Abstract: Particulate matter is one of the most persistent global air pollutants that is causing health problems, climate disturbance and building deterioration. A sustainable technique that is able to degrade soot using (sun)light is photocatalysis. Currently, research on photocatalytic soot oxidation focusses on large band gap TiO2-based photocatalysts and thus requires the use of UV light. It would prove useful if visible light, and thus a larger fraction of the (freely available) solar spectrum, could additionally be utilised to drive this process. In this work, a visible light-active photocatalyst, WO3, is benchmarked to TiO2 under both UV and visible light. At the same time, the versatility and drastic improvement of a recently introduced digital image-based soot degradation detection method are demonstrated. An additional step correcting for non-soot related catalyst colour changes is applied, resulting in accurate detection and quantification of soot degradation for all studied photocatalysts, even for materials such as WO3 that are inherently coloured. With this study, we aim to broaden the scope of photocatalytic soot oxidation technology to visible light-active photocatalyst. Along with this study, we provide a versatile soot degradation detection methodology based on digital image analysis that is made widely applicable.

Abstract: The human population is projected to grow to 9.7 billion by 2050, resulting in an estimated increase in protein demand of 50%. From an environmental perspective, the current and future demand of protein cannot be sustainably met as the conventional food production chain is severely altering biogeochemical cycles of nitrogen and phosphorus, biodiversity and land-use, with flows towards the biosphere and oceans that are exceeding the planetary boundaries. Microbial protein (protein derived from microorganisms) has been suggested as an excellent sustainable protein source, a fortiori when produced in a land- and fossil free manner. The photoautohydrogenotrophic cultivation (i.e. with light, CO2 and H2) of purple bacteria links up perfectly with the upcoming green electrification of industry (green H2) and the need for carbon capture and utilization. However, this metabolism represented a gap in literature, and thus this thesis aimed to establish a basic knowledge platform on its kinetic, stoichiometric and nutritional performance. At first, three originally photoheterotrophically enriched purple bacteria were studied of which Rhodobacter capsulatus reached the highest protein productivity of 0.16 g protein/L/d, which aligned well with the commonly-known photoautotrophic microalgae. Moreover, a full dietary essential amino acid match was found for human food, while the fatty acid content was dominated by the health-stimulating vaccenic acid (82-86%). Lastly, the achieved protein yield in photoautohydrogenotrophic purple bacteria was 2.3 times higher compared to hydrogen oxidizing bacteria, indicating a resource-efficient use of H2. Next, a photoautohydrogenotrophic enrichment of wastewater treatment microbiomes was performed in search for specialist species. While the isolates of this enrichment showed improvements in their performance during acclimation, the kinetic and nutritional performance of Rhodobacter capsulatus still excelled. Subsequently, the influence of nutrient limitations (C or N) and nitrogen gas fixation was studied on the nutritional tuning potential. Both the limitations as well as the N2 fixation resulted in the shift of the essential amino acid profiles. Additionally, the limitations significantly decreased the pigment content, while an increase in the storage of poly-P was seen in case of carbon limitations. The next major challenge was the production intensification in a photobioreactor of which the design was linked to minimizing both H2 and light limitations. The chosen bubble-column photobioreactor already resulted in a doubled biomass productivity. Finally, the remaining technological and non-technological challenges ahead for the production of a high-value, cost-efficient, environment-friendly microbial protein that complies with legislative requirements and appeals to future consumers were discussed.

Abstract: Memristors are considered to be the fourth circuit element and have great potential in areas like logic operations, information storage, and neuromorphic computing. The functional material in a memristor, which has a nonlinear resistance, is the key component to be developed. Herein, resistive switching is demonstrated and the structural evolutions in Ag2Te are examined under an external electric field. It is shown that the electroresistance effect is originating from an electronically triggered phase transition together with directional Ag+-ion diffusion. Using in situ transmission electron microscopy, the phase transition from the monoclinic alpha-Ag2Te into the face-centered cubic beta-Ag2Te, accompanied by a change in resistance, is directly observed. Diffusion of Ag+-ions modulates the localized density of Ag+-ion vacancies, leading to a change in electrical conductivity and influences the threshold voltage to trigger the phase transition. During the electric field-driven phase transition, the spontaneous and localized multiple polarizations from the low-symmetry alpha-Ag2Te (referring to an antiferroelectric structure) are vanishing in the cubic beta-Ag2Te (referring to a paraelectric structure). The abrupt resistance change of thin Ag2Te caused by the phase transition and modulated by the applied electric field demonstrates its great potential as functional material in volatile memory and memristors with a low-energy consumption.

