Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

Abstract: The EPS Antwerp Young Minds (AYM) invited Prof. Nir Navon (Yale University) to hold a colloquium for the physics department. For an audience of students and researchers, Prof. Navon presented recent advances in ultracold quantum matter and research from his own lab. His experimental work paves the way to make toy models used by theorists a reality. We sat down afterwards to discuss ultracold physics, box traps and setting up a lab from scratch.

Abstract: Supplementary information for the article “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” containing the videos of in-situ SEM imaging (mp4 files), raw data/images, and Jupyter notebooks (ipynb files) for data treatment and plots. Link to the preprint: https://doi.org/10.48550/arXiv.2308.15123 Explanation of the data files can be found in the Information.pdf file. The Videos folder contains the in-situ SEM image series mentioned in the paper. If there are any questions/bugs, feel free to contact me at lukas.grunewaldatuantwerpen.be

Abstract: Plasma-based CO2 conversion is worldwide gaining increasing interest. The aim of this work is to find potential pathways to improve the energy efficiency of plasma-based CO2 conversion beyond what is feasible for thermal chemistry. To do so, we use a combination of modeling and experiments to better understand the underlying mechanisms of CO2 conversion, ranging from non-thermal to thermal equilibrium conditions. Zero-dimensional (0D) chemical kinetics modelling, describing the detailed plasma chemistry, is developed to explore the vibrational kinetics of CO2, as the latter is known to play a crucial role in the energy efficient CO2 conversion. The 0D model is successfully validated against pulsed CO2 glow discharge experiments, enabling the reconstruction of the complex dynamics underlying gas heating in a pure CO2 discharge, paving the way towards the study of gas heating in more complex gas mixtures, such as CO2 plasmas with high dissociation degrees. Energy-efficient, plasma-based CO2 conversion can also be obtained upon the addition of a reactive carbon bed in the post-discharge region. The reaction between solid carbon and O2 to form CO allows to both reduce the separation costs and increase the selectivity towards CO, thus, increasing the energy efficiency of the overall conversion process. In this regard, a novel 0D model to infer the mechanism underlying the performance of the carbon bed over time is developed. The model outcome indicates that gas temperature and oxygen complexes formed at the surface of solid carbon play a fundamental and interdependent role. These findings open the way towards further optimization of the coupling between plasma and carbon bed. Experimentally, it has been demonstrated that “warm” plasmas (e.g. microwave or gliding arc plasmas) can yield very high energy efficiency for CO2 conversion, but typically only at reduced pressure. For industrial application, it will be important to realize such good energy efficiency at atmospheric pressure as well. However, recent experiments illustrate that the microwave plasma at atmospheric pressure is too close to thermal conditions to achieve a high energy efficiency. Hence, we use a comprehensive set of advanced diagnostics to characterize the plasma and the reactor performance, focusing on CO2 and CO2/CH4 microwave discharges. The results lead to a deeper understanding of the mechanism of power concentration with increasing pressure, typical of plasmas in most gases, which is of great importance for model validation and understanding of reactor performance.

Abstract: New Cinema History broadened film studies by emphasising the complexity of cinema as a multifaceted phenomenon that includes the socio-economic context in which films were made, circulated, shown and received. As part of the digital turn, the discipline adopted computational methods and created quantitative research data to research this socio-economic context at scale. However, not all datasets created in this context adhere to FAIR principles, decreasing their reusability. By reconciling 14 cinema-related datasets, Cinema Belgica facilitates research into the history of Belgian cinema. This research paper documents and critically reflects on the choices made when selecting, modelling and reconciling information for the Cinema Belgica database.

Abstract: Climate change is an ever-increasing threat to our planet, with the urbanisation of previously open spaces exacerbating the issue. The loss of open space leads to a decrease in ecosystem services, which negatively impacts the liveability in urbanised environments, and beyond. The incorporation of green infrastructure (GI) into the built environment is acknowledged as an effective and multi-functional measure to make our living environment resilient and future-proof. Notwithstanding that the local level is essential for effective GI implementation, research into local decision making is very limited. This thesis therefore aims to address two significant gaps in the implementation of GI. The first objective is to bridge the science-policy gap by integrating scientific knowledge on ES and GI into local decision-making processes. In this context, the policy dimension within this thesis involves the process of translating overarching policy objectives into practical actions within local decision-making practices, abstracting from the intricacies of higher-level policymaking itself. The second objective focuses on the people-policy gap, which involves understanding stakeholders' perspectives and priorities regarding GI and its associated ecosystem services. Through stated preference valuation techniques (discrete choice experiments and a best-worst scaling experiment), multi-stakeholder GI perceptions are gathered. Finally, a novel tool to GI valuation is developed, acknowledging the different stakeholder views and building on the insights of collaborative tool development and design. By gaining insights into the demand, prioritisation, and provision of GI from the two most important stakeholder groups at the local level (residents and local decision-makers), this research aims to foster effective communication and alignment between public preferences and policy implementation. Ultimately, addressing these gaps will contribute to more informed planning and decision-making practices related to green infrastructure. The overall goal of this thesis is to enhance the uptake of GI knowledge in the local decision-making context, proposing pathways to facilitate and optimise investments in public GI.

