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: 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: Biological membranes are under constant attack of reactive oxygen and nitrogen species (RONS), which may lead to a complex mixture of nitro-oxidized lipids that are responsible for structural and dynamic changes on the membrane. Because of that, nitro-oxidized lipids are also associated with several tumors and inflammatory and neurodegenerative diseases. Moreover, lipid oxidation may induce membrane phase-separated domains, which also drastically affect the membrane function. Evidence suggests that domain interfaces are “hot spots” for pore formation, but the underlying mechanisms remain elusive. There is an urgent need for an improved understanding of oxidation-induced phase separation on membrane properties. Likewise, the molecular structure at domain interfaces still needs to be elucidated. To evaluate the effect of lipid nitro-oxidation on the permeability of single-phase (homogeneous) and phase-separated (heterogeneous) phospholipid bilayers (PLBs), we performed atomistic molecular dynamics (MD) simulations using: (1) single-phase PLBs composed of several isomers of nitrated and/or oxidized lipids; (2) phase-separated PLBs composed of coexisting liquid ordered (Lo) and liquid disordered (Ld) domains, where the Ld domain is composed of non-oxidized and/or oxidized lipids. Our results show that nitrated lipids increase the membrane permeability of single-phase PLBs by three-fold compared to oxidized lipids. In addition, we show that oxidized lipids in the presence of nitrated lipids decrease the membrane permeability, suggesting an interaction between nitrated and oxidized lipids. Overall, the permeability of single-phase and phase-separated PLBs was comparable, and the presence of oxidized lipids increases the membrane permeability only in single-phase PLBs. Despite the latter, the presence of only 1.5% of lipid aldehydes at the Lo/Ld domain interfaces of phase-separated PLBs was able to increase the membrane permeability. In consequence of this, we also performed coarse-grained MD simulations to evaluate whether lipid aldehydes have a preference to accumulate at the interface between Lo/Ld domains. Our results show that lipid aldehydes derived from mono-unsaturated lipids accumulate at the interface, but those derived from poly-unsaturated lipids remain in the Ld domain. This study is of interest for photodynamic therapy and plasma medicine for cancer treatment, to understand the effects caused by RONS in cell membranes.

Abstract: Ammonia (NH3) synthesis is crucial for the production of artificial fertilizer and is carried out through the Haber-Bosch process. With an energy consumption of 30 GJ/t-NH3 and the emission of 2 kg-CO2/kg-NH3, ammonia is the chemical with the largest environmental footprint. Haber-Bosch operates under high pressure and high temperature conditions. Plasma technology potentially allows greener ammonia production. Dielectric barrier discharges are a popular plasma source in which a catalyst is easily incorporated. The combination of plasma and catalyst can circumvent the harsh reaction conditions of the Haber-Bosch process. Plasma kinetics modelling is used to gain insight into the mechanisms of such plasma-catalytic systems. Special attention is given to the instantaneous power absorbed by the electrons, the relevant fraction of the microdischarges and the discharge volumes. The importance of vibrational excitation is investigated. Depending on the exact discharge conditions, it was found that both the strong microdischarges and vibrational excitation can be simultaneously important for the ammonia yield. The temporal behavior of filamentary dielectric barrier discharges was explicitly taken into account. Ammonia was found to decompose during the microdischarges due to electron impact dissociation. At the same time atomic nitrogen and other excited species are created. Those reactive species recombine to ammonia in the afterglow through various elementary Eley-Rideal and Langmuir-Hinshelwood surface reaction steps with a net ammonia gain. Finally, the concept of the fraction of microdischarges was generalized. It directly represents the efficiency with which the applied electric power is transferred to each individual particle in the plasma reactor. It is argued that any type of spatial or temporal non-uniformity of the plasma will cause unequal treatment of the gas molecules in the reactor, corresponding to a lower efficiency at which the power is transferred to the gas molecules. All of those insights aid in an increased understanding of plasma-catalytic ammonia synthesis as a potential green chemistry solution to the synthesis of ammonia on small scale.  

