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: 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: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: In present work, we have performed the Grand Canonical Monte Carlo (GCMC) simulations to quantify CO2 capture inside porous silica at high operating temperatures of 673.15 K and 873.15 K; and over a operating pressure range of 500 kPa – 4000 kPa that are methane steam reforming process parameters. Related chemical potential values at these thermodynamic conditions are obtained from the bulk phase simulations in the Canonical ensemble in conjunction with Widom’s insertion technique, where the CO2 has been accurately represented by TraPPE force field. Present structure of the porous silica is a single slit pore geometry of various heights (H = 20 Å, 31.6 Å, 63.2 Å and 126.5 Å), dimensions in which possible vapour-liquid equilibria for generic square well fluids has been reported in literature. Estimation of the pore-fluid interactions show a higher interaction between silica pore and adsorbed CO2 compared to the reported pore-fluid interactions between homogeneous carbon slit pore and adsorbed CO2; thus resulting in an enhancement of adsorption inside silica pores of H = 20 Å and H = 126.5 Å, which are respectively 3.5 times and 1.5 times higher than that in homogeneous carbon slit pores of same dimensions and at 673.15 K and 500 kPa. Estimated local density plots indicate the presence of structured layers due to more molecular packing, which confirms possible liquid-like and vapour-like phase coexistence of the supercritical bulk phase CO2 under confinement.

Abstract: Generalized Möbius-Listing surfaces and bodies generalize Möbius bands, and this research was motivated originally by solutions of boundary value problems. Analogous to cutting of the original Möbius band, for this class of surfaces and bodies, results have been obtained when cutting such bodies or surfaces. In general, cutting leads to interlinked and intertwined different surfaces or bodies, resulting in very complex systems. However, under certain conditions, the result of cutting can be a single surface or body, which reduces complexity considerably. These conditions are based on congruence and rotational symmetry of the resulting cross sections after cutting, and on the knife cutting the origin

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: 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: Gian Giacomo Inchiocchio (1604-1656), better known as Barbelli, was one of the main exponents of Lombard painting of the seventeenth century. A large body of work is attributed to him, encompassing a wide range of drawings, murals, and oil paintings. However, despite his broad production, there are still many open questions regarding his painting techniques and materials. In this paper, a multi-analytical study of the cycle Stories of the life of Saint George that originally decorated the presbytery of the parish church of Casaletto Vaprio (Cremona, Italy) was performed, combining non-invasive techniques with the characterisation of selected micro samples. Results show that Barbelli used a very limited number of inorganic pigments, often mixing them together to create different colours and shades. Remains of caseinate and degradation products (i.e. weddellite and whewellite) related to the strappo intervention were also highlighted. The study helped to decipher the materials and technique of this painting, providing data that can be used as a reference to study his extensive production.

Abstract: Plasma-based CO2 conversion is worldwide gaining increasing interest. The aim of this work is to find potential pathways to improve the energy efficiency of plasma-based CO2 conversion beyond what is feasible for thermal chemistry. To do so, we use a combination of modeling and experiments to better understand the underlying mechanisms of CO2 conversion, ranging from non-thermal to thermal equilibrium conditions. Zero-dimensional (0D) chemical kinetics modelling, describing the detailed plasma chemistry, is developed to explore the vibrational kinetics of CO2, as the latter is known to play a crucial role in the energy efficient CO2 conversion. The 0D model is successfully validated against pulsed CO2 glow discharge experiments, enabling the reconstruction of the complex dynamics underlying gas heating in a pure CO2 discharge, paving the way towards the study of gas heating in more complex gas mixtures, such as CO2 plasmas with high dissociation degrees. Energy-efficient, plasma-based CO2 conversion can also be obtained upon the addition of a reactive carbon bed in the post-discharge region. The reaction between solid carbon and O2 to form CO allows to both reduce the separation costs and increase the selectivity towards CO, thus, increasing the energy efficiency of the overall conversion process. In this regard, a novel 0D model to infer the mechanism underlying the performance of the carbon bed over time is developed. The model outcome indicates that gas temperature and oxygen complexes formed at the surface of solid carbon play a fundamental and interdependent role. These findings open the way towards further optimization of the coupling between plasma and carbon bed. Experimentally, it has been demonstrated that “warm” plasmas (e.g. microwave or gliding arc plasmas) can yield very high energy efficiency for CO2 conversion, but typically only at reduced pressure. For industrial application, it will be important to realize such good energy efficiency at atmospheric pressure as well. However, recent experiments illustrate that the microwave plasma at atmospheric pressure is too close to thermal conditions to achieve a high energy efficiency. Hence, we use a comprehensive set of advanced diagnostics to characterize the plasma and the reactor performance, focusing on CO2 and CO2/CH4 microwave discharges. The results lead to a deeper understanding of the mechanism of power concentration with increasing pressure, typical of plasmas in most gases, which is of great importance for model validation and understanding of reactor performance.

