Abstract: In this article we report on the synthesis and characterization of a system of colloidal spheres suspended in an aqueous solvent which can be refractive index-matched, thus allowing for investigations of the particle near-wall dynamics by evanescent wave dynamic light scattering at concentrations up to the isotropic to ordered transition and beyond. The particles are synthesized by copolymerization of a fluorinated acrylic ester monomer with a polyethylene-glycol (PEG) oligomer by surfactant free emulsion polymerization. Static and dynamic light scattering experiments in combination with cryo transmission electron microscopy reveal that the particles have a core shell structure with a significant enrichment of the PEG chains on the particles surface. In index-matching DMSO/water suspensions the particles arrange in an ordered phase at volume fraction above 7%, if no additional electrolyte is present. The near-wall dynamics at low volume fraction are quantitatively described by the combination of electrostatic repulsion and hydrodynamic interaction between the particles and the wall. At volume fractions close to the isotropic to ordered transition, the near-wall dynamics are more complex and qualitatively reminiscent of the behaviour which was observed in hard sphere suspensions at high concentrations.

Abstract: Nitrate contamination of groundwater has been recognized as a significant environmental problem world widely. Sulfur-driven mixotrophic denitrification has been demonstrated as a promising groundwater treatment process, which though plays an important role in nitrous oxide (N2O) emissions, significantly contributing to the overall carbon footprint of the system. However, the current process optimizations only focus on nitrate removal and excess sulfate control, with the N2O emission being ignored. In this work, an integrated mathematical model was proposed to evaluate the N2O emission as well as the excess sulfate production and carbon source utilization in sulfur-driven mixotrophic denitrification process. In this model, autotrophic and heterotrophic denitrifiers use their corresponding electron donors (sulfur and organic matter, respectively) to reduce nitrate to nitrogen gas, with each modeled as three-step denitrification (NO3 to N-2 via NO2 and N2O) driven by sulfur or organic matter to describe all potential N2O accumulation steps. The developed model, employing model parameters previously reported in literature, was successfully validated using N2O and sulfate data from two mixotrophic denitrification systems with different initial conditions. Modeling results revealed substantial N2O accumulation due to the relatively low autotrophic N2O reduction activity as compared to heterotrophic N2O reduction activity, explaining the observation that higher carbon source addition resulted in lower N2O accumulation in sulfur-driven mixotrophic denitrifying system. Based on the validated model, optimizations of the overall system performance were carried out. Application of the model to simulate long-term operations of sulfur-driven mixotrophic denitrification process indicates that longer sludge retention time reduces N2O emission due to better retention of active biomass. High-level total nitrogen removal with significant N2O emission mitigation, appropriate excess sulfate control and maximized COD utilization can be achieved simultaneously through controlling the influent nitrate and COD concentrations. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: Belgium has passed the 45% cap, mandated by the European Union, by achieving a collection rate of over 50% in 2012. Having such a collection rate, Belgium is amongst the frontrunners in battery recycling in Europe. However, despite the efforts, about 40% of used batteries are still not properly collected. Particularly troublesome according to the national producer responsibility organization are the battery packs. In this paper we therefore investigate the drivers and barriers to battery pack drop-off intention perceived by Belgian households using an integrative model based on the Theory of Planned Behaviour. An R2 of 0.64 was found, which according to the literature on partial least squares structural equation modelling signals a moderate yet very close to substantial coefficient of determination. We find that on average perceived behavioural control and moral norms have the largest influence on the intention to drop-off used battery packs as quickly as possible. Based on the insights gained, recommendations are made for both behaviour change interventions and future research.

Abstract: As the search for marketable photovoltaic solar cells continues, organic photovoltaic (OPV) solar cells have been identified as a technology with many attractive features for commercialization. Most photovoltaic technologies on the market today were improved in the consumer electronics market segment. A similar evolution has been envisioned for OPV. Hence this paper investigates consumer preferences for solar cells directly powering consumer electronics. Choice experiments were designed and responses were collected using a random sample of 300 individuals from the Flemish region (northern part of Belgium). Results allow for computation of attribute importance, willingness to pay (WTP), and simulation of theoretical market share. These measures point towards OPV being able to reach considerable market share in the long run, bearing in mind that efforts are first needed in elevating OPV's efficiency and lifetime as they most determine consumers' preferences. Price is found to be the least important product characteristic for OPV solar cells to be incorporated in consumer electronics devices. We therefore warn against generalizing attributes' importance across the boundaries of market segments. (C) 2012 Elsevier B.V. All rights reserved.

