Abstract: Solid carbon deposition is a persistent challenge in dry reforming of methane (DRM), affecting both classical and plasma-based processes. In this work, we use a microwave plasma in reverse vortex flow configuration to overcome this issue in CO₂/CH₄plasmas. Indeed, this configuration efficiently mitigates carbon deposition, enabling operation even with pure CH₄feed gas, in contrast to other configurations. At the same time, high reactor performance is achieved, with CO₂and CH₄conversions reaching 33% and 44% respectively, at an energy cost of 14 kJ L⁻¹for a CO₂ : CH₄ratio of 1 : 1. Laser scattering and optical emission imaging demonstrate that the shorter residence time in reverse vortex flow lowers the gas temperature in the discharge, facilitating a shift from full to partial CH₄pyrolysis. This underscores the pivotal role of flow configuration in directing process selectivity, a crucial factor in complex chemistries like CO₂/CH₄mixtures and very important for industrial applications.

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: LNMO (LiNi0.5Mn1.5O4-delta) is a high-energy density positive electrode material for lithium ion batteries. Unfortunately, it suffers from capacity loss and impedance rise during cycling due to electrolyte oxidation and electrode/electrolyte interface instabilities at high operating voltages. Here, a solution-gel synthesis route was used to coat 0.5-2.5 mu m LNMO particles with amorphous Li-Ti-O (LTO) for improved Li conduction, surface structural stability and cyclability. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) analysis coupled with energy dispersive X-ray (EDX) showed Ti-rich amorphous coatings/islands or Ti-rich spinel layers on many of the LTO-modified LNMO facets, with a thickness varying from about 1 to 10 nm. The surface modification in the form of amorphous islands was mostly possible on high-energy crystal facets. Physicochemical observations were used to propose a molecular mechanism for the surface modification, combining insights from metalorganic chemistry with the crystallographic properties of LNMO. The improvements in functional properties were investigated in half cells. The cell impedance increased faster for the bare LNMO compared to amorphous LTO modified LNMO, resulting in R-ct values as high as 1247 Omega (after 1000 cycles) for bare LNMO, against 216 Omega for the modified material. At 10C, the modified material boosted a 15% increase in average discharge capacity. The improvements in electrochemical performance were attributed to the increase in electrochemically active surface area, as well as to improved HF-scavenging, resulting in the formation of protective byproducts, generating a more stable interface during prolonged cycling.

Abstract: The atomically laminated layered ternary transition-metal borides (the MAB phases) have demonstrated outstanding properties and have been applied in various fields. Understanding their thermal and mechanical properties is critical to determining their applicability in various fields such as high-temperature applications. To achieve this, we conducted first-principles calculations based on density-functional theory and the quasiharmonic approximation to determine the thermal expansion coefficients, Gruneisen parameters, bulk moduli, hardness, thermal conductivity, electron-phonon coupling parameters, and the structural and vibrational properties of MoAlB, WAlB, Cr2AlB2, and Ti2InB2. We found varying degrees of anisotropy in the thermal expansion and mechanical properties in spite of similarities in their crystal structures. MoAlB has a mild degree of anisotropy in its thermal expansion coefficient (TEC), while Cr2AlB2 and WAlB display the highest level of TEC anisotropy. We assessed various empirical models to calculate hardness and thermal conductivity, and correlated the calculated values with the material properties such as elastic moduli, Gruneisen parameter, Debye temperature, and type of bonding. Owing to their higher Gruneisen parameters, implying a greater degree of anharmonicity in lattice vibrations and lower phonon group velocities, MoAlB and WAlB have significantly lower lattice thermal conductivity values than those of Cr2AlB2 and Ti2InB2. The hardness and lattice thermal conductivity of MAB phases can be predicted with high accuracy if one utilizes an appropriate model.

