Abstract: In this paper, an overview is given of modeling activities going on in our research group, for describing the plasma chemistry and plasmasurface interactions in reactive plasmas. The plasma chemistry is calculated by a fluid approach or by hybrid Monte Carlo (MC)fluid modeling. An example of both is illustrated in the first part of the paper. The example of fluid modeling is given for a dielectric barrier discharge (DBD) in CH4/O2, to describe the partial oxidation of CH4 into value-added chemicals. The example of hybrid MCfluid modeling concerns an inductively coupled plasma (ICP) etch reactor in Ar/Cl2/O2, including also the description of the etch process. The second part of the paper deals with the treatment of plasmasurface interactions on the atomic level, with molecular dynamics (MD) simulations or a combination of MD and MC simulations.

Abstract: We present here some of our modeling efforts for PECVD growth of nanostructured carbon materials with focus on amorphous hydrogenated carbon. Experimental data from an expanding thermal plasma setup were used as input for the simulations. Attention was focused both on the film growth mechanism, as well as on the hydrocarbon reaction mechanisms during growth of the films. It is found that the reaction mechanisms and sticking coefficients are dependent on the specific surface sites, and the structural properties of the growth radicals. The film growth results are in correspondence with the experiment. Furthermore, it is found that thin a-C:H films can be densified using an additional H-flux towards the substrate.

Abstract: Plasma-based CO2 conversion is gaining increasing interest worldwide. A large research effort is devoted to improving the energy efficiency. For this purpose, it is very important to understand the underlying mechanisms of the CO2 conversion. The latter can be obtained by computer modeling, describing in detail the behavior of the various plasma species and all relevant chemical processes. However, the accuracy of the modeling results critically depends on the accuracy of the assumed input data, like cross sections. This is especially true for the cross section of electron impact dissociation, as the latter process is believed
to proceed through electron impact excitation, but it is not clear from the literature which excitation channels effectively lead to dissociation. Therefore, the present paper discusses the effect of different electron impact dissociation cross sections reported in the literature on the calculated CO2 conversion, for a dielectric barrier discharge (DBD) and a microwave (MW) plasma. Comparison is made to experimental data for the DBD case, to elucidate which cross section might be the most realistic. This comparison reveals that the cross sections proposed
by Itikawa and by Polak and Slovetsky both seem to underestimate the CO2 conversion. The cross sections recommended by Phelps with thresholds of 7 eV and 10.5 eV yield a CO2 conversion only slightly lower than the experimental data, but the sum of both cross sections overestimates the values, indicating that these cross sections represent dissociation, but most probably also include other (pure excitation) channels. Our calculations indicate that the choice of the electron impact dissociation cross section is crucial for the DBD, where this process is the dominant mechanism for CO2 conversion. In the MW plasma, it is only significant at pressures up to 100 mbar, while it is of minor importance for higher pressures, when dissociation proceeds mainly through collisions of CO2 with heavy particles.

Abstract: Modeling results are presented to gain a better insight in the properties of a SiH4/O2/Ar inductively coupled plasma (ICP) and how it interacts with a silicon substrate (wafer), as applied in the microelectronics industry for the fabrication of electronic devices. The SiH4/O2/Ar ICP is used for the filling of microtrenches with isolating material (SiO2), as applied in shallow trench isolation (STI). In this article, a detailed reaction set that describes the plasma chemistry of SiH4/O2/Ar discharges as well as surface processes, such as sputtering, oxidation, and deposition, is presented. Results are presented on the plasma properties during the plasma enhanced chemical vapor deposition process (PECVD) for different gas ratios, as well as on the shape of the filled trenches and the surface compositions of the deposited layers. For the operating conditions under study it is found that the most important species accounting for deposition are SiH2, SiH3O, SiH3 and SiH2O, while SiH+2, SiH+3, O+2 and Ar+ are the dominant species for sputtering of the surface. By diluting the precursor gas (SiH4) in the mixture, the deposition rate versus sputtering rate can be controlled for a desired trench filling process. From the calculation results it is clear that a high deposition rate will result in undesired void formation during the trench filling, while a small deposition rate will result in undesired trench bottom and mask damage by sputtering. By varying the SiH4/O2 ratio, the chemical composition of the deposited layer will be influenced. However, even at the highest SiH4/O2 ratio investigated (i.e., 3.2:1; low oxygen content), the bulk deposited layer consists mainly of SiO2, suggesting that low-volatile silane species deposit first and subsequently become oxidized instead of being oxidized first in the plasma before deposition. Finally, it was found that the top surface of the deposited layer contained less oxygen due to preferential sputtering of O atoms, making the top layer more Si-rich. However, this effect is negligible at a SiH4/O2 ratio of 2:1 or lower.

Abstract: Recently, a process has been proposed for generating negatively-curved carbon schwarzites via zeolite-templating (Braun et al., 2018). However, the proposed process leads to atomistic models which are not very symmetric and often rather defective. In the present work, an improved generation approach is developed, by imposing symmetry constraints, which systematically leads to defect-free, hence more stable, schwarzites. The stability of the newly predicted symmetric schwarzites is also compared to that of other carbon nanostructures (in particular carbon nanotubes – CNTs), which could also be accommodated within the same templates. Our results suggest that only a few of these (such as FAU, SBT and SBS) can fit schwarzites more stable than CNTs. Our predictions could help experimentalists in the crucial choice of the template for the challenging synthesis of schwarzites. Furthermore, being highly symmetric and stable phases, the models could also be synthesized by means of other experimental procedures.

