Abstract: Particulate matter is one of the most persistent global air pollutants that is causing health problems, climate disturbance and building deterioration. A sustainable technique that is able to degrade soot using (sun)light is photocatalysis. Currently, research on photocatalytic soot oxidation focusses on large band gap TiO2-based photocatalysts and thus requires the use of UV light. It would prove useful if visible light, and thus a larger fraction of the (freely available) solar spectrum, could additionally be utilised to drive this process. In this work, a visible light-active photocatalyst, WO3, is benchmarked to TiO2 under both UV and visible light. At the same time, the versatility and drastic improvement of a recently introduced digital image-based soot degradation detection method are demonstrated. An additional step correcting for non-soot related catalyst colour changes is applied, resulting in accurate detection and quantification of soot degradation for all studied photocatalysts, even for materials such as WO3 that are inherently coloured. With this study, we aim to broaden the scope of photocatalytic soot oxidation technology to visible light-active photocatalyst. Along with this study, we provide a versatile soot degradation detection methodology based on digital image analysis that is made widely applicable.

Abstract: Photoactive nanoparticles and their light-driven applications have gained tremendous scientific attention towards remediation of the global environmental problems, meeting alternative energy demands, and other new technological discoveries. The research work presented in this dissertation includes a fundamental investigation of such nanoparticles to gain deeper insights that will ultimately benefit their application. In particular, the study of plasmonic metal nanoparticles and metal oxide nanoparticles for light driven applications is the major theme of this work. The investigation begins with isolated plasmonic Au and Ag nanoparticles, followed by a natural extension to nanoparticle clusters, and then further to nanoparticle films. Next, the application of such plasmonic nanoparticle films for gaseous phase sensing of volatile organic compounds is explored. Finally, the film formation of metal-oxide nanoparticles by self-assembly is investigated for the fabrication of photoactive functional interfaces. The fundamental theoretical investigation of the isolated plasmonic nanoparticles encompasses alloy and core-shell nanostructures of Au-Ag bimetallic compositions. First, the optical properties of bimetallic alloy and core-shell nanoparticles are compared for different structures such as nanospheres, nanotriangles and nanorods. Based on the optical properties, the photothermal properties of these nanostructures are also evaluated for relevant light-driven applications. Further, to bridge the gap between the theoretical and experimental optical properties of colloidal plasmonic nanoparticles, the effect of different statistical parameters pertaining to the particle size distribution is studied. Going from isolated nanoparticles to nanoparticle clusters, the changes in the optical properties of plasmonic nanoparticles when they form finite clusters is investigated. A strong effect of clustering on the absorption intensities of the nanoparticles and hence, on the photothermal properties is found. Next, for the study of plasmonic nanoparticle infinite arrays, Au and Ag nanoparticles films are experimentally obtained by the self-assembly at the air-ethylene glycol interface. Upon further validation of the computational models with the experimental optical properties of these films, the near-field and far-field optical response of the plasmonic nanoparticle arrays is investigated. An application of the self-assembled Au nanoparticle film is then demonstrated in the sensing of volatile organic compounds (VOCs). Finally, the focus is shifted from plasmonic nanoparticles to metal oxide nanoparticles for their self-assembly at the air-water interface to obtain self-assembled films. For this, the hydrophobic functionalization of four metal oxides nanoparticles namely, TiO2, ZnO, WO3 and CuO is investigated. The insights from this work is useful for the design and fabrication of functional nanoparticles and interfaces for light driven applications.

Abstract: Stimuli-responsive metal-organic frameworks (MOFs) are highly versatile porous materials with the ability to respond to different external stimuli, including temperature, pressure, pH, and light. The MOF properties can switch reversibly under specific light irradiation, opening the doors to various applications. This review focuses on design strategies to obtain photo-responsive MOFs, namely (i) encapsulation of photo-switchable molecules as guests in MOF porous structures, (ii) fabrication of MOF composites, (iii) post-synthesis modification, and (iv) synthesis of MOFs with photo-responsive ligands. The most recent reports from the literature are herein reviewed and analyzed in terms of material chemistry and performance. Comparisons between the different strategies are performed and future challenges are discussed. The critical aspect of the fatigue of photo-responsive MOFs applied for prolonged cycling of irradiation is also discussed.

Abstract: Repeated intraperitoneal injections of lead acetate in rats caused a calcification of the skin of the abdomen near the site of the injections. In the lead-induced calcifications, electron dense collagen bundles could be observed. On the surface of the collagen fibrils, needle-like crystals were visible. With energy-dispersive X-ray analysis, phosphorus, calcium and lead were detected in the electron dense collagen bundles. X-ray maps of the P-Kα, Ca-Kα, and Pb-Lα plus Pb-Lβ lines showed an equivalent distribution along the collagen fibrils for phosphorus and calcium. The occurrence of the most electron dense areas in the STEM-image was comparable to the lead distribution. A good correlation existed between the structural and the elemental images of the same area. Although the medicinal use of preparations containing lead is no longer recommended, some are still prescribed. From our results we can conclude that they should not be applied to injured or inflamed skin.

Abstract: The superconducting properties of two recently synthesized ternary silicides with unit formula X₄CoSi (X = Nb, Ta) are investigated through ab initio calculations combined with Eliashberg theory. Interestingly, their crystal structure comprises interlocking honeycomb networks of Nb/Ta atoms. Nb₄CoSi is found to harbor better conditions for phonon-mediated superconductivity, as it possesses a higher density of states at the Fermi level, fostering stronger electron-phonon coupling. The superconducting critical temperatures (T_c) follow the same trend, with Nb₄CoSi having a twice higher value than Ta₄CoSi. Furthermore, the calculated T_c values (5.9 K vs 3.1 K) agree excellently with the experimentally obtained ones, establishing superconductivity in this new materials class as mediated by the electron-phonon coupling. Furthermore, my calculations show that the superconducting properties of these compounds do not simply correlate with the parameters of their honeycomb networks, contrary to proposals raised in the literature. Rather, their complete fermiology and phonon spectrum should be taken into account in order to explain their respective superconducting properties.

Abstract: In most semiconducting metal chalcogenides, a large deformation is usually accompanied by a phase transformation, while the deformation mechanism remains largely unexplored. Herein, a phase-transformation-induced deformation in Ag2Se is investigated by in situ transmission electron microscopy, and a new ordered high-temperature phase (named as alpha '-Ag2Se) is identified. The Se-Se bonds are folded when the Ag+-ion vacancies are ordered and become stretched when these vacancies are disordered. Such a stretch/fold of the Se-Se bonds enables a fast and large deformation occurring during the phase transition. Meanwhile, the different Se-Se bonding states in alpha-, alpha '-, beta-Ag2Se phases lead to the formation of a large number of nanoslabs and the high concentration of dislocations at the interface, which flexibly accommodate the strain caused by the phase transformation. This study reveals the atomic mechanism of the deformation in Ag2Se inorganic semiconductors during the phase transition, which also provides inspiration for understanding the phase transition process in other functional materials.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.