Abstract: As natural gas prices proved to be very volatile, sustainable alternatives are highly needed. Water-derived H2 was revealed as a promising substitute, allowing to produce a green energy carrier with a minimum of harmful emissions. Direct splitting of earth-abundant seawater provides an eco-friendly route for the production of clean H2, but is hampered by selectivity and stability issues due to the presence of salts.Photocatalytic seawater splitting is particularly promising for this purpose, as it seems less affected by adversary seawater effects and might rely on free and renewable solar power. Unfortunately, the benchmark photocatalyst, TiO2, still suffers from its low solar light activity. It is only actived upon illumination with energetic ultraviolet light (<5% of the sunlight). In order to broaden the activity window to the visible light, the concept of the 'plasmonic rainbow' was explored. Here, TiO2 is modified with various gold-silver composites that possess the unique optical phenomenon of Surface Plasmon Resonance (SPR). This phenomenon enables the absorption of light at very specific wavelengths, depending on the metal type, size, shape and dielectric environment. The light energy might then be converted into hot carriers, strong local electromagnetic fields and/or heat. By combining multiple composites with various sizes and compositions, a broadband absorption could be obtained, resulting in significantly enhanced activity in photocatalytic model reactions under simulated sunlight. The major disadvantage of these plasmonic nanoparticles is their tendency to oxidize and deactivate. To overcome this, polymer shell stabilization strategies were found to be effective to protect the metal cores. Both conductive and non-conductive polymers were studied. For the former, a mix-and-wait strategy generating polyaniline shells of 2-5 nm was used, whille the latter was based on a Layer-by-Layer approach, allowing (sub) nanometer thickness control. For the actual H2 production experiments, the plasmonic loading was optimized in a pure water:methanol scavenger (7:1) mixture and initially the stabilization strategies proofed to be effective for simulated seawater (0.5M NaCl), even after 2 years. However, in real seawater, the activity decreased drastically due to aggregation of the photocatalyst in the presence of multivalent cations. Finally, facile immobilization strategies using 3D printing showed to be able to yield stable, solar active photocatalyst for real seawater splitting.

Abstract: Humanity feels the urge of shifting to a sustainable society more than at any other time in its history. Electrification of chemical industry plays a key role in this transition. The possibility of producing fertilizers from air using renewable electricity, and simultaneously, no greenhouse gas emission, resulted in an increasing interest toward plasma technology as a solution for electrification of a part of the chemical industry in the past few years. Additionally, the activation of nitrogen molecules by vibrational and electronic excitation reactions in plasma can lead to an energy-efficient process. Last but not least, the modularity (fast on/off characteristic) of plasma technology makes it capable of using intermittent renewable electricity on site for the production of fertilizers using air. All these advantages offered by plasma technology make it a potential solution for the on-site production of fertilizers in small and decentralized plants using air and renewable electricity, which leads to a considerable reduction in fertilizer production and transportation costs. However, industrialization of plasma-based NF suffers from several challenges, including challenges of plasma catalysis for the selective production of desired species, the high energy cost of plasma-based NF compared to current industrial processes, and the design and development of scaled up and energy-efficient plasma reactors for industrial purposes. In the framework of this thesis we have tried to add to the state-of-the-art (SOTA) in plasma-based NOx production and deal with its limitations using a combination of experimental and modelling work.

