Abstract: A wide variety of organic and inorganic compounds have been frequently released into the environment without control by industries and agricultural activities. This has caused significant impact on the development and health of living organisms, and biodiversity. Therefore, the challenge of monitoring and/or remediation of these contaminants remains. This thesis presents the development of three sensing strategies based on photoelectrochemical sensors to monitor phenolic contaminants. The well-known semiconductors TiO2 and ZnO were used for building novel setups for nM analysis of phenolic compounds in water. The setups employing TiO2-based photosensors were integrated into a photoelectrochemical flow cell. The flow system favored higher sensitivity of the method by periodic wash sequences of the electrode, significantly reducing the electrode fouling. Firstly, a straightforward method was developed based on the immobilization of TiO2 on screen printed graphite electrodes. Under UV light, the developed photosensor presented high performance for the detection of 4- aminophenol. A second study was developed by impregnating gold nanoparticles into TiO2 structure. The incorporation of gold nanoparticles can broaden the light absorption region of TiO2 and improve its photocatalytic activity for the detection of hydroquinone under visible light. In both systems, the detection was possible due to the presence of reactive oxygen species at the surface of TiO2 upon light, which participate in the oxidation process of the analyte. By applying a reductive potential, the oxidized form of the analyte gets reduced and a measurable amperometric response proportional to the initial analyte concentration is recorded. The third proposed setup is a ZnO-based photosensor for the quantification of 4-nitrophenol under UVA light. Nanostructured ZnO was electrochemically synthesized on FTO glass without the use of catalysts or seed layer. A post-growth annealing treatment significantly improved ZnO nanorods physicochemical properties. Subsequent modification of ZnO nanorods with a photosensitizer (perylene acid) increased the photocurrent response and the sensitivity. In this system, the detection mechanism is based on the decrease of the photocurrent response at the presence of an electron harvesting molecule, such as 4-nitrophenol. The decrease in photocurrent is proportional to the increase of 4-nitrophenol concentration in the solution. The applicability of the photoelectrochemical semiconductor-based sensing setups was verified to analyze phenolic compounds in natural and supply water samples. The proposed robust and sensitive approaches were designed for the on-site monitoring of phenolic compounds. The encouraging results confirm the potential of these photosensors as promising tools for tracelevel sensing purposes.

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: Tidal marshes take up and release certain elements from and to the river water. Hence, they act as a filter, improving the estuarine water quality. This filtering function depends on the interaction between the marsh soil and water that infiltrates into the marsh platform at high tide and seeps out of the creek banks at low tide. In the past centuries, many tidal marshes disappeared due to large scale land reclamations, together with their associated ecosystem services. Nowadays, tidal marshes are increasingly restored on formerly embanked agricultural areas to regain these ecosystem services. Here, we studied the effect of historical agricultural land use on the contribution of restored tidal marshes to water quality improvement, and we investigated several solutions to stimulate the water quality improving function in newly restored tidal marshes. In restored tidal marshes, the soil is often compacted due to the historical agricultural land use, leading to a reduced organic matter content and micro- and macroporosity. In this compacted soil, groundwater flow is hindered, leading to a more waterlogged soil and reduced groundwater dynamics in the restored marsh as compared to a natural marsh. The depth of groundwater drainage and the groundwater flow velocity have important implications for the processes that contribute to water quality improvement, e.g. removal of nitrogen, phosphorus retention and silica cycling. Where groundwater drains deeper, i.e. in the vicinity of tidal creeks and in a more porous soil, these processes are promoted. We suggest that, in newly restored tidal marshes, the soil porosity can be increased by amending the soil (e.g. with organic matter), and the distance to the nearest tidal creek can be reduced by creek excavation. Numerical modelling showed that the largest gain in groundwater dynamics and seepage was attained when both measures were applied together. The effect of organic soil amendments on groundwater dynamics and nutrient cycling was further explored in a large scale in situ mesocosm experiment. Where the soil was amended, groundwater drained deeper and nitrogen removal increased. For new tidal marsh restoration projects, we advise to conduct an explorative soil study. When the soil is heavily compacted, design measures, such as creek initiation and organic soil amendments can be applied to jumpstart the contribution to water quality improvement of newly restored tidal marshes.

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: Atomic layer deposition (ALD) typically employs metal precursors and co-reactant pulses to deposit thin films in a layer-by-layer fashion. While conventional ABAB-type ALD sequences implement only two functionalities, namely, a metal source and ligand exchange agent, additional functionalities have emerged, including etching and reduction agents. Herein, we construct gas-phase sequences-coined as ALD+-with complex-ities reaching beyond the classic ABAB-type ALD by freely combining multiple functionalities within irregular pulse schemes, e.g., ABCADC. The possibilities of such combinations are explored as a smart strategy to tailor bimetallic thin films and nanoparticle (NP) properties. By doing so, we demonstrate that bimetallic thin films can be tailored with target thickness and through the full compositional range, while the morphology can be flexibly modulated from thin films to NPs by shuI 1ing the pulse sequence. These complex pulse schemes are expected to be broadly applicable but are here explored for Pd-Ru bimetallic thin films and NPs.

