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: Background Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. Methods Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. Results OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D (R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, infra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. Conclusion Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

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: Although the heterogeneity of pyrolyzed Fe???N???C materials is known and has been reported previously, the atomic structure of the active sites and their detailed reaction mechanisms are still unknown. Here, we identified two pyridinic Fe???N4-like centers with different local C coordinates, i.e., FeN4C8 and FeN4C10, and studied their electrocatalytic activity for the nitrogen reduction reaction (NRR) based on density functional theory (DFT) calculations. We also discovered the influence of the adsorption of NH2 as a functional ligand on catalyst performance on the NRR. We confirmed that the NRR selectivity of the studied catalysts is essentially governed either by the local C coordination or by the dynamic structure associated with the FeII/FeIII. Our investigations indicate that the proposed traditional pyridinic FeN4C10 has higher catalytic activity and selectivity for the NRR than the robust FeN4C8 catalyst, while it may have outstanding activity for promoting other (electro)catalytic reactions. <comment>Superscript/Subscript Available</comment

Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.

Abstract: The application of dielectric barrier discharge (DBD) plasma reactors is promising in various environmental and energy processes, but is limited by their low energy yield. In this study, we put a number of stainless steel rings over the inner electrode rod of the DBD reactor to change the local discharge gap and electric field, and we studied the dry reforming performance. At 50 W supplied power, the metal rings mostly have a negative impact on the performance, which we attribute to the non-uniform spatial distribution of the discharges caused by the rings. However, at 30 W supplied power, the energy yield is higher than at 50 W and the placement of the rings improves the performance of the reactor. More rings and with a larger cross-sectional diameter can further improve the performance. The reactor with 20 rings with a 3.2 mm cross-sectional diameter exhibits the best performance in this study. Compared to the reactor without rings, it increases the CO2 conversion from 7% to 16 %, the CH4 conversion from 12% to 23%, and the energy yield from 0.05 mmol/kJ supplied power to 0.1 mmol/kJ (0.19 mmol/kJ if calculated from the plasma power), respectively. The presence of the rings increases the local electric field, the displaced charge and the discharge fraction, and also makes the discharge more stable and with more uniform intensity. It also slightly improves the selectivity to syngas. The performance improvement observed by placing stainless steel rings in this study may also be applicable to other plasma-based processes.

Abstract: The effect of pore size on plasma catalysis is crucial but still unclear. Studies have shown plasma cannot enter micropores and mesopores, so catalysts for traditional thermocatalysis may not fit plasma catalysis. Here, 3D porous Cu and CuO with different pore sizes were prepared using uniform silica particles (10–2000 nm) as templates, and compared in plasma-catalytic dry reforming. In most cases, the smaller the pore size, the higher the conversion of CH4 and CO2. Large pores reachable by more electrons did not improve the reaction efficiency. We attribute this to the small surface area and large crystallite size, as indicated by N2-sorption, mercury intrusion and XRD. While the smaller pores might not be reachable by electrons, due to the sheath formed in front of them, as predicted by modeling, they can still be reached by radicals formed in the plasma, and ions can even be attracted into these pores. An exception are the samples synthesized from 1 μm silica, which show better performance. We believe this is due to the electric field enhancement for pore sizes close to the Debye length. The performances of CuO and Cu with different pore sizes can provide references for future research on oxide supports and metal components of plasma catalysts.

Abstract: Electron tomography is a widely used technique for 3D structural analysis of nanomaterials, but it can cause damage to samples due to high electron doses and long exposure times. To minimize such damage, researchers often reduce beam exposure by acquiring fewer projections through tilt undersampling. However, this approach can also introduce reconstruction artifacts due to insufficient sampling. Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples. Current methods for determining this optimal number of projections involve acquiring and post-processing multiple reconstructions with different numbers of projections, which can be time-consuming and requires multiple samples due to sample damage. To improve this process, we propose a protocol that combines golden ratio scanning and quasi-3D reconstruction to estimate the optimal number of projections in real-time during a single acquisition. This protocol was validated using simulated and realistic nanoparticles, and was successfully applied to reconstruct two beam-sensitive metal–organic framework complexes.

