Abstract: Generalized Möbius-Listing surfaces and bodies generalize Möbius bands, and this research was motivated originally by solutions of boundary value problems. Analogous to cutting of the original Möbius band, for this class of surfaces and bodies, results have been obtained when cutting such bodies or surfaces. In general, cutting leads to interlinked and intertwined different surfaces or bodies, resulting in very complex systems. However, under certain conditions, the result of cutting can be a single surface or body, which reduces complexity considerably. These conditions are based on congruence and rotational symmetry of the resulting cross sections after cutting, and on the knife cutting the origin

Abstract: Carbon dioxide electrochemical reduction (CO2ER) has attracted considerable attention as a technology to recycle CO2 into raw materials for chemicals using renewable energies. We recently found that Zn-Al layered double hydroxides (Zn-Al LDH) have the CO-forming CO2ER activity. However, the activity was only evaluated by using the liquid-phase CO2ER. In this study, Ni-Al and Ni-Fe LDHs as well as Zn-Al LDH were synthesized using a facile coprecipitation process and the gas-phase CO2ER with the LDH-loaded gas-diffusion electrode (GDE) was examined. The products were characterized by XRD, STEM-EDX, BF-TEM and ATR-IR spectroscopy. In the ATR-IR results, the interaction of CO2 with Zn-Al LDH showed a different carbonates evolution with respect to other LDHs, suggesting a different electrocatalytic activity. The LDH-loaded GDE was prepared by simple drop-casting of a catalyst ink onto carbon paper. For gas-phase CO2ER, only Zn-Al LDH exhibited the CO2ER activity for carbon monoxide (CO) formation. By using different potassium salt electrolytes affording neutral to strongly basic conditions, such as KCl, KHCO3 and KOH, the gas-phase CO2ER with Zn-Al LDH-loaded GDE showed 1.3 to 2.1 times higher partial current density for CO formation than the liquid-phase CO2ER.

Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

Abstract: The foodborne pathogens and microorganisms have played a prevalent role in the ebb and flow of the economy worldwide. The increasing population has strained the food processing industry to produce food in large quantity, which in turn has affected the quality of food. To curb this issue, there is immense pressure to produce and maintain quality food within a short time frame. Hence, high throughput technology is used to determine and timely assess the safety and hygiene of food. Further, the revolution of the food industry has also seen an upsurge of new pathogens and microorganisms, thereby increasing the risk of exposure towards rarest diseases to a larger population. This chapter sheds light on the different types of foodborne pathogens affecting the food industry and its social impact. It further emphasizes the safety measures to be taken on the prevention of the disease from the farm to the processing industries and in turn to the household.

Abstract: Climate change is an ever-increasing threat to our planet, with the urbanisation of previously open spaces exacerbating the issue. The loss of open space leads to a decrease in ecosystem services, which negatively impacts the liveability in urbanised environments, and beyond. The incorporation of green infrastructure (GI) into the built environment is acknowledged as an effective and multi-functional measure to make our living environment resilient and future-proof. Notwithstanding that the local level is essential for effective GI implementation, research into local decision making is very limited. This thesis therefore aims to address two significant gaps in the implementation of GI. The first objective is to bridge the science-policy gap by integrating scientific knowledge on ES and GI into local decision-making processes. In this context, the policy dimension within this thesis involves the process of translating overarching policy objectives into practical actions within local decision-making practices, abstracting from the intricacies of higher-level policymaking itself. The second objective focuses on the people-policy gap, which involves understanding stakeholders' perspectives and priorities regarding GI and its associated ecosystem services. Through stated preference valuation techniques (discrete choice experiments and a best-worst scaling experiment), multi-stakeholder GI perceptions are gathered. Finally, a novel tool to GI valuation is developed, acknowledging the different stakeholder views and building on the insights of collaborative tool development and design. By gaining insights into the demand, prioritisation, and provision of GI from the two most important stakeholder groups at the local level (residents and local decision-makers), this research aims to foster effective communication and alignment between public preferences and policy implementation. Ultimately, addressing these gaps will contribute to more informed planning and decision-making practices related to green infrastructure. The overall goal of this thesis is to enhance the uptake of GI knowledge in the local decision-making context, proposing pathways to facilitate and optimise investments in public GI.