Abstract: Electron tomography (ET) is an indispensable tool for determining the three-dimensional (3D) structure of nanomaterials in (scanning) transmission electron microscopy ((S)TEM). ET enables 3D characterization of a variety of nanomaterials across different fields, including life sciences, chemistry, solid-state physics, and materials science down to atomic resolution. However, the acquisition of a conventional tilt series for ET is a time-consuming process and thus cannot capture fast transformations of materials in realistic conditions. Moreover, only a limited number of nanoparticles (NPs) can be investigated, hampering a general understanding of the average properties of the material. Therefore, alternative characterization techniques that allow for high-resolution characterization of the surface structure without the need to acquire a full tilt series in ET are required which would enable a more time-efficient investigation with better statistical value. In the first part of this work, an alternative technique for the characterization of the morphology of NPs to improve the throughput and temporal resolution of ET is presented. The proposed technique exploits surface-sensitive secondary electron (SE) imaging in STEM employed using a modification of electron beam-induced current (EBIC) setup. The time- and dose efficiency of SEEBIC are tested in comparison with ET and superior spatial resolution is shown compared to conventional scanning electron microscopy. Finally, contrast artefacts arising in SEEBIC images are described, and their origin is discussed. The second part of my thesis focuses on real applications of the proposed technique and introduces a high-throughput methodology that combines images acquired by SEEBIC with quantitative image analysis to retrieve information about the helicity of gold nanorods. It shows that SEEBIC imaging overcomes the limitation of ET providing a general understanding of the connection between structure and chiroptical properties.

Abstract: With the rapid increase in the speed of new-generation aerospace vehicles, conventional heat-resistant aluminum alloys cannot meet the long-term service of the equipment. Therefore, the development of new high-strength heat-resistant aluminum alloys is of great strategic for the sustainable and high-quality development of industries. Al-Cu-Mg-Ag alloy is an age-hardenable heat-resistant aluminum alloy and has high strength and heat resistance. The addition of alloying elements such as Si and Sc to Al-Cu-Mg-Ag alloy introduces a competitive relationship among the σ-Al5Cu6Mg2, θ′-Al2Cu, and Ω phases. Therefore, a systematic investigation of precipitation behavior and heat resistance of Al-Cu-Mg-Ag-(Si) is essential for guiding the design of high-strength heat-resistant aluminum alloys. Combined characterization testing methods such as scanning electron microscopy, transmission electron microscopy, atom probe tomography, microhardness testing, and tensile testing with simulation calculation methods such as calculation of phase diagram, first-principles calculations, and Ab initio molecular dynamics, the effects of heat treatment processes and element content on the precipitation behavior, mechanical properties, and heat resistance of Al-Cu-Mg-Ag-(Si) alloys were systematically investigated. Furthermore, a multiple interface segregation structure was constructed at the θ′/Al interface, and a new Al-Cu-Mg-Ag-Si-Sc alloy with synergistically improved strength and heat resistance was developed. The main conclusions are as follows: (1) Based on the Kampmann-Wagner-Numerical theory, the relationship between the coarsening rate of the Ω phase and the aging process was analyzed, revealing for the first time that the critical size of Ω phase ( ) under thermal exposure temperature was the key factor determining the coarsening rate of Ω phase during long time thermal exposure heat treatment. After artificial ageing, when the size of Ω phase was smaller than the critical size , the dissolution of smaller Ω phase leaded to a rapid decrease in the number density of Ω phases, thereby reducing the heat resistance of the alloy. When the size of Ω phase was greater than or equal to the critical size , the coarsening rate of Ω phase was consistent, but a larger initial size would result in a larger final size after long-term thermal exposure. Therefore, the closer the size of Ω phase in the alloy is to the critical size under heat exposure temperature, the better the heat resistance of the alloy. (2) A concept of constructing a multiple interface segregation structure at the precipitate/matrix interface was proposed, and based on this concept, a multiple interface segregation structure containing the C/L-AlMgSiCu interfacial phase, newly discovered χ-AgMg interfacial phase, and Sc segregation layer was successfully constructed at the θ′/Al interface. The existence of the multiple interface segregation structure ensured that the designed Al-Cu-Mg-Ag-Si-Sc alloy maintains a yield strength of 400 MPa after thermal exposure at 200 C for 100 h, with a strength retention rate of 97%, creating a new record for the synergistic improvement of strength and heat resistance in aluminum alloys. In addition, combining transmission electron microscopy ex-situ/in-situ characterization with first-principles calculations, it is shown that the χ-AgMg interface phase will be destroyed due to the diffusion of the outer Ag layer during thermal exposure, and gradually dissolve into the matrix, but it can still delay the coarsening behavior of θ′-Al2Cu phase. (3) The criteria for determining whether Ω phase can precipitate are updated in Al-Cu-Mg-Ag-Si alloys with low Mg/Si ratio based on phase diagram thermodynamic calculations and multi-scale structural characterization. When W(Mg)/W(Si) > 1.4 and X(Ag)/X(Mgexcess) > 1, Ω phase can precipitate in Al-Cu-Mg-Ag-Si alloys, where X(Mgexcess) represents the atomic percentage of residual Mg elements after the formation of the AlMgSiCu quaternary precipitate phase C/L phase in the supersaturated solid solution, and the W(Mg) is the mass fraction of Mg in the supersaturated solid solution before artificial ageing. (4) The effects of alloy element content on precipitation behavior and heat resistance of Al-Cu-Mg-Ag-Si alloys were systematically analyzed. Critical conditions for the precipitation of σ-Al5Cu6Mg2 and Ω phase in Al-Cu-Mg-Ag-Si alloys are revealed. Based on calculation of phase diagram results, the conditions for precipitating σ-Al5Cu6Mg2 phase in the alloy are: ① W(Mg)/W(Si) > 1.8; ② W(Cu) > 2.7W(Mg) – 5W(Si). When W(Mg)/W(Si) < 1.8, the alloy is mainly precipitated with C/L/Q′-AlMgSiCu. When W(Cu) < 2.7W(Mg) – 5W(Si), the alloy will generate GPB zone. In addition, W(Ag)/W(Si) > 4 is the critical condition which the Ω phase can the main precipitates in Al-Cu-Mg-Ag-Si alloys. Furthermore, the correlation between precipitate types and heat resistance was summarized, showing that Al-Cu-Mg-Ag-(Si) alloys with Ω phase as the main strengthening phase are more suitable for the preparation of structures with short service time but high temperature, while Al-Cu-Mg-Ag-(Si) alloys with low Mg content and multiple segregation structures are more suitable for structures requiring long-term service at medium to high temperatures. This study, for the first time, combines calculation of phase diagram with multi-scale microstructure characterization, systematically unraveling the effects of element content on precipitation behavior, strength, and heat resistance of Al-Cu-Mg-Ag-(Si) alloys. In addition, a concept of constructing a multiple interface segregation structure at the precipitate/matrix interface was proposed to synergistically improve alloy strength and heat resistance. This work provides theoretical guidance for optimizing the composition and processing of Al-Cu-Mg-Ag-(Si) alloy and regulating the microstructure. Furthermore, it also offers new ideas and theoretical guidance for the development of novel high-strength heat-resistant alloys in other systems.

