Abstract: 200 years ago, humanity started the industrial revolution by discovering fossil fuels, which lead to unprecedented technological advancements. However it has become alarmingly clear that the major environmental concerns associated with fossil fuels require a short-term transition from a carbon-based energy economy to a sustainable one based on green electricity. A key step concerning this transition exists in developing electricity-driven alternatives for chemical processes that rely on fossil fuels as a raw material. A technology that is gaining increasing interest to achieve this, is plasma technology. Using plasmas to induce chemical reactions by selectively heating electrons in a gas has already delivered promising results for gas conversion applications like CO2 conversion and N2 fixation, but plasma reactors still require optimization to be considered industrially competitive to existing fossil fuel-based processes and emerging other electricity-based technologies. In this thesis I develop computational models to describe plasma reactors and identify key mechanisms in three different plasma reactors for three different gas conversion applications, i.e. N2 fixation, combined CO2-CH4 conversion and CO2 splitting. I first developed models to describe a new rotating gliding arc (GA) reactor operating in two arc modes, which, as revealed by my model, are characterized by distinct plasma chemistry pathways. Subsequently, my colleague and I study the quenching effect of an effusion nozzle to this rotating GA reactor, reaching the best results to date for N2 fixation into NOx at atmospheric pressure, i.e., NOx concentrations up to 5.9%, at an energy cost down to 2.1 MJ/mol. Afterwards, I investigate the possible improvement of N2 admixtures in plasma-based CO2 and CH4 conversion, as significant amounts of N2 are often found in industrial CO2 waste streams, and gas separations are financially costly. Through combining my models with the experiment from a fellow PhD student, we reveal that moderate amounts of N2 (i.e. around 20%) increase both the electron density and the gas temperature to yield an overall energy cost reduction of 21%. Finally, I model quenching nozzles for plasma-based CO2 conversion in a microwave reactor, to explain the enhancements in CO2 conversion that were demonstrated in experiments. Through computational modelling I reveal that the nozzle introduces fast gas quenching resulting in the suppression of recombination reactions, which have more impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: A facile, “one-pot”, chemical approach to synthesize gold-based nanoparticles finely dispersed on porous activated carbon (Norit) was demonstrated in this work. The pH of the synthesis bath played a critical role in determining the optimal gold-carbon interaction, which enabled a successful deposition of the gold nanoparticles onto the carbon matrix with a maximized metal utilization of 93 %. The obtained AuNP/C nanocomposite was characterized using SEM, HAADF-STEM electron tomography and electrochemical techniques. It was found that the Au nanoparticles, with diameters between 5 and 20 nm, were evenly distributed over the carbon matrix, both inside and outside the pores. Electrochemical characterization indicated that the composite had a very large electroactive surface area (EASA), as high as 282.4 m2 gAu-1. By exploiting its very high EASA, the catalyst was intended to boost the productivity of glucaric acid in the electrooxidation of its precursor, gluconic acid. However, cyclic voltammetry experiments revealed a very limited reactivity towards gluconic acid oxidation, due to the spacial hindrance of gluconic acid molecule which prevented diffusion inside the catalyst nanopores. On the other hand, the as-synthesized nanocomposite promises to be effective towards the ORR, and might thus find potential application as anode catalyst for fuel cells as well as for the scalability of all those electrochemical reactions involving small molecules with high diffusivity and catalysed by noble metals (i. e. CO2, CH4, N2, etc..). Electrocatalysis: Gold nanoparticles with diameter between 5 and 20 nm evenly distributed onto porous activated carbon (Norit) were obtained using a facile “one-pot” chemical synthesis technique with very high metal utilization. The AuNP/C nanocomposite was characterized using SEM, HAADF-STEM electron tomography and electrochemical techniques, revealing a very large electroactive surface area (EASA). The figure shows the HAADF-STEM image (a) and the respective EDX elemental distribution (b) for the AuNP/C composite with 9.3 % Au-loading developed in this work (Au is marked in red and C in green).image

Abstract: A portable and highly sensitive sensor was designed for the specific detection of 3,4-methyl-enedioxy-methamphetamine (MDMA), in a range of field-testing situations. The sensor can detect MDMA in street samples, even when other controlled substances drugs, or adulterants are present. In this work, we report for the first time a sensor using electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA and then produced using solid phase synthesis. A composite comprising chitosan, reduced graphene oxide, and molecularly imprinted polymer nanoparticles synthesized for MDMA for the first time was immobilized on screen-printed carbon electrodes. The sensors displayed a satisfactory sensitivity (106.8 nA x mu M-1), limit of detection (1.6 nM; 0.31 ng/mL), and recoveries (92-99%). The accuracy of the results was confirmed through validation using Ultra-High Performance Liquid Chromatography coupled with tandem Mass Spectrometry (UPLC-MS/MS). This technology could be used in forensic analysis and make it possible to selectively detect MDMA in street samples. A highly sensitive and portable sensor has been developed to detect MDMA in street samples. It uses electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA, which were immobilized on screen-printed carbon electrodes with chitosan and graphene. The sensor showed good sensitivity and satisfactory recoveries (92-99%), confirmed with UPLC-MS/MS validation. This technology has the potential to be used in forensic analysis.image

Abstract: A supersolid, a counterintuitive quantum state in which a rigid lattice of particles flows without resistance, has to date not been unambiguously realized. Here we reveal a supersolid ground state of excitons in a double-layer semiconductor heterostructure over a wide range of layer separations outside the focus of recent experiments. This supersolid conforms to the original Chester supersolid with one exciton per supersolid site, as distinct from the alternative version reported in cold-atom systems of a periodic density modulation or clustering of the superfluid. We provide the phase diagram augmented by the supersolid. This new phase appears at layer separations much smaller than the predicted exciton normal solid, and it persists up to a solid-solid transition where the quantum phase coherence collapses. The ranges of layer separations and exciton densities in our phase diagram are well within reach of the current experimental capabilities.