Abstract: It is standard practice in virtual reality applications to synthesize binaural audio based on a discrete set of directionally-dependent head-related impulse responses (HRIRs). This set of HRIRs is often time-aligned in a pre-processing step, to allow for high-fidelity interpolation between HRIRs corresponding with neighbouring directions. The fidelity of this operation depends on the similarity of neighbouring aligned HRIRs. The pairwise quality of similarity makes it a difficult criterion to optimize globally and consequently one often resorts to alignment methods based on a specific feature that can be extracted for each HRIR separately, e.g., the first-onset of the peak or the group delay. However, such proxies for similarity are very sensitive to noise and therefore require a high signal-to-noise ratio, which makes them less suitable for processing HRIRs acquired outside an anechoic room. In this paper, we advance a novel alignment method, which maximizes the similarity – defined as the correlation between the full-length HRIRs – between neighbouring aligned HRIRs for all directions at once. We show that this correlation-based alignment procedure outperforms the first-onset alignment with regards to the fidelity of the spherical harmonics representation of both the spectral and interaural time difference (ITD) information, when tested on the KEMAR HRIR and six human HRIRs. Finally, we show that the correlation-based alignment is more robust to noise.

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: Grafting organophosphonic acids modification (PAs) on metal oxides has shown to be a flexible technology to tune the surface properties of metal oxides for various applications. Nevertheless, there are still puzzles that need to be addressed, such as the correlations between metal oxides properties (types of surface reactive sites) and the modification (modification degree), the correlations between metal oxides properties and the properties of modified surfaces. Moreover, the currently used liquid-phase method for the grafting has associated impeding effects of solvent on tailoring the modification degrees, and also causes the formation of metal phosphonate side products. The solid-phase method can induce the unwanted changes in crystal phase of supports. Based on these questions, the three titania supports with divergent surface properties were selected as the metal oxides supports investigated, propylphosphonic acid (3PA) modification was carried out under the same synthesis conditions: four different concentrations, two solvents (water or toluene), and one reaction time (4 h) and temperature (90 ). MeOH chemisorption was introduced to probe the surface (un)reactive sites for 3PA modification. On the other hand, MeOH chemisorption and inverse gas chromatography (IGC) were combined to characterize the changes in surface polarity and acidic properties induced by the modification. Next, a solid-phase method, manual grinding, was proposed to graft 3PA on titania, avoiding the impeding effects of solvent on improving modification degree and the formation of the titania phosphonate side products, as well as preserving the crystal phase. The results indicate that methanol chemisorption can qualitatively analyze the surface active sites that are consumed by 3PA modification, its chemisorption capacity shows the consistent trend with the maximum modification degree, hereby revealing the kinds of interactions that are important in controlling surface coverage. Titania supports is found to play an important role in changes in surface polarity and acidic properties by charactering the three modified titania samples at a similar modification degree using the methanol chemisorption coupled with in-situ infrared and thermogravimetric-mass spectrometer, and the IGC. Moreover, IGC provides additional information about the changes in binding modes. Furthermore, grafting 3PA modification on titania was achieved by manual grinding. Compared to the liquid-phase method, the maximum modification degree obtained by the manual grinding is 25 % higher while using 83.3 % or 75.0% lower amounts of expensive 3PA and limiting the formation of titania phosphonate side products. Compared to the reactive milling method, the proposed manual grinding method preserves the crystal phase(s) of titania.

