Abstract: Economic and environmental impact assessments are increasingly being adopted in the design and implementation of emerging systems. However, their emerging nature leads to several assessment challenges that need to be addressed to ensure the validity and usefulness of results in understanding their potential performance and supporting their development. There is the need to (i) account for spatial and temporal variability to allow a broader perspective at an early stage of development; (ii) handle uncertainties to systematically identify the critical factors and their interrelations that drive the results; (iii) integrate environmental and economic results to support sound decision-making based on two sustainability aspects. To address these assessment challenges, this study presents an alternative approach with the following corresponding features: (i) multiple scenario development to conduct an exploratory assessment of the systems under varying conditions and settings, (ii) global sensitivity analysis to identify the main critical factors and their interrelations, and (iii) trade-off and ecoefficiency analysis to integrate the economic and environmental results. The integrated approach is applied to a case study on plasma gasification for solid waste management. The results of the study highlight how the approach allows the identification of the dynamic relations between project settings and surrounding conditions. For example, the choice of gasifying agent largely depends on the background energy system, which dictates the impacts of the process energy requirement and the savings from the substituted energy of the syngas output. Based on these findings, the usefulness and validity of the proposed integrated approach are discussed in terms of how the key assessment challenges are addressed and how it can provide guidance for the development of emerging systems.

Abstract: The cation distribution of the negative temperature coefficient (NTC) thermistor spinel NiMn2O4 was studied in the temperature range from 55 to 900 degrees C, using a combined in situ neutron diffraction and thermopower study. Rietveld refinements of in situ neutron diffraction data reveal a temperature dependence of the degree of inversion with an inversion parameter of 0.70(1) at 900 degrees C and 0.87(1) at 55 degrees C. Thermopower measurements were evaluated using a modified Heikes formula, and the [Mn4+]/[Mn3+] ratio on octahedral sites of the spinel structure was calculated considering spin and orbital degeneracy. The inversion degree and disproportionation parameter, determined independently as function of temperature, were used to calculate the cation distribution of NiMn2O4 in the whole temperature range. At high temperature, within the stability range of the spinel, the cation distribution is characterized by a moderate degree of inversion with a concentration of NiB2+${\mathrm{Ni}}_\mathrm{B}<

Abstract: Graphene matter in a strong magnetic field, realizing one-dimensional quantum Hall channels, provides a unique platform for studying electron interference. Here, using the Landauer-Buttiker formalism along with the tightbinding model, we investigate the quantum Hall (QH) effects in unipolar and bipolar monolayer-bilayer graphene (MLG-BLG) junctions. We find that a Hall bar made of an armchair MLG-BLG junction in the bipolar regime results in valley-polarized edgechannel interferences and can operate a fully tunable Mach-Zehnder (MZ) interferometer device. Investigation of the bar-width and magnetic-field dependence of the conductance oscillations shows that the MZ interference in such structures can be drastically affected by the type of (zigzag) edge termination of the second layer in the BLG region [composed of vertical dimer or non-dimer atoms]. Our findings reveal that both interfaces exhibit a double set of Aharonov-Bohm interferences, with the one between two oppositely valley-polarized edge channels dominating and causing a large amplitude conductance oscillation ranging from 0 to 2e2/h. We explain and analyze our findings by analytically solving the Dirac-Weyl equation for a gated semi-infinite MLG-BLG junction.

Abstract: The COVID-19 pandemic had large repercussions for our economy and organizations. Improved resilience can give organizations the ability to withstand crises and build back better and faster. This article assesses resilience of organizations and sole proprietorships in the context of the COVID-19 pandemic with eight circular strategies as explanatory variables. Furthermore, these eight circular strategies are also used to assess the organizations' and sole proprietorships' resilience outside of the COVID-19 pandemic. This analysis is conducted to explain how circular strategies can help companies and sole proprietorships maintain stability. The analysis was performed by means of a survey conducted between May and June 2020 in Flanders (Belgium), using a sample of 542 respondents. After performing a regression analysis combined with expert opinions collected through interviews, we find that companies and sole proprietorships with a higher circularity score have a significantly higher resilience score during crises and during normal times, compared to less circular companies. Furthermore, we find that the size of the company does not matter during a crisis to adapt and react flexibly, while it is important when there is no crisis. Finally, we argue that it is the combination of different circular strategies which yields to the highest results for the organizations' resilience and we provide policy recommendations based on the most asked support measures.