Abstract: Hydrogen (H2) is expected to become a key molecule in the transition towards a society running on renewable energy. It can be used to store excess renewable energy at peak production moments and release this energy at a later stage when renewable energy production is less. However, storing H2 is challenging due to the low density of this gas. As a solution, Liquid Organic Hydrogen Carriers or LOHC molecules have been proposed in the passed to increase volumetric energy density of H2. LOHC are a class of molecules that have storage sites available, to which the H2 gas can be chemically bounded. The LOHC molecule under investigation was dibenzyltoluene (DBT), which is an oil like liquid, that is easy to transport and poses little fire or explosion risks. To release the H2 from the DBT carrier, via a so-called dehydrogenation reaction, efficient mass and heat transfer is required during the process, since a large volume increase is expected from H2 release and the reaction is endothermic, i.e., a self – cooling process that takes place at temperatures around 300 C. The heat has to be supplied specifically to the active sites of catalyst particles that are present inside the reactor and which enable the dehydrogenation to proceed. For heat transfer limited processes fluidized bed reactors are often used, which is a type of reactor where the particle phase is being agitated by the fluid flow. The research proposed in this work, was to explore via computational fluid dynamics (CFD) simulations the possibilities and challenges of using fluidized bed reactors for the dehydrogenation of LOHC. The model selection required for CFD simulations of a three-phase system was investigated in this work, with a main emphasis on the drag model selection. The CFD modelling study was focused on the use of swirling fluidized bed reactors, since it was hypothesised that the swirling effect could also aid in increased removal of the gas phase from the reaction medium to increase the efficiency of the process. Ultimately, it was shown that the main challenges in the design of fluidized bed reactors will be to create uniform particle distribution inside the reactor. A new design for a dehydrogenation reactor is proposed based on the insights gained in this thesis.