Abstract: The rate of charge deposition in quartz grains irradiated in natural conditions is computed by radiation transport modeling. Quartz luminescence models are modified with the addition of the resulting charge deposition term, and the influence of this process on the optically stimulated luminescence (OSL) signal is analyzed. The results indicate that the charge deposition occurring in the quartz grain during the time of residence within rock could lead to the depletion of trapped holes in the recombination centres. For the two different quartz models investigated here, complete depletion is expected to occur for rock ages between 500 Ma and 1100 Ma. It is predicted that for sedimentary quartz derived from such rocks, the OSL signal is dominated by the slow component. It was also found that the shape and saturation level of the natural sensitivity-corrected dose response curve (DRC) of quartz is affected by the charge deposition; specifically, a linear reduction of the saturation level with the age of the rock is observed.

Abstract: The possibility of application of nanomaterials is determined by our ability to control the properties of the materials, which are ultimately determined by their structure and hence their growth processes. We employ hybrid molecular dynamics / Monte Carlo (MD/MC) simulations to explore the growth of SWNTs and graphene on nickel as a catalyst, with the specific goal of unraveling the growth mechanisms. While the general observations are in agreement with the literature, we find a number of interesting phenomena to be operative which are crucial for the growth, and which are not accessible by MD simulations alone due to the associated time scale. Specifically, we observe metal mediated healing and restructuring processes to take place, reorganizing the carbon network during the initial nucleation step. In the case of carbon nanotube growth, this leads to the growth of tubes with a determinable chirality. In the case of graphene formation, we find that graphene is only formed at temperatures above 700 K. These results are of importance for understanding the growth mechanisms of these carbon nanomaterials on the fundamental level.

Abstract: We develop an analytical model for a tunnel field-effect transistor (TFET) with a tilted source junction angle. The tunnel current is derived by using circular tunnel paths along the electric field. The analytical model predicts that a smaller junction angle improves the TFET performance, which is supported by device simulations. An analysis is also made based on straight tunnel paths and tunnel paths corresponding to the trajectory of a classical particle. In all the aforementioned cases, the same conclusions are obtained. A TFET configuration with an encroaching polygon source junction is studied to analyze the junction angle dependence at the smallest junction angles. The improvement of the subthreshold swing (SS) with decreasing junction angle can be achieved by using thinner effective oxide thickness, smaller band gap material and longer encroaching length of the encroaching junction. A TFET with a smaller junction angle on the source side also has an innate immunity against the degradation of the fringing field from the gate electrode via a high-k spacer. A large junction angle on the drain side can suppress the unwanted ambipolar current of TFETs. (c) 2011 Elsevier Ltd. All rights reserved.

Abstract: Natural deep eutectic solvents (NADES) are mixtures of naturally derived compounds with a significantly decreased melting point due to the specific interactions among the constituents. NADES have benign properties (low volatility, flammability, toxicity, cost) and tailorable physicochemical properties (by altering the type and molar ratio of constituents), hence they are often considered as a green alternative to common organic solvents. Modeling the relation between their composition and properties is crucial though, both for understanding and predicting their behavior. Several efforts were done to this end, yet this review aims at structuring the present knowledge as an outline for future research. First, we reviewed the key properties of NADES and relate them to their structure based on the available experimental data. Second, we reviewed available modeling methods applicable to NADES. At the molecular level, density functional theory and molecular dynamics allow interpreting density differences and vibrational spectra, and computation of interaction energies. Additionally, properties at the level of the bulk media can be explained and predicted by semi-empirical methods based on ab initio methods (COSMO-RS) and equation of state models (PC-SAFT). Finally, methods based on large datasets are discussed; models based on group contribution methods and machine learning. A combination of bulk media and dataset modeling allows qualitative prediction and interpretation of phase equilibria properties on the one hand, and quantitative prediction of melting point, density, viscosity, surface tension and refractive indices on the other hand. In our view, multiscale modeling, combining the molecular and macroscale methods, will strongly enhance the predictability of NADES properties and their interaction with solutes, yielding truly tailorable solvents to accommodate (bio)chemical reactions.

Abstract: A theoretical study of ultrashort laser-induced electron emission from a negatively biased metallic cathode has been performed. Classical as well as tunneling electron emission mechanisms are considered. It was found that electron emission is governed by an interplay of processes inside as well as above the cathode. A hybrid model is proposed, where the electron distribution within the target is retrieved from Boltzmann scattering integrals, while the charge distribution above it is studied by a Particle-In-Cell simulation. The results indicate that non-equilibrium effects determine the initial emission process, whereas the space charge above the target suppresses the effectively emitted charge.

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: Antibiotics such as sulfamethoxazole (SFX) are environmentally hazardous after being released into the aquatic environment and challenges remain in the development of engineered prevention strategies. In this work, a mathematical model was developed to describe and evaluate cometabolic biotransformation of SFX and its transformation products (TPs) in an enriched ammonia oxidizing bacteria (AOB) culture. The growth-linked cometabolic biodegradation by AOB, non-growth transformation by AOB and nongrowth transformation by heterotrophs were considered in the model framework. The production of major TPs comprising 4-Nitro-SFX, Desamino-SFX and N-4-Acetyl-SFX was also specifically modelled. The validity of the model was demonstrated through testing against literature reported data from extensive batch tests, as well as from long-term experiments in a partial nitritation sequencing batch reactor (SBR) and in a combined SBR + membrane aerated biofilm reactor performing nitrification/denitrification. Modelling results revealed that the removal efficiency of SFX increased with the increase of influent ammonium concentration, whereas the influent organic matter, hydraulic retention time and solid retention time exerted a limited effect on SFX biodegradation with the removal efficiencies varying in a narrow range. The variation of influent SFX concentration had no impact on SFX removal efficiency. The established model framework enables interpretation of a range of experimental observations on SFX biodegradation and helps to identify the optimal conditions for efficient removal. (C) 2017 Elsevier Ltd. All rights reserved.