Abstract: Dibismuth dioxychalcogenides, Bi2O2Ch (Ch = S, Se, Te), are a promising class of materials for next-generation electronics and thermoelectrics due to their ultrahigh carrier mobility and excellent air stability. An interesting member of this family is Bi2O2S, which has a stereochemically active 6s2 lone pair of Bi3+ cations, heterogeneous bonding, and a high mass contrast between its constituent elements. In the present study, we have used first-principles calculations in combination with Boltzmann transport theory to systematically investigate the effect of hydrostatic pressure on lattice dynamics and phonon transport properties of Bi2O2S. We found that the ambient Pnmn phase has a low average lattice thermal conductivity (kappa l) of 1.71 W/(m K) at 300 K. We also predicted that Bi2O2S undergoes a structural phase transition from a low-symmetry (Pnmn) to a high-symmetry (I4/mmm) structure at around 4 GPa due to centering of Bi3+ cations with pressure. Upon compression, the lone pair activity of Bi3+ cations is suppressed, which increases kappa l by almost 3 times to 4.92 W/ (m K) at 5 GPa for the I4/mmm phase. The computed phonon lifetimes and Gru''neisen parameters show that anharmonicity decreases with increasing pressure due to further suppression of the lone pair activity and strengthening of intra-and intermolecular interactions, leading to an average room-temperature kappa l of 12.82 W/(m K) at 20 GPa. Overall, this study provides a comprehensive understanding of the effect of hydrostatic pressure on the stereochemical activity of the lone pair of Bi3+ cations and its implications on the phonon transport properties of Bi2O2S.

Abstract: Permanent magnets generally require a favorable, but difficult-to-achieve combination of high magnetization, Curie point, and magnetic anisotropy. Thus there have been few, if any, viable permanent magnets developed since the 1982 discovery of Nd2Fe14B [M. Sagawa, S. Fujimura, H. Yamamoto, Y. Matsuura, and S. Hirosawa, J. Appl. Phys. 57, 4094 (1985)]. Here we point out, both by direct first-principles calculations on the iron carbides and silicides Fe5C2, Fe5SiC, and Fe7C3 as well as a discussion of recent experimental findings, that there are numerous rare-earth-free iron-rich potential permanent-magnet materials with sufficient intrinsic magnetic properties to reasonably achieve room-temperature energy products of 20-25 MG Oe. This is substantially better than the performance of the best available rare-earth-free magnets based on ferrite, as well as shape-anisotropy-employing alnico. These magnets could plausibly fill, at low cost, the present performance “gap” [J. M. D. Coey, Scr. Mater. 67, 524 (2012)] between the best rare-earth-free magnets and rare-earth magnets such as Nd2Fe14B and Sm-Co.

Abstract: Hierarchicalassembly of arc-like fractal nanostructures not onlyhas its unique self-similarity feature for stability enhancement butalso possesses the structural advantages of highly exposed surface-activesites for activity enhancement, remaining a great challenge for high-performancemetallic nanocatalyst design. Herein, we report a facile strategyto synthesize a novel arc-like hierarchical fractal structure of PtPdbimetallic nanoparticles (h-PtPd) by using pyridinium-type ionic liquidsas the structure-directing agent. Growth mechanisms of the arc-likenanostructured PtPd nanoparticles have been fully studied, and precisecontrol of the particle sizes and pore sizes has been achieved. Dueto the structural features, such as size control by self-similaritygrowth of subunits, structural stability by nanofusion of subunits,and increased numbers of exposed active atoms by the curved homoepitaxialgrowth, h-PtPd displays outstanding electrocatalytic activity towardoxygen reduction reaction and excellent stability during hydrothermaltreatment and catalytic process.

Abstract: Two-dimensional materials have been attracting increasing interests because of their outstanding properties for Lithium-ion battery applications. In particular, a material family called MXenes (Mn+1Cn, where n = 1, 2, 3) have been recently attracted immense interest in this respect due to their incomparable fast-charging properties and high capacity promises. In this article, we review the state-of-the-art computational progress on Li-ion battery applications of MXene materials in accordance with our systematical DFT calculations. Structural, mechanical, dynamical, and electrical properties of 20 distinct MXene (M: Sc, Ti, V, Cr, Nb, Mo, Hf, Ta, W, and Zr) have been discussed. The battery performances of these MXene monolayers are further investigated by Li-ion binding energies, open circuit voltage values, and Li migration energy barriers. The experimental and theoretical progress up to date demonstrates particularly the potential of non-terminated or pristine MXene materials in Li ion-storage applications. Stability analyses show most of the pristine MXenes should be achievable, however susceptible to the development progress on the experimental growth procedures. Among pristine MXenes, Ti2C, V2C, Sc2C, and Zr2C compounds excel with their high charge/discharge rate prospect due to their extremely low Li diffusion energy barriers. Considering also their higher predicted gravimetric capacities, Sc, Ti, V, and Zr containing MXenes are more promising for their utilization in energy storage applications.

