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“Multielementmassenspektrometrie (MMS)”. Jochum KP, Gijbels R, Adriaens A Schweizerbart, Stuttgart, page 188 (2000).
Keywords: H3 Book chapter; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Multi-element trace analysis of geothermal waters : problems, characteristics and applicability”. Vandelannoote R, Blommaert W, Van 't dack L