Abstract: Ever since the industrial revolution, the emission of greenhouse gasses dramatically increased, resulting in high CO2 concentration in the atmosphere. The electrochemical conversion of CO2 to value added products, such as carbon monoxide, formic acid, methane, ethylene and ethanol is a very promising strategy to inhibit CO2 emissions. Nevertheless, at the moment, the electrochemical CO2 reduction (eCO2R) is not yet industrially viable, mainly due to the lack of good electrocatalysts. On the other hand, core-shell nanoparticles (NPs) have emerged over the last couple of years as promising candidates. It is believed that bimetallic enhancement effects are behind the improved performance of these core-shell NPs when compared to the individual metals. Although widely investigated, there are still some remaining issues and/or open questions. Indeed, the development of a robust and straightforward synthesis method along with fundamental insight into their resistance towards electrochemical stress remains absent. A good control over morphology, size and composition is key in determining which properties are beneficial for the eCO2R. Since these catalysts are designed to be implemented in electrolyzers, they have to maintain long-term performance. This makes the design of a reproducible method, unveiling structure-performance relationships the effect of electrochemical stress, a crucial aspect. Exploring and modifying existing synthesis methods, have led to the acquisition of a robust and reproducible synthesis method where thermal decomposition of the Cu core is combined with the galvanic replacement of Ag in organic solvents. The implementation of this method has led to the design of a wide variety of Cu-Ag bimetallic NPs and enabled to investigate their composition-selectivity profile. Introducing Ag on Cu suppressed hydrogen and increased the CO formation. CO production was boosted by using Cu@Ag core-shells and was promoted even more by changing the type of electrolyte. As these nanoparticles suffered from degradation, the 3D mapping of the structural changes of Cu@Ag core-shells under operating conditions led to the hypothesis of a two-step degradation mechanism where initially Cu leaching was observed with the subsequent sintering of the Ag shells. One approach to avoid this electrochemical degradation, investigated in this research, was the application of an ultrathin carbon layer to protect the active layer. This ultrathin carbon layer operated as a protective layer, suppressing hydrogen production and increasing the stability of the electrocatalyst. In conclusion, the product selectivity can be tuned by using different Cu-Ag bimetallic nanoparticles synthesized through a robust method. Their unique degradation pathway of Cu@Ag core-shell nanoparticles has led to the proposition of a more accurate stabilization strategy. These findings can contribute significantly in the quest for improved electrocatalysts for the eCO2R.

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: 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: Irradiation assisted stress corrosion cracking (IASCC) is an intergranular cracking effect which can occur in heavily irradiated internal structural components of nuclear reactor cores. It is a complex phenomenon which is not yet fully understood because it occurs through an interplay of several material degradation processes. The factors that influence IASCC susceptibility include irradiation damage (neutrons and other irradiation particles stemming from the nuclear fission reaction), the operating temperature of the nuclear reactor, water corrosion, operating stresses, and the composition of materials susceptible to IASCC. Such materials are typically fabricated from austenitic stainless steels because of their relatively high strength, ductility, and fracture toughness. However, besides excellent metallurgical and corrosion resistant qualities, the operating conditions may still cause severe material degradation and component failure, which is extremely important for nuclear power plant safety and lifetime managements. Despite much accumulated data in the literature, both crack initiation and crack propagation mechanisms still need to be further elucidated. To that end, a probabilistic fracture model entitled the subcritical crack propagation (SCP) was recently developed, which assumes that the oxidized part of stainless steel in front of the crack plays an essential role in the crack initiation and crack propagation in sample failures. Still, despite a very good agreement with experimental observations, the SCP model but also other contemporary models favoured within the literature, require further experimental verification to what concerns the investigation of (IA)SCC. To that end, the main objective of this doctorate was to utilize experimental instrumentations like SEM, FIB-SEM and (S)TEM to conduct the investigation of the crack initiation and propagation processes in both tested and industrial specimens. Some of the investigated materials were retrieved within a nuclear reactor and are thus considered as unique test material to investigate the material degradation processes relevant for cracking. Other specimens were tailor-made to simulate the cracking processes of irradiated materials in otherwise un-irradiated materials. The newly acquired experimental results in this doctorate help rationalize existing models and methodologies used in the literature to analyse the IASCC failures of structural materials of reactor components. These results also facilitate in the development of predictive methodologies and mitigation strategies towards IASCC cracking and provide more information on IASCC from a microstructural perspective.

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: 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.