Abstract: De bijdrage gaat dieper in op de relatie tussen ruimte en gezondheidsongelijkheid, bespreekt gezondheidsongelijkheid vanuit een rechtenperspectief en illustreert een aantal praktijken waarin de aandacht voor ruimte en gezondheidsongelijkheid samenkomen.

Abstract: Climate change is causing alterations in precipitation patterns, leading to adverse ecological consequences in many ecosystems. Recently, an increasingly persistent weather pattern has emerged, characterized by lengthening the duration of alternating dry and wet periods, which is more complex than exclusively drought or increasing precipitation. It is currently unclear how soil microbial communities respond to these new regimes in relation to their interactions with plants, especially in precipitation-sensitive ecosystems, such as tropical rainforests and grasslands. In this thesis, we explored responses of soil bacterial and fungal communities to increasing weather persistence in rainforests and grasslands, using high throughput sequencing technology. We firstly investigated the resistance and resilience of microbial communities to prolonged drought in a mature seasonal tropical rainforest which experiences unusually intensive dry seasons in the current century. Through excluding rainfall during and after the dry season, a simulated prolongation of the dry season by five months was compared to the control. Our results indicate that as rain exclusion progressed, the microbial communities increasingly diverged from the control, indicating a moderate resistance to prolonged drought. However, when the drought ceased, the composition and co-occurrence patterns of soil microbial communities immediately recovered to that in the control, implying a high resilience. To further investigate the ecological roles of soil microbial communities in response to increasing weather persistence, we set up grassland mesocosm experiments. In these experiments, precipitation frequency was adjusted along a series, ranging from 1 to 60 consecutive days alternating of dry and wet periods, while keeping the total precipitation constant. Our results show that microbial community assembly tended to be more stochastic processes at intermediate persistence of dry and wet alternations while more deterministic processes dominated at low and high persistence within 120 days regime exposure. Moreover, more persistent precipitation reduced the fungal diversity and network connectivity but barely impacted that of bacterial communities. The prior experiences of persistent weather events for one year caused legacy effects. The soil microbial legacy induced by soil microbial communities subjected to prior persistent weather events was more enduring in subsequent fungal communities than bacterial communities, likely due to slower growth of fungi compared to bacteria. However, a minor effect of soil microbial legacy  was observed on plant performance. In addition, we kept the grassland mesocosm experiment for two growing seasons. The effects of precipitation persistence on soil microbial communities increased in the second year. The dissimilarities of microbial communities between the first and second year were less with more persistent precipitation, potentially resulting in more vulnerable microbial communities, due to some taxa disappearing and a reduction in functional redundancy under more persistent weather. To conclude, our findings provide a comprehensive theoretical understanding of soil microbial communities in response to the current and future climate change, drawing from both natural and experimental systems. It helps in predicting and managing the impacts of future climate change on ecosystems mediated by microbial communities. Additionally, the findings of microbe-mediated legacy effects on grassland ecosystems can provide practical guidance for their application in agriculture, specifically for using an inoculum to mitigate the impacts of climate change.

Abstract: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.

Abstract: Artificial photosynthesis of H2O2, an environmentally friendly oxidant and a clean fuel, holds great promise. However, improving its efficiency and stability for industrial implementation remains highly challenging. Here, we report the visible-light H2O2 artificial photosynthesis by digging pro-superoxide radical carbon vacancies in three-dimensional hierarchical porous g-C3N4 through a simple hydrolysis-freeze-drying-thermal treatment. A significant electronic structure change is revealed upon the implantation of carbon vacancies, broadening visible-light absorption and facilitating the photogenerated charge separation. The strong electron affinity of the carbon vacancies promotes superoxide radical (O-center dot(2)-) formation, significantly boosting the H2O2 photocatalytic production. The developed photocatalyst shows an H2O2 evolution rate of 6287.5 mM g(-1) h(-1) under visible-light irradiation with a long cycling stability being the best-performing photocatalyst among all reported g-C3N4-based systems. Our work provides fundamental insight into highly active and stable photocatalysts with great potential for safe industrial H2O2 production.