Abstract: Effective abatement of the greenhouse gas sulphur hexafluoride (SF6) waste is of great importance for the environment protection. This work investigates the size effect and the surface properties of gamma-Al2O3 pellets on SF6 degradation in a packed bed dielectric barrier discharge (PB-DBD) system. Experimental results show that decreasing the packing size improves the filamentary discharges and promotes the ignition and the maintenance of plasma, enhancing the degradation performance at low input powers. However, too small packing pellets decrease the gas residence time and reduce the degradation efficiency, especially for the input power beyond 80 W. Besides, lowering the packing size promotes the generation of SO2, while reduces the yields of S-O-F products, corresponding to a better degradation. After the discharge, the pellet surface becomes smoother with the appearance of S and F elements. Density functional theory calculations show that SF6 is likely to be adsorbed at the Al-III site over the gamma-Al2O3(110) surface, and it is much more easily to decompose than in the gas phase. The fluorine gaseous products can decompose and stably adsorb on the pellet surface to change the surface element composition. This work provides a better understanding of SF6 degradation in a PB-DBD system.

Abstract: A uniform description of natural shapes and phenomena is an important goal in science. Such description should check some basic principles, related to 1) the complexity of the model, 2) how well its fits real objects, phenomena and data, and 3) ia direct connection with optimization principles and the calculus of variations. In this article, we present nine principles, three for each group, and we compare some models with a claim to universality. It is also shown that Gielis Transformations and power laws have a common origin in conic sections

Abstract: The application of dielectric barrier discharge (DBD) plasma reactors is promising in various environmental and energy processes, but is limited by their low energy yield. In this study, we put a number of stainless steel rings over the inner electrode rod of the DBD reactor to change the local discharge gap and electric field, and we studied the dry reforming performance. At 50 W supplied power, the metal rings mostly have a negative impact on the performance, which we attribute to the non-uniform spatial distribution of the discharges caused by the rings. However, at 30 W supplied power, the energy yield is higher than at 50 W and the placement of the rings improves the performance of the reactor. More rings and with a larger cross-sectional diameter can further improve the performance. The reactor with 20 rings with a 3.2 mm cross-sectional diameter exhibits the best performance in this study. Compared to the reactor without rings, it increases the CO2 conversion from 7% to 16 %, the CH4 conversion from 12% to 23%, and the energy yield from 0.05 mmol/kJ supplied power to 0.1 mmol/kJ (0.19 mmol/kJ if calculated from the plasma power), respectively. The presence of the rings increases the local electric field, the displaced charge and the discharge fraction, and also makes the discharge more stable and with more uniform intensity. It also slightly improves the selectivity to syngas. The performance improvement observed by placing stainless steel rings in this study may also be applicable to other plasma-based processes.

Abstract: 200 years ago, humanity started the industrial revolution by discovering fossil fuels, which lead to unprecedented technological advancements. However it has become alarmingly clear that the major environmental concerns associated with fossil fuels require a short-term transition from a carbon-based energy economy to a sustainable one based on green electricity. A key step concerning this transition exists in developing electricity-driven alternatives for chemical processes that rely on fossil fuels as a raw material. A technology that is gaining increasing interest to achieve this, is plasma technology. Using plasmas to induce chemical reactions by selectively heating electrons in a gas has already delivered promising results for gas conversion applications like CO2 conversion and N2 fixation, but plasma reactors still require optimization to be considered industrially competitive to existing fossil fuel-based processes and emerging other electricity-based technologies. In this thesis I develop computational models to describe plasma reactors and identify key mechanisms in three different plasma reactors for three different gas conversion applications, i.e. N2 fixation, combined CO2-CH4 conversion and CO2 splitting. I first developed models to describe a new rotating gliding arc (GA) reactor operating in two arc modes, which, as revealed by my model, are characterized by distinct plasma chemistry pathways. Subsequently, my colleague and I study the quenching effect of an effusion nozzle to this rotating GA reactor, reaching the best results to date for N2 fixation into NOx at atmospheric pressure, i.e., NOx concentrations up to 5.9%, at an energy cost down to 2.1 MJ/mol. Afterwards, I investigate the possible improvement of N2 admixtures in plasma-based CO2 and CH4 conversion, as significant amounts of N2 are often found in industrial CO2 waste streams, and gas separations are financially costly. Through combining my models with the experiment from a fellow PhD student, we reveal that moderate amounts of N2 (i.e. around 20%) increase both the electron density and the gas temperature to yield an overall energy cost reduction of 21%. Finally, I model quenching nozzles for plasma-based CO2 conversion in a microwave reactor, to explain the enhancements in CO2 conversion that were demonstrated in experiments. Through computational modelling I reveal that the nozzle introduces fast gas quenching resulting in the suppression of recombination reactions, which have more impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Abstract: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.

