Science

Public defences 2021

Attend a phd defence or find the archive of concluded doctoral research

Phase transitions in driven-dissipative many-body quantum systems: Gutzwiller quantum trajectories and a study of mean-field validity - Dolf Huybrechts (08/07/2021)

Dolf Huybrechts


Abstract

Open quantum systems have become subject of intense research in the latest years due to technological and experimental advances and their potential for quantum information applications. An open quantum system is subject to an interaction with its environment with which it can exchange e.g. particles or energy. Usually this type of interaction results in a dissipation of the system’s energy into the environment and a drive is needed to compensate for this loss. The competition of these driving and dissipation processes can result in very interesting physical phenomena, such as phase transitions, that are markedly distinct from their equilibrium counterparts. Subsequently, the theoretical interest in these systems has burgeoned and a plethora of theoretical techniques have been developed. Due to the scarcity of analytical solutions, these are mainly based on numerical simulations. A crucial obstacle to be overcome is the exponential growth in computational resources that is required in a numerically exact approach. As a result, there is a clear need for the development of approximative methods and methods that exploit the symmetries that are present in these systems to allow for a more efficient numerical study.

In this thesis the properties of driven-dissipative quantum systems are studied by resorting to approximative methods based on a factorisation of the system’s state as well as exact simulation methods based on the exploitation of permutational symmetries. Additionally, an efficient method to extract the properties of these systems in the long time limit has been introduced. Our techniques have been applied to the study of the properties of the dissipative XYZ Heisenberg model as well as those of the driven-dissipative Bose Hubbard model, shedding light on the importance of quantum and classical correlations in these systems.


Unravelling the determinants of molecular host-pathogen interactions with machine learning - Pieter Moris (05/07/2021)

Pieter Moris

  • ​05/07/2021
  • 5 p.m.
  • Online PhD defence
  • Supervisors: Kris Laukens & Pieter Meysman
  • Department of Computer Science


Abstract

In this thesis we study the application of data mining and machine learning techniques in the broad context of biomolecular networks. We cover three main topics, each related to a different type of network data, analysis method and underlying research question.

In the first section, we explore a new framework, based on frequent itemset mining and association rule mining, to distil biologically relevant information from host-pathogen protein-protein interaction networks and their annotation data, into a more interpretable format. The technique offers a translation of expert knowledge into a rule-based summary, which also lends itself nicely to visualizations, although it remains challenging to find the appropriate level of granularity for the specific taxonomic subject of interest.

The second module focuses on the well-studied problem of finding subgraph patterns in a bigger graph. Here we build upon earlier work that aims to uncover those subgraphs that are associated with a specific set of nodes of interest. It provides a unique extension to the widely used enrichment analysis methodologies by integrating network structure and functional annotations in order to discern novel biological subgraphs which are enriched in the targets of interest. We present a software package, termed MILES, which adds additional functionality and visualization capabilities to the original work.

The final part of this work is situated in the field of immunoinformatics. The molecular interactions between epitopes and T-cell receptors (TCRs) play an important role in the adaptive immune system. These interactions can also be represented as a network, and we showcase a novel technique for predicting new edges within it. Namely, we employ convolutional neural networks and a feature representation method inspired by image classification to create a generic classification model that can operate directly on the amino acid sequence of the two molecular partners. In addition, we compare validation strategies to assess the generalization performance for both seen and unseen epitopes, as well as discuss various challenges that are inherent to TCR-epitope data. While our method shows promise, it is clear that the open problem of predicting TCR-epitope interaction for unseen epitopes still requires further improvements, especially in terms of the diversity of the available data.

Analysis of Large Scale Randomized Load Balancing Policies - Tim Hellemans (30/06/2021)

Tim Hellemans

  • ​30/06/2021
  • 5 p.m.
  • Online PhD defence
  • Supervisor: Benny Van Houdt
  • Department of Computer Science


Abstract

In the load balancing literature, there has been a lot of interest in policies which balance load based on some information of d randomly selected servers. The analysis of these policies for a finite system is intractable in most cases, therefore one often relies on mean field methods. That is, you assume that all queues are i.i.d. which allows to describe the system's behaviour through the behaviour of a single queue.

Most prior work has focused on load balancing methods which balance the load based on the queue length. While reducing response times, small jobs may still get stuck behind long jobs for these policies. In contrast, our main focus is on policies which employ the actual work present at the servers. While causing additional overhead, these policies do allow to detect all large jobs. This includes policies which either favour servers with a low load, use some form of redundancy, have a memory at the dispatcher, assign jobs in batches,... We additionally consider policies which combine the queue length information with the runtime of the job currently receiving service. This allows us to detect large jobs if they have been receiving service for some time.

For all policies considered we obtain a numerical method to study its performance. We make use of simulations to illustrate the accuracy of the mean field approximation. Moreover, assuming exponential job sizes often allows us to compute performance metrics in closed form. In particular we noticed that by using a proper scaling, we can often obtain simple closed form formulas for the expected waiting time in case the system load is either close to instability or close to zero.


Fast approaches for investigating 3D elemental distribution in nanomaterials - Alexander Skorikov (25/06/2021)

Alexander Skorikov


Abstract

Precise determination of 3D distribution of chemical elements is a problem of key importance for a range of advanced nanomaterials. Examples of such materials are catalysts, semiconductor electronics and nanoparticles with advanced optical properties, where even minute changes in the elemental distribution drastically alter the relevant properties of the material.

Currently, among the best-suited methods to analyze the elemental distribution in materials at the nanoscale are techniques based on a combination of transmission electron microscopy, spectroscopy and tomography, which offer excellent spatial resolution, high elemental sensitivity and the ability to retrieve the full 3D structure of the studied object. Unfortunately, these methods require very long acquisition times, which does not allow to apply them for high-throughput studies, such as statistical analysis of nanomaterials, in industrial settings or for investigating dynamic processes in materials. Moreover, the long exposure to the electron beam damages the materials under investigation, further limiting the applicability of such techniques.

In this thesis, the problem of high acquisition time and electron irradiation dose requirements for 3D analysis of elemental distribution in nanomaterials is approached by developing new improved methods for this task and optimizing the existing methodology for data acquisition and analysis. The utility of the proposed approaches for answering relevant materials science questions is demonstrated and the outlook on the future developments in this field is outlined.

