Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.

Abstract: During the past decades, metallic nanoparticles (NPs) have attracted great attention in materials science due to their specific optical properties based on surface plasmon resonances. Because of these phenomena, plasmonic NPs (or nanoplasmonics) are very promising for application in biosensing, photocatalysts, medicine, data storage, solar energy conversion, etc. Currently, colloidal synthesis techniques enable scientists to routinely produce mono and bimetallic NPs of various shapes, sizes, composition, and elemental distribution, with superior properties for plasmonic applications. Two primary directions for further advancing nanoplasmonic-based technologies include synthesizing novel morphologies, such as highly asymmetric chiral NPs, and gaining deeper insights into the factors affecting the stability of produced nanoplasmonics. With the increasing complexity of nanoplasmonics morphologies and higher stability requirements, there is a pressing need for thorough investigations into their 3D structures and their evolution under different conditions, with high resolution. Electron tomography (ET) emerges as an ideal tool to retrieve shape and element-sensitive information about individual nanoparticles in 3D, achieving resolutions down to the atomic level. Moreover, ET techniques can be combined with in situ holders, enabling detailed studies of processes mimicking real applications of nanoplasmonic-based devices. The first part of this thesis will focus on detailed studies of chiral Au NPs, promising for spectroscopy techniques based on the differential absorption of left- and right-handed circularly polarized light. Specifically, I will discuss the primary strategies for wet-colloidal growth of the various types of intrinsically chiral Au NPs. Advanced ET methods will be demonstrated as powerful tools for characterizing the final helical morphologies of the produced Au NPs and for studying the chiral growth mechanisms by examining intermediate structures obtained during chiral growth. The second part will focus on the heat-induced stability of various Au@Ag core-shell NPs. Operating in real conditions, such as elevated temperatures, may cause particle reshaping and redistribution of metals between the core and shell, gradually altering nanoplasmonics properties. Hence, a thorough understanding of the influence of size, shape, and defects on these processes is crucial for further developments. Recently developed techniques, combining fast ET with in-situ heating holders, have allowed me to evaluate the influence of various parameters (size, shape, defect structure) on heat-induced elemental redistribution in Au@Ag core-shell nanoparticles qualitatively and quantitatively. Additionally, I will discuss the prospects of high-resolution ET for visualizing the diffusion of individual atoms within complex nanostructures.

Abstract: Delve into the diverse aspects of plant morphology, their responses to global climate change, and the spatiotemporal dynamics of forest productivity. Join us on a journey through the intricate web of plant characteristics and their impact on the environment.

Abstract: Single nucleotide point mutations in the KRAS oncogene occur frequently in human cancers, rendering them intriguing targets for diagnosis, early detection and personalized treatment. Current detection methods are based on polymerase chain reaction, sometimes combined with next-generation sequencing, which can be expensive, complex and have limited availability. Here, we propose a novel singlet oxygen (1O2)-based photoelectrochemical detection methodology for single-point mutations, using KRAS mutations as a case study. This detection method combines the use of a sandwich assay, magnetic beads and robust chemical photosensitizers, that need only air and light to produce 1O2, to ensure high specificity and sensitivity. We demonstrate that hybridization of the sandwich hybrid at high temperatures enables discrimination between mutated and wild-type sequences with a detection rate of up to 93.9%. Additionally, the presence of background DNA sequences derived from human cell-line DNA, not containing the mutation of interest, did not result in a signal, highlighting the specificity of the methodology. A limit of detection as low as 112 pM (1.25 ng/mL) was achieved without employing any amplification techniques. The developed 1O2-based photoelectrochemical methodology exhibits unique features, including rapidity, ease of use, and affordability, highlighting its immense potential in the field of nucleic acid-based diagnostics.

Abstract: The efficiency of light emission is a critical performance factor for monolayer transition metal dichalcogenides (1L-TMDs) for photonic applications. While various methods have been studied to compensate for lattice defects to improve the quantum yield (QY) of 1L-TMDs, exciton-exciton annihilation (EEA) is still a major nonradiative decay channel for excitons at high exciton densities. Here, we demonstrate that the combined use of a proximal Au plate and a negative electric gate bias (NEGB) for 1L-WS2 provides a dramatic enhancement of the exciton lifetime at high exciton densities with the corresponding QY enhanced by 30 times and the EEA rate constant decreased by 80 times. The suppression of EEA by NEGB is attributed to the reduction of the defect-assisted EEA process, which we also explain with our theoretical model. Our results provide a synergetic solution to cope with EEA to realize high-intensity 2D light emitters using TMDs.

Abstract: Ceramics and composites, many of whose physicochemical properties significantly exceed similar properties of metals and their alloys, are processed qualitatively mainly by the electroerosion method. Despite the existing works, the mechanism of the initial stage of the removal of materials has not yet been identified. For a comprehensive understanding of the mechanism of the removal of dielectrics, a new model is proposed based on the experimental results obtained on an improved electroerosion installation. It was revealed that the initial stage of the removal of a dielectric material consists of three successive stages that are associated with the synergistic effect on the process of the anionic group of electrolytes, plasma flare, and the cavitation shock. This makes it possible to better understand the mechanism of the removal of composite and ceramic materials, which should contribute to ensuring the machinability of those materials and their wide use in promising technologies.

