Abstract: Polarons are quasiparticles emerging in materials from the interaction of extra charge carriers with the surrounding atomic lattice. They appear in a wide va- riety of compounds and can have a profound impact on their properties, making the concept of a polaron a central and ubiquitous topic in material science. Al- though the concept is known for about 75 years, the origin of polarons is not yet fully elucidated. This thesis focuses on WO 3 as a well-known prototypical system for studying polarons, which inherent polaronic nature is linked to its remark- able electrical and chromic properties. The primary objective of this research is to provide a comprehensive atomistic description and understanding of polaron formation in WO 3 using first-principles density functional theory (DFT) calcula- tions. Additionally, the investigation explores the interactions between polarons and the possibility of bipolaron formation. Following a systematic strategy, we first extensively analyze the dielectric and lattice dynamical properties of WO 3 in both the room-temperature P 2 1 /n and ground-state P 2 1 /c phases. Our specific focus is on characterizing the zone-center phonons, which serve as the founda- tion for identifying the phonon modes involved in the polaron formation and charge localization process. Subsequently, we examine the impact of structural distortions on the electronic structure of WO 3 to elucidate the interplay between structural distortions and electronic properties, thereby laying the groundwork for understanding electron-phonon couplings. By incorporating these critical fac- tors, we address our primary research goals. The most common explanation for the polaron formation is associated with the electrostatic screening of the extra charge by the polarizable lattice. Here, we show that, even in ionic crystals, this is not necessarily the case. We demonstrate that polarons in this compound arise primarily from non-polar atomic distortions. We then unveil that this unexpected behavior originates from the undoing of distortive atomic motions, which lowers the bandgap. As such, we coin the name of anti-distortive polaron and validate its appearance through a simple quantum-dot model, in which charge localization is the result of balancing structural, electronic, and confinement energy costs. Then, we also study the polaron-polaron interaction and present the formation of the antiferromagnetic W 4+ bipolaronic state with relatively large formation energy. Our analysis of the W 4+ bipolaronic distortions on the global structure reveals the same behavior as in experiments where the highly distorted monoclinic phase transforms into a tetragonal phase as a function of doping. Additionally, leveraging our previous findings on asymmetric polaronic distortion and examin- ing different merging orientations, we stabilize the antiferromagnetic W 5+ -W 5+ bipolaronic state with an energy lower than the W 4+ state. This thesis clari- fies the formation of unusual medium-size 2D polarons and bipolarons in WO3,which might be relevant to the whole family of ABO 3 perovskites, to which WO 3 is closely related. The simplicity of the concept provides also obvious guidelines for tracking similar behavior in other families of compounds.

Abstract: Air pollution is proclaimed by the World Health Organiaation (WHO) as the biggest environmental threat to human health. Street canyons, or urban roads flanked by a continuous row of high buildings on both sides, are perceived as typical bottleneck areas for air quality due to their lack of natural ventilation. This doctoral thesis aims to integrate expert knowledge on in-canyon flow fields and pollution dispersion in street canyons from the specialized field of (bio)engineering into the field of urban planning and vice versa. In Chapter 1, a Geospatial Information System (GIS) method was developed to detect exposure zones and hotspot street canyons. A critical combination between aspect ratio (AR > 0.65) and traffic volume (TVmax > 300) was detected and subsequently used to detect hotspot street canyons in three major European cities (Antwerp, London and Paris). Chapter 2 focusses on acquiring in-depth knowledge on flow and concentration fields in street canyons by conducting an extensive literature review on over 200 studies and translates this knowledge into nineteen guidelines and eleven spatial tools, comprised in a toolbox for urban planning. Subsequently, computational fluid dynamics (CFD) was used into a research trough design process (Chapter 4) to illustrate how the design tools can be applied to a specific case study (Belgiëlei, Antwerp). Alternations to traffic lanes (traffic lane reduction and lateral displacement) combined with low boundary walls (LBWs), were found to reduce NO2 levels in the entire pedestrian area up to – 3.6 % and peak pollutions were reduced by -8 %. A maximum NO2 reduction was reached by combining a traffic lane displacement with hedges, adjustments to the tree planting pattern and an increased ground-level permeability, leading to reductions up to – 4.5 % in the pedestrian areas. In conclusion, urban design was found to be a valuable tool to enhance the effect of emission reduction strategies and draw in-canyon concentrations closer to the value of the background concentration. However, the background concentration seemed to dominate the efficiency of the urban design interventions and therefore, additional measures should be taken to reduce background pollution levels. This dissertation aims to contribute to the awareness of air pollution in street canyons, as well as support local governments in taking action by delivering spatial tools and guidelines applicable for urban planning and represents a framework for the dissemination of expert information on air quality in street canyons to the field of urban planning.