Abstract: Polarons are quasiparticles emerging in materials from the interaction of extra charge carriers with the surrounding atomic lattice. They appear in a wide va- riety of compounds and can have a profound impact on their properties, making the concept of a polaron a central and ubiquitous topic in material science. Al- though the concept is known for about 75 years, the origin of polarons is not yet fully elucidated. This thesis focuses on WO 3 as a well-known prototypical system for studying polarons, which inherent polaronic nature is linked to its remark- able electrical and chromic properties. The primary objective of this research is to provide a comprehensive atomistic description and understanding of polaron formation in WO 3 using first-principles density functional theory (DFT) calcula- tions. Additionally, the investigation explores the interactions between polarons and the possibility of bipolaron formation. Following a systematic strategy, we first extensively analyze the dielectric and lattice dynamical properties of WO 3 in both the room-temperature P 2 1 /n and ground-state P 2 1 /c phases. Our specific focus is on characterizing the zone-center phonons, which serve as the founda- tion for identifying the phonon modes involved in the polaron formation and charge localization process. Subsequently, we examine the impact of structural distortions on the electronic structure of WO 3 to elucidate the interplay between structural distortions and electronic properties, thereby laying the groundwork for understanding electron-phonon couplings. By incorporating these critical fac- tors, we address our primary research goals. The most common explanation for the polaron formation is associated with the electrostatic screening of the extra charge by the polarizable lattice. Here, we show that, even in ionic crystals, this is not necessarily the case. We demonstrate that polarons in this compound arise primarily from non-polar atomic distortions. We then unveil that this unexpected behavior originates from the undoing of distortive atomic motions, which lowers the bandgap. As such, we coin the name of anti-distortive polaron and validate its appearance through a simple quantum-dot model, in which charge localization is the result of balancing structural, electronic, and confinement energy costs. Then, we also study the polaron-polaron interaction and present the formation of the antiferromagnetic W 4+ bipolaronic state with relatively large formation energy. Our analysis of the W 4+ bipolaronic distortions on the global structure reveals the same behavior as in experiments where the highly distorted monoclinic phase transforms into a tetragonal phase as a function of doping. Additionally, leveraging our previous findings on asymmetric polaronic distortion and examin- ing different merging orientations, we stabilize the antiferromagnetic W 5+ -W 5+ bipolaronic state with an energy lower than the W 4+ state. This thesis clari- fies the formation of unusual medium-size 2D polarons and bipolarons in WO3,which might be relevant to the whole family of ABO 3 perovskites, to which WO 3 is closely related. The simplicity of the concept provides also obvious guidelines for tracking similar behavior in other families of compounds.

Abstract: Pretreatment is a critical step in the conversion of lignocellulose into biofuels and biochemicals. During pretreatment, the recalcitrance of lignocellulose is reduced, e.g. by removing lignin, thereby making the carbohydrates more accessible for enzymatic saccharification. Fungal delignification by white-rot fungi is a biotechnological alternative to chemical/physicochemical methods, which is carried out in solid-state fermentation with mild reaction conditions and without the formation of microbial inhibitors. However, fungal pretreatment presents some challenges, such as long pretreatment time, non-selective and low delignification, low enzymatic digestibility and feedstock sterilisation requirement, making its commercial implementation challenging compared to conventional methods. This study investigates the possibility of improving and characterising the solid-state fungal pretreatment of poplar wood by Phanerochaete chrysosporium. The individual and combined effects of MnSO4 and CuSO4 supplements on the delignification of sterilised wood are investigated using response surface methodology to improve the degree and selectivity of fungal delignification. Spore-inoculated solid-state fermentations are carried out for 4 weeks in sterile vented bottles. The mechanism of the concerted action of the metal ions on lignin degradation is then elucidated by relating fungal growth and ligninolytic enzyme activities to lignocellulose degradation as a function of pretreatment time. The optimised metal-supplemented system is then applied to the pretreatment of non-sterilised wood using different inoculation techniques (spores and pre-colonised substrate), nutrients (metal ions with or without glucose and sodium nitrate) and cultivation environments (sterile aerated bottles and open trays). The fermentations are then characterised using infrared spectroscopy, in particular NIR and ATR-FTIR spectroscopy, with the aim of developing rapid lignin quantification methods as an alternative to conventional wet chemical methods. Finally, the feasibility of producing fermentable sugars from sterilised and non-sterilised poplar wood using fungal pretreatment is evaluated through a techno-economic analysis. Supplementing the pretreatment system with 2.01 µmol CuSO4 and 0.77 µmol MnSO4 g-1 wood resulted in 1.9-fold higher lignin degradation, 2.3-fold higher delignification selectivity value and 2.9-fold higher glucose yield. The improved delignification could be explained by the concerted action of Mn2+ and Cu2+ ions, with Mn2+ ions inducing and Cu2+ prolonging manganese peroxidase production responsible for delignification. Fungal pretreatment at non-sterile conditions was obtained using trays in a simple solid-state fermentation set-up without sterile aeration. A 1:3 ratio of pre-colonised and untreated wood was applied for inoculation and only Cu2+, Mn2+ and sodium nitrate as supplements. Remarkably, this technology resulted in a comparably high glucose yield (28.51 ± 0.28%) to the traditional method using sterilised wood, sterile aeration and spores as inoculum, while reducing the amount of wood to be sterilised by 71.2%. Infrared spectroscopy-based methods with high coefficients of determination (R_CV