Abstract: Phenolic compounds can be found everywhere in our daily lives but exhibit high toxicity, low (bio)degradability and hormone-disrupting effects when they are released in the environment. It is for this reason imperative to develop detection strategies for these pollutants. A promising approach involves the use of a photoelectrochemical (PEC) sensor. In this sensor, a photosensitiser (PS) type II, which generates 1O2 under illumination, is used to oxidise phenolic compounds present in the sample. The oxidised phenols are reduced at the electrode surface leading to the generation of an electrocatalytic redox cycle. In this thesis, an in-depth understanding, through the identification of the reactive oxygen species (ROS) in the PEC sensing mechanism, is obtained. The detection strategy is optimised by choosing the PS with the highest 1O2 production and by optimising the detection parameters so that the PEC sensor can be successfully applied for the detection of phenols in industrial samples. First, it was determined that the use of highly fluorinated zinc phthalocyanine derivatives, F52PcZn and F64PcZn, as photocatalysts was optimal for the sensing of phenol due to their high 1O2 production and improved single-site isolation. However, next to 1O2, it was shown that the ROS O2•- and H2O2 were also generated in the PEC sensor. Their contribution to the photocurrent response was studied by rotating disk electrode measurements in function of the pH and applied potential. After this, the PEC detection strategy was optimised in terms of pH and applied potential for the detection of doxycycline, cefadroxil, and phenol. It was found that the use of alkaline pH-levels led to nmol L-1-level detection limits. The combination with square wave voltammetry (SWV) was, also, proposed to allow the quantification and identification of phenolic compounds in a specific sample. At last, the developed PEC and SWV sensors were applied for the measurement of phenolic compounds in industrial water samples. The PEC sensor could follow the decrease of the phenolic concentration throughout the wastewater treatment process while the SWV sensor provided the electrochemical fingerprints of these samples. The thesis concluded that the use of the PEC sensor was advantageous in the measurement of lower concentrated phenolic samples due to its high sensitivity and fast measurement time in comparison to commercial test kits.

Abstract: In this theoretical study, we assess the impact of a graphene capping layer on the resistivity of defective, extremely scaled interconnects. We investigate the effect of graphene capping on the electronic transport in ultrascaled interconnects, in the presence of grain boundary defects in the metal layer. We compare the results obtained using our quantum mechanical model to a simple parallel-conductor model and find that the parallel-conductor model does not capture the effect of the graphene cap correctly. At 0.5 nm metal thickness, the parallel-conductor model underestimates the conductivity by 3.0% to 4.0% for single-sided and double sided graphene capping, respectively.

Abstract: Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.

Abstract: Our scientific and technological worldviews are largely dominated by the concepts of entropy and complexity. Originating in 19th-century thermodynamics, the concept of entropy merged with information in the last century, leading to definitions of entropy and complexity by Kolmogorov, Shannon and others. In its simplest form, this worldview is an application of the normal rules of arithmetic. In this worldview, when tossing a coin, a million heads or tails in a row is theoretically possible, but impossible in practice and in real life. On this basis, the impossible (in the binary case, the outermost entries of Pascal's triangle xn and yn for large values of n) can be safely neglected, and one can concentrate fully on what is common and what conforms to the law of large numbers, in fields ranging from physics to sociology and everything in between. However, in recent decades it has been shown that what is most improbable tends to be the rule in nature. Indeed, if one combines the outermost entries xn and yn with the normal rules of arithmetic, either addition or multiplication, one obtains Lamé curves and power laws respectively. In this article, some of these correspondences are highlighted, leading to a double conclusion. First, Gabriel Lamé's geometric footprint in mathematics and the sciences is enormous. Second, conic sections are at the core once more. Whereas mathematics so far has been exclusively the language of patterns in the sciences, the door is opened for mathematics to also become the language of the individual. The probabilistic worldview and Lamé's footprint can be seen as dual methods. In this context, it is to be expected that the notions of information, complexity, simplicity and redundancy benefit from this different viewpoint.

Abstract: Today, illicit drugs are omnipresent in society. Clandestine markets are growing faster than ever before, record amounts of cocaine are seized in seaports and airports, while the associated violence is spiralling out of control. In addition, drug monitoring centres worldwide are warning for the increasing complexity of the drug markets, as the traditionally popular drugs are joined by countless new synthetic variants, while medical drugs are also increasingly being abused. In order to provide services confronted with illicit drug samples (police, customs, forensic scientists, first responders, …) with important information on the identity of an unknown sample, suitable analytical tests are required. While these exist for laboratory environments, on-site applicable tests are important to accelerate the decision-making process. Electrochemical sensors have all the advantages required for such on-site tests: they are fast, portable, easy-to-use and reliable. Furthermore, they are not influenced by colours, which are frequently added to drug samples to deceive the existing tests. Previous work has mainly focussed on the detection of a single drug per analysis. However, many drugs could be encountered due to the diversity of the drug markets. Therefore, this project developed electrochemical strategies for the detection of multiple drugs simultaneously. First, the electrochemical behaviour of the individual drugs was studied in different measuring conditions (assessing the influence of pH, concentration and temperature). Then, all findings and strategies were combined to detect multiple targets simultaneously. An electrochemical sensor was developed for the four most popular drugs at music festivals: cocaine, MDMA, amphetamine and ketamine. This sensor generates a so-called ‘superfingerprint’ of the sample, which is then automatically interpreted by a developed algorithm in order to produce a straightforward output. Finally, a pill analysis sensor was developed in the context of drug checking services, where a consumer can anonymously have a sample chemically analysed to obtain information on the composition, dose and potentially harmful additives. The sensor achieved an outstanding accuracy in identifying the main component and provided the option to quantify, as well as an indication on the presence of other substances in the sample. The project’s findings demonstrate the potential for electrochemistry in illicit drug detection and provide a basis for the development of new sensors, targeting other drug combinations.

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: 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.