Abstract: Solar-powered consumer electronics are a likely starting point for organic photovoltaic (OPV) market development. Therefore, a generic discrete choice experiments study can determine how Flemish consumers value solar-cell characteristics for solar-poweied consumer electronics. Such characteristics include efficiency, lifetime, aesthetics, integratability, and price. We contribute to the literature by investigating preference heterogeneity in a solar-power niche market with an experimental design with a fixed reference alternative. The error components random parameter logit (ECRPL) with interactions provides a better fit than the latent class (LC) model for our choice data. The main effects had the expected signs. Consequently, aesthetics and integratability are OPV's assets. Nevertheless, heterogeneity puts the results that are valid for the average consumer into perspective. Based on our findings, OPV commercialization efforts should target the experienced, impatient user who highly values design and functionality. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Advanced electron microscopy techniques, including scanning electron microscopes (SEM), scanning transmission electron microscopes (STEM), and transmission electron microscopes (TEM), have revolutionized imaging capabilities. However, achieving high-quality experimental images remains a challenge due to various distortions stemming from the instrumentation and external factors. These distortions, introduced at different stages of imaging, hinder the extraction of reliable quantitative insights. In this paper, we will discuss the main sources of distortion in TEM and S(T)EM images, develop models to describe them, and propose a method to correct these distortions using a convolutional neural network. We validate the effectiveness of our method on a range of simulated and experimental images, demonstrating its ability to significantly enhance the signal-to-noise ratio. This improvement leads to a more reliable extraction of quantitative structural information from the images. In summary, our findings offer a robust framework to enhance the quality of electron microscopy images, which in turn supports progress in structural analysis and quantification in materials science and biology.

Abstract: A new version of the open source program MULTEM is presented here. It includes a graphical user interface, tapering truncation of the atomic potential, CPU multithreading functionality, single/double precision calculations, scanning transmission electron microscopy (STEM) simulations using experimental detector sensitivities, imaging STEM (ISTEM) simulations, energy filtered transmission electron microscopy (EFTEM) simulations, STEM electron energy loss spectroscopy (EELS) simulations along with other improvements in the algorithms. We also present a mixed channeling approach for the calculation of inelastic excitations, which allows one to considerably speed up time consuming EFTEM/STEM-EELS calculations.

Abstract: The main features and the GPU implementation of the MULTEM program are presented and described. This new program performs accurate and fast multislice simulations by including higher order expansion of the multislice solution of the high energy Schrodinger equation, the correct subslicing of the three-dimensional potential and top-bottom surfaces. The program implements different kinds of simulation for CTEM, STEM, ED, PED, CBED, ADF-TEM and ABF-HC with proper treatment of the spatial and temporal incoherences. The multislice approach described here treats the specimen as amorphous material which allows a straightforward implementation of the frozen phonon approximation. The generalized transmission function for each slice is calculated when is needed and then discarded. This allows us to perform large simulations that can include millions of atoms and keep the computer memory requirements to a reasonable level. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Metal halide perovskites are one of the most investigated materials in optoelectronics, with their lead-based counterparts being renowned for their enhanced optoelectronic performance. The 3D CsPbX3 structure has set the standard with many studies currently attempting to substitute lead with other metals while retaining the properties of this material. This effort has led to the fabrication of metal halides with lower dimensionality, wherein particular 2D layered perovskite structures have captured attention as inspiration for the next generation of colloidal semiconductors. Here we report the synthesis of the Ruddlesden-Popper Cs2CdCl4:Sb3+ phase as colloidal nanoplatelets (NPs) using a facile hot injection approach under atmospheric conditions. Through strict adjustment of the synthesis parameters with emphasis on the ligand ratio, we obtained NPs with a relatively uniform size and good morphological control. The particles were characterized through transmission electron microscopy, synchrotron X-ray diffraction, and pair distribution function analysis. The spectroscopic characterization revealed most strikingly an intense cyan emission under UV excitation with a measured PLQY of similar to 20%. The emission was attributed to the Sb3+-doping within the structure.

Abstract: Plasma-catalytic dry reforming of CH4 (DRM) is promising to convert the greenhouse gasses CH4 and CO2 into value-added chemicals, thus simultaneously providing an alternative to fossil resources as feedstock for the chemical industry. However, while many experiments have been dedicated to plasma-catalytic DRM, there is no consensus yet in literature on the optimal choice of catalyst for targeted products, because the underlying mechanisms are far from understood. Indeed, plasma catalysis is very complex, as it encompasses various chemical and physical interactions between plasma and catalyst, which depend on many parameters. This complexity hampers the comparison of experimental results from different studies, which, in our opinion, is an important bottleneck in the further development of this promising research field. Hence, in this perspective paper, we describe the important physical and chemical effects that should be accounted for when designing plasma-catalytic experiments in general, highlighting the need for standardized experimental setups, as well as careful documentation of packing properties and reaction conditions, to further advance this research field. On the other hand, many parameters also create many windows of opportunity for further optimizing plasma-catalytic systems. Finally, various experiments also reveal the lack of improvement in plasma catalysis compared to plasma-only, specifically for DRM, but the underlying mechanisms are unclear. Therefore, we present our newly developed coupled plasma-surface kinetics model for DRM, to provide more insight in the underlying reasons. Our model illustrates that transition metal catalysts can adversely affect plasmacatalytic DRM, if radicals dominate the plasma-catalyst interactions. Thus, we demonstrate that a good understanding of the plasma-catalyst interactions is crucial to avoiding conditions at which these interactions negatively affect the results, and we provide some recommendations for improvement. For instance, we believe that plasma-catalytic DRM may benefit more from higher reaction temperatures, at which vibrational excitation can enhance the surface reactions.