Abstract: Singlet molecular oxygen (1O2) has continuously attracted researchers' interest because of its involvement in various processes, such as in photodynamic reactions in biological and chemical systems. 1O2 is an effective electrophile and potent oxidizing agent and can be easily generated by photosensitization via the illumination of organic dyes with visible light. As described in Chapter 1, 1O2 has gained prominence in various applications such as wastewater treatment, photodynamic therapy of cancer, organic synthesis, and recently developed 1O2-based photoelectrochemical (PEC) sensing of phenolic compounds. Phenolic compounds are a potential source of contaminants that originates from industrial effluents and waste products of chemical and pharmaceutical industries. These phenolic compounds pose severe threats to humans and aquatic life after reaching the environment. Therefore, it is imperative to develop photoactive materials that efficiently generate 1O2 and oxidize phenolic compounds and antibiotics. The existing 1O2 generating photosensitizers (PSs) include porphyrins, phthalocyanines (Pcs), subphthalocyanines (SubPcs), and other dyes such as derivatives of xanthene (e.g., Rose Bengal (RB)), and fluorinated boron-dipyrromethene (BODIPYs), and phenothiazinium dyes (e. g. Methylene Blue (MB)) which display long-lived triplet excited state and can be used in 1O2-based applications. This thesis focuses on preparing efficient hybrid materials based on newly synthesized Pcs, different surface area titanium dioxide (TiO2) and plasmonic gold nanoparticles (AuNPs) for their use in the PEC detection of phenolic compounds. The first focus was on developing a fast amperometric method to test the photo-electrocatalytic activity of 1O2 producing PSs dissolved in MeOH based on the redox cycling of an electroactive phenolic compound, hydroquinone (HQ) (Chapter 2). This method of testing PSs does not require the accumulation of a reaction product since the amperometric signal develops near instantly when the light is on, which enables dynamic monitoring of a PSs activity at varying conditions in a single experiment. This method was crucial to measure high 1O2 quantum yield and low yield in the same experimental conditions. Moreover, the obtained results revealed a range of working parameters affecting the PEC activity of PSs. The next goal was to immobilize tert-butyl substituted aluminum Pc (t-BuPcAlCl) on the solid support, which showed a high 1O2 quantum yield. However, before immobilizing Pc on a solid support such as TiO2, it is essential to know the electronic energy level of Pcs for the possible electron transfers from Pcs to TiO2. Therefore, Chapter 3 explored the (spectro)electrochemical properties of t-BuPcAlCl Pc. Next, in Chapter 4, t-BuPcAlCl Pc and other tert-butyl substituted Pcs with Zn central metal, t-BuPcZn, and its metal-free derivative t-BuPcH2 were immobilized on different surface area TiO2. The PEC activity of immobilized Pcs on TiO2 toward different phenols and antibiotics was studied, and the action mechanism was revealed and compared with sterically hindered fluorinated Pc F64PcZn. In the final part of this thesis plasmonic AuNPs were introduced combined with trimethylsilane-protected acetylene functionalized ZnPc (TMSZnPc) to study the synergistic effect that boosts the overall activity toward the detection of phenols under visible light illumination (Chapter 5) . The TMSZnPc was coupled with AuNPs via a click chemistry approach. The 1O2 quantum yield of TMSZnPc improved significantly after conjugating with AuNPs, and, subsequently, the PEC activity for detecting HQ. The theoretical and experimental investigation demonstrated that the plasmonic enhancement of TMSZnPc is driven by the near-field mechanism. This shows the importance of plasmonic AuNPs with other photoactive species for their use in 1O2-based applications. The fundamental knowledge obtained in this doctoral study will ultimately deepen the understanding of developing 1O2-based PEC sensors for detecting phenolic compounds and pharmaceuticals in the wastewater stream, helping to choose efficient materials and, in the last instance, a more sustainable future especially access to clean water for everyone.

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: Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification. ,

Abstract: This work reports the first study on the possible application of nanodiamond-derived onion-like carbons (OLCs), in comparison with conductive carbon black (CB), as an electrode platform for the electrocatalytic detection of tramadol (an important drug of abuse). The physicochemical properties of OLCs and CB were determined using X-ray diffraction (XRD), Raman, scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET), and thermogravimetric analysis (TGA). The OLC exhibits, among others, higher surface area, more surface defects, and higher thermal stability than CB. From the electrochemical analysis (interrogated using cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy), it is shown that an OLC-modified glassy carbon electrode (GCE-OLC) allows faster electron transport and electrocatalysis toward tramadol compared to a GCE-CB. To establish the underlying science behind the high performance of the OLC, theoretical calculations (density functional theory (DFT) simulations) were conducted. DFT predicts that OLC allows for weaker surface binding of tramadol (Ead = -26.656 eV) and faster kinetic energy (K.E. = -155.815 Ha) than CB (Ead = -40.174 eV and -305.322 Ha). The GCE-OLC shows a linear calibration curve for tramadol over the range of similar to 55 to 392 mu M, with high sensitivity (0.0315 mu A/mu M) and low limit of detection (LoD) and quantification (LoQ) (3.8 and 12.7 mu M, respectively). The OLC-modified screen-printed electrode (SPE-OLC) was successfully applied for the sensitive detection of tramadol in real pharmaceutical formulations and human serum. The OLC-based electrochemical sensor promises to be useful for the sensitive and accurate detection of tramadol in clinics, quality control, and routine quantification of tramadol drugs in pharmaceutical formulations.

