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: Stimuli-responsive metal-organic frameworks (MOFs) are highly versatile porous materials with the ability to respond to different external stimuli, including temperature, pressure, pH, and light. The MOF properties can switch reversibly under specific light irradiation, opening the doors to various applications. This review focuses on design strategies to obtain photo-responsive MOFs, namely (i) encapsulation of photo-switchable molecules as guests in MOF porous structures, (ii) fabrication of MOF composites, (iii) post-synthesis modification, and (iv) synthesis of MOFs with photo-responsive ligands. The most recent reports from the literature are herein reviewed and analyzed in terms of material chemistry and performance. Comparisons between the different strategies are performed and future challenges are discussed. The critical aspect of the fatigue of photo-responsive MOFs applied for prolonged cycling of irradiation is also discussed.

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

Abstract: This dissertation focuses on the materials and techniques used by the Brussels artists Michael Sweerts (1618-1664) and Michaelina Wautier (1614-1689). It tries to answer the following research questions: 1.Did 17th-century Brussels-based artists use idiosyncratic painting materials and techniques, and can their work be distinguished from paintings created in other artistic centers based on these materials and techniques? 2.How did Sweerts and Wautier influence each other’s work? In order to answer the research questions, a selection of relevant and representative paintings from Sweerts’ and Wautier’s oeuvre has been studied with MA-XRF scanning and microscopic examination. The results are discussed in volume 2 of this dissertation, and form the basis upon which the chapters in volume 1 are built. MA-XRF scanning is a non-destructive imaging technique based on the technique of X-ray fluorescence (XRF). The technique allows for the collection of elemental information about the materials present in a work of art. The work presented in this dissertation has shed more light on the working methods of Sweerts and Wautier. It has shown they both showed an openness and willingness to continue learning and developing as an artist. Wautier did not feel constrained to work only in one genre and apparently carried on developing her skills throughout her career, as evidenced by Flower Garland with Butterfly. She might have trained with a specialized artist to master their idiosyncratic working methods and this diverse genre. This suggests that Wautier had an interest in art education. Sweerts too had a passion for art education: he was involved in the drawing academy of Camillo Pamphilj in Rome, and later established his own academy for life drawing in Brussels. Sweerts’ work clearly shows the influence of his Italian contemporaries. Whilst living in Rome, he adapted his working methods to local customs such as working on brightly colored grounds. Wautier’s oeuvre shows that she was open to explore different genres and that she took inspiration from her contemporaries, including Theodoor van Loon and Daniël Seghers. In doing so, she furthered the development of different genres as she added original elements to her compositions. It is the conclusion of this dissertation that Michaelina Wautier can thus be considered one of the innovative artists of mid-17th-century Flemish painting, who inspired other artists in the Low Countries, including Michael Sweerts.

Abstract: Using state-of-the-art simulation methods, we optimized the performance of nanoscale superconducting scanning probe tips for advanced spatial imaging of magnetic fields. The systematic studies of the tips’ static properties as a function of the tilted magnetic field, geometric parameters, and material parameters were carried out. The sensitivity of different superconducting quantum interference devices (SQUIDs) to the magnetic field emanating from the magnetic nanoparticle, where the location of a magnetic nanoparticle is considered below the primary loop's center, was examined as a function of the primary and secondary loop dimensions. The main objective of the research was to characterize and optimize the performance of a nano-sized SQUID-on-tip (SOT) device. Optimal SOT sensitivity was sought, for different loop sizes, arm linewidth, and lead dimensions. Moreover, we revealed that a constriction in the loop arms of the SOT can substantially improve the sensitivity of the device. Finally, the properties of the theta-SOT device were examined in the presence of in-plane and out-of-plane magnetic field components, enabling nanoscale imaging of 3D distributions of the magnetic field. Altogether, the obtained results deliver an engineering solution for the optimum performance of the SOT device in desired conditions.