Abstract: Tropical rainforests host an exceptional biodiversity and play a fundamental role in the regulation of global climatic cycles. Soil fungi and bacteria are key players in the transformation and processing of nutrients in terrestrial ecosystems while having an essential role as tree mutualists or antagonists. Still, there are gaps in our understanding of the main variables driving soil microbes on these forests and it is unclear how future climate change scenarios may impact soil microbes and further affect the ecosystem. In this thesis, we first explored the drivers of the microbial community composition in two pristine forests in French Guiana by using amplicon DNA sequencing. The neighboring tree species were found to be a crucial factor influencing the fungal and bacterial community composition at our sites regardless of the season. Additionally, within the environmental factors explored, soil moisture, phosphorus (P) and nitrogen (N) availability were consistently the main soil properties controlling the composition of soil microbial communities. Secondly, as increased nutrient deposition due to anthropogenic activities are expected to affect tropical forests ecosystems N and P availability, a factorial N and P nutrient addition experiment in the same sites was used to assess the effects of changes in the soil nutrient stoichiometry on the soil microbial communities. These results showed that after 3 years of nutrient additions, the bacterial and fungal community composition was affected by both the N and P additions. Besides, the fungal community composition had a stronger response to the nutrient addition, especially when P was added. Moreover, when the nutrient addition effect was assessed in bacteria and fungi with different life strategies, we found different nutrient optima between them. Furthermore, to study the effect of the connection to an existing mycorrhizal mycelium on tree seedlings, I established a mycelium exclusion experiment. Interestingly, we could not detect an effect of the mycorrhizal mycelium exclusion on the seedling N uptake, performance, or fungal community composition in roots after one year. All together this work provides a deeper understanding of the factors influencing the soil microbial communities on these lowland tropical forests, demonstrating that the tree community composition exerts a higher influence on the soil microbial community composition than previously expected. Moreover, our results show that the fungal and bacterial community composition and its relationship with trees in the vicinity is highly dependent on the ecosystem nutrient availability.

Abstract: This dataset contains 1000 simulated nanoparticle-like 3D structures and noisy EDX-like elemental maps based on them. These data are intended to be used for quantitative analysis of data processing methods in (EDX) tomography of nanoparticles and training the data-driven approaches for these tasks. The dataset is structured as follows: voxel_data/clean 3D voxel grid representation of the simulated nanoparticles. Voxel intensities are adjusted so that the total intensity equals 103. All 3D structures have unique identifiers in 0..999 range. The data derived from a 3D structure preserves this unique identifier. sinograms/clean Tilt series of projection images obtained from the corresponding 3D structures over an angular range of -75..75 degrees with a tilt step of 10 degrees to simulate a typical tilt series used in EDX tomography. Total intensity in each projection image equals 103. sinograms/noisy Tilt series of projection images corrupted with Poisson noise and an additional spatially uniform background noise. projections/clean Projection images extracted from the clean tilt series at 0 degrees tilt angle. projections/noisy Projection images extracted from the noisy tilt series at 0 degrees tilt angle. images/clean Visualizations of the clean projections as PNG images with the intensity range adjusted to 0..255 images/noisy Visualizations of the noisy projections as PNG images with the intensity range adjusted to 0..255

Abstract: We placed crystals of different compounds to explore the possibility of fingerprinting them through EELS. Here are representative datasets of 7 different compounds: b-cyclodextrin hexacarboxy cyclohexane tannin TH-15 peptide TH-27 peptide two different forms of piroxicam The datasets were collected at EMAT, using a monochromated FEI Titan3 TEM, within the scope of an EUSMI request. More information as well as analysis methodologies adopted for the data are detailed in the paper: Das et al. “Reliable Characterization of Organic & Pharmaceutical Compounds with High Resolution Monochromated EEL Spectroscopy”, Polymers 2020, 12(7), 1434.

