompatibilität der TRP-Substrate.
Eine präzisere räumliche Kontrolle des Auswachsens der Zellen sollte durch lokales Schalten der TRP-Beschichtung erreicht werden. Dafür wurden Mikroheizchips mit Mikroelektroden zur lokalen Jouleschen Erwärmung der Substratoberfläche entwickelt. Zur Evaluierung der generierten Temperaturprofile wurde eine Temperaturmessmethode entwickelt und die erhobenen Messwerte mit numerisch simulierten Werten abgeglichen. Die Temperaturmessmethode basiert auf einfach zu applizierenden Sol-Gel-Schichten, die den temperatursensitiven Fluoreszenzfarbstoff Rhodamin B enthalten. Sie ermöglicht oberflächennahe Temperaturmessungen in trockener und wässriger Umgebung mit hoher Orts- und Temperaturauflösung. Numerische Simulationen der Temperaturprofile korrelierten gut mit den experimentellen Daten. Auf dieser Basis konnten Geometrie und Material der Mikroelektroden hinsichtlich einer lokal stark begrenzten Temperierung optimiert werden. Ferner wurden für die Kultvierung der Zellen auf den Mikroheizchips eine Zellkulturkammer und Kontaktboard für die elektrische Kontaktierung der Mikroelektroden geschaffen.
Die vorgestellten Ergebnisse demonstrieren erstmalig das enorme Potential thermoresponsiver Zellkultursubstrate für die zeitlich und räumlich gesteuerte Formation geordneter neuronaler Verbindungen in vitro. Zukünftig könnte dies detaillierte Studien zur neuronalen Informationsverarbeitung oder zu Neuropathologien an relevanten, humanen Zellmodellen ermöglichen.
Digitale Logopädie
(2021)
Emotions are a complex concept and they are present in our everyday life. Persons on the autism spectrum are said to have difficulties in social interactions, showing deficits in emotion recognition in comparison to neurotypically developed persons. But social-emotional skills are believed to be positively augmented by training. A new adaptive social cognition training tool “E.V.A.” is introduced which teaches emotion recognition from face, voice and body language. One cross-sectional and one longitudinal study with adult neurotypical and autistic participants were conducted. The aim of the cross-sectional study was to characterize the two groups and see if differences in their social-emotional skills exist. The longitudinal study, on the other hand, aimed for detecting possible training effects following training with the new training tool. In addition, in both studies usability assessments were conducted to investigate the perceived usability of the new tool for neurotypical as well as autistic participants. Differences were found between autistic and neurotypical participants in their social-emotional and emotion recognition abilities. Training effects for neurotypical participants in an emotion recognition task were found after two weeks of home training. Similar perceived usability was found for the neurotypical and autistic participants. The current findings suggest that persons with ASC do not have a general deficit in emotion recognition, but are in need for more time to correctly recognize emotions. In addition, findings suggest that training emotion recognition abilities is possible. Further studies are needed to verify if the training effects found for neurotypical participants also manifest in a larger ASC sample.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Sustainable urban growth
(2022)
This dissertation explores the determinants for sustainable and socially optimalgrowth in a city. Two general equilibrium models establish the base for this evaluation, each adding its puzzle piece to the urban sustainability discourse and examining the role of non-market-based and market-based policies for balanced growth and welfare improvements in different theory settings. Sustainable urban growth either calls for policy actions or a green energy transition. Further, R&D market failures can pose severe challenges to the sustainability of urban growth and the social optimality of decentralized allocation decisions. Still, a careful (holistic) combination of policy instruments can achieve sustainable growth and even be first best.
In the frame of a world fighting a dramatic global warming caused by human-related activities, research towards the development of renewable energies plays a crucial role. Solar energy is one of the most important clean energy sources and its role in the satisfaction of the global energy demand is set to increase. In this context, a particular class of materials captured the attention of the scientific community for its attractive properties: halide perovskites. Devices with perovskite as light-absorber saw an impressive development within the last decade, reaching nowadays efficiencies comparable to mature photovoltaic technologies like silicon solar cells. Yet, there are still several roadblocks to overcome before a wide-spread commercialization of this kind of devices is enabled. One of the critical points lies at the interfaces: perovskite solar cells (PSCs) are made of several layers with different chemical and physical features. In order for the device to function properly, these properties have to be well-matched.