Abstract: Plasma medicine, or the biomedical application of cold atmospheric plasma (CAP), is an expanding field within plasma research. CAP has demonstrated remarkable versatility in diverse biological applications, including cancer treatment, wound healing, microorganism inactivation, and skin disease therapy. However, the precise mechanisms underlying the effects of CAP remain incompletely understood. The therapeutic effects of CAP are largely attributed to the generation of reactive oxygen and nitrogen species (RONS), which play a crucial role in the biological responses induced by CAP. Specifically, RONS produced during CAP treatment have the ability to chemically modify cell membranes and membrane proteins, causing nitro-oxidative stress, thereby leading to changes in membrane permeability and disruption of cellular processes. To gain atomic-level insights into these interactions, non-reactive molecular dynamics (MD) simulations have emerged as a valuable tool. These simulations facilitate the examination of larger-scale system dynamics, including protein-protein and protein-membrane interactions. In this comprehensive review, we focus on the applications of non-reactive MD simulations in studying the effects of CAP on cellular components and interactions at the atomic level, providing a detailed overview of the potential of CAP in medicine. We also review the results of other MD studies that are not related to plasma medicine but explore the effects of nitro-oxidative stress on cellular components and are therefore important for a broader understanding of the underlying processes.

Abstract: During the past decades, metallic nanoparticles (NPs) have attracted great attention in materials science due to their specific optical properties based on surface plasmon resonances. Because of these phenomena, plasmonic NPs (or nanoplasmonics) are very promising for application in biosensing, photocatalysts, medicine, data storage, solar energy conversion, etc. Currently, colloidal synthesis techniques enable scientists to routinely produce mono and bimetallic NPs of various shapes, sizes, composition, and elemental distribution, with superior properties for plasmonic applications. Two primary directions for further advancing nanoplasmonic-based technologies include synthesizing novel morphologies, such as highly asymmetric chiral NPs, and gaining deeper insights into the factors affecting the stability of produced nanoplasmonics. With the increasing complexity of nanoplasmonics morphologies and higher stability requirements, there is a pressing need for thorough investigations into their 3D structures and their evolution under different conditions, with high resolution. Electron tomography (ET) emerges as an ideal tool to retrieve shape and element-sensitive information about individual nanoparticles in 3D, achieving resolutions down to the atomic level. Moreover, ET techniques can be combined with in situ holders, enabling detailed studies of processes mimicking real applications of nanoplasmonic-based devices. The first part of this thesis will focus on detailed studies of chiral Au NPs, promising for spectroscopy techniques based on the differential absorption of left- and right-handed circularly polarized light. Specifically, I will discuss the primary strategies for wet-colloidal growth of the various types of intrinsically chiral Au NPs. Advanced ET methods will be demonstrated as powerful tools for characterizing the final helical morphologies of the produced Au NPs and for studying the chiral growth mechanisms by examining intermediate structures obtained during chiral growth. The second part will focus on the heat-induced stability of various Au@Ag core-shell NPs. Operating in real conditions, such as elevated temperatures, may cause particle reshaping and redistribution of metals between the core and shell, gradually altering nanoplasmonics properties. Hence, a thorough understanding of the influence of size, shape, and defects on these processes is crucial for further developments. Recently developed techniques, combining fast ET with in-situ heating holders, have allowed me to evaluate the influence of various parameters (size, shape, defect structure) on heat-induced elemental redistribution in Au@Ag core-shell nanoparticles qualitatively and quantitatively. Additionally, I will discuss the prospects of high-resolution ET for visualizing the diffusion of individual atoms within complex nanostructures.

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

Abstract: 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: Natural listening involves a constant deployment of small head movement. Spatial listening is facilitated by head movements, especially when resolving front-back confusions, an otherwise common issue during sound localization under head-still conditions. The present study investigated which acoustic cues are utilized by human listeners to localize sounds using small head movements (below ±10° around the center). Seven normal-hearing subjects participated in a sound localization experiment in a virtual reality environment. Four acoustic cue stimulus conditions were presented (full spectrum, flattened spectrum, frozen spectrum, free-field) under three movement conditions (no movement, head rotations over the yaw axis and over the pitch axis). Localization performance was assessed using three metrics: lateral and polar precision error and front-back confusion rate. Analysis through mixed-effects models showed that even small yaw rotations provide a remarkable decrease in front-back confusion rate, whereas pitch rotations did not show much of an effect. Furthermore, MSS cues improved localization performance even in the presence of dITD cues. However, performance was similar between stimuli with and without dMSS cues. This indicates that human listeners utilize the MSS cues before the head moves, but do not rely on dMSS cues to localize sounds when utilizing small head movements.

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.