Abstract: Using a particle based model, we investigate the skyrmion dynamical behavior in a channel where the upper wall contains divots of one depth and the lower wall contains divots of a different depth. Under an applied driving force, skyrmions in the channels move with a finite skyrmion Hall angle that deflects them toward the upper wall for -x direction driving and the lower wall for +x direction driving. When the upper divots have zero height, the skyrmions are deflected against the flat upper wall for -x direction driving and the skyrmion velocity depends linearly on the drive. For +x direction driving, the skyrmions are pushed against the lower divots and become trapped, giving reduced velocities and a nonlinear velocity-force response. When there are shallow divots on the upper wall and deep divots on the lower wall, skyrmions get trapped for both driving directions; however, due to the divot depth difference, skyrmions move more easily under -x direction driving, and become strongly trapped for +x direction driving. The preferred -x direction motion produces what we call a Magnus diode effect since it vanishes in the limit of zero Magnus force, unlike the diode effects observed for asymmetric sawtooth potentials. We show that the transport curves can exhibit a series of jumps or dips, negative differential conductivity, and reentrant pinning due to collective trapping events. We also discuss how our results relate to recent continuum modeling on a similar skyrmion diode system.

Abstract: The cation distribution of the negative temperature coefficient (NTC) thermistor spinel NiMn2O4 was studied in the temperature range from 55 to 900 degrees C, using a combined in situ neutron diffraction and thermopower study. Rietveld refinements of in situ neutron diffraction data reveal a temperature dependence of the degree of inversion with an inversion parameter of 0.70(1) at 900 degrees C and 0.87(1) at 55 degrees C. Thermopower measurements were evaluated using a modified Heikes formula, and the [Mn4+]/[Mn3+] ratio on octahedral sites of the spinel structure was calculated considering spin and orbital degeneracy. The inversion degree and disproportionation parameter, determined independently as function of temperature, were used to calculate the cation distribution of NiMn2O4 in the whole temperature range. At high temperature, within the stability range of the spinel, the cation distribution is characterized by a moderate degree of inversion with a concentration of NiB2+${\mathrm{Ni}}_\mathrm{B}<

Abstract: Graphene matter in a strong magnetic field, realizing one-dimensional quantum Hall channels, provides a unique platform for studying electron interference. Here, using the Landauer-Buttiker formalism along with the tightbinding model, we investigate the quantum Hall (QH) effects in unipolar and bipolar monolayer-bilayer graphene (MLG-BLG) junctions. We find that a Hall bar made of an armchair MLG-BLG junction in the bipolar regime results in valley-polarized edgechannel interferences and can operate a fully tunable Mach-Zehnder (MZ) interferometer device. Investigation of the bar-width and magnetic-field dependence of the conductance oscillations shows that the MZ interference in such structures can be drastically affected by the type of (zigzag) edge termination of the second layer in the BLG region [composed of vertical dimer or non-dimer atoms]. Our findings reveal that both interfaces exhibit a double set of Aharonov-Bohm interferences, with the one between two oppositely valley-polarized edge channels dominating and causing a large amplitude conductance oscillation ranging from 0 to 2e2/h. We explain and analyze our findings by analytically solving the Dirac-Weyl equation for a gated semi-infinite MLG-BLG junction.

Abstract: The COVID-19 pandemic had large repercussions for our economy and organizations. Improved resilience can give organizations the ability to withstand crises and build back better and faster. This article assesses resilience of organizations and sole proprietorships in the context of the COVID-19 pandemic with eight circular strategies as explanatory variables. Furthermore, these eight circular strategies are also used to assess the organizations' and sole proprietorships' resilience outside of the COVID-19 pandemic. This analysis is conducted to explain how circular strategies can help companies and sole proprietorships maintain stability. The analysis was performed by means of a survey conducted between May and June 2020 in Flanders (Belgium), using a sample of 542 respondents. After performing a regression analysis combined with expert opinions collected through interviews, we find that companies and sole proprietorships with a higher circularity score have a significantly higher resilience score during crises and during normal times, compared to less circular companies. Furthermore, we find that the size of the company does not matter during a crisis to adapt and react flexibly, while it is important when there is no crisis. Finally, we argue that it is the combination of different circular strategies which yields to the highest results for the organizations' resilience and we provide policy recommendations based on the most asked support measures.

Abstract: Purple non-sulfur bacteria (PNSB) show great potential for environmental and industrial biotechnology, producing microbial protein, biohydrogen, polyhydroxyalkanoates (PHAs), pigments, etc. When grown photoheterotrophically, the carbon source is typically more reduced than the PNSB biomass, which leads to a redox imbalance. To mitigate the excess of electrons, PNSB can exhibit several ‘electron sinking’ strategies, such as CO2 fixation, N2 fixation, and H2 and PHA production. The lack of a comprehensive (over)view of these redox strategies is hindering the implementation of PNSB for biotechnology applications. This review aims to present the state of the art of redox homeostasis in phototrophically grown PNSB, presenting known and theoretically expected strategies, and discussing them from stoichiometric, thermodynamic, metabolic, and economic points of view.