Abstract: Purple non-sulfur bacteria (PNSB) show great potential for environmental and industrial biotechnology, producing microbial protein, biohydrogen, polyhydroxyalkanoates (PHAs), pigments, etc. When grown photoheterotrophically, the carbon source is typically more reduced than the PNSB biomass, which leads to a redox imbalance. To mitigate the excess of electrons, PNSB can exhibit several ‘electron sinking’ strategies, such as CO2 fixation, N2 fixation, and H2 and PHA production. The lack of a comprehensive (over)view of these redox strategies is hindering the implementation of PNSB for biotechnology applications. This review aims to present the state of the art of redox homeostasis in phototrophically grown PNSB, presenting known and theoretically expected strategies, and discussing them from stoichiometric, thermodynamic, metabolic, and economic points of view.

Abstract: With climate change still a pressing issue, there is a great need for carbon capture, utilisation and storage (CCUS)
methods. We propose a novel concept where CO2 conversion is accomplished by O2 splitting followed by the
addition of O atoms to CO2. The latter is studied here by means of kinetic modelling. In the first instance, we
study various CO2/O ratios, and we observe an optimal CO2 conversion of around 30–40% for 50% O addition.
Gas temperature also has a large influence, with a minimum temperature of around 1000 K to a maximum of
2000 K for optimal conversion. In the second instance, we study various CO2/O/O2 ratios, due to O2 being a
starting gas. Also here we define optimal regions for CO2 conversion, which reach maximum conversion for a
CO2 fraction of 50% and an O/O2 ratio bigger than 1. Those can be expanded by heating on one hand, for low
atomic oxygen availability, and by quenching after reaction on the other hand, for cases where the temperatures
are too high. Our model predictions can serve as a guideline for experimental research in this domain.

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: As natural gas prices proved to be very volatile, sustainable alternatives are highly needed. Water-derived H2 was revealed as a promising substitute, allowing to produce a green energy carrier with a minimum of harmful emissions. Direct splitting of earth-abundant seawater provides an eco-friendly route for the production of clean H2, but is hampered by selectivity and stability issues due to the presence of salts.Photocatalytic seawater splitting is particularly promising for this purpose, as it seems less affected by adversary seawater effects and might rely on free and renewable solar power. Unfortunately, the benchmark photocatalyst, TiO2, still suffers from its low solar light activity. It is only actived upon illumination with energetic ultraviolet light (<5% of the sunlight). In order to broaden the activity window to the visible light, the concept of the 'plasmonic rainbow' was explored. Here, TiO2 is modified with various gold-silver composites that possess the unique optical phenomenon of Surface Plasmon Resonance (SPR). This phenomenon enables the absorption of light at very specific wavelengths, depending on the metal type, size, shape and dielectric environment. The light energy might then be converted into hot carriers, strong local electromagnetic fields and/or heat. By combining multiple composites with various sizes and compositions, a broadband absorption could be obtained, resulting in significantly enhanced activity in photocatalytic model reactions under simulated sunlight. The major disadvantage of these plasmonic nanoparticles is their tendency to oxidize and deactivate. To overcome this, polymer shell stabilization strategies were found to be effective to protect the metal cores. Both conductive and non-conductive polymers were studied. For the former, a mix-and-wait strategy generating polyaniline shells of 2-5 nm was used, whille the latter was based on a Layer-by-Layer approach, allowing (sub) nanometer thickness control. For the actual H2 production experiments, the plasmonic loading was optimized in a pure water:methanol scavenger (7:1) mixture and initially the stabilization strategies proofed to be effective for simulated seawater (0.5M NaCl), even after 2 years. However, in real seawater, the activity decreased drastically due to aggregation of the photocatalyst in the presence of multivalent cations. Finally, facile immobilization strategies using 3D printing showed to be able to yield stable, solar active photocatalyst for real seawater splitting.

