Abstract: Based on extensive field information, farmer-led small-scale irrigation systems along the dam-regulated Tekeze River is investigated and the likelihood of future irrigation expansion within the area with modelled potential is discussed, considering facilitating and hampering factors. Due to dam-induced hydrologic alterations, downstream socio-ecological systems have strongly transformed as the irrigated area has quadrupled and the post-dam potential for perennial crop cultivation has attracted numerous migrant investors to the area, inducing inequalities but also providing opportunities. Future dam construction should involve tailored policy interventions to facilitate irrigation expansion, while safeguarding equal and sustainable access to water and land.

Abstract: Biobased chemistry has gained interest and has the potential to tackle some of the sustainability challenges the chemical industry must endure. Sustainability impacts need to be evaluated and monitored to highlight the advantages and pitfalls of different biobased routes over the product life cycle. A better understanding of the potential sustainability of emerging biobased technologies and products is essential to guide additional research and further technology development. This PhD thesis aims to develop a framework for a techno-sustainability assessment (TSA), while accounting for technological as well as economic, environmental, and social aspects in an integrated approach. First, a review of the state-of-the-art sustainability indicators for biobased chemicals was conducted and a gap analysis was performed to identify indicator development needs. Afterwards, a Delphi study was performed to select sustainability indicators specifically for biobased chemical assessment and to reach consensus among experts on a prioritization of these indicators. Next, the selected sustainability indicators were quantified while integrating technological and country-specific data with environmental characterization factors, economic values and social data. Finally, a stochastic, hierarchical multi-criteria decision analysis (MCDA) integrates the independent techno-sustainability indicators expressed in different units, taking into account stochastic and flexible method options. The developed integrated TSA framework was applied to a case for which a production and harvesting plant of microalgae-based food colorants is assessed. The final aim of the integrated TSA is to compare the potential sustainability performance of different scenarios and to make better-informed choices between alternatives by evaluating environmental, economic and social sustainability impacts in one holistic model. Integrated TSA offers a novel framework where decision makers can assess sustainability already in early technology development stages by identifying potential hurdles and opportunities to guide R&D and make sustainable investment decisions.

Abstract: Although traditional ferroelectric materials are usually dielectric and nonconductive, GeTe is a typical ferroelectric semiconductor, possessing both ferroelectric and semiconducting properties. GeTe is also a widely studied thermoelectric material, whose performance has been optimized by doping with various elements. However, the impact of the ferroelectric domains on the thermoelectric properties remains unclear due to the difficulty to directly observe the ferroelectric domains and their evolutions under actual working conditions where the material is exposed to high temperatures and electric currents. Herein, based on in-situ investigations of the ferroelectric domains and domain walls in both pure and Sb-doped GeTe crystals, we have been able to analyze the dynamic evolution of the ferroelectric domains and domain walls, exposed to an electric field and temperature. Local structural heterogeneities and nano-sized ferroelectric domains are generated due to the interplay of the Sb3+ dopant and the Ge-vacancies, leading to the increased number of charged domain walls and a much improved thermoelectric performance. This work reveals the fundamental mechanism of ferroelectric thermoelectrics and provides insights into the decoupling of previously interdependent properties such as thermo-power and electrical conductivity.

Abstract: Road traffic is the most widespread environmental noise source in Europe, proven to affect human health and well-being adversely. Noise barriers can be a very effective way to objectively reduce the noise levels to which the population is exposed, leading to positive effects on noise perception and quality of life. In this paper, surveys were used to assess subjective noise level indicators (annoyance and quality of life) from residents of the vicinity of a highway where obsolete noise barriers were to be replaced. %HA before the barrier replacement was measured from the surveys (26.8%) and estimated based on the acoustic simulation and two existing exposure/response relationships (14.6 and 18.8% before and 13.6 and 8.3% after). The difference in the measured %HA to those calculated from the ERRs shows that those models might not estimate %HA fairly for small samples or particular situations where high Lden is reported. Noise annoyance correlated differently with the quality of life indicators: a weak link was observed with health problems, while a strong correlation was found with the comfort level to perform activities outdoors. Objective noise measurements gave LA,eq,(15 min.) reductions of 4.1dB(A) due to the new barrier, while in acoustics models, calculated as Lday, expected this reduction to be 5.2 dB(A). After replacing the noise barriers, a second survey could still not be distributed due to the unknown effect of the COVID-19 measures that are still active

Abstract: A multiscale modeling and simulation approach, including first-principles calculations, ab initio molecular dynamics simulations, and a tight binding approach, is employed to study band flattening of the electronic band structure of oxidized monolayer graphene. The width offlat bands can be tuned by strain, the external electric field, and the density of functional groups and their distribution. A transition to a conducting state is found for monolayer graphene with impurities when it is subjected to an electric field of similar to 1.0 V/angstrom. Several parallel impurity-induced flat bands appear in the low-energy spectrum of monolayer graphene when the number of epoxy groups is changed. The width of the flat band decreases with an increase in tensile strain but is independent of the electric field strength. Here an alternative and easy route for obtaining band flattening in thermodynamically stable functionalized monolayer graphene is introduced. Our work discloses a new avenue for research on band flattening in monolayer graphene.