Abstract: Plasma catalysis is emerging for plasma-assisted gas conversion
processes. However, the underlying mechanisms of plasma catalysis are poorly
understood. In this work, we present a 1D heterogeneous catalysis model with axial
dispersion (i.e., accounting for back-mixing and molecular diffusion of fluid elements in
the process stream in the axial direction), for plasma-catalytic NO production from
N2/O2 mixtures. We investigate the concentration and reaction rates of each species
formed as a function of time and position across the catalyst, in order to determine the
underlying mechanisms. To obtain insights into how the performance of the process
can be further improved, we also study how changes in the postplasma gas flow
composition entering the catalyst bed and in the operation conditions of the catalytic
stage affect the performance of NO production.

Abstract: Sustainable management of industrial plastic waste is crucial in the transition to a circular economy. Today, most industrial plastic waste is incinerated, whereas it could be recycled. As a consequence, governments increasingly make use of incineration taxes to improve current waste management practices. This paper presents an econometric panel analysis that studies the effects of an incineration tax on industrial plastic waste in Flanders (Belgium). Not only is this study the first econometric analysis on industrial plastic waste management in which firm heterogeneity is explicitly taken into account by including firm-specific characteristics, but this study also provides policymakers with insights into the effectiveness of an incineration tax to change current waste management practices. Empirical estimates imply that heterogeneous firms generate industrial plastic waste in different ways and that heterogeneous firms reduce their waste generation in different ways after the incineration tax rate increases. The estimates also show that the unique decrease of the incineration tax in 2007, did not change waste management practices. These estimates show that firms do not disinvest or indicate that loss aversion theory, i.e. a preference for avoiding losses over acquiring equivalent gains, might apply to firms that are faced with environmental taxation in a waste management context.

Abstract: The current global energy crisis indicated that increasing our
insight into nonfossil fuel nitrogen fixation pathways for synthetic fertilizer
production is more crucial than ever. Nonequilibrium plasma is a good candidate
because it can use N2 or air as a N source and water directly as a H source, instead
of H2 or fossil fuel (CH4). In this work, we investigate NH3 gas phase formation
pathways from humid N2 and especially humid air up to 2.4 mol % H2O (100%
relative humidity at 20 °C) by optical emission spectroscopy and Fouriertransform
infrared spectroscopy. We demonstrate that the nitrogen fixation
capacity is increased when water vapor is added, as this enables HNO2 and NH3
production in both N2 and air. However, we identified a significant loss
mechanism for NH3 and HNO2 that occurs in systems where these species are
synthesized simultaneously; i.e., downstream from the plasma, HNO2 reacts with NH3 to form NH4NO2, which rapidly decomposes
into N2 and H2O. We also discuss approaches to prevent this loss mechanism, as it reduces the effective nitrogen fixation when not
properly addressed and therefore should be considered in future works aimed at optimizing plasma-based N2 fixation. In-line removal
of HNO2 or direct solvation in liquid are two proposed strategies to suppress this loss mechanism. Indeed, using liquid H2O is
beneficial for accumulation of the N2 fixation products. Finally, in humid air, we also produce NH4NO3, from the reaction of HNO3
with NH3, which is of direct interest for fertilizer application.

Abstract: Electron microscopy is an indispensable tool for the characterization of (nano) materials. Electron microscopes are typically very expensive and their internal operation is often shielded from the user. This situation can provide fast and high quality results for researchers focusing on e.g. materials science if they have access to the relevant instruments. For researchers focusing on technique development, wishing to test novel setups, however, the high entry price can lead to risk aversion and deter researchers from innovating electron microscopy technology further. The closed attitude of commercial entities about how exactly the different parts of electron microscopes work, makes it even harder for newcomers in this field. Here we propose an affordable, easy-to-build electron detector for use in a scanning electron microscope (SEM). The aim of this project is to shed light on the functioning of such detectors as well as show that even a very modest design can lead to acceptable performance while providing high flexibility for experimentation and customization.