Optical spectroscopy of 1D nanostructures encapsulated inside carbon nanotubes - Miles Martinati (22/06/2021)

Miles Martinati

  • ​22/06/2021
  • 10 a.m.
  • Online PhD defence
  • Supervisors: Sofie Cambré & Wim Wenseleers
  • Department of Physics


Abstract

Carbon nanotubes (CNTs) represent the most ideal system to confine molecules in a 1D nanospace, due to their hollow structure, their smooth and impermeable sidewalls and the precise tunability of their diameter. These unique characteristics can be exploited to study the behavior of atoms and molecules confined in 1D, or to synthesize and stabilize new 1D nanostructures, overcoming the problem of chemical instability in free space. In this thesis, three 1D structures encapsulated inside CNTs are studied, i.e. graphene nanoribbons (GNR@SWCNTs), linear carbon chains (LCC@DWCNTs) and chains of water molecules (water@CNTs), by means of photoluminescence excitation (PLE) spectroscopy and/or wavelength-dependent resonant Raman spectroscopy. In particular, by analyzing the typical Raman modes of the GNRs together with their corresponding resonant Raman profiles (RRP), both the vibrational and the electronic properties of the encapsulated GNRs can be revealed. This enables us to assign the observed Raman modes to two specific structures of GNRs, namely the 6-armchair GNR and the 7-armchair GNR with widths of 0.61 and 0.74 nm and electronic band gaps of 1.83 and 2.18 eV, respectively. A similar wavelength-dependent analysis is used to study the excited vibronic states of two samples of LCC encapsulated inside DWCNTs. In this case, the analysis of the RRP enables to observe multiple Raman resonances and consequently to estimate the energies of the excited vibronic states. Lastly, the properties of 1D chains of water molecules are studied by probing the variation of the optical properties of the surrounding CNTs as a function of temperature with respect to a reference empty CNT sample. The phase transitions of water encapsulated inside four different CNT chiralities, i.e. (6,5), (7,5), (9,4) and (8,6), with diameters smaller than 1 nm, are observed at temperatures between 110 and 150 K, in agreement with the only observation reported so far in this diameter range.



Mixed metal and temperature stress in aquatic environments: establishing functional links across different levels of organisation - Giovanni Castaldo (18/06/2021)

Giovanni Castaldo

  • ​18/06/2021
  • 4 p.m.
  • Online PhD defence
  • Supervisors: Gudrun De Boeck & Ronny Blust
  • Department of Biology


Abstract

Worldwide, aquatic ecosystems are under threat from metal pollution. Natural environments receive a wide variety of compounds and the prediction of mixture toxicity based on the toxicity of single compounds is difficult and shows a certain degree of uncertainty. Moreover, the effects of metal mixtures together with the effect of the temperature on toxicological processes remain very poorly documented. Considering that the temperature is one of the most important driving factors in organismal physiology and a crucial ecological factor, this is surprising.

In this work, common carp (Cyprinus carpio) were exposed via water to copper (Cu (II), zinc (Zn (II)) and cadmium (Cd (II)) in single or mixture exposure scenarios. Differences in the accumulation of these metals were observed, with Cu and Cd accumulating to a greater extent compared to Zn in the analysed tissues. When present together, different metals can interact with each other influencing the uptake, bioaccumulation and toxicity. For instance in our experiments, we observed reduced Cd levels in the gills of common carp simultaneously exposed to Cu and Cd.

Copper was the only metal found to cause an impairment in ion-homeostasis in the single exposure scenarios. In addition, when it is present in mixture scenarios (e.g Cu plus Cd) more marked effects on electrolyte levels (e.g. sodium) can be observed. In the final part of this work we focused on understanding to which extent different temperatures can affect metal mixture toxicity in common carp. In fish exposed to either a low (10 ºC) or high (20 ºC) temperature, both Cu and Cd accumulated in the gills, whereas Zn levels remained stable. However in fish kept at 10 ºC, Cu metal levels in the gills were higher compared to fish exposed at 20 ºC, in contrast to what was observed for Cd. Moreover at 20 ºC, after one week of exposure fish started to eliminate excess Cu. The obtained results suggest that at 20 ºC, fish had more efficient depuration processes for the essential elements Cu and Zn.

Overall, the present thesis provides new insights into the effects of metal ion toxicity when present in mixture scenarios. Moreover, these findings highlight the importance of considering the effect of environmental parameters in designing standard toxicology tests to derive water quality guidelines that are protective for environmentally realistic conditions.

Ecological risk assessment of amphibians in the Phongolo River floodplain - Nicolaas Wolmarans (15/06/2021)

Nicolaas Wolmarans

  • ​15/06/2021
  • 2 p.m.
  • Online PhD defence
  • Supervisors: Victor Wepener, Lieven Bervoets & Patrick Meire
  • Department of Biology


Abstract

The Phongolo River floodplain in South Africa hosts the highest floodplain biodiversity in the country, while also being highly utilised for commercial and subsistence agriculture. The floodplain falls within the malaria risk region where vector control in the form of indoor residual spraying is still practised with dichlorodiphenyltrichloroethane (DDT). This region operates on a fragile socio-ecological balance. Previous studies identified a gap in available knowledge on malaria vector control pesticides and the associated toxicity to amphibians. This study used a tiered assessment approach to assess the risk to amphibian well-being in the Phongolo River floodplain. Ecosystem services were incorporated into the assessment alongside the risk to amphibian well-being to assess the relationship between these aspects. The first tier to this study involved identifying the data requirements, which included sub-lethal effects data regarding amphibians and malaria vector control pesticides along with a lack of current field monitoring data of these pesticide in amphibians. The second tier involved generating field monitoring data. This study showed amphibians from Ndumo Game Reserve in the floodplain actively accumulate DDT at sub-lethal levels. The next tiers in the assessment involved sub-lethal toxicity data generation. This was done through laboratory and simulated field exposures of Xenopus laevis to vector control pesticides. Behaviour, metabolomics and pesticide accumulation was measured as effect outcomes. Behavioural changes were seen in frogs exposed to a mixture of DDT and deltamethrin. Metabolomic changes were mostly attributed to a general stress response affected in all exposures compared to control. Metabolomic responses in the simulated field exposure had low overlap with those found in laboratory exposures, which was attributed to the addition of food sources in the simulated field environment. The mixture exposure of DDT and deltamethrin resulted in significant loss of invertebrate diversity. The final risk assessment incorporated data generated in this study to determine risk levels to amphibians using a relative risk model. Overall amphibian well-being was at moderate risk, driven by the likelihood of chronic or sub-lethal effects from pesticides and high amphibian biodiversity in the region. The aquatic habitats in the floodplain (river, temporary pans, and permanent pans) were identified as priority habitats for conservation in order to benefit socio-ecological functioning and maximise amphibian wellbeing in the process. The outcome of this study supports the use of amphibian well-being as a monitoring tool for the floodplain through amphibian well-being and biodiversity monitoring serving as sensitive indicators of ecological change.

