Abstract: We present a Ginzburg-Landau theory for a two-band superconductor with emphasis on MgB2. We propose experiments which lead to identification of the possible scenarios: whether both sigma- and pi-bands superconduct or sigma-alone. According to the second scenario a microscopic theory of superconducting MgB2 is proposed based on the strongly interacting or-electrons and non-correlated pi-electrons of boron ions. The kinematic and Coulomb interactions of sigma-electrons provide the superconducting state with an anisotropic gap of s(*)-wave symmetry. The critical temperature T-c has a non-monotonic dependence on the distance r between the centers of gravity of sigma- and pi-bands. The position of MgB2 on a bell-shaped curve T-c (r) is identified in the overdoped region. The derived superconducting density of electronic states is in agreement with available experimental and theoretical data. It is argued that the effects of pressure are crucial to identify the microscopic origin of superconductivity in MgB2. Possibilities for increase of T, are discussed.

Abstract: This thesis provides three potential ways to enhance the nitrogen removal efficiency of mainstream partial nitritation/anammox (PN/A), a key technology to enable energy-positive sewage treatment. In Chapter 1, the typical technologies to promote nitrogen removal efficiency are summarized. In Chapters 2 and 3, the concept ‘winter bioaugmentation with stored summer surplus sludge’ is proposed. Applying that, a cost-effective sludge preservation strategy is required. Preserving PN/A biomass without cooling and redox adjustment proved to be the cost-effective strategy. The reactivation of these stored sludges was also tested in low-temperature systems (15 and 10℃). Respectively 56% and 41% of granules activity compared to pre-storage activity (after Arrhenius-based temperature correction) could be recovered within a month (41% and 32% for flocs activity). In the end, the stored AnAOB bioaugmentation was successfully validated in the lab (20℃). In Chapter 4, a return-sludge nursery concept, applying the sidestream nitritation and blending the resulting effluent with mainstream effluent to achieve an intermediate temperature and nitrogen concentrations, is proposed. That led to a 33 – 36% increase in nitrogen removal efficiency. Arrhenius’ expectations (10 ℃ higher temperature, θ = 1.09) could only explain 49-51% of the activity increase in the nursery reactor, pointing to the role of other factors, e.g., the ~400% elevated electrical conductivity (15-16%), the 56-335% higher effluent nitrogen concentrations (12-14%), and the synergy and unknown factors (20-23%). Thus, the return-sludge biostimulation approach could also enhance nitrogen efficiency in the mainstream. In Chapter 5, the N2O emissions, linked to three typical nitrite-oxidizing bacteria (NOB) suppression strategies (low dissolved oxygen (DO) level, free ammonia (FA), and free nitrous acids (FNA) treatments) were tested in a biofilm system. A low emerged DO level (~0.60 mg O2 L-1) was effective to suppress NOB activity and decrease N2O emissions, but NOB adaptation gradually appeared after 200 days. Further NOB inhibition was successfully achieved by periodical (3 hours per week) FA (~30 mg NH3-N L-1) or FNA (~3 mg HNO2-N L-1) treatments. The FA treatment promoted N2O production, while the FNA treatment had no effect. Thus, PN/A systems should be operated at relatively low DO levels with periodical FNA treatment. In Chapter 6, the major findings proposed and the main conclusions drawn in this thesis are outlined. Beyond that, the possible design of a mainstream PN/A configuration that combined all described three technologies is demonstrated. Overall, the novel insights from this thesis potential to improve nitrogen removal efficiency in the mainstream.

Abstract: Irradiation assisted stress corrosion cracking (IASCC) is an intergranular cracking effect which can occur in heavily irradiated internal structural components of nuclear reactor cores. It is a complex phenomenon which is not yet fully understood because it occurs through an interplay of several material degradation processes. The factors that influence IASCC susceptibility include irradiation damage (neutrons and other irradiation particles stemming from the nuclear fission reaction), the operating temperature of the nuclear reactor, water corrosion, operating stresses, and the composition of materials susceptible to IASCC. Such materials are typically fabricated from austenitic stainless steels because of their relatively high strength, ductility, and fracture toughness. However, besides excellent metallurgical and corrosion resistant qualities, the operating conditions may still cause severe material degradation and component failure, which is extremely important for nuclear power plant safety and lifetime managements. Despite much accumulated data in the literature, both crack initiation and crack propagation mechanisms still need to be further elucidated. To that end, a probabilistic fracture model entitled the subcritical crack propagation (SCP) was recently developed, which assumes that the oxidized part of stainless steel in front of the crack plays an essential role in the crack initiation and crack propagation in sample failures. Still, despite a very good agreement with experimental observations, the SCP model but also other contemporary models favoured within the literature, require further experimental verification to what concerns the investigation of (IA)SCC. To that end, the main objective of this doctorate was to utilize experimental instrumentations like SEM, FIB-SEM and (S)TEM to conduct the investigation of the crack initiation and propagation processes in both tested and industrial specimens. Some of the investigated materials were retrieved within a nuclear reactor and are thus considered as unique test material to investigate the material degradation processes relevant for cracking. Other specimens were tailor-made to simulate the cracking processes of irradiated materials in otherwise un-irradiated materials. The newly acquired experimental results in this doctorate help rationalize existing models and methodologies used in the literature to analyse the IASCC failures of structural materials of reactor components. These results also facilitate in the development of predictive methodologies and mitigation strategies towards IASCC cracking and provide more information on IASCC from a microstructural perspective.

Abstract: Nanomaterialen kunnen uiterst interessante eigenschappen vertonen voor een verscheidenheid aan veelbelovende toepassingen, gaande van zonnecrème tot batterijen voor elektrische auto’s. Een nanometer is een miljard keer kleiner dan een meter. Op deze schaal kunnen de materiaaleigenschappen volledig verschillen van bulkmaterialen op grotere schaal. Bovendien hangen de eigenschappen van nanomaterialen sterk af van hun exacte grootte en vorm. Kleine verschillen in de posities van de atomen, in de grootte-orde van een picometer (nog eens duizend maal kleiner dan een nanometer), kunnen de fysische eigenschappen al drastisch beïnvloeden. Daarom is een betrouwbare kwantificering van de atomaire structuur van kritisch belang om de evolutie naar materiaalontwerp mogelijk te maken en inzicht te verwerven in de relatie tussen de fysische eigenschappen en de structuur van nanomaterialen. Daarnaast kan de atomaire structuur van nanomaterialen ook veranderen in de loop van de tijd ten gevolge van verschillende fysische processen. Het onderzoek dat in deze thesis gepresenteerd wordt, maakt het mogelijk om de dynamische structuurveranderingen van nanomaterialen betrouwbaar te kwantificeren op atomaire schaal door gebruik te maken van raster transmissie elektronenmicroscopie (STEM). Ik heb dit gerealiseerd door methodes te ontwikkelen waarmee ik het aantal atomen “achter elkaar” kan tellen in elke atoomkolom van een nanomateriaal, en dit op basis van beelden opgenomen met een elektronenmicroscoop. Een belangrijk verschil met telmethodes voor de analyse van een enkel beeld is het schatten van de kans dat een atoomkolom atomen zal verliezen of bijkrijgen van het ene naar het andere beeld in de tijdreeks. Deze kwantitatieve methode kan het ontrafelen van de tijdsafhankelijke structuur-eigenschappen relatie van een nanomateriaal mogelijk maken, wat uiteindelijk kan leiden tot efficiënter design en productie van nanomaterialen voor innovatieve toepassingen.

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.