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: The implementation of green walls is increasingly seen as a strategy to tackle urban air pollution and to make cities more climate resilient. The correct description of the vegetation-wind interaction is key in describing the effect of vegetation in computational fluid dynamics (CFD) models. The accuracy of the modelled wind flow is highly linked to the uncertainty about the drag coefficient (C-d). In addition, at low wind speeds viscous drag (K) is not negligible and it should be regarded in CFD models. This research aims to address the uncertainty related to C-d and K by including the effect of climbers on both the momentum and turbulence equations in the Wilcox revised k-omega model. The change of K with increasing Reynolds number showed an increase from 5.10(-8 )m(2) up to the dynamic viscosity of air (asymptotic to 10(-5) m(2)) following a logistic function. Beyond the transition region from viscous to form drag, C-d, in the range of 0.1-1.1, declined with increasing Reynolds number following a power law function. Furthermore, the plant morphological parameters determining permeability and drag coefficient were identified. This study showed that the knowledge of viscous and shape resistance is necessary to obtain accurate statistics for air flow through vegetation.

Abstract: Transmission electron microscopy (TEM) is a technique that uses an electron beam to analyze materials. This analysis is based on the interaction between the electron beam and the sample, such as photon emission and electron diffraction pattern, to name a few. Sample damage, however, also occurs when such interaction alters the structure of the sample. To ensure information from the undamaged material can be acquired, the electron expense to probe the material is thus limited. In this work, we propose efficient methods for acquiring and processing the information originating from the electron-sample interaction so that the study of the material and the conducting of the TEM experiment can be less hindered by the limited dose usage. In the first part of the work, the relationship between the scattering of the electron and the local physical property of the sample is studied. Based on this relationship, two reconstruction schemes are proposed capable of producing high-resolution images at low-dose conditions. Besides, the proposed reconstructions are not restricted to complete datasets but instead work on pieces of data, therefore allowing live feedback during data acquisition. Such feature of the methods allows the whole TEM experiment to be carried out under low dose conditions and thus further reduces possible beam damage on the studied material. In the second part of the work, we discuss our approach to modulating the electron beam and its benefits. An electrostatic device that can alter the wavefront of the passing electron wave is introduced and characterized. The beam-modulation ability is demonstrated by creating orthogonal beam sets, and applications that exploit the adaptability of the wave modulator are demonstrated with both simulation and experiments.

Abstract: High-energy-density nickel (Ni)-rich cathode materials are used in commercial lithium (Li)-ion batteries for electric vehicles, but they suffer from severe structural degradation upon cycling. Planar gliding and microcracking are seeds for fatal mechanical fracture, but their origin remains unclear. Herein, we show that “layer-by -layer delithiation”is activated at high voltages during the charge process when the “lattice collapse”(a characteristic high-voltage lattice evolution in Ni-rich cathodes) occurs. Layer-by-layer deli-thiation is evidenced by direct observation of the consecutive lattice collapse using in situ scanning transmission electron micro-scopy (STEM). The collapsing of the lattice initiates in the expanded planes and consecutively extends to the whole crystal. Localized strain will be induced at lattice-collapsing interface where planar gliding and intragranular microcracks are generated to release this strain. Our study reveals that layer-by-layer delithia-tion during lattice collapse is the fundamental origin of the mechanical instability in single-crystalline Ni-rich cathodes.

Abstract: This study focuses on optimizing the composition and firing temperature of porcelain tiles using statistical analysis techniques. A full factorial design, including model adequacy checking, analysis of variance, Pareto charts, interaction plots, regression model, and response optimizer is employed. The key factors were the Seger ratios of SiO2/Al2O3, Na2O/K2O, MgO/CaO, and firing temperature. The response variables investigated were bulk density, water absorption, linear shrinkage, coefficient of thermal expansion (at 500 degrees C), and strength. The statistical analysis revealed highly significant results, which were further validated, confirming their reliability for practical use in the production of porcelain tiles. The study demonstrated the effectiveness of utilizing Seger formulas and properties of typical raw materials to accurately predict the final properties of ceramic tiles. By employing SiO2/Al2O3 = 5.2, Na2O/K2O = 1.50, MgO/CaO = 3.0, and firing temperature of 1180 degrees C, optimized properties, such as maximum strength, maximum bulk density, and minimum water absorption, was achieved with a composite desirability of 0.9821.