Shaping up oligonucleotides: aptamer-target recognition investigated by native mass spectrometry - Elise Daems (03/06/2021)

Elise Daems

  • 03/06/2021
  • 4 p.m.
  • Online PhD defence
  • Supervisors: Karolien De Wael & Frank Sobott
  • Department of Chemistry


Abstract

Aptamers are short, synthetic DNA or RNA molecules that are characterized by a specific 3D conformation which enables specific target recognition. Aptamers are promising tools in many application fields from sensing to therapeutics. One of the major challenges in the aptamer field is understanding the relationship between the sequence and what determines the higher-order structure and specific interactions with targets. Therefore, this PhD thesis focuses on the use of different mass spectrometry (MS) based approaches to characterize aptamers and their interactions. Several of these approaches are already widely applied to study other biomolecules, such as proteins, but are still largely unexplored for aptamers and oligonucleotides in general.

A first focus was put on obtaining information on the higher-order structure and conformational stability of aptamers using a combination of MS and with ion mobility (IM) spectrometry by performing collision-induced unfolding (CIU) experiments. CIU was shown to hold great promise to analyze the conformational dynamics and gas-phase stabilities of aptamers.

Next, the capabilities and limitations of native IM-MS for the analysis of noncovalent interactions of aptamers were demonstrated. The conformational behavior and interactions of cocaine-binding aptamers were studied and it was found that relative binding affinities of aptamers that only differ slightly in sequence and structure can be determined using native MS. Moreover, native IM-MS allowed the detection of small conformational changes upon binding of a target, which were found to be dependent on the binding mode of the aptamer. An adaptive binding mechanism was suggested for flexible aptamers that require more reorganization upon binding.

In the final part of this thesis, the importance of thoroughly characterizing and validating aptamer-target interactions before using them in an application was emphasized. Moreover, the gathered insights were applied in our own development of a proof-of-concept aptamer-based sensor. This was shown by investigating the interactions of ampicillin aptamers which were found to not bind the target they were selected for in the first place. A multi-analytical approach combining complementary techniques was used for this purpose since no single technique is generally applicable to characterize all aptamers and their interactions and to obtain a comprehensive picture of the aptamer-target interactions. Furthermore, such multi-analytical approach was used to characterize a testosterone-binding aptamer while developing an aptamer-based electrochemiluminescent sensing strategy for this target. This shows the importance of native MS, in combination with other techniques, to thoroughly understand the aptamer-target interactions in the development of a designed application.

Analysis of the food safety and microbial ecology of fermented carrot juice - Wannes Van Beeck (12/05/2021)

Wannes Van Beeck

  • 12/05/2021
  • 5 p.m.
  • Online PhD defence
  • Supervisor: Sarah Lebeer
  • Department of Bioscience engineering


Abstract

Food fermentation is often considered the oldest biotechnology within the world, because it has been used by the Egyptians to preserve fresh food for an extended time. Recently, artisanal (plant-based) fermentations have regained interests by the broad public and haute cuisine chefs, because of their increased organoleptic properties. Fermented carrot juice is an example of such an artisanal vegetable fermentation. Spontaneous fermentations are generally considered as safe, but it was not yet well studied whether pathogens could persist when the fresh produce is highly contaminated. Therefore, we explored the food safety of the spontaneous carrot juice by doing a challenge test with three common food pathogens: Listeria monocytogenes, Salmonella Typhimurium and Escherichia coli O157:H7. These pathogens could survive and persist within the fermentation up to 8 days of fermentation.

A dedicated starter culture could be used to guide and speed up the fermentation and reduce potential pathogen load as early as possible. Traditionally, starter cultures are chosen from isolates from the food product itself (autochthonous), but isolates from others sources (allochthonous) and with additional functionalities could have benefits for the consumer. How and when such allopatric starter cultures could also guide vegetable fermentations such as fermented carrot juice was also not yet widely explored. Starter cultures were chosen from three important genera of the carrot juice fermentation: Leuconostoc, Lactiplantibacillus, and Lacticaseibacillus. Leuconostoc starter cultures had the largest impact on the acidification of the fermentation and resulted in a pH lower than 4.6 after one day of fermentation. This pH of 4.6 is an important food safety threshold. In general, the autochthonous starter cultures belonging to the Lacticaseibacillus and Lactiplantibacillus were able to better guide the fermentation towards a uniform end community than their allochthonous counterparts. There were some exceptions with allochthonous probiotic L. rhamnosus GR-1 being able to persist within the fermentation. Therefore, we subsequently aimed to explore characteristics important for persisting and guiding the carrot juice fermentation using an ecological framework. Biotic factors such as microbial competitions, appeared to be important for persistence in the fermentation whereas abiotic factors such as salt stress also played a role, but their effect was minor.

The results obtained during this PhD have shown that carrot juice fermentation is safe to consume when fermented for at least eight days, but that vegetable fermentations can be further enhanced using dedicated functional starter cultures.

Novel insights and approaches for the analytical characterization of tangible cultural heritage objects - Andrea Marchetti (29/04/2021)

Andrea Marchetti

  • 29/04/2021
  • 1 p.m.
  • Online PhD defence
  • Supervisor: Karolien De Wael
  • Department of Bioscience Engineering


Abstract

Cultural heritage represents the vehicle of our cultural identity, handed over from past to future generations throughout human history. As a repository of fundamental cultural and social values, the preservation of all forms of cultural heritage is a responsibility of every society and of humankind as a whole. When it comes to tangible cultural heritage, preservation of heritage translates into preservation of objects and, therefore, of the materials they are constituted of. This crucial task relies heavily on the application of scientific analytical methods to answer material and conservation-related questions.

The fundamental contribution of this analytical approach led, in the past decades, to an ever-deepening understanding of the factors governing the degradation of cultural heritage. However, the extreme complexity of the heritage object-environment system results in a massive research field, which inevitably presents relevant open questions. This is where the present PhD work comes into play, attempting to fill knowledge gaps in literature by starting from specific case studies and un-answered research questions. 

The multianalytical research conducted during this PhD unraveled fundamental information on the properties governing the reactivity and long-term behavior of different classes of materials, from α-brass in an indoor environment to artists’ pigments in the presence of light, moisture and soluble particulate matter (PM). The paramount importance of the synthesis conditions on the composition, physical properties and reactivity of heritage materials was also demonstrated, in particular for stable lead pyroantimonate and unstable Geranium lake artists’ pigments. Moreover, the study and characterization of specific heritage objects, namely a series of 16th century reliquary altarpieces and the painting L’Arlesienne, by Vincent Van Gogh, allowed to obtain relevant insights into their composition and on potential risks for their conservation. The challenging nature of the samples considered, created the perfect opportunity to test an innovative spectroscopic technique, optical photo-thermal IR (O-PTIR), for the characterization of heritage materials. Striking results were obtained, highlighting a great potential for the application of this non-destructive sub-micron molecular spectroscopy to the analysis of cultural heritage. Finally, in the last section of this work, strategies to implement the continuous monitoring of PM levels in indoor environmental quality studies were also considered, with a particular focus on the identification of environmental hazards for the collections housed in specific conservation environments (War Heritage Institute in Brussels and St. Martin’s church in Aalst, BE). 