Abstract: More and more countries and organisations emphasise the value of harm reduction measures in the context of illicit drug use and abuse. One of these measures is drug checking, a preventive action that can represent a quick win by tailored consultation on the risks of substance use upon analytical screening of a submitted sample. Unlike drop-in centres that operate within a fixed setting, enabling drug checking in a harm reduction context at events requires portable, easy to use analytical approaches, operated by personnel with limited knowledge of analytical chemistry. In this case study, four different approaches were compared for the characterisation of 3,4-methylenedioxymethamphetamine samples and this in the way the approaches would be applied today in an event context. The four approaches are mid-infrared (MIR), near-infrared, and Raman spectroscopy, which are today used in drug checking context in Belgium, as well as an electrochemical sensor approach initially developed in the context of law enforcement at ports. The MIR and the electrochemical approach came out best, with the latter allowing for a direct straightforward analysis of the percentage 3,4-methylenedioxymethamphetamine (as base equivalent) in the samples. However, MIR has the advantage that, in a broader drug checking context, it allows to screen for several molecules and so is able to identify unexpected active components or at least the group to which such components belong. The latter is also an important advantage in the context of the growing emergence of new psychotropic substances. MIR, NIR, Raman spectroscopy, and an electrochemical sensor (Narcoreader (R)) for MDMA analysis were compared in a realistic harm reduction context. NIR and Raman failed in simple library approaches. MIR and Narcoreader (R) were preferred. MIR came out as first choice. MIR and Narcoreader (R) have complementary (dis)advantages and could be used in a two-step approach: MIR for screening and Narcoreader (R) for dosage/risk evaluation of MDMA samples.image

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: Ptychography provides high dose efficiency images that can reveal light elements next to heavy atoms. However, despite ptychography having an otherwise single signed contrast transfer function, contrast reversals can occur when the projected potential becomes strong for both direct and iterative inversion ptychography methods. It has recently been shown that these reversals can often be counteracted in direct ptychography methods by adapting the focus. Here we provide an explanation of why the best contrast is often found with the probe focused to the middle of the sample. The phase contribution due to defocus at each sample slice above and below the central plane in this configuration effectively cancels out, which can prevent contrast reversals when dynamical scattering effects are not overly strong. In addition we show that the convergence angle can be an important consideration for removal of contrast reversals in relatively thin samples.

Abstract: Dry deposition is an important process determining pollutant concentrations, especially when studying the influence of urban green infrastructure on particulate matter (PM) levels in cities. Computational fluid dynamics (CFD) models of PM capture by vegetation are useful tools to increase their applicability. The meso-scale models of Zhang et al. (Atmos Environ 35:549-560, 2001) and Petroff and Zhang (Geosci Model Dev 3(2):753-769, 2010) have often been adopted in CFD models, however a comparison of these models with measurements including all PM particle sizes detrimental to health has been rarely reported and certainly not for green wall species. This study presents dry deposition experiments on real grown Hedera helix in a wind tunnel setup with wind speeds from 1 to 4 m s(-1) and PM consisting of a mixture of soot (0.02 – 0.2 mu mu m) and dust particles (0.3 – 10 mu mu m). Significant factors determining the collection efficiency (%) were particle diameter and wind speed, but relative air humidity and the type of PM (soot or dust) did not have a significant influence. Zhang's model outperformed Petroff's model for particles < 0.3 mu mu m, however the inclusion of turbulent impaction in Petroff's model resulted in better agreement with the measurements for particles > 2 – 3 mu mu m. The optimised model had an overall root-mean-square-error of similar to 4% for collection efficiency (CE) and 0.4 cm s-1 for deposition velocity (nu d), which was shown to be highly competitive against previously described models. It can thus be used to model PM deposition on other plant species, provided the correct parameterisation of the drag by this species. A detailed description of the spatial distribution of the vegetation could solve the underestimation for particle sizes of 0.3 – 2 mu mu m.

Abstract: Electrochemical sensors have emerged as a new analytical tool for illicit drug detection to facilitate ultrafast and accurate identification of suspicious compounds on-site. Drugs of abuse can be identified using their unique voltammetric fingerprint at a given pH. Today, the right buffer solution is manually selected based on drug appearance, and in some cases, a consecutive analysis in two different pH solutions is required. In this work, we present a disposable microfluidic multichannel sensor system that automatically records fingerprints in two pH solutions (e.g., pH 5 and pH 12). This system has two advantages. It will overcome the manual selection of a buffer solution at the right pH, decrease analysis time, and minimize the risk of human errors. Second, the combination of two fingerprints, the superfingerprint, contains more detailed information about the samples, which enhances the selectivity of the analytical technique. First, real-time pH measurements proved that the sample can be brought to the desired pH within a minute. Subsequently, an electrochemical study on the microfluidic platform with 1 mM illicit drug standards of MDMA, cocaine, heroin, and methamphetamine showed that the characteristic voltammetric fingerprints and peak potentials are reproducible, also in the presence of common cutting agents. Finally, the microfluidic concept was validated with real confiscated samples, showing promising results for the user-friendly identification of drugs of abuse. In short, this paper presents a successful proof-of-concept study of a multichannel microfluidic sensor system to enrich the fingerprints of illicit drugs at pH 5 and pH 12, thus providing a low-cost, portable, and rapid identification system of illicit drugs with minimal user intervention.