Abstract: Metal halide perovskite (MHP) quantum dots (QDs) offer immense potential for several areas of photonics research due to their easy and low-cost fabrication and excellent optoelectronic properties. However, practical applications of MHP QDs are limited by their poor stability and, in particular, their tendency to aggregate. Here, we develop a two-step double-solvent strategy to grow and confine CsPbBr3 QDs within the three-dimensional (3D) cavities of a mesoporous SBA-16 silica scaffold (CsPbBr3@SBA-16). Strong confinement and separation of the MHP QDs lead to a relatively uniform size distribution, narrow luminescence, and good ambient stability over 2 months. In addition, the CsPbBr3@SBA-16 presents a high activity and stability for visible-light-driven photocatalytic toluene C(sp(3))-H bond activation to produce benzaldehyde with similar to 730 mu mol g(-1) h(-1) yield rate and near-unity selectivity. Similarly, the structural stability of CsPbBr3@SBA-16 QDs is superior to that of both pure CsPbBr3 QDs and those confined in MCM-41 with 1D channels.

Abstract: The efficiency of a catalytic process is assessed based on conversion, yield, and time effectiveness. However, these parameters are insufficient for evaluating environmentally sustainable research. As the world is urged to shift towards green catalysis, additional factors such as reaction media, raw material availability, sustainability, waste minimization and catalyst biosafety, need to be considered to accurately determine the efficacy and sustainability of the process. By combining the high porosity and versatility of metal organic frameworks (MOFs) and the activity of gold nanoparticles (AuNPs), efficient, cyclable and biosafe composite catalysts can be achieved. Thus, a composite based on AuNPs and the nanometric flexible porous iron(III) aminoterephthalate MIL-88B-NH2 was successfully synthesized and fully characterized. This nanocomposite was tested as catalyst in the reduction of nitroarenes, which were identified as anthropogenic water pollutants, reaching cyclable high conversion rates at short times for different nitroarenes. Both synthesis and catalytic reactions were performed using green conditions, and even further tested in a time-optimizing one-pot synthesis and catalysis experiment. The sustainability and environmental impact of the catalytic conditions were assessed by green metrics. Thus, this study provides an easily implementable synthesis, and efficient catalysis, while minimizing the environmental and health impact of the process.

Abstract: Humanity feels the urge of shifting to a sustainable society more than at any other time in its history. Electrification of chemical industry plays a key role in this transition. The possibility of producing fertilizers from air using renewable electricity, and simultaneously, no greenhouse gas emission, resulted in an increasing interest toward plasma technology as a solution for electrification of a part of the chemical industry in the past few years. Additionally, the activation of nitrogen molecules by vibrational and electronic excitation reactions in plasma can lead to an energy-efficient process. Last but not least, the modularity (fast on/off characteristic) of plasma technology makes it capable of using intermittent renewable electricity on site for the production of fertilizers using air. All these advantages offered by plasma technology make it a potential solution for the on-site production of fertilizers in small and decentralized plants using air and renewable electricity, which leads to a considerable reduction in fertilizer production and transportation costs. However, industrialization of plasma-based NF suffers from several challenges, including challenges of plasma catalysis for the selective production of desired species, the high energy cost of plasma-based NF compared to current industrial processes, and the design and development of scaled up and energy-efficient plasma reactors for industrial purposes. In the framework of this thesis we have tried to add to the state-of-the-art (SOTA) in plasma-based NOx production and deal with its limitations using a combination of experimental and modelling work.