Adaptive management of Wi-Fi networks in dynamic and heterogeneous environments - Patrick Bosch (29/04/2021)

Patrick Bosch

  • 29/04/2021
  • 4 p.m.
  • Online PhD defence
  • Supervisor: Steven Latré
  • Department of Computer Science


Abstract

The last two decades brought a phenomenal increase in communication devices, mobile and stationary. The overall number of connected devices went past 18 billion with many available technologies. Two wireless technologies dominate the market space: LTE/5G and Wi-Fi. Other new wireless technologies also rose in popularity. This situation gave rise to new applications that require high bandwidth and low latency.

However, technologies share use cases, devices can not fully use their technologies, and technologies can interfere with each other. Avoiding interference and enabling technology cooperation are major cornerstones of improving user experience. Nevertheless, cooperation can not overcome all obstacles. Estimation and modeling of performance within certain environments are necessary.

Current solutions for integrated technology management are limited. They focus on specific technologies, specific use cases, or have limited management capability. Performance modeling is more common but focuses on interference from other communication technologies, not interference from generic electronic devices. The increasing use of electrical devices multiplies the problem and affects many devices and technologies. This dissertation provides three significant contributions to address these challenges.

The first contribution explores and models IEEE 802.11 systems' performance when an interfering source is present that is not a communication technology. We first explore the performance of IEEE 802.11 in a challenging environment via a wireless mesh network and further in a controlled setup and simulation. We provide two models. The first is based on base performance when no interference is present and is computationally fast. The second is an analytical model that models the entire system's behavior but is computationally expensive.

The second contribution consists of the ORCHESTRA framework, enabling inter-technology management seamlessly to the user and operator. This framework offers interference mitigation by using multiple technologies. It uses technology abstraction through a virtual layer and advanced packet-level functionalities, such as handovers, load balancing, and duplication. A central controller maintains a global view of the network and makes intelligent decisions to improve performance.

 As a third contribution, we present a load balancing solution that normalizes latency for links with different latency properties. Different technologies exhibit different latency properties that cause problems when using packet-level load balancing. We provide a machine learning based normalization method that smooths and reduces latency on a flow. Instead of sending out bursts of packets after reordering, packets are sent with a short time in between to avoid burst behavior.

Towards an Energy-efficient, Responsive and Reliable Industrial Internet of Things - Glenn Daneels (26/04/2021)

Glenn Daneels

  • 26/04/2021
  • 4 p.m.
  • Online PhD defence
  • Supervisors: Jeroen Famaey & Steven Latré
  • Department of Computer Science


Abstract

The Internet of Things (IoT) paradigm is the shift towards a world where all things are connected to the Internet. While nowadays IoT has an impact on every aspect of society, it is being applied particularly efficiently to further revolutionize the automation and control of traditional manufacturing and industrial processes, leading to the term Industrial Internet of Things (IIoT). To fulfill the high-end requirements of IIoT applications, interconnecting all sensing and actuating devices was initially typically done through wiring. While the reliability advantage of wiring is obvious, it is costly and can be impractical in hard to reach locations or mobile machinery. Therefore, the transition to wireless communication seemed unavoidable and is becoming more and more ubiquitous. However, for this transition to be successful, wireless communication should show wire-like reliability in harsh industrial environments that suffer from external interference and multi-path fading effects that may easily disrupt the wireless signal. Additionally, to avoid having to frequently replace batteries in inconvenient places, the wireless devices should be able to run on limited battery capacity for years. Therefore, while required to be highly reliable, they should also exhibit low-power operations. A relatively recent wireless technique that has proven to be successful in fulfilling these requirement, is IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH), that combines frequency diversity with strict time-synchronization, achieving wired-like reliability of more than 99.999% while having ultra-low power consumption.

In this PhD thesis, I study the TSCH Medium Access Control (MAC) layer and how it can be further improved to deploy it successfully in industrial networks. More specifically, I focus on 3 research questions related to the energy consumption, latency and reliability of TSCH networks. First, I investigate how the TSCH power consumption can be precisely characterized. Second, I aim at minimizing the communication delay of recurrent monitoring data that is typical for IIoT applications. Finally, I aim at further improving the industrial network’s overall reliability by introducing a technique to allows multiple physical (PHY) layers simultaneously in a single TSCH network. As such, each device is able to adapt its PHY layer to the link’s propagation characteristics. Additionally, a heuristic is also proposed that helps a device in making an appropriate parent and PHY selection in multi-PHY TSCH networks.

 In summary, this PhD thesis targets an energy-efficient, responsive and reliable TSCH network, thereby contributing to a wireless network deployment that is ready for the IIoT.

Advanced chemical imaging of artworks - Stijn Legrand (19/03/2021)

Stijn Legrand


Abstract

Last century the field of heritage sciences expanded beyond imagination. The inventions of X-ray radiography and infrared reflectography allowed experts to investigate paintings below the surface as well. More recent developments led to the advent of the field of hyperspectral imaging, to which the advanced chemical imaging methods, used in this thesis work, belong. These techniques not only allow to identify the components present in artworks, but also to visualize their distribution over these objects. The resulting distribution maps permit a broader public to interpret the scientific data and to relate these results with the artwork itself.

During this thesis work a range of flat artworks were investigated in a non-destructive manner using mainly two macroscopic imaging techniques: macroscopic X-ray fluorescence scanning and macroscopic Fourier transformed mid-infrared scanning in reflectance mode. The resulting images were sometimes supplemented with microscopic techniques on a minute selection of samples to fully understand the layer build-up, composition and distribution of these materials over the stratigraphy.

Illuminated manuscripts pushed the interpretation of the macroscopic imaging techniques: due to the impossibility of sampling, all answers had to be obtained non-destructively. Documenting masterpieces such as the Ghent Altarpiece by means of chemical imaging techniques, helped the restoration team, assisted by the international commission to make the daring decision of manually removing the non-original paint layers. Scanning stained-glass windows allowed experts to document the panels, create situation reports, identify later infills and guide the restoration process in a more efficient manner.

By initially applying non-destructive imaging techniques, many of the research/conservation questions could already be answered. Based on the resulting distribution maps, only a very limited amount of sampling was required to obtain a representative set to answer the remaining questions. In most cases the combination of multiple methods was necessary to fully understand the situation. A similar trend could be seen in the research field: the collaboration between divergent disciples was often required in order to explain all observations.

In order to completely break through, the scanning speed of these techniques has to increase even more in order to cover an acceptable surface in one workday. Parallel with the operational speed, the (basic) data treatment should also be streamlined more in order to allow a broader user group to access the results. Once these two improvements are carried out, these techniques become accessible to a larger public.