Abstract: The EPS Antwerp Young Minds (AYM) invited Prof. Nir Navon (Yale University) to hold a colloquium for the physics department. For an audience of students and researchers, Prof. Navon presented recent advances in ultracold quantum matter and research from his own lab. His experimental work paves the way to make toy models used by theorists a reality. We sat down afterwards to discuss ultracold physics, box traps and setting up a lab from scratch.

Abstract: Electrons, X-rays and neutrons that pass through a thin crystalline sample will be diffracted. Diffraction patterns of crystalline materials contain Bragg reflections (sharp discrete intensity maxima) and diffuse scattering (a weak continuous background). The Bragg reflections contain information about the average crystal structure (the type of atoms and the average atomic positions), whereas the diffuse scattering contains information about the short-range order (deviations from the average crystal structure that are ordered on a local scale). Because the properties of many materials depend on the short-range order, refining short-range order parameters is essential for understanding and optimizing material properties. The refinement of short-range order parameters has previously been applied to the diffuse scattering in single-crystal X-ray and single-crystal neutron diffraction data but not yet to the diffuse scattering in single-crystal electron diffraction data. In this work, we will verify the possibility to refine short-range order parameters from the diffuse scattering in single-crystal electron diffraction data. Electron diffraction allows to acquire data on submicron-sized crystals, which are too small to be investigated with single-crystal X-ray and single-crystal neutron diffraction. In the first part of this work, we will refine short-range order parameters from the one-dimensional diffuse scattering in electron diffraction data acquired on the lithium-ion battery cathode material Li1.2Ni0.13Mn0.54Co0.13O2. The number of stacking faults and the twin percentages will be refined from the diffuse scattering using a Monte Carlo refinement. We will also describe a method to determine the spinel/layered phase ratio from the intensities of the Bragg reflections in electron diffraction data. In the second part of this work, we will refine short-range order parameters from the three-dimensional diffuse scattering in both single-crystal electron and single-crystal X-ray diffraction data acquired on Nb0.84CoSb. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms will be refined from the diffuse scattering using a Monte Carlo refinement and a three-dimensional difference pair distribution function refinement. The effect of different experimental parameters on the spatial resolution of the observed diffuse scattering will also be investigated. Finally, the model of the short-range Nb-vacancy order in Nb0.84CoSb will also be applied to LiNi0.5Sn0.3Co0.2O2.

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: Illicit drugs are harmful substances, posing a threat to the health and safety of society. Policies, such as supply reduction and harm reduction, are in place to combat the illicit drug problem. Science can play a substantial role in this fight, by providing tools that enable these policies to be successfully enforced. One example are on-site detection tools, i.e. sensors that allow the on-site identification of an illicit drug in a sample of interest. Several technologies, such as color tests and portable spectroscopic techniques, are currently employed for this goal. Although these are valuable techniques, there is an opportunity for voltammetry, an electrochemical technique, to make an impactful addition to this repertoire of on-site detection tools. Despite its attractive features (low-cost, portable, short analysis time, indifference to color,...), voltammetric illicit drug sensor have failed to make an impact in real scenarios. The work outlined in this PhD thesis aims to change this by bringing the technology from the lab to the field. Strategic choices, fueled by feedback from end-users, were made to further develop those specific aspects of the technology that previously haltered the technology to fulfill its potential. A detection algorithm was introduced that converts the voltammetric output into a clear-cut interpretation thereof, opening up the technology to end-users without prior knowledge of the technology. A sensor that allows qualitative and quantitative detection of the psychoactive drug MDMA was introduced, and importantly, validated on a large set of 212 confiscated samples. A state-of-the art mobile application and adequate sampling methodology were developed, alongside other, often more practical studies and product developments, to evolve the technology into a product that truly creates value for end-users. Important steps towards multidrug detection were made with a festival sensor and a flowchart based on visual appearance that ties together a variety of voltammetric single sensors into a single multidrug sensing approach. Last but not least, multiple valorization aspects were researched, including a market study and an analysis to determine the optimal commercialization strategy. Overall, this PhD thesis has facilitated the transition of the voltammetric illicit drug sensing technology from lab to on-site application. The final application creates value for end-users, and is ready to make an impact in real on-site scenarios.

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: We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification.  The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to  – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at:                    Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323)

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.