Abstract: A wave-packet time evolution method, based on the split-operator technique, is developed to investigate the scattering of quasiparticles at a normal-superconductor interface of arbitrary profile and shape. As a practical application, we consider a system where low-energy electrons can be described as Dirac particles, which is the case for most two-dimensional materials, such as graphene and transition-metal dichalcogenides. However, the method is easily adapted for other cases such as electrons in few-layer black phosphorus or any Schrodinger quasiparticles within the effective mass approximation in semiconductors. We employ the method to revisit Andreev reflection in mono-, bi-, and trilayer graphene, where specular-and retro-reflection cases are observed for electrons scattered by a steplike superconducting region. The effect of opening a zero-gap channel across the superconducting region on the electron and hole scattering is also addressed, as an example of the versatility of the technique proposed here.

Abstract: Accurate barriers for rate controlling elementary reactions on metal surfaces are key to understanding, controlling, and predicting the rate of heterogeneously catalyzed processes. While barrier heights for gas phase reactions have been extensively benchmarked, dissociative chemisorption barriers for the reactions of molecules on metal surfaces have received much less attention. The first database called SBH10 and containing 10 entries was recently constructed based on the specific reaction parameter approach to density functional theory (SRP-DFT) and experimental results. We have now constructed a new and improved database (SBH17) containing 17 entries based on SRP-DFT and experiments. For this new SBH17 benchmark study, we have tested three algorithms (high, medium, and light) for calculating barrier heights for dissociative chemisorption on metals, which we have named for the amount of computational effort involved in their use. We test the performance of 14 density functionals at the GGA, GGA+vdW-DF, and meta-GGA rungs. Our results show that, in contrast with the previous SBH10 study where the BEEF-vdW-DF2 functional seemed to be most accurate, the workhorse functional PBE and the MS2 density functional are the most accurate of the GGA and meta-GGA functionals tested. Of the GGA+vdW functionals tested, the SRP32-vdW-DF1 functional is the most accurate. Additionally, we found that the medium algorithm is accurate enough for assessing the performance of the density functionals tested, while it avoids geometry optimizations of minimum barrier geometries for each density functional tested. The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. While these are avoided in the light algorithm, this algorithm is found not to give a reliable description of functional performance. The combination of relative ease of use and demonstrated reliability of the medium algorithm will likely pave the way for incorporation of the SBH17 database in larger databases used for testing new density functionals and electronic structure methods.

Abstract: Air pollution is proclaimed by the World Health Organiaation (WHO) as the biggest environmental threat to human health. Street canyons, or urban roads flanked by a continuous row of high buildings on both sides, are perceived as typical bottleneck areas for air quality due to their lack of natural ventilation. This doctoral thesis aims to integrate expert knowledge on in-canyon flow fields and pollution dispersion in street canyons from the specialized field of (bio)engineering into the field of urban planning and vice versa. In Chapter 1, a Geospatial Information System (GIS) method was developed to detect exposure zones and hotspot street canyons. A critical combination between aspect ratio (AR > 0.65) and traffic volume (TVmax > 300) was detected and subsequently used to detect hotspot street canyons in three major European cities (Antwerp, London and Paris). Chapter 2 focusses on acquiring in-depth knowledge on flow and concentration fields in street canyons by conducting an extensive literature review on over 200 studies and translates this knowledge into nineteen guidelines and eleven spatial tools, comprised in a toolbox for urban planning. Subsequently, computational fluid dynamics (CFD) was used into a research trough design process (Chapter 4) to illustrate how the design tools can be applied to a specific case study (Belgiëlei, Antwerp). Alternations to traffic lanes (traffic lane reduction and lateral displacement) combined with low boundary walls (LBWs), were found to reduce NO2 levels in the entire pedestrian area up to – 3.6 % and peak pollutions were reduced by -8 %. A maximum NO2 reduction was reached by combining a traffic lane displacement with hedges, adjustments to the tree planting pattern and an increased ground-level permeability, leading to reductions up to – 4.5 % in the pedestrian areas. In conclusion, urban design was found to be a valuable tool to enhance the effect of emission reduction strategies and draw in-canyon concentrations closer to the value of the background concentration. However, the background concentration seemed to dominate the efficiency of the urban design interventions and therefore, additional measures should be taken to reduce background pollution levels. This dissertation aims to contribute to the awareness of air pollution in street canyons, as well as support local governments in taking action by delivering spatial tools and guidelines applicable for urban planning and represents a framework for the dissemination of expert information on air quality in street canyons to the field of urban planning.