Evolutionary Genomics of Lactic Acid Bacteria - Stijn Wittouck (15/03/2021)

Stijn Wittouck

  • 15/03/2021
  • 5 p.m.
  • Online PhD defence
  • Supervisors: Sarah Lebeer & Vera van Noort
  • Department of Bioscience Engineering


Abstract

Lactic Acid Bacteria (LAB) are responsible for many types of fermented foods and are part of our natural microbiota. The goal of this PhD was to leverage publicly available genomes of LAB to gain new insights into the evolutionary history and habitat-adaptation of these bacteria. To make this possible, important taxonomic and computational challenges were solved.

Three groups of LAB were studied in the thesis. The first was the Lacticaseibacillus casei group: a cluster of closely related species with many applications as oral probiotics and in dairy fermentations, but with much confusion surrounding the classification of strains of the species L. casei, L. paracasei and L. zeae. Based on a comparison of all publicly available genomes from this group, the taxonomic confusion was cleared up, and a number of potentially habitat-relevant properties were identified that could discriminate between the species. For example, genes encoding catalases and putative epithelial adhesins were detected in L. casei genomes, and superoxide dismutase genes were found in L. paracasei genomes. The former were particularly relevant, because an L. casei strain with probiotic potential had previously been isolated from the upper respiratory tract of a healthy individual. Next, the family Lactobacillaceae was studied. For this purpose, a novel computational tool was developed to identify the core genes of a set of genomes in linear time. This tool was used to correct many species-level misclassifications of strains belonging to the family and to suggest mergers and splits of published species. For instance, a merger of the species Weissella thailandensis and Weissella jogaejeotgali was proposed, as well as a split of Ligilactobacillus aviarius. In addition, the genus Lactobacillus was split into 25 smaller genera and the families Leuconostocaceae and Lactobacillaceae were merged based on an analysis that included the use of signature genes to find biologically relevant clades. Finally, a novel tool was developed that could infer a pangenome (the collection of all gene families in a set of genomes) in near-linear time. This tool was then applied to create a pangenome database for the order Lactobacillales, which was subsequently explored to identify some trends in the evolution of these bacteria. For example, it was found that the number of core genes of species changes relatively slowly, and that genes encoding amino acid transporters experienced many duplications in the evolutionary history of the order.

Physiological stress as a mechanism underlying the effects of forest logging on tropical birds - Simone Messina (15/03/2021)

Simone Messina

  • 15/03/2021
  • 2 p.m.
  • Online PhD defence
  • Supervisors: Marcel Eens, David Costantini & David P. Edwards
  • Department of Biology


Abstract

Land-use changes are one main cause of biodiversity loss. Selective logging is the most common technique of timber extraction applied to tropical forests, driving species loss and population abundance changes. One main question to understand species’ responses to selective logging is which proximate mechanisms underlie species abundance changes. In this Ph.D. project I have used a cross-sectional approach to investigate the effects of selective logging on the stress physiology of understorey birds, and correlative analyses to investigate the effects of physiological changes on population abundance, across unlogged and selectively logged forest of Borneo.

The first goal of the project was to determine which physiological endpoints of vertebrates are affected by forest disturbance. To this end, I reviewed all available literature and used meta-analytical techniques to quantify the size of the effects of different forest disturbances, including selective logging, on physiological and immunological parameters.

I have then investigated the effect of selective logging on the activity of the hypothalamic-pituitary-adrenal (HPA) axis in 10 understorey bird species. I used as marker of HPA axis activity the concentrations of corticosterone, the avian glucocorticoid hormone, deposited in feathers.

Another important physiological mechanism for maintaining homeostasis is the regulation of cellular oxidative status. Thus, I measured eight different markers of oxidative status in 15 understorey bird species living either in unlogged and selectively logged forests. I also investigated differences in the oxidative status between feeding guilds (i.e. insectivores and omnivores) and how they are affected by selective logging.

Last, I tested for differences in body size and body condition of more than 50 bird species across unlogged and selectively logged forests. Changes in body size and body condition can be sub-lethal effects of habitat degradation that may act as early signals to predict future population responses. This hypothesis was tested correlating changes in body size and body condition with changes in population abundance between the two types of forest.

Results point to feather corticosterone as a promising tool for monitoring the impacts of sylvicultural practises on understorey birds. There is little long-term effect of logging on the oxidative status of understorey bird species. Last, frugivores and omnivores have reduced body size in the logged forest compared to unlogged, pointing to potential functional consequences related to seed dispersal.

Effects of climate change on growth and development of Berula erecta as model species for freshwater macrophytes - Rosanne Reitsema (26/02/2021)

Rosanne Reitsema

  • 26/02/2021
  • 9 a.m.
  • Online PhD defence
  • Supervisors: Jonas Schoelynck & Patrick Meire
  • Department of Biology


Abstract

Freshwater ecosystems are one of the most diverse, but also one of the most threatened ecosystems in the world. Aquatic macrophytes are highly affected by consequences of climate change like increased concentrations of dissolved organic carbon (DOC) and carbon dioxide (CO2), but also changes in flow dynamics and eutrophication. Knowledge on the effects of DOC and CO2 on macrophytes, and especially their interaction effects with other effects of climate change, is relatively limited. Therefore, the aim of this thesis was to study effects of climate change, like increases in carbon concentrations, using a holistic approach that also focused on their interaction effects with other environmental variables, rather than only studying effects separately.

The main macrophyte species studied in this thesis was Berula erecta (lesser water parsnip). Under natural conditions in a temperate lowland stream, this species was found to be highly variable in its biomass, morphology and nutrient content throughout the growing season, and there were interactions between plant growth (biomass and morphology) and environmental parameters like flow velocity and fine sediment depth.

The effects of climate change were tested in a greenhouse experiment by exposing two macrophytes species, B. erecta and Myriophyllum spicatum to different concentrations of CO2 and DOC in a wide range. The macrophytes responded to both treatments, with the strongest effects in the highest doses. There were large differences between the two species, with regard to growth and morphological responses. Finally, the interaction effects among different aspects of climate change were tested in further greenhouse experiments. In these experiments, B. erecta was exposed to varying combinations of DOC, CO2, flow velocity and nutrients. Those stressors sometimes had opposing effects: CO2 highly stimulated growth, DOC turned the water brown and limited macrophyte growth by shading effects, high nutrient concentrations indirectly limited growth by stimulating the growth of epiphytic algae that shaded the macrophytes, and increased flow velocity led to a more compact growth form.

From this thesis it can be concluded that climate change can have a large effect on macrophytes. Different aspects of climate change often have opposing effects, with many interaction effects occurring among them. Taking all aspects of climate change together, the results from this thesis indicate that submerged macrophytes in temperate lowland streams and rivers will decrease in biomass quantity and quality under continuing climate change. This will in turn have negative consequences for ecosystem processes and organisms that depend on the macrophytes.