Abstract: Nitrogen (N) is an indispensable building block for all living organisms as well as for pharmaceutical and chemical industry. In a nutshell, N is needed for plants to grow and beings to live and nitrogen fixation (NF) is the process that makes N available for plants as food by converting N2 into a reactive form, such as ammonia (NH3) or nitrogen oxides (NOx), upon reacting with O2 and H2. The aim of this thesis is to elucidate (wet) plasma-based nitrogen fixation with a focus on (1) the role of pulsing in achieving low energy consumption, (2) the role of H2O as a hydrogen source in nitrogen fixation and (3) elucidation of nitrogen fixation pathways in humid air and humid N2 plasma in a combined experimental and computational study. Furthermore, this thesis aims to take into account the knowledge-gaps and challenges identified in the discussion of the state of the art. Specifically, (1) we put our focus on branching out to another way of introducing water into the plasma system, i.e. H2O vapor, (2) we de-couple the problem for pathway elucidation by starting with characterization of the chosen plasma, next a simpler gas mixture and building up from there, (3) we include modelling, though not under wet conditions and (4) we focus on also analyzing species and performance outside liquid H2O. Firstly, based on the reaction analysis of a validated quasi-1D model, we can conclude that pulsing is indeed the key factor for energy-efficient NOx- formation, due to the strong temperature drop it causes. Secondly, the thesis shows that added H2O vapor, and not liquid H2O, is the main source of H for NH3 generation. Related to this, we discuss how the selectivity of plasma-based NF in humid air and humid N2 can be controlled by changing the humidity in the feed gas. Interestingly, NH3 production can be achieved in both N2 and air plasmas using H2O as a H source. Lastly, we identified a significant loss mechanism for NH3 and HNO2 that occurs in systems where these species are synthesized simultaneously, i.e. downstream from the plasma, HNO2 reacts with NH3 to form NH4NO2, which decomposes into N2 and H2O. This reduces the effective NF when not properly addressed, and should therefore be considered in future works aimed at optimizing plasma-based NF. In conclusion, this thesis adds further to the current state of the art of plasma-based NF both in the presence of H2O and in dry systems.

Abstract: Nanoscience and nanotechnologies are of immense importance across many fields of science and for numerous practical applications. In this context, scanning transmission electron microscopy (STEM) and 4D-STEM are among the most powerful characterization methods at the atomic scale. Annular dark-field (ADF)-STEM can be used to quantify atomic structures in 3D by counting atoms based on a single projection image. In 4D-STEM a full diffraction pattern is recorded at each scan step, which enables more dose efficient imaging and the utilization of various advanced imaging modalities, which can however be complex and slow. Both, STEM and 4D-STEM suffer from noise and distortions. In the first section of this work the most important of these distortions are discussed and it is shown how image restoration with a dedicated convolutional neural network (CNN) can be beneficial for atomic structure quantifications in ADF-STEM. In the second part, a new 4D-STEM imaging method real-time-integrated-centre-of-mass (riCOM) is introduced, which is a very dose-efficient and fast algorithm that enables unprecedented live-imaging capabilities for 4D-STEM. It is based on the integrated centre-of-mass approach, but is reformulated with variable integration ranges and optional filters, which allows for a tunable contrast transfer function. This enables the imaging of light and heavy elements simultaneously at very low doses. In the third part another new 4D-STEM method, coined AIRPI (AI-assisted rapid phase imaging) is introduced, which uses a CNN to retrieve a patch of the specimen's phase image for each scan position, based on the diffraction patterns in the probe's immediate surroundings. This allows also live imaging in principle and surpasses comparable state-of-the-art algorithms in terms of resolution also at low doses. Different atomic columns can be reliably distinguished over a wide range of atomic numbers, enabling a very good image interpretability. Further, AIRPI can recover low frequency image components, which preserves thickness information. This is a unique and important feature which could make quantitative 4D-STEM feasible.