Abstract: The pursuit for the next generation of nanodevices made scientists focus the attention to two dimensional materials. Experimental works of two dimensional materials are hardly free of structural defects, which, in turn, modify drastically the physical properties of its defect-free counterpart. In this work the presence of structural defects is study in two different materials. First, the dependence of the Hall, bend and longitudinal resistances to a perpendicular magnetic field and to vacancy defects in a four-terminal phosphorene single layer Hall bar is investigated. A tight-binding model in combination with the Landauer-Büttiker formalism is used to calculate the energy spectrum, the lead-to-lead transmissions, and the Hall and bend resistances of the system. It is shown that the terminals with zigzag edge orientation are responsible for the absence of quantized plateaus in the Hall resistance and peaks in the longitudinal resistance. A negative bend resistance in the ballistic regime is found due to the presence of high- and low- energy transport modes in the armchair and zigzag terminals, respectively. The system density of states, with single vacancy defects, shows that the presence of in-gap states is proportional to the number of vacancies. Quantized plateaus in the Hall resistance are only formed in a sufficiently clean system. The effects of different kinds of vacancies in the regime where the quantized plateaus are destroyed and a diffusive regime appears in the bend resistance are investigated. Next, we explore effects due to point defect clustering on the electronic and transport properties of bilayer graphene nanoribbons, for AA and AB stacking and zigzag and armchair boundaries, by means of the tight-binding approach and scattering matrix formalism. Evidence of vacancy concentration signatures exhibiting a maximum amplitude and an universality regardless of the system size, stacking and boundary types, in the density of states around the zero-energy level are observed. Our results are explained via the coalescence analysis of the strong sizeable vacancy clustering effect in the system and the breaking of inversion symmetry at high vacancy densities, demonstrating a similar density of states for two equivalent degrees of concentration disorder, below and above the maximum value.

Abstract: Supershapes are used in Parametric Design to model, literally, thou-sands of natural and man-made shapes with a single 6 parameter formula. However, users are left to probe such a rich yet dense collection of supershapes using a set of independent 1-D sliders. Some of the formula’s parameters are non-linear in nature, making them particularly difficult to grasp with conventional 1-D sliders alone. VR appears as a promising setting for Parametric Design with supershapes since it empowers users with more natural visual inspection and shape browsing techniques, with multiple solutions being displayed at once and the possibility to design more interesting forms of slider interaction. In this work, we propose VR shape widgets that allow users to probe and select supershapes from a multitude of solutions. Our designs take leverage on thumbnails, mini-maps, haptic feedback and spatial interaction, while supporting 1-D, 2-D and 3-D supershape parameter spaces. We conducted a user study (N = 18) and found that VR shape widgets are effective, more efficient, and natural than conventional VR 1-D sliders while also usable for users without prior knowledge on supershapes. We also found that the proposed VR widgets provide a quick overview of the main supershapes, and users can easily reach the desired solution without having to perform fine-grain handle manipulations.

Abstract: The interaction of diatoms with sunlight is fundamental in order to deeply understand their role in terrestrial ecology and biogeochemistry, essentially due to their massive contribution to global primary production through photosynthesis and its e↵ect on carbon, oxygen and silicon cycles. Following the journey of light through natural waters, its propagation through the intricate frustule micro- and nano-structure and, finally, its fate inside the photosynthetic machinery of the living cell requires several mathematical and computational models in order to accurately describe all the involved phenomena taking place at di↵erent space scales and physical regimes. In this chapter, we review the main analytical models describing the underwater optical field, the essential numerical algorithms for the study of photonic properties of the diatom frustule seen as a natural metamaterial, as well as the principal models describing photon harvesting in diatom plastids and methods for complex EM propagation problems and wave propagation in dispersive materials with multiple relaxation times. These mathematical methods will be integrated in a unifying geometric perspective.

Abstract: The nonreciprocal charge transport property which depends on the polarity of the applied current, such as the diode effect and the rectification effect, is of great importance for both theoretical research and engineering application. The nonreciprocal transport property in superconductors generally requires to break both the spatial inversion symmetry and the time-reversal symmetry, and therefore becomes one of the fundamental issues in superconductivity. Of particular interest, the superconducting diode effect, which exhibits one-way superconductivity, can potentially be applied to dissipationless diode devices, as a consequence has received extensive attention in recent years. In this Ph. D thesis, we simulate vortex dynamics with heat dissipation by numerically solving time-dependent Ginzburg-Landau equations and heat transfer equation. The nonreciprocal transport properties of the following three superconducting systems are studied. We study a superconducting film patterned with a conformal pinning array and find a giant rectification effect which is consistent with the experimental observation. In presence of the funneling effect due to the geometry of the conformal pinning array, Joule heating of the accumulating vortices creates hot spots and drives the sample to the normal state. Meanwhile, the density gradient of vortex does not match the gradient of pinning. The two mechanisms together lead to the giant rectification effect. We study the nonreciprocal charge transport property in a pinning-free superconducting nano-ring. We systematically calculate the response of the ratchet signal to various parameters in both D.C. and A.C. currents. By analyzing the vortex potential, we find that the nonreciprocal transport property is caused by the asymmetry potential barriers for vortex entry and exit. We study a superconductor/nanoscale-magnetic-dot hybrid structure. It takes advantage of the external current to control the nucleation of vortex-antivortex pairs, and can produce superconducting diode effect without applied magnetic fields. Our vortex dynamics simulation details the progress of the superconducting-normal phase transition due to motion of vortex pairs and heat dissipation. The nonreciprocal transport properties of the above three systems are all based on the broken symmetry of spatial inversion, which is caused by the anisotropic pinning array, the asymmetric geometry, and the nonuniform distribution of the magnetic field, respectively. The mechanisms we discuss in this thesis do not require special property of the materials and thus can be applied to any kinds of conventional superconductors. The present studies would provide solid theoretical basis for the future design and application of the dissipationless superconducting devices.