Abstract: In this work, we report a new method for depositing thin films of MnO2 on planar and complex nanostructured surfaces, with high precision and conformality. The method is based on repeating cycles of adsorption of an unsaturated alcohol on a surface, followed by its oxidation with aqueous KMnO4 and formation of thin, solid MnO2. The amount of manganese oxide formed in each cycle is limited by the quantity of the adsorbed alcohol; thus, the growth exhibits the self-limiting characteristics of atomic layer deposition (ALD). Contrary to the typical ALD, however, the new redox layer deposition is performed in air, at room temperature, using common chemicals and simple laboratory glassware, which greatly reduces its cost and complexity. We also demonstrate application of the method for the fabrication of a nanostructured MnO2/Ni electrode, which was not possible with thermal ALD because of the rapid decomposition of the gaseous precursor on the high surface-area substrate. Thanks to its simplicity, the conformal deposition of MnO2 can be easily upscaled and thus exploited for its numerous (electro)chemical applications.

Abstract: Hoofd-halskanker vormt een aanzienlijke uitdaging met bijna 900.000 nieuwe diagnoses per jaar, waarbij de jaarlijkse incidentie blijft stijgen. Vaak wordt de diagnose pas in een laat stadium gesteld, wat complexe behandelingen noodzakelijk maakt. Terugval van patiënten is helaas een veelvoorkomend probleem. De gemiddelde overlevingsduur is beperkt tot enkele maanden. Daarom is er een dringende behoefte om nieuwe, veelbelovende behandelingen te ontwikkelen voor patiënten met hoofd-halskanker. Voor het bereiken van deze vooruitgang spelen innovatieve studiemodellen een cruciale rol. Het ontwikkelen van deze nieuwe behandelingen start met laboratoriumonderzoek, waarbij traditionele tweedimensionale celculturen hun beperkingen hebben. Daarom verschuiven onderzoekers hun aandacht meer en meer naar geavanceerdere driedimensionale modellen, met hoofd-halskankerorganoïden als beloftevol nieuw model. Dit model behoudt immers zowel het genetische profiel als de morfologische kenmerken van de originele tumor van de hoofd-halskankerpatiënt. Hoofdhalskankerorganoïden bieden daarom de mogelijkheid om innovatieve behandelingen te testen en kunnen mogelijk zelfs de respons van een patiënt op bepaalde therapieën voorspellen. Hoewel tumororganoïden als ‘patiënt-in-het-lab’ veelbelovend zijn, zijn er uitdagingen te overwinnen, zoals de ontwikkelingstijd en de toepasbaarheid bij alle tumortypes, evenals het ontbreken van immuuncellen en andere micro-omgevingscomponenten. Er is daarom een grote behoefte aan gestandaardiseerde protocollen voor de ontwikkeling van organoïden en verkorting van de ontwikkelingstijd. Concluderend bieden driedimensionale hoofd-halskankerorganoïden een veelbelovend perspectief voor de toekomst van kankerbehandelingen. Ze hebben het potentieel om bij te dragen aan de ontwikkeling van gepersonaliseerde behandelingen en zo de overlevingskansen van kankerpatiënten te verbeteren. Het is echter belangrijk om hun voorspellend vermogen en toepassingsmogelijkheden verder te onderzoeken, voordat ze op grote schaal worden geïmplementeerd.

Abstract: Van der Waals quantum wells, naturally formed in two-dimensional layered materials with nanoscale thickness, possess many inherent advantages over conventional molecular beam epitaxy grown counterparts, and could bring up intriguing physics and applications. However, optical transitions originated from the series of quantized states in these emerging quantum wells are still elusive. Here, we show that multilayer black phosphorus appears to be an excellent candidate for van der Waals quantum wells with well-defined subbands and high optical quality. Using infrared absorption spectroscopy, we probe subband structures of multilayer black phosphorus with tens of atomic layers, revealing clear signatures for optical transitions with subband index as high as 10, far from what was attainable previously. Surprisingly, in addition to allowed transitions, an unexpected series of “forbidden” transitions is also evidently observed, which enables us to determine energy spacings separately for conduction and valence subbands. Furthermore, the linear tunability of subband spacings by temperature and strain is demonstrated. Our results are expected to facilitate potential applications for infrared optoelectronics based on tunable van der Waals quantum wells.