Abstract: With climate change still a pressing issue, there is a great need for carbon capture, utilisation and storage (CCUS)
methods. We propose a novel concept where CO2 conversion is accomplished by O2 splitting followed by the
addition of O atoms to CO2. The latter is studied here by means of kinetic modelling. In the first instance, we
study various CO2/O ratios, and we observe an optimal CO2 conversion of around 30–40% for 50% O addition.
Gas temperature also has a large influence, with a minimum temperature of around 1000 K to a maximum of
2000 K for optimal conversion. In the second instance, we study various CO2/O/O2 ratios, due to O2 being a
starting gas. Also here we define optimal regions for CO2 conversion, which reach maximum conversion for a
CO2 fraction of 50% and an O/O2 ratio bigger than 1. Those can be expanded by heating on one hand, for low
atomic oxygen availability, and by quenching after reaction on the other hand, for cases where the temperatures
are too high. Our model predictions can serve as a guideline for experimental research in this domain.

Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: Hoofd-halskanker vormt een aanzienlijke uitdaging met bijna 900.000 nieuwe diagnoses per jaar, waarbij de jaarlijkse incidentie blijft stijgen. Vaak wordt de diagnose pas in een laat stadium gesteld, wat complexe behandelingen noodzakelijk maakt. Terugval van patiënten is helaas een veelvoorkomend probleem. De gemiddelde overlevingsduur is beperkt tot enkele maanden. Daarom is er een dringende behoefte om nieuwe, veelbelovende behandelingen te ontwikkelen voor patiënten met hoofd-halskanker. Voor het bereiken van deze vooruitgang spelen innovatieve studiemodellen een cruciale rol. Het ontwikkelen van deze nieuwe behandelingen start met laboratoriumonderzoek, waarbij traditionele tweedimensionale celculturen hun beperkingen hebben. Daarom verschuiven onderzoekers hun aandacht meer en meer naar geavanceerdere driedimensionale modellen, met hoofd-halskankerorganoïden als beloftevol nieuw model. Dit model behoudt immers zowel het genetische profiel als de morfologische kenmerken van de originele tumor van de hoofd-halskankerpatiënt. Hoofdhalskankerorganoïden bieden daarom de mogelijkheid om innovatieve behandelingen te testen en kunnen mogelijk zelfs de respons van een patiënt op bepaalde therapieën voorspellen. Hoewel tumororganoïden als ‘patiënt-in-het-lab’ veelbelovend zijn, zijn er uitdagingen te overwinnen, zoals de ontwikkelingstijd en de toepasbaarheid bij alle tumortypes, evenals het ontbreken van immuuncellen en andere micro-omgevingscomponenten. Er is daarom een grote behoefte aan gestandaardiseerde protocollen voor de ontwikkeling van organoïden en verkorting van de ontwikkelingstijd. Concluderend bieden driedimensionale hoofd-halskankerorganoïden een veelbelovend perspectief voor de toekomst van kankerbehandelingen. Ze hebben het potentieel om bij te dragen aan de ontwikkeling van gepersonaliseerde behandelingen en zo de overlevingskansen van kankerpatiënten te verbeteren. Het is echter belangrijk om hun voorspellend vermogen en toepassingsmogelijkheden verder te onderzoeken, voordat ze op grote schaal worden geïmplementeerd.

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: Plasma is considered one of the promising technologies to solve greenhouse gas problems, as it can activate CO2 and CH4 at relatively low temperatures. Among the various types of plasmas, the gliding arc plasmatron (GAP) is promising, as it has a high level of non-equilibrium and high electron density. Nevertheless, the conversion of CO2 and CH4 in the GAP reactor is limited. Therefore, combining the GAP reactor with catalysts and making use of the heat produced by the plasma to provide thermal energy to the catalyst, forming a post-plasma catalytic (PPC) system, is hypothesized to improve its performance. Therefore, in this PhD research, we investigate important aspects of the PPC concept towards the use of the heat produced by GAP plasma to heat the plasma bed, without additional energy input. Aiming at this, based on a literature study (chapter 1), Ni-loaded layered double hydroxide (LDH) derived catalyst with good thermal catalytic DRM performance were chosen as the catalyst material. Before applying the LDH as a support material, the rehydration property of calcined LDH in moist and liquid environment was studied as part of chapter 2. The data indicated that after high temperatures calcination (600-900 C), the obtained layered double oxides (LDOs) can rehydrate into LDH, although, the rehydrated LDH were different from the original LDH. In chapter 3, different operating conditions, such as gas flow rate, gas compositions (e.g. CH4/CO2 ratio and nitrogen dilution), and addition of H2O were studied to investigate optimal conditions for PPC DRM, identifying possible differences in temperature profiles and exhaust gas compositions that might influence the catalytic performance. Subsequently, the impact of different PPC configurations, making use of the heat and exhaust gas composition produced by the GAP plasma, is shown in Chapter 4. Experiments studying the impact of adjusting the catalyst bed distance to the post-plasma, the catalyst amount, the influence of external heating (below 250 C) and the addition of H2O are discussed. As only limited improvement in the performance was achieved, a new type of catalyst bed was designed and utilized, as described in chapter 5. This improved configuration can realize better heat and mass transfer by directly connecting to the GAP device. The performance was improved and became comparable to the traditional thermal catalytic DRM results obtained at 800 C, although obtained by a fully electrically driven plasma.