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

Abstract: The recent advantages of the fabrication of artificial nanochannels enabled new research on the molecular transport, permeance, and selectivity of various gases and molecules. However, the physisorption/chemisorption of the unwanted molecules (usually hydrocarbons) inside nanochannels results in the alteration of the functionality of the nanochannels. We investigated contamination due to hydrocarbon molecules, nanochannels made of graphene, hexagonal boron nitride, BC2N, and molybdenum disulfide using molecular dynamics simulations. We found that for a certain size of nanochannel (i.e., h = 0.7 nm), as a result of the anomalous hydrophilic nature of nanochannels made of graphene, the hydrocarbons are fully adsorbed in the nanochannel, giving rise to full uptake. An increasing temperature plays an important role in unclogging, while pressure does not have a significant role. The results of our pioneering work contribute to a better understanding and highlight the important factors in alleviating the contamination and unclogging of nanochannels, which are in good agreement with the results of recent experiments.

Abstract: We report a high-throughput first-principles characterization of the structural, mechanical, electronic, and vibrational properties of tetragonal single-layer transition metal Xenes (t-TMXs). Our calculations revealed 22 dynamically, mechanically and chemically stable structures among the 96 possible free-standing layers present in the t-TMX family. As a fingerprint for their structural identification, we identified four characteristic Raman active phonon modes, namely three in-plane and one out-of-plane optical branches, with various intensities and frequencies depending on the material in question. Spin-polarized electronic calculations demonstrated that anti-ferromagnetic (AFM) metals, ferromagnetic (FM) metals, AFM semiconductors, and non-magnetic semiconductor materials exist within this family, evidencing the potential of t-TMXs for further use in multifunctional heterostructures.

Abstract: This study reports the low temperature and low pressure conversion (up to 160 °C, p = 3.5 bar) of CO2 and H2 to CO using plasmonic Au/TiO2 nanocatalysts and mildly concentrated artificial sunlight as the sole energy source (up to 13.9 kW·m-2 = 13.9 suns). To distinguish between photothermal and non-thermal contributors, we investigated the impact of the Au nanoparticle size and light intensity on the activity and selectivity of the catalyst. A comparative study between P25 TiO2-supported Au nanocatalysts of a size of 6 nm and 16 nm displayed a 15 times higher activity for the smaller particles, which can only partially be attributed to the higher Au surface area. Other factors that may play a role are e.g., the electronic contact between Au and TiO2 and the ratio between plasmonic absorption and scattering. Both catalysts displayed ≥84% selectivity for CO (side product is CH4). Furthermore, we demonstrated that the catalytic activity of Au/TiO2 increases exponentially with increasing light intensity, which indicated the presence of a photothermal contributor. In dark, however, both Au/TiO2 catalysts solely produced CH4 at the same catalyst bed temperature (160 °C). We propose that the difference in selectivity is caused by the promotion of CO desorption through charge transfer of plasmon generated charges (as a non-thermal contributor).

Abstract: Recently, an extremely low lattice thermal conductivity value has been reported for the alkali-based telluride material BaIn2Te4. The value is comparable with low-thermal conductivity metal chalcogenides, and the glass limit is highly intriguing. Therefore, to shed light on this issue, we performed first-principles phonon thermal transport calculations. We predicted highly anisotropic lattice thermal conductivity along different directions via the solution of the linearized phonon Boltzmann transport equation. More importantly, we determined several different factors as the main sources of the predicted ultralow lattice thermal conductivity of this crystal, such as the strong interactions between low-frequency optical phonons and acoustic phonons, small phonon group velocities, and lattice anharmonicity indicated by large negative mode Gruneisen parameters. Along with thermal transport calculations, we also investigated the electronic transport properties by accurately calculating the scattering mechanisms, namely the acoustic deformation potential, ionized impurity, and polar optical scatterings. The inclusion of spin-orbit coupling (SOC) for electronic structure is found to strongly affect the p-type Seebeck coefficients. Finally, we calculated the thermoelectric properties accurately, and the optimal ZT value of p-type doping, which originated from high Seebeck coefficients, was predicted to exceed unity after 700 K and have a direction averaged value of 1.63 (1.76 in the y-direction) at 1000 K around 2 x 1020 cm-3 hole concentration. For n-type doping, a ZT around 3.2 x 1019 cm-3 concentration was predicted to be a direction-averaged value of 1.40 (1.76 in the z-direction) at 1000 K, mostly originating from its high electron mobility. With the experimental evidence of high thermal stability, we showed that the BaIn2Te4 compound has the potential to be a promising mid- to high-temperature thermoelectric material for both p-type and n-type systems with appropriate doping.