Abstract: Given the ecological problems associated to the CO2 emissions of fossil fuels, plasma technology has gained
interest for conversion of CO2 into value-added products. Microwave plasmas operating at atmospheric pressure
have proven to be especially interesting, due to the high gas temperatures inside the reactor (i.e. up to 6000 K)
allowing for efficient thermal dissociation of CO2 into CO and O2. However, the performance of these high
temperature plasmas is limited by recombination of CO back into CO2 once the gas cools down in the afterglow.
In this work, we computationally investigated several quenching nozzles, developed and experimentally tested
by Hecimovic et al., [1] for their ability to quickly cool the gas after the plasma, thereby quenching the CO
recombination reactions. Using a 3D computational fluid dynamics model and a quasi-1D chemical kinetics
model, we reveal that a reactor without nozzle lacks gas mixing between hot gas in the center and cold gas near
the reactor walls. Especially at low flow rates, where there is an inherent lack of convective cooling due to the
low gas flow velocity, the temperature in the afterglow remains high (between 2000 and 3000 K) for a relatively
long time (in the 0.1 s range). As shown by our quasi-1D chemical kinetics model, this results in a important loss
of CO due to recombination reactions. Attaching a nozzle in the effluent of the reactor induces fast gas quenching
right after the plasma. Indeed, it introduces (i) more convective cooling by forcing cool gas near the walls to mix
with hot gas in the center of the reactor, as well as (ii) more conductive cooling through the water-cooled walls of
the nozzle. Our model shows that gas quenching and the suppression of recombination reactions have more
impact at low flow rates, where recombination is the most limiting factor in the conversion process.

Abstract: Immunoassays exploiting magnetization dynamics of magnetic nanoparticles are highly promising for mix-and-measure, quantitative, and point-of-care diagnostics. However, how single-core magnetic nanoparticles can be employed to reduce particle concentration and concomitantly maximize assay sensitivity is not fully understood. Here, we design monodisperse Néel and Brownian relaxing magnetic nanocubes (MNCs) of different sizes and compositions. We provide insights into how to decouple physical properties of these MNCs to achieve ultrahigh sensitivity. We find that tri-component-based Zn0.06 Co0.80Fe2.14 O4 particles, with out-of-phase to initial magnetic susceptibility χ /χ ratio of 0.47 out of 0.50 for magnetically blocked ideal particles, show the ultrahigh magnetic sensitivity by providing rich magnetic particle spectroscopy (MPS) harmonics spectrum despite bearing lower saturation magnetization than di-component Zn0.1Fe2.9O4 having high saturation magnetization. The Zn0.06Co0.80Fe2.14O4 MNCs, coated with catechol-based polyethylene glycol ligands, measured by our benchtop MPS show three orders of magnitude better particle LOD than that of commercial nanoparticles of comparable size.

Abstract: We present a zero-dimensional kinetic model to characterise specifically the gas-phase dynamics of methane
conversion in a nanosecond pulsed discharge (NPD) plasma reactor. The model includes a systematic approach to
capture the nanoscale power discharges and the rapid ensuing changes in electric field, gas and electron temperature,
as well as species densities. The effects of gas temperature and reactor pressure on gas conversion and
product selectivity are extensively investigated and validated against experimental work. We discuss the
important reaction pathways and provide an analysis of the dynamics of the heating and cooling mechanisms. H
radicals are found to be the most populous plasma species and they participate in hydrogenation and dehydrogenation
reactions, which are the dominant recombination reactions leading to C2H4 and C2H2 as main
products (depending on the pressure).