The photocatalytic reduction of CO2 with H2 over modified Ti-Beta zeolites - Nick Hoeven (18/02/2021)

Nick Hoeven


Abstract

The earth has been warming up at an unprecedented pace during the last decades, which is majorly caused by increasing greenhouse gases. High CO2 concentrations in the atmosphere led to worldwide awareness of environmentally conscious thinking and acting to reduce this compound and other greenhouse gases. CO2 conversion makes valorization possible through valuable chemicals and fuels. This cradle-to-cradle philosophy is necessary in our current society, both reducing atmospheric greenhouse gases and simultaneously partly responding to the need for alternative fuels. This is fundamental as continuous increase of anthropogenic greenhouse gases are one of the most important issues of this and future generations.

In this thesis, the photocatalytic reduction of CO2 with H2 in the gas phase over modified Ti-Beta zeolites is studied. The goal of this thesis is the development of improved photocatalytic materials for CO2 applications in the gas phase and to overcome limitations posed by the use of TiO2 and classical semiconductors.

Different methods for CO2 utilization and conversion have been discussed. Furthermore, an overview on the mechanism of photocatalysis and the limitations of the use of TiO2, as well as the strategies to overcome those limitations have been described. In particular, the superior photocatalytic activity of isolated tetrahedrally coordinated Ti-species in combination with the high surface area of zeolites has been highlighted. The importance of a well-designed photocatalytic reactor and its influence on the turnover frequencies (TOFs) of the reaction products are also described. The experimental work focusses on the optimization of the synthesis method and the Ti loading of the Ti-Beta zeolites. Next, the synthesized zeolites are tested in a photocatalytic reactor and the influences of the material properties on the product TOFs are discussed. In order to further enhance the photocatalytic properties and the product selectivities of the catalysts, noble metal nanoparticles (Pt and Pd) are deposited onto the Ti-Beta zeolites. Finally, alternative catalysts (e.g. 3D printed structures and Z-scheme catalysts) are tested in the photocatalytic reactor and compared to the highest performing Ti-Beta catalysts.

In conclusion, this PhD has put a step forward in the development of novel and highly active photocatalytic materials, with improved performance compared to classical pure TiO2, for the photocatalytic reduction of CO2 in the gas phase.

Towards co-utilization of CO2 and Fe-rich sources to prepare clinker-free carbonate-bonded monoliths - Sumit Srivastava (15/02/2021)

Sumit Srivastava


Abstract

The main objective of this work was to contribute towards the co-utilization of CO2(g) and residues from metallurgical industries to produce Fe-carbonate bonded monoliths that are free from cement clinker. While excessive CO2 is considered a significant problem due to the increased global warming and its associated effects, Fe-rich metallurgical wastes are still used for low-value applications or are landfilled. Moreover, due to the volume of their use, construction materials production accounts for 7-8% of total CO2-emissions. Therefore, the co-utilization of slag and CO2 to produce construction materials has significant potential to contribute towards achieving future sustainability goals. In this study, Fe(0) is initially chosen as a model system to understand the feasibility of producing FeCO3-bonded monoliths under the desired reaction conditions (<100 °C, and <25 bar CO2-pressure). In addition to demonstrating the feasibility of FeCO3-cementation, the underlying reaction mechanisms are also discussed. Since the dissolution of Fe-sources is usually known to be the rate-limiting step, Fe-dissolution in dilute conditions is studied as a function of temperature, CO2-pressure, and time. Similar to the dissolution studies on Fe(0), dissolution studies in dilute solutions are also extended to the Fe-Si rich non-ferrous slags as a function of temperature, CO2-pressure, and time. In both the studies, it is shown that high temperature and CO2-pressure are conducive towards the dissolution of Fe(0) and Fe-rich slags. To transfer the knowledge of FeCO3-cementation from the model Fe(0) system to the sources in which Fe co-exists with Ca, FeCO3-cementation in CO2-H2O-Fe(0)-Ca(OH)2 systems is also studied. The importance of microstructures of the products, and the formation of mixed (Ca, Fe)-carbonates is pointed in this study. Finally, it is shown that the non-ferrous slags can be co-utilized with ferrous metallurgical slags rich in Ca to produce carbonate-bonded monoliths with high mechanical strength. It is shown that the carbonation of the non-ferrous slags as mixes with ferrous slags can lead to a significant decrease in environmental leaching. With more than 575 million tonnes of metallurgical slags produced every year, they offer an opportunity for significant CO2-mineralization as well as to produce low-carbon construction materials.

Sharing is caring: A Machine-Learning Based Management Framework for Efficient Spectrum Collaboration - Ruben Mennes (08/02/2021)

Ruben Mennes

  • 08/02/2021
  • 4 p.m.
  • Online PhD defence
  • Supervisor: Steven Latré
  • Department of Computer Science


Abstract

Wireless communication technologies became a part of our modern society. Every year the number of wireless devices and wireless technologies increases. Cisco expects that around 25.4 and 42.6 billion wireless devices will be connected to the Internet in 2022. This growth introduces some major challenges. One of these challenges is to use the wireless spectrum, used by all of these wireless devices, more efficient, especially within the radio bands itself.

To meet the demand of more wireless devices and higher throughput, new techniques are necessary to optimise the use of the wireless spectrum. Based on literature, it was expected that collaboration between neighboring wireless networks (from all kind of technologies) can improve the efficiency of the use of the wireless spectrum. Increasing spectrum efficiency can be accomplished in two ways: (i) the improvement of physical transmission, (ii) the use Artificial Intelligence (AI) to improve the decisions made by the wireless nodes. The improvement of the physical transmissions has a direct effect on the efficiency of the use of the spectrum. It is clear that the more efficient data can be transmitted, to improve the bits per Hertz, the less spectrum will be used for the same data. AI, on the other hand, gives us the opportunity make smarter decisions based on the physical limitations of the wireless system and behavior of the environment. The use of AI can also enable the possibility to start and maintain collaboration with other neighboring technologies to improve the efficiency of the wireless spectrum. This dissertation focuses on the contributions made for the AI decision engine for wireless network technologies. Within the context of this dissertation we focus on the use of AI to improve the decisions made by the wireless nodes.

This dissertation provides multiple improvements to enable collaboration for wireless networks, which will lead to a more efficient use of the wireless spectrum. First, we describe a decision-making framework designed to enable AI-enabled algorithms within wireless radio stacks. All other algorithms described in this dissertation are implemented within the framework. Secondly, we present a spectrum prediction algorithm. This prediction algorithm is able to predict the behavior of neighboring wireless networks, even if insufficient information is available. This ability provides us to select better transmission moments. Finally, we introduce the policy-based flow selection algorithm. This algorithm is able to collaborate to improve the Quality of Service and optimize the spectrum footprint. 