Abstract: The development of coatings with tunable performances is critical to meet a wide range of technological applications each one with different requirements. Using the plasma-enhanced chemical vapor deposition (PECVD) process, scientists can create hydrogenated amorphous carbon coatings doped with metal (a-C:H:Me) with a broad range of mechanical properties, varying from those resembling polymers to ones resembling diamond. These diverse properties, without clear relations between the different families, make the material selection and optimization difficult but also very rich. An innovative approach is proposed here based on projected performance indices related to fracture energy, strength, and stiffness in order to classify and optimize a-C:H:Me coatings. Four different a-C:H:Cr coatings deposited by PECVD with Ar/C2H2 discharge under different bias voltage and pressures are investigated. A path is found to produce coatings with a selective critical energy release rate between 5–125 J/m2 without compromising yield strength (1.6–2.7 GPa) and elastic limit (≈0.05). Finally, fine-tuned coatings are categorized to meet desired applications under different testing conditions.

Abstract: Mannosylerythritol lipids (MELs) are a promising group of biosurfactants due to their high fermentation yield, selfassembly and biological activity. During fermentation by Pseudozyma aphidis, a mixture of MELs with different levels of acylation is formed, of which the fully deacetylated form is the most valuable. In order to reduce the environmental impact of deacetylation, an enzymatic process using natural deep eutectic solvents (NADES) has been developed. We tested the deacetylation of a purified MELs mixture with immobilized Candida antarctica lipase B enzyme and 2-ethylhexanol as co-substrate in 140 h reactions with different NADES. We identified hydrophobic NADES systems with similar yields and kinetics as in pure 2-ethylhexanol solvent. Our results indicate that deacetylation of MELs mixtures in NADES as a solvent is possible with yields comparable to pure co-substrate and that hydrophobic NADES without carboxylic acid compounds facilitate the reaction to the greatest extent.

Abstract: In this paper, we examined the effects of proximity-induced interactions such as Rashba spin-orbit coupling and effective Zeeman fields (EZFs) on the optical spectrum of n-type and p-type monolayer (ML)-MoS2. The optical conductivity is evaluated using the standard Kubo formula under random-phase approximation by including the effective electron-electron interaction. It has been found that there exist two absorption peaks in n-type ML-MoS2 and two knife shaped absorptions in p-type ML-MoS2, which are contributed by the inter-subband spin-flip electronic transitions within conduction and valence bands at valleys K and K ' with a lifted valley degeneracy. The optical absorptions in n-type and p-type ML-MoS 2 occur in THz and infrared radiation regimes and the position, height, and shape of them can be effectively tuned by Rashba parameter, EZF parameters, and carrier density. The interesting theoretical predictions in this study would be helpful for the experimental observation of the optical absorption in infrared to THz bandwidths contributed by inter-subband spin-flip electronic transitions in a lifted valley degeneracy monolayer transition metal dichalcogenides system. The obtained results indicate that ML-MoS2 with the platform of proximity interactions make it a promising infrared and THz material for optics and optoelectronics.

Abstract: Cadmium sulfide (CdS)-based yellow pigments have been used in a number of early 20th century artworks, including The Scream series painted by Edvard Munch. Some of these unique paintings are threatened by the discoloration of these CdS-based yellow oil paints because of the oxidation of the original sulfides to sulfates. The experimental data obtained here prove that moisture and cadmium chloride compounds play a key role in promoting such oxidation. To clarify how these two factors effectively prompt the process, we studied the band alignment between CdS, CdCl2, and Cd-(OH)Cl as well as the radicals center dot OH and H3O center dot by density functional theory (DFT) methods. Our results show that a stack of several layers of Cd-(OH)Cl creates a pocket of positive holes at the Cl-terminated surface and a pocket of electrons at the OH-terminated surface by leading in a difference in ionization energy at both surfaces. The resulting band alignment indicates that Cd-(OH)Cl can indeed play the role of an oxidative catalyst for CdS in a moist environment, thus providing an explanation for the experimental evidence.

Abstract: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Abstract: Mitigating the adverse effects of air pollution, especially on human health, is one of the greater contemporary challenges for cities. Street canyons have herein been identified as bottleneck areas in urbanized environments. Focusing on the necessity of fast-response interventions, strategies to control source-receptor pathways (e.g. implementing low boundary walls (LBWs)) are gaining interest. A potential strategy which is greatly overlooked is the adjustment (reduction or displacement) of traffic lanes in order to increase the distance between source (traffic) and recipient (pedestrians). Within our study, computation fluid dynamics (CFD) is used to simulate the impact of alternations to traffic lanes (whether or not combined with LBWs) on the pedestrian exposure to NO2 for a specific case-study (Belgie center dot lei, Antwerp) under two prevailing wind directions. The average differences in NO2 concentrations for the entire pedestrian area ranged between +1.0 % to-3.6 %. On specific locations, reduction up to-8.0 % were reached. In case of perpendicular winds, a lateral displacement of all traffic lanes towards the windward facade including LBWs was found most beneficial to reduce pedestrian exposure. LBWs also showed to be efficient in reducing potential adverse effects of lane displacement under less frequent wind directions.

Abstract: In this study, the multi-layer self-assembled molecular network formation of an alkylated tetrathiafulvalene compound is studied at the liquid-solid interface between 1-phenyloctane and graphite. A combined theoretical/experimental approach associating force-field and quantum-chemical calculations with scanning tunnelling microscopy is used to determine the two-dimensional self-assembly beyond the monolayer, but also to further the understanding of the molecular adsorption conformation and its impact on the molecular packing within the assemblies at the monolayer and bilayer level.

Abstract: Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.