Abstract: Air pollution is proclaimed by the World Health Organiaation (WHO) as the biggest environmental threat to human health. Street canyons, or urban roads flanked by a continuous row of high buildings on both sides, are perceived as typical bottleneck areas for air quality due to their lack of natural ventilation. This doctoral thesis aims to integrate expert knowledge on in-canyon flow fields and pollution dispersion in street canyons from the specialized field of (bio)engineering into the field of urban planning and vice versa. In Chapter 1, a Geospatial Information System (GIS) method was developed to detect exposure zones and hotspot street canyons. A critical combination between aspect ratio (AR > 0.65) and traffic volume (TVmax > 300) was detected and subsequently used to detect hotspot street canyons in three major European cities (Antwerp, London and Paris). Chapter 2 focusses on acquiring in-depth knowledge on flow and concentration fields in street canyons by conducting an extensive literature review on over 200 studies and translates this knowledge into nineteen guidelines and eleven spatial tools, comprised in a toolbox for urban planning. Subsequently, computational fluid dynamics (CFD) was used into a research trough design process (Chapter 4) to illustrate how the design tools can be applied to a specific case study (Belgiëlei, Antwerp). Alternations to traffic lanes (traffic lane reduction and lateral displacement) combined with low boundary walls (LBWs), were found to reduce NO2 levels in the entire pedestrian area up to – 3.6 % and peak pollutions were reduced by -8 %. A maximum NO2 reduction was reached by combining a traffic lane displacement with hedges, adjustments to the tree planting pattern and an increased ground-level permeability, leading to reductions up to – 4.5 % in the pedestrian areas. In conclusion, urban design was found to be a valuable tool to enhance the effect of emission reduction strategies and draw in-canyon concentrations closer to the value of the background concentration. However, the background concentration seemed to dominate the efficiency of the urban design interventions and therefore, additional measures should be taken to reduce background pollution levels. This dissertation aims to contribute to the awareness of air pollution in street canyons, as well as support local governments in taking action by delivering spatial tools and guidelines applicable for urban planning and represents a framework for the dissemination of expert information on air quality in street canyons to the field of urban planning.

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: Illicit drugs are harmful substances, posing a threat to the health and safety of society. Policies, such as supply reduction and harm reduction, are in place to combat the illicit drug problem. Science can play a substantial role in this fight, by providing tools that enable these policies to be successfully enforced. One example are on-site detection tools, i.e. sensors that allow the on-site identification of an illicit drug in a sample of interest. Several technologies, such as color tests and portable spectroscopic techniques, are currently employed for this goal. Although these are valuable techniques, there is an opportunity for voltammetry, an electrochemical technique, to make an impactful addition to this repertoire of on-site detection tools. Despite its attractive features (low-cost, portable, short analysis time, indifference to color,...), voltammetric illicit drug sensor have failed to make an impact in real scenarios. The work outlined in this PhD thesis aims to change this by bringing the technology from the lab to the field. Strategic choices, fueled by feedback from end-users, were made to further develop those specific aspects of the technology that previously haltered the technology to fulfill its potential. A detection algorithm was introduced that converts the voltammetric output into a clear-cut interpretation thereof, opening up the technology to end-users without prior knowledge of the technology. A sensor that allows qualitative and quantitative detection of the psychoactive drug MDMA was introduced, and importantly, validated on a large set of 212 confiscated samples. A state-of-the art mobile application and adequate sampling methodology were developed, alongside other, often more practical studies and product developments, to evolve the technology into a product that truly creates value for end-users. Important steps towards multidrug detection were made with a festival sensor and a flowchart based on visual appearance that ties together a variety of voltammetric single sensors into a single multidrug sensing approach. Last but not least, multiple valorization aspects were researched, including a market study and an analysis to determine the optimal commercialization strategy. Overall, this PhD thesis has facilitated the transition of the voltammetric illicit drug sensing technology from lab to on-site application. The final application creates value for end-users, and is ready to make an impact in real on-site scenarios.

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.