Abstract: The Night Watch, painted in 1642 and on view in the Rijksmuseum in Amsterdam, is considered Rembrandt's most famous work. X-ray powder diffraction (XRPD) mapping at multiple length scales revealed the unusual presence of lead(II) formate, Pb(HCOO)(2), in several areas of the painting. Until now, this compound was never reported in historical oil paints. In order to get insights into this phenomenon, one possible chemical pathway was explored thanks to the preparation and micro-analysis of model oil paint media prepared by heating linseed oil and lead(II) oxide (PbO) drier as described in 17(th) century recipes. Synchrotron radiation based micro-XRPD (SR-mu-XRPD) and infrared microscopy were combined to identify and map at the micro-scale various neo-formed lead-based compounds in these model samples. Both lead(II) formate and lead(II) formate hydroxide Pb(HCOO)(OH) were detected and mapped, providing new clues regarding the reactivity of lead driers in oil matrices in historical paintings.

Abstract: The colloidal synthesis of functional nanoparticles has gained tremendous scientific attention in the last decades. In parallel to these advancements, another rapidly growing area is the self-assembly or self-organization of these colloidal nanoparticles. First, the organization of nanoparticles into ordered structures is important for obtaining functional interfaces that extend or even amplify the intrinsic properties of the constituting nanoparticles at a larger scale. The synthesis of large-scale interfaces using complex or intricately designed nanostructures as building blocks, requires highly controllable self-assembly techniques down to the nanoscale. In certain cases, for example, when dealing with plasmonic nanoparticles, the assembly of the nanoparticles further enhances their properties by coupling phenomena. In other cases, the process of self-assembly itself is useful in the final application such as in sensing and drug delivery, amongst others. In view of the growing importance of this field, this review provides a comprehensive overview of the recent developments in the field of nanoparticle self-assembly and their applications. For clarity, the self-assembled nanostructures are classified into two broad categories: finite clusters/patterns, and infinite films. Different state-of-the-art techniques to obtain these nanostructures are discussed in detail, before discussing the applications where the self-assembly significantly enhances the performance of the process.