This dissertation deals with some of the challenges related to interfaces in PSCs, with a focus on the interface between the perovskite material itself and the subsequent charge transport layer. In particular, molecular assemblies with specific properties are deposited on the perovskite surface to functionalize it. The functionalization results in energy level alignment adjustment, interfacial losses reduction, and stability improvement.
First, a strategy to tune the perovskite’s energy levels is introduced: self-assembled monolayers of dipolar molecules are used to functionalize the surface, obtaining simultaneously a shift in the vacuum level position and a saturation of the dangling bonds at the surface. A shift in the vacuum level corresponds to an equal change in work function, ionization energy, and electron affinity. The direction of the shift depends on the direction of the collective interfacial dipole. The magnitude of the shift can be tailored by controlling the deposition parameters, such as the concentration of the solution used for the deposition. The shift for different molecules is characterized by several non-invasive techniques, including in particular Kelvin probe. Overall, it is shown that it is possible to shift the perovskite energy levels in both directions by several hundreds of meV. Moreover, interesting insights on the molecules deposition dynamics are revealed.
Secondly, the application of this strategy in perovskite solar cells is explored. Devices with different perovskite compositions (“triple cation perovskite” and MAPbBr3) are prepared. The two resulting model systems present different energetic offsets at the perovskite/hole-transport layer interface. Upon tailored perovskite surface functionalization, the devices show a stabilized open circuit voltage (Voc) enhancement of approximately 60 meV on average for devices with MAPbBr3, while the impact is limited on triple-cation solar cells. This suggests that the proposed energy level tuning method is valid, but its effectiveness depends on factors such as the significance of the energetic offset compared to the other losses in the devices.
Finally, the above presented method is further developed by incorporating the ability to interact with the perovskite surface directly into a novel hole-transport material (HTM), named PFI. The HTM can anchor to the perovskite halide ions via halogen bonding (XB). Its behaviour is compared to that of another HTM (PF) with same chemical structure and properties, except for the ability of forming XB. The interaction of perovskite with PFI and PF is characterized through UV-Vis, atomic force microscopy and Kelvin probe measurements combined with simulations. Compared to PF, PFI exhibits enhanced resilience against solvent exposure and improved energy level alignment with the perovskite layer. As a consequence, devices comprising PFI show enhanced Voc and operational stability during maximum-power-point tracking, in addition to hysteresis reduction. XB promotes the formation of a high-quality interface by anchoring to the halide ions and forming a stable and ordered interfacial layer, showing to be a particularly interesting candidate for the development of tailored charge transport materials in PSCs.
Overall, the results exposed in this dissertation introduce and discuss a versatile tool to functionalize the perovskite surface and tune its energy levels. The application of this method in devices is explored and insights on its challenges and advantages are given. Within this frame, the results shed light on XB as ideal interaction for enhancing stability and efficiency in perovskite-based devices.
Two-photon polymerization of hydrogels – versatile solutions to fabricate well-defined 3D structures
(2014)
Hydrogels are cross-linked water-containing polymer networks that are formed by physical, ionic or covalent interactions. In recent years, they have attracted significant attention because of their unique physical properties, which make them promising materials for numerous applications in food and cosmetic processing, as well as in drug delivery and tissue engineering. Hydrogels are highly water-swellable materials, which can considerably increase in volume without losing cohesion, are biocompatible and possess excellent tissue-like physical properties, which can mimic in vivo conditions. When combined with highly precise manufacturing technologies, such as two-photon polymerization (2PP), well-defined three-dimensional structures can be obtained. These structures can become scaffolds for selective cell-entrapping, cell/drug delivery, sensing and prosthetic implants in regenerative medicine. 2PP has been distinguished from other rapid prototyping methods because it is a non-invasive and efficient approach for hydrogel cross-linking. This review discusses the 2PP-based fabrication of 3D hydrogel structures and their potential applications in biotechnology. A brief overview regarding the 2PP methodology and hydrogel properties relevant to biomedical applications is given together with a review of the most important recent achievements in the field.