Metal pollution and intoxication from artisanal gold mining in Kamituga, Eastern Congo - Bossissi Nkuba (02/02/2021)

Bossissi Nkuba

  • 02/02/2021
  • 4 p.m.
  • Online PhD defence
  • Supervisors: Lieven Bervoets, Sara Geenen & Landry Cizungu (Catholic University of Bukavu)
  • Department of Biology


Abstract

This thesis investigates the use of mercury (Hg) in artisanal small-scale gold mining (ASGM), pollution of aquatic ecosystem by Hg and other metals, and human intoxication by these metals in Kamituga (Eastern Congo).

The first part assesses perceptions on mercury, making use of qualitative data as well as a quantitative survey. It  found that despite existing laws banning Hg use in ASGM, a lack of enforcement leads to widespread use of Hg. Miners use Hg on ore concentrates, thereby limiting Hg pollution. But they use Hg in residential areas and within streams’ watersheds, thus exposing communities and aquatic ecosystems. People are poorly informed on effects of Hg on environment and health. However, the findings include some promising signs, since our respondents prioritize environment and health protection more than economic profit from ASGM.

The second part analyses samples collected on a tributary of the Congo river (Zalya) and its network. It investigates the concentration of  metals in water, sediment, indigenous labeo fish captured in selected streams and in experimentally-exposed tilapia. It found that metal concentration in sediments, unlike in water, often exceeded environmental standards. Indigenous fish from mining-affected streams had higher metal concentration. For experimentally-exposed fish, high mortality was observed but no significant differences in terms of metal accumulation in surviving fish. Water consumers are safe, but fish consumers may be at risk of Hg, Cd and Cr intoxication if their daily consumption exceeds respectively 77, 145 g and 138 g.

The third part analyses the diet, health status and symptoms relatable to metal poisoning of miners and non-miners and compared to metal levels in their blood, urine, nails and hair. It found that many people had Hg levels in their blood, urine, nail and hair as well as concentration of other metals in different tissues above reference value. Miners had higher nail Hg but similar blood, urine and hair had similar Hg levels to non-miners. Prevalence of potential Hg poisoning was equally spread in the community but was higher for people with tilapia-rich diet. Symptoms were not correlated to higher Hg levels, but with other factors such as age and undernourishment.

The thesis recommends raising awareness in the community about dietary and occupational exposure, risks of mercury and quantities of fish that are safe for consumption; increasing formalization of the ASGM sector and capacity of law-enforcement agencies that supervise Hg use in mines; and monitoring of potentially polluted streams.


Chemical transformation of bio-aromatic feedstock into building blocks for the production of bulk and fine chemicals - Jeroen Bomon (02/02/2021)

Jeroen Bomon


Abstract

With the decline of petroleum feedstock, rise of crude oil price and the necessity to reduce CO2 emission, society must innovate to discover new, more sustainable means to meet the needs of an ever expanding world population. The manufacture of products based upon (bio)renewable resources is one of the ways to address this. Particularly, (hemi)cellulose derived products have already been investigated intensively and even found mature applications in industry. However, these bio-polymers do not contain aromatic moieties, preferentially requiring other parts of plant tissue to access these key entities for chemical industry.

In this PhD Thesis, the use of different biorenewable substrates containing aromatic entities were considered for chemical conversion. For example, bio-polymer lignin, Earth’s largest resource of bioaromatic compounds, could serve as suitable feedstock. Several routes are known to depolymerize lignin in low molecular weight monomers, which are described in Chapter 1. In Chapter 2-4, several lignin-derived substrates were transformed into valuable products by defunctionaliztion and functionalization reactions. Next to lignin, also ferulic acid and eugenol, extracted from rice bran and clove, respectively, served as useful substrates.

In Chapter 2, a cheap methodology, only requiring strong acid and hot pressurized water, is presented to defunctionalize these monomers on carbon and oxygen atoms of the alkoxyarene moieties, delivering a hydroxybenzene (phenol, catechol, pyrogallol and derived isomers) as product. Similar conditions, based on the employment of the same strong acid or a heterogeneous alternative, are described in Chapter 3, dealing with selective defunctionalization on oxygen atoms in these monomers, forming C-alkylated hydroxybenzenes. Next to these defunctionalization approaches, functionalization of the considered starting material with nitrogen atoms is described in Chapter 4, since incorporation of this element is highly desired for the production of compounds with pharmaceutical or agrochemical application.

The use of a biorenewable substrate is one of the 12 Principles of Green Chemistry. In order to analyze if the developed reactions with these subtrates can also be considered as “green”, the CHEM21 Green Metrics Toolkit was applied on both our newly developed approaches and on literature procedures delivering the same reaction or product, allowing us to make a useful comparison. The result of this analysis is described in Chapter 5.

The impact of cadmium in the maize leaf growth zone - Jonas Bertels (01/02/2021)

Jonas Bertels


Abstract

Much is known about the impact of cadmium (Cd) stress on plants and the plant’s response to this form of abiotic stress. However, it is remarkable that the impact of Cd in the growth zone of monocotyledonous leaves remained largely unstudied. This growth zone hosts the two cellular processes driving growth, i.e. cell division and cell elongation. The aim of my PhD study was to assess the impact of Cd in this maize leaf growth zone at several biological levels.

We have found that Cd inhibited leaf growth mainly because it results in a significant reduction of cell production. Cells were halted at the G1-S transition of the cell cycle, which increased the cell cycle duration. In addition, when exposed to Cd, growing leaves had a lower number of meristematic cells and therefore less cells are contributing to cell division. In addition, we have found that Cd accumulated highest in the meristematic tissue, indicating that it could impact processes therein directly. To reveal these processes, we have performed a transcriptome study. This resulted in a broad range of Cd affected processes, which led me to perform biochemical analyses of several phytohormones, minerals, two oxidative stress related parameters and carbohydrates. We showed that Cd caused an increase in stress hormone levels (i.e. salicylic acid, abscisic acid and 1-aminocyclopropane 1-carboxylic acid (ACC, an ethylene precursor)) and a decrease of growth promoting hormones (i.e. gibberellin 1 and trans-zeatin riboside). For gibberellin 1, we were able to directly link changes in the spatial distribution of this phytohormone to changes in transcript levels of key gibberellin synthesis and degradation genes. Regarding the measured minerals, we mainly found manganese to be the most strongly and consistently Cd affected nutrient. Lipid peroxidation and antioxidant potential were increased throughout the entire maize leaf growth zone, demonstrating that Cd resulted in oxidative stress in all developmental stages. Lastly, we found that carbohydrates were increased under Cd stress, perhaps in response to oxidative or osmotic stress. 

During my PhD study, we have also published leafkin, an R package that contains four functions which allow the user to perform all calculations in a kinematic analysis of monocot leaf growth. In addition, it allows cell length profiles and leaf elongation rates to be easily extracted, which in turn can be used in separate analyses.