Abstract: Intending to tackle road traffic noise in urban environments, noise barriers have been proven to effectively reduce environmental noise levels, leading to positive effects on noise perception by the exposed population. This work assesses the impacts of replacing an obsolete noise barrier in a site near a highway. The effects of this change were monitored via a combination of field surveys, acoustic measurements and noise maps. The results have shown that even though the barrier replacement led to a 4.1 dB reduction in the LA,eq,(15 min.), the annoyance levels of the respondents increased. Possibly, the expectations regarding the improvement of the noise barrier were not met, after a history of complaints. Additionally, existing exposure-response relationships were not successful in predicting the annoyance levels in this particular case. In this dataset, noise annoyance presented a weak link with reported health problems, while a strong correlation was found with the comfort level to perform activities outdoors. Questions regarding the COVID-19 pandemic showed that even though the respondents were spending more time at home, they were less annoyed due to road traffic noise in the period when circulation restrictions were in place.

Abstract: The precise control of skyrmionics and magnonics in magnetic materials is key to the development of novel spin-based technology and information transport applications. Essentially, the inherent stability of magnetic skyrmions (provided by their topological charge) together with their extremely small size (down to a few nanometers) and the ultralow threshold current necessary to move them in nanostructures are the main advantages of skyrmionics. Not least, magnonics offers lower power consumption compared to electronics and the excitation of high frequency (sub-100~nm wavelength) magnons makes it possible for the creation of nanometric devices for ultrafast information transport. Even though extensive research has been carried out in recent years, the precise manipulation of skyrmions and spin waves (magnons) in nanostructures is not fully mastered and needs to be addressed before making functional skyrmionic and magnonic devices. In this thesis, we reveal multiple alternatives for the manipulation of skyrmions and spin-waves in different materials, such as bulk chiral magnets, heterochiral structures, magnet-supperconductor hybrids and two-dimentional magnetic materials. We make use of a multiscale model to numerically simulate the magnetic states at each considered material, from micromagnetic to atomistic control. We first explore the different nucleation mechanisms, activation energy, and the time evolution of the skyrmion formation in chiral magnetic films, crucial for the realization of skyrmion-based devices. We show that the skyrmion lattice is formed from the conical phase progressively, most probably by the formation of chiral bobbres, followed by the cylindrical growth of individual skyrmions from the film surface. That reflects a rod-like (one-dimensional) nucleation of the skyrmion phase, with an activation barrier of several electronvolts per skyrmion for the case of MnSi (Manganese monosilicide). In addition, we reveal the interesting blinking (creation-annihilation) behavior of skyrmions close to the phase boundary between the conical and skyrmion phases, where we recall that such switching between topologically distinct states has been proposed as a bit operation for information storage. Next, we discuss the motion of ferromagnetic and antiferromagnetic skyrmions in heterochiral magnets. We report the characteristic deflection of ferromagnetic skyrmions when moving across a heterochiral interface, where the extent of such deflection is tuned by the applied spin-polarized current and the magnitude of Dzyaloshinskii-Moriya interaction. Following, we show that the antiferromagnetic skyrmion achieves much higher velocities than its ferromagnetic counterpart, yet experiences far stronger confinement in nanoengineered heterochiral tracks, which reinforces antiferromagnetic skyrmions as a favorable choice for skyrmion-based devices. After that, we study the interesting coupling of magnetic skyrmions and superconducting vortices in magnet-superconductor heterostructures. We perform numerical simulations, based on experimental observations, to demonstrate that the stray field of magnetic skyrmions can nucleate antivortices in an adjacent superconducting film, giving rise to a hybrid topological object, the skyrmion-vortex pair, which harbor promising features for skyrmionics and quantum computing applications. We then explore the manipulation of a single skyrmion-vortex pair when currents are applied into both superconducting and magnetic parts of the heterostructure, which is of importance for the facilitated skyrmion guidance in racetrack applications. Afterwards, we make use of the high tunability of magnetic parameters in two-dimensional magnetic materials to reveal the rich phase diagram of exotic magnetic configurations in magnetic monolayers with suppressed nearest-neighbour exchange, where we show that several unique cycloidal, checkerboard, row-wise and spin-ice states are stabilized by the competition between the second-nearest-neighbor exchange, Dzyaloshinskii-Moriya, and dipolar interactions. Additionally, we show the coexistence of ferromagnetic and antiferromagnetic spin-cycloids, as well as novel types of skyrmions and chiral domain walls. Finally, in the last part of the thesis, we present the spin wave properties in the two-dimensional magnetic materials CrBr$3$ and CrI$3$. Using spin-dynamics simulations parametrized from first principles, we reveal that the spin wave dispersion in such materials can be tuned in a broad range of frequencies by strain-engineering, and that a designed pattern of strain, as well as structural defects (halide vacancies) can be turned useful in the design of spin-wave guides. Lastly, we discuss the realization of magnonic crystals by moiré-periodic modulation of magnetic parameters in van der Waals heterostructures, where we show that the several nanometer small periodicities in such samples are ideal for the interference of terahertz spin waves. Recalling the wide range of possibilities for manipulating spin waves in such two-dimensional materials, we therefore suggest these systems as a front-runner for prospective terahertz magnonic applications.