Abstract: Electron Bessel beams have been generated by inserting an annular aperture in the illumination system of a TEM. These beams have passed through a localised magnetic field. As a result a low amount of image rotation (which is expected to be proportional to the longitudinal component of the magnetic field) is observed in the far field. A measure of this rotation should give access to the magneti field. The two datasets have been acquired in a FEI Titan3 microscope, operated at 300kV. The file focalseries.tif contains a series of images acquired varying the magnetic field through the objective lens. The file lineprofile.ser contains a series of images acquired by scanning the beam over a sample with several magnetised nanopillars. For reference, check the associated publication.

Abstract: The determination of the mechanical properties of serpentinites is essential towards the understanding of the mechanics of faulting and subduction. Here, we present the first in situ tensile tests on antigorite in a transmission electron microscope. A push-to-pull deformation device is used to perform quantitative tensile tests, during which force and displacement are measured, while the microstructure is imaged with the microscope. The experiments have been performed at room temperature on beams prepared by focused ion beam. The specimens are not single crystals despite their small sizes. Orientation mapping indicated that some grains were well-oriented for plastic slip. However, no dislocation activity has been observed even though engineering tensile stress went up to 700 MPa. We show also that antigorite does not exhibit an pure elastic-brittle behaviour since, despite the presence of defects, the specimens underwent plastic deformation and did not fail within the elastic regime. Instead, we observe that strain localizes at grain boundaries. All observations concur to show that under our experimental conditions, grain boundary sliding is the dominant deformation mechanism. This study sheds a new light on the mechanical properties of antigorite and calls for further studies on the structure and properties of grain boundaries in antigorite and more generally in phyllosilicates.

Abstract: We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification.  The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to  – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at:                    Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323)

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: Aim: We aimed to assess the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. Location: Globally distributed mountain regions Time Period: 2007-2018 Taxa studied: Plants (linked to their associated mycorrhizal fungi) Methods: We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal-plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Results: Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. Main Conclusions: These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance.

Abstract: Being confronted with increasing and expanding urbanisation and the loss of natural green spaces, our living environment is threatened more and more by the effects of global climate change. Green infrastructure is often thought of as the solution to increase climate resilience and reinforce the quality of the lived environment simultaneously. While the benefits, or ecosystem services, that are generated through green infrastructure have been studied intensively, forces that influence green infrastructure decision-making have been far less subjected to thorough research. In this study a discrete choice experiment was conducted with local decision makers in Flemish municipalities to reveal crucial factors in the decision process applied to green infrastructure projects. Flanders is one of the most densely built regions in Europe, stressing the urgency to understand local spatial decision factors to guarantee green space. 568 decision makers active in the local administration of 235 Flemish municipalities participated in the experiment, set in a hypothetical neighbourhood park. Every choice alternative exists of five attributes: investment cost, maintenance cost, deferred investment, recreational value, and climate impact. We find that barriers hampering Flemish munipalities' GI implementation, differ over size of the municipality: smallers municipalities are more affected by knowledge gaps, while larger municipalities are experiencing prioritization issues. Results from hierarchical Bayes choice models indicate that municipal decisions on green infrastructure are highly – almost solely -cost-driven, rarely consider the full range of benefits, and centre around short-term and immediate arguments. Moreover, interaction models reveal that a municipalities' financial result is a key determinant of its willingness to invest in public greening and consider long term benefits, suggesting that GI is a luxury good. The results expose some of the heuristics in GI decision making and can be used to inform higher authorities on ways to overcome barriers towards informed decision-making and to facilitate GI investment.