Development of advanced hyperspectral unmixing methods - Bikram Koirala (18/01/2021)

Bikram Koirala


Abstract

Hyperspectral cameras collect the reflected light of materials in hundreds of narrow, contiguous spectral bands in the visible, near and shortwave infrared wavelengths to provide a continuous reflectance spectrum for each pixel. Due to the complex interaction of light with materials, these spectra are highly nonlinear mixtures of the reflectances of the material constituents. The general goal of this thesis is to estimate the composition of materials from reflectance spectra.

Mixing models describe the reflectance spectrum of a material as a (nonlinear) mixture of the constituent materials. The main disadvantage of these models is that the model parameters are not properly interpretable in terms of the fractions. Moreover, not all spectra necessarily follow the same particular mixing model.

Alternatively, the complex mixing effects can be learned using supervised machine learning methods. This requires ground truth training data, in the form of the actual compositions (i.e., the spectra and fractions of the constituents). One major drawback of these strategies is that the estimated fractions do not comply with their physical constraints, leading to a loss of the physical meaning of the estimated parameters. Another disadvantage of the learned models is that they cannot perform well in case training and test spectra are obtained under different environmental conditions or by different sensors, causing spectral variability of the acquired spectra.

In this thesis, a hybrid framework was developed that combines the physical interpretability of a model and the flexibility of data-driven approaches. The general idea is to learn the complex relation between the nonlinear spectra and spectra that follow a particular mixing model by utilizing advanced machine learning regression algorithms. Based on this strategy, a number of different nonlinear unmixing methods were developed:

1) A supervised method that learns a mapping between the nonlinear spectra and the linear mixing model. 

2) A strategy for the estimation of leaf biochemical parameters from leaf reflectance and transmittance spectra, by learning a mapping to a leaf biochemical model (PROSPECT).

3) A semi-supervised method to reduce the number of training samples required to learn the nonlinearities, and additionally does not require the availability of pure pixels. 

4) A robust supervised method for nonlinear spectral unmixing that is invariant to endmember variability.

The impact of long-duration spaceflight on brain structure and function - Steven Jillings (14/01/2021)

Steven Jillings

  • 14/01/2021
  • 5 p.m.
  • Online PhD defence
  • Supervisors: Floris Wuyts, Angelique Van Ombergen, Ben Jeurissen & Athena Demertzi
  • Department of Physics


Abstract

In over half a century of crewed missions to space, many different effects of spaceflight on the human body have been uncovered so far. However, little focus has been directed to investigating how space stressors affect the human brain. The largest body of work in this dissertation describes pioneering findings on brain structural and functional changes after spaceflight in Roscosmos cosmonauts by means of multi-modal magnetic resonance imaging (MRI) in a longitudinal and prospective design. Structural MRI modalities, such as T1-weighted and diffusion MRI, were used to unravel macroscopic volume and microstructural brain tissue composition changes. We found a widespread redistribution of the cerebrospinal fluid (CSF) with secondary mechanistic effects on the grey matter (GM) tissue. We also revealed increased neural tissue volume in motor regions of the brain that suggest evidence for structural brain adaptations, also known as neuroplasticity, associated with altered motor strategies in space. Most CSF changes after spaceflight were still detectable more than half a year after return to Earth, while the GM changes after spaceflight partially reversed in the long term. In addition, functional MRI data was acquired in these cosmonauts to study functional reorganisation of the brain after spaceflight, showing numerous functional connectivity (FC) alterations after spaceflight. Some of these changes persisted in the longer-term, whereas other changes returned back to pre-flight levels. Furthermore, this work also describes the experimental work and preliminary analyses of several Earth-based models. One is a longitudinal MRI pilot study in hindlimb-unloaded (HLU) mice, inducing fluid shifts to the head region, in order to better understand the consequence of these fluid shifts on the brain. A second study was performed in fighter pilots as a model for exposure to high g-levels and sensory conflicts, in which FC was compared to that in a control group. This work rendered a vast increase in available information on structural and functional brain changes after spaceflight compared to several years ago. In the future, the underlying mechanisms of the observed findings need to be understood in more detail. Ultimately, we aim to characterise the effects space stressors have on the brain, to then attempt to mitigate these changes through countermeasures and characterise beneficial coping mechanisms that we can enhance, in order to be fully prepared for future exploration missions into deep space.

Unlocking the Potential of Plasma Catalysis - Yannick Engelmann (12/01/2021)

Yannick Engelmann

  • 12/01/2021
  • 3 p.m.
  • Online PhD defence
  • Supervisors: Annemie Bogaerts & Erik Neyts
  • Department of Chemistry


Abstract

CO2 conversion, CH4 conversion and NH3 synthesis are three essential processes that can help to reduce greenhouse gas emissions. However, these processes typically require harsh reaction conditions when performed thermally, because of the strong chemical bonds of the reactants. Plasma catalysis can provide alternative methods to activating chemical bonds at ambient conditions. Due to the complexity of plasma-catalytic systems, fundamental understanding of the underlying mechanisms is still lacking, impeding the optimization of the technology and holding back its full potential. The aim of this dissertation is to provide fundamental understanding, needed to unlock the full potential of plasma catalysis.

As a tool to acquire the fundamental understanding, we introduced microkinetic modelling to provide detailed information on reaction mechanisms, kinetics and thermodynamics of the processes. In this way, we identified the limitations of thermal processes, but also unraveled if and how plasma-catalytic processes can overcome these limitations. The main difficulty of CO2 hydrogenation is to selectively produce CH3OH at sufficient rates. In plasma catalysis, the contribution of the plasma is twofold: excitation of the reactant molecules, lowering the barrier of dissociation and increasing the conversion rates of the thermal pathways, and generation of reactive radicals and intermediates, allowing new, unique pathways that potentially lead to CH3OH (often in a much faster way).

In the study on the conversion of CH4, we showed the limitations of transition metal catalysts to produce C2-hydrocarbons under thermal conditions. Thermally, the more noble catalysts are not able to dissociate the strong chemical bonds of the CH4 molecule, while the less noble catalysts suffer from cokes formation. In plasma catalysis, dissociation rates on noble catalysts can be increased by vibrationally exciting the reactants, or catalytic dissociation can be avoided by adsorption of plasma-generated radicals. Whether the adsorbed species couple directly to C2-hydrocarbons or undergo further dehydrogenation before coupling, can be controlled by the catalyst binding strength.

Lastly, the potential of the plasma-catalytic NH3 synthesis is locked in the enhanced catalytic rates, caused by plasma-induced excitation and plasma-generated radicals. Again, both vibrationally excited species and plasma-generated radicals are found to improve the NH3 synthesis rates. Due to the contribution of ER reactions, rates are not only increased on noble catalysts, but also on more strongly binding catalysts, making the choice of the catalyst material much less impactful.