Abstract: In this thesis, a first-principles research to tune the physical properties of group III-V materials in the thinnest limit is carried out. Among the different methods to tune the mechanical, electronic and magnetic properties of these graphene related materials, we use: two-dimensional (2D) multilayers, straintronics, hydrogen functionalization, and transition metal adsorption. The first part of this research is devoted to a complete characterization of the structural, electronic, mechanical and vibrational properties of 2D group III-As monolayers, obtained from density functional theory. Our findings are used to understand the contribution of the

Abstract: Melanoma remains a deadly cancer despite significant advances in immune checkpoint blockade and targeted therapies. The incidence of melanoma is also growing worldwide, which highlights the need for novel treatment options and strategic combination of therapies. Here, we investigate non-thermal plasma (NTP), an ionized gas, as a promising, therapeutic option. In a melanoma mouse model, direct treatment of tumors with NTP results in reduced tumor burden and prolonged survival. Physical characterization of NTP treatment in situ reveals the deposited NTP energy and temperature associated with therapy response, and whole transcriptome analysis of the tumor identified several modulated pathways. NTP treatment also enhances the cancer-immunity cycle, as immune cells in both the tumor and tumor-draining lymph nodes appear more stimulated to perform their anti-cancer functions. Thus, our data suggest that local NTP therapy stimulates systemic, anti-cancer immunity. We discuss, in detail, how these fundamental insights will help direct the translation of NTP technology into the clinic and inform rational combination strategies to address the challenges in melanoma therapy.

Abstract: Tin-based perovskites are promising alternative absorber materials for leadfree perovskite solar cells but need strategies to avoid fast tin (Sn) oxidation. Generally, this reaction can be slowed down by the addition of tin fluoride (SnF2) to the perovskite precursor solution, which also improves the perovskite layer morphology. Here, this work analyzes the spatial distribution of the additive within formamidinium tin triiodide (FASnI(3)) films deposited on top of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) hole transporting layers. Employing time-of-flight secondary ion mass spectrometry and a combination of hard and soft X-ray photoelectron spectroscopy, it is found that Sn F2 preferably accumulates at the PEDOT:PSS/perovskite interface, accompanied by the formation of an ultrathin SnS interlayer with an effective thickness of approximate to 1.2 nm.

Abstract: Plasma catalysis is gaining increasing interest for various applications, but the underlying mechanisms are still far from understood. Hence, more fundamental research is needed to understand these mechanisms. This can be obtained by both modelling and experiments. This foundations paper describes the fundamental insights in plasma catalysis, as well as efforts to gain more insights by modelling and experiments. Furthermore, it discusses the state-of-the-art of the major plasma catalysis applications, as well as successes and challenges of technology transfer of these applications.

Abstract: Although recent studies have advanced the understanding of pyrolyzed
Fe−N−C materials as oxygen reduction reaction (ORR) catalysts, the atomic and
electronic structures of the active sites and their detailed reaction mechanisms still remain unknown. Here, based on first-principles density functional theory (DFT) computations, we discuss the electronic structures of three FeN4 catalytic centers with different local topologies of the surrounding C atoms with a focus on unraveling the mechanism of their ORR activity in acidic electrolytes. Our study brings back a forgotten, synthesized pyridinic Fe−N coordinate to the community’s attention, demonstrating that this catalyst can exhibit excellent activity for promoting direct four-electron ORR through the addition of a fifth ligand such as −NH2, −OH, and −SO4. We also identify sites with good stability properties through the combined use of our DFT calculations and Mössbauer spectroscopy data.

Abstract: Structural analysis of metal clusters confined in nanoporous materials is typically performed by X-ray-driven techniques. Although X-ray analysis has proved its strength in the characterization of metal clusters, it provides averaged structural information. Therefore, we here present an alternative workflow for bringing the characterization of confined metal clusters towards the local scale. This workflow is based on the combination of aberration-corrected transmission electron microscopy (TEM), TEM image simulations, and powder X-ray diffraction (XRD) with advanced statistical techniques. In this manner, we were able to characterize the clustering of Pb atoms in Linde Type A (LTA) zeolites with Pb loadings as low as 5 wt%. Moreover, individual Pb clusters could be directly detected. The proposed methodology thus enables a local-scale characterization of confined metal clusters in zeolites. This is important for further elucidation of the connection between the structure and the physicochemical properties of such systems.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.