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: Matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has become a powerful method to extract spatially resolved chemical information in complex materials. This study provides the first use of MALDI-MSI to define spatial–temporal changes in oil paints. Due to the highly heterogeneous nature of oil paints, the sample preparation had to be optimized to prevent molecules from delocalizing. Here, we present a new protocol for the layer-specific analysis of oil paint cross sections achieving a lateral resolution of 10 μm and without losing ionization efficiency due to topographic effects. The efficacy of this method was investigated in oil paint samples containing a mixture of two historic organic pigments, geranium lake and lead white, a mixture often employed in the work of painter Vincent Van Gogh. This methodology not only allows for spatial visualization of the molecules responsible for the pink hue of the paint but also helps to elucidate the chemical changes behind the discoloration of paintings with this composition. The results demonstrate that this approach provides valuable molecular compositional information about the degradation pathways of pigments in specific paint layers and their interaction with the binding medium and other paint components and with light over time. Since a spatial correlation between molecular species and the visual pattern of the discoloration pattern can be made, we expect that mass spectrometry imaging will become highly relevant in future degradation studies of many more historical pigments and paints.

Abstract: Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain.In this work, we generated a comprehensive hyperspectral dataset of intimate mineral powder mixtures by homogeneously mixing five different clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide). In total 325 samples were prepared. Among the 325 samples, 60 mixtures were binary, 150 were ternary, 100 were quaternary, and 15 were quinary. For each mixture (and pure clay powder), reflectance spectra are acquired by 13 different sensors, with a broad wavelength range between the visible and the long-wavelength infrared regions (i.e., between 350 nm and 15385 nm) and with a large variation in sensor types, platforms, and acquisition conditions. We will make this dataset public, to be used by the community for the validation of nonlinear unmixing methodologies (https://github.com/VisionlabUA/Multisensor_datasets)

Abstract: Plasma is considered one of the promising technologies to solve greenhouse gas problems, as it can activate CO2 and CH4 at relatively low temperatures. Among the various types of plasmas, the gliding arc plasmatron (GAP) is promising, as it has a high level of non-equilibrium and high electron density. Nevertheless, the conversion of CO2 and CH4 in the GAP reactor is limited. Therefore, combining the GAP reactor with catalysts and making use of the heat produced by the plasma to provide thermal energy to the catalyst, forming a post-plasma catalytic (PPC) system, is hypothesized to improve its performance. Therefore, in this PhD research, we investigate important aspects of the PPC concept towards the use of the heat produced by GAP plasma to heat the plasma bed, without additional energy input. Aiming at this, based on a literature study (chapter 1), Ni-loaded layered double hydroxide (LDH) derived catalyst with good thermal catalytic DRM performance were chosen as the catalyst material. Before applying the LDH as a support material, the rehydration property of calcined LDH in moist and liquid environment was studied as part of chapter 2. The data indicated that after high temperatures calcination (600-900 C), the obtained layered double oxides (LDOs) can rehydrate into LDH, although, the rehydrated LDH were different from the original LDH. In chapter 3, different operating conditions, such as gas flow rate, gas compositions (e.g. CH4/CO2 ratio and nitrogen dilution), and addition of H2O were studied to investigate optimal conditions for PPC DRM, identifying possible differences in temperature profiles and exhaust gas compositions that might influence the catalytic performance. Subsequently, the impact of different PPC configurations, making use of the heat and exhaust gas composition produced by the GAP plasma, is shown in Chapter 4. Experiments studying the impact of adjusting the catalyst bed distance to the post-plasma, the catalyst amount, the influence of external heating (below 250 C) and the addition of H2O are discussed. As only limited improvement in the performance was achieved, a new type of catalyst bed was designed and utilized, as described in chapter 5. This improved configuration can realize better heat and mass transfer by directly connecting to the GAP device. The performance was improved and became comparable to the traditional thermal catalytic DRM results obtained at 800 C, although obtained by a fully electrically driven plasma.

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.