Abstract: Understanding the behaviour of vortices under nanoscale confinement in superconducting circuits is important for the development of superconducting electronics and quantum technologies. Using numerical simulations based on the Ginzburg-Landau theory for non-homogeneous superconductivity in the presence of magnetic fields, we detail how lateral confinement organises vortices in a long superconducting nanostripe, presenting a phase diagram of vortex configurations as a function of the stripe width and magnetic field. We discuss why the average vortex density is reduced and reveal that confinement influences vortex dynamics in the dissipative regime under sourced electrical current, mapping out transitions between asynchronous and synchronous vortex rows crossing the nanostripe as the current is varied. Synchronous crossings are of particular interest, since they cause single-mode modulations in the voltage drop along the stripe in a high (typically GHz to THz) frequency range.

Abstract: A high dispersion of the active metal phase of transition metals on oxide supports is important when designing efficient heterogeneous catalysts. Besides nanoparticles, clusters and even single metal atoms can be attractive for a wide range of reactions. However, many industrially relevant catalytic transformations suffer from structure sensitivity, where reducing the size of the metal particles below a certain size substantially lowers catalytic performance. A case in point is the low activity of small cobalt nanoparticles in the hydrogenation of CO and CO2. Here we show how engineering of catalytic sites at the metal–oxide interface in cerium oxide–zirconium dioxide (ceria–zirconia)-supported cobalt can overcome this structure sensitivity. Few-atom cobalt clusters dispersed on 3 nm cobalt(II)-oxide particles stabilized by ceria–zirconia yielded a highly active CO2 methanation catalyst with a specific activity higher than that of larger particles under the same conditions.

Abstract: Bamboo is an important component in subtropical and tropical forest communities. The plant has characteristic long lanceolate leaves with parallel venation. Prior studies have shown that the leaf shapes of this plant group can be well described by a simplified version (referred to as SGE-1) of the Gielis equation, a polar coordinate equation extended from the superellipse equation. SGE-1 with only two model parameters is less complex than the original Gielis equation with six parameters. Previous studies have seldom tested whether other simplified versions of the Gielis equation are superior to SGE-1 in fitting empirical leaf shape data. In the present study, we compared a three-parameter Gielis equation (referred to as SGE-2) with the two-parameter SGE-1 using the leaf boundary coordinate data of six bamboo species within the same genus that have representative long lanceolate leaves, with >300 leaves for each species. We sampled 2000 data points at approximately equidistant locations on the boundary of each leaf, and estimated the parameters for the two models. The root–mean–square error (RMSE) between the observed and predicted radii from the polar point to data points on the boundary of each leaf was used as a measure of the model goodness of fit, and the mean percent error between the RMSEs from fitting SGE-1 and SGE-2 was used to examine whether the introduction of an additional parameter in SGE-1 remarkably improves the model’s fitting. We found that the RMSE value of SGE-2 was always smaller than that of SGE-1. The mean percent errors among the two models ranged from 7.5% to 20% across the six species. These results indicate that SGE-2 is superior to SGE-1 and should be used in fitting leaf shapes. We argue that the results of the current study can be potentially extended to other lanceolate leaf shapes.

Abstract: Chemically synthesized metal nanoparticles with morphological chiral features are known to exhibit strong circular dichroism. However, we still lack understanding of the correlation between morphological and chiroptical features of plasmonic nanoparticles. To shed light on that question, single nanoparticle experiments are required. We performed photothermal circular dichroism measurements of single chiral and achiral gold nanoparticles and correlated the chiroptical response to the 3D morphology of the same nanoparticles retrieved by electron tomography. In contrast to an ensemble measurement, we show that individual particles within the ensemble display a broad distribution of strength and handedness of circular dichroism signals. Whereas obvious structural chiral features, such as helical wrinkles, translate into chiroptical ones, nanoparticles with less obvious chiral morphological features can also display strong circular dichroism signals. Interestingly, we find that even seemingly achiral nanoparticles can display large g-factors. The origin of this circular dichroism signal is discussed in terms of plasmonics and other potentially relevant factors.