Abstract: In the last few decades, nanostructuring has driven significant attention towards the development of novel metallic materials with advanced mechanical properties. Nanocrystalline (nc) metals are a class of nanostructured materials with grain sizes smaller than about 100 nm. These exhibit outstanding mechanical strength and fatigue properties compared to their coarse-grained (cg) counterparts. These are promising candidates for application as structural or functional materials. Nc metals in the form of thin films are employed as hard coatings on bulk components, structural components, and conductive layers in various micro-/nanoscale devices. These structural components and devices are often subjected to cyclic stresses or fatigue loading. Under these cyclic stresses, nc metals tend to exhibit the Bauschinger effect (BE). The strength loss during the BE is of great importance concerning the strength-ductility trade-off in nc metals. Furthermore, contact surfaces of the engineering components in service often undergo relative motion and are subject to both friction and wear. These extreme loading conditions demand nc metals with tailored interfacial characteristics for improved tribological performance. Aiming at ensuring high reliability and mechanical robustness for optimum performance of these components, there has been a strong motivation for understanding the mechanical properties and governing deformation mechanisms in nc metallic materials. This thesis aimed at in-depth investigation of microstructures at micro-/nanoscales using state-of-the-art in situ and ex situ transmission electron microscopy (TEM) to develop a closer link between the deformation structure and underlying deformation mechanisms in some nc metallic materials. The thesis has primarily focused on the in situ TEM nanomechanics of the BE and rotational deformation of grains in nc palladium thin films. A sputtered thin film of nc Pd was deformed inside TEM by cyclic loading-unloading experiments and the evolving microstructure was studied in real-time under different TEM imaging modes. The stress-strain response of the film exhibited a characteristic non-linear unloading behavior confirming the BE in the film. The corresponding bright-field TEM imaging revealed evidence of partially reversible dislocation activity. Towards a quantitative understanding of the deformation structure in real-time, in situ nanomechanical testing was coupled with precession-assisted automated crystal orientation mapping in scanning TEM (ACOM-STEM). Global ACOM-STEM analysis offered crystal orientation of a large number of grains at different states of deformation and confirmed partially reversible rotations of nanosized grains fitting to the observed BE during loading and unloading. Analysis of intragranular rotations showed substantial changes in the sub-structure within most of these grains indicating a dominant role of dislocation-based processes in driving these rotations. Globally, an unusually random evolution of texture was seen that demonstrated the influence of deformation heterogeneity and grain interactions on the resulting texture characteristics in nc metals. In the quest of understanding the grain interactions, local investigations based on annular dark-field STEM imaging during loading-unloading showed reversible changes in the contrast of grains with sets of adjoining grains exhibiting a unique cooperative rotation. Local analysis of the density of geometrically necessary dislocations (GNDs) showed the formation of dislocation pile-up at grain boundaries due to the generation of back-stresses during unloading. Critical observations of the evolution of GND density offered greater insights into the mechanism of cooperative grain rotations and these rotations were related to grain structure and grain boundary characteristics. In addition to understanding the influence of grain structure and grain boundaries, the thesis has further investigated the role of heterointerfaces in sputtered Au-Cu and Cu-Cr nanocrystalline multilayered composites (NMCs) deformed under cyclic sliding contact. The microstructural evolution in the NMCs was investigated at different deformation states by classical TEM imaging, ACOM-STEM as well as energy-filtered TEM (EFTEM). Au-Cu NMC with an initial high density of twin boundaries deformed by stress-driven detwinning with a concurrent change in grain structure in both Au and Cu. The formation of a vortex structure was observed due to plastic flow instabilities at Au-Cu interfaces that led to codeformation and mechanical intermixing. Cu-Cr NMC showed a preferential grain growth in Cu layers whereas no noticeable change in the grain sizes was seen in Cr layers. The phase maps revealed sharp interfaces between Cu and Cr layers indicating no intermixing between the immiscible phases. EFTEM results exposed the cracking processes in Cr layers with a concurrent migration of Cu in the cracks. Overall, the thesis has attempted to analyze the competing deformation processes and relate these with the microstructural heterogeneity in terms of grain structure and GB and interfacial characteristics in nc metallic materials.

Abstract: One of the most basic criteria in documenting rangeland use prospects is the recognition of byproducts and their economic appraisal. The current study was conducted to assess the economic indices of exploiting byproduct production in Shahindej, Northwest Iran. For this purpose, 24 by-product-generating species were selected in 114 locations that belong to 49 rangeland units. The total expected value of 24 by-product generating species yield and forage production was calculated at 44.22 USD ha(-1). The results of this study showed that the sustainability of natural resources depends on the effective participation and empowerment of local communities. Furthermore, by-product exploitation contributes significantly to the local economy and employment while also reducing grazing intensity. Overall, the findings of this study show that by-product earnings should be considered in range management schemes and comprehensive natural-area management.

Abstract: In Ethiopia, the state owns all lands within the territory of the country. Cities are incorporating large parcels of land from their surrounding rural agricultural areas through land expropriation. However, these land developments do not consider the nonmarket value of ecosystem services (ES), which is causing a deterioration of the existing ES and reduction on the potential supply of ES from agricultural land. The aim of this study was to estimate the monetary value of nonmarketable ES from the agricultural land using a double-bounded dichotomous choice contingent valuation method. A survey of 524 smallholder farmers was conducted. In the survey, respondents were asked to state their willingness to pay for the improvement of some of the nonmarketable ES: erosion control, air and climate regulation, water regulation, and soil fertility. The estimation was carried out using a bivariate probit model. The results revealed that farmers are willing to pay on average 276 ETB (7.9 USD) per hectare per year for a period of 10 years. We found that individual characteristics such as age, family size, and a recent land expropriation experience adversely affect the willingness to pay by the farmers. On the other hand, individuals with higher income and larger land size are willing to pay more. In general, the study indicated that the nonmarket ES, which are affected by the land expropriation for urban expansion, are valuable for the farmers. Therefore, we recommend that the government consider the value of nonmarketable ES in its land use decisions and hence achieve sustainable land development.

Abstract: Novel emerging biorefinery technologies have gained interest and have the potential to tackle several sustainability challenges in our society. A lignin-first biorefinery process – reductive catalytic fractionation (RCF) – is currently under development with the aim to process wood into high-value end-products that replace highly polluting fossil oil-based products. However, such emerging technologies are not matured yet, holding a certain degree of technological, economic, and environmental uncertainty. Hence, an appropriate assessment method is required to assess techno-economic feasibility and environmental impacts of emerging uncertain technologies (e.g lignin-first RCF process). This dissertation aims to develop an integrated techno-environmental economic assessment framework to assess emerging technologies dynamically and prospectively from economic and environmental points of view. First, a techno-economic assessment (TEA) is performed to assess the economic feasibility and the most influential economic and technological parameters of the lignin-first RCF biorefinery taking the whole wood value chain into account. By making the relations across the wood value chain, the scale of the biorefinery, wood species, and output prices highly determine the economic feasibility. The economic feasibility can be reached by a sufficient capacity level which depends on wood species-specific conditions. Also, waste wood proves to be the most profitable feedstock in comparison to virgin wood. Second, an analytical real options analysis (ROA) is performed taking two correlated market uncertainties and the value of flexibility into account to identify the optimal investment decision in an RCF biorefinery. Two different investment options, separated and united investments in harvesting equipment and RCF biorefinery, are analyzed. In both scenarios, market uncertainty postpones the investment. When both investment decisions are united, the probability of investment increases in comparison to separated investments. The study reveals that RCF has the potential to stimulate investments within the wood value chain. Third, a consequential life cycle assessment (LCA) is performed to assess the carbon emissions and the environmental consequences of the lignin-first RCF process and its products. The study reveals that at the current stage RCF products have higher carbon emissions than their alternative counterparts. Several options to improve the environmental performance are discussed such as different RCF technology configurations, targeting different RCF products with the ability to replace higher polluting alternative counterparts on the markets. Other discussion points such as transportation type and the distance, (in-)direct land-use change, the use stage and disposal stages implications, and a more comprehensive environmental view of the RCF products, show the potential to improve the environmental performance of the RCF technology. Overall, the study shows that the RCF process can be environmentally desirable if the appropriate RCF configuration and products are chosen. Finally, the above-mentioned methods – techno-economic assessment, analytical real options analysis, and consequential life cycle assessment – are uniquely integrated within the newly developed integrated assessment framework. The framework has the aim to complement the shortcomings and combine the advantages of all three methods. The framework assesses emerging technologies to give predictive insights about the time-specific economic and environmental performance under the newly developed three threshold conditions: technological readiness, economic feasibility, and environmental desirability. The developed integrated assessment framework assesses dynamically and prospectively the RCF biorefinery implementation under Belgian conditions. It reveals that the economic feasibility increases and carbon emissions decrease over time. The RCF biorefinery fulfills all three threshold conditions – technological readiness, economic feasibility, and environmental desirability – consecutively. The newly developed integrated assessment framework offers decision support to several stakeholders of emerging technologies starting from low technology readiness level (TRL). Practitioners such as the technology developers, researchers, and policymakers can use the framework to evaluate emerging technologies that deal with high levels of technological, economic, and environmental uncertainties. The framework assesses emerging technologies on a detailed level to give decision-makers in-depth insights into the intertwined nature of the technological, economic, and environmental dimensions. It offers insights into the expected time-specific economic and environmental performances, potential, and challenges of the emerging technology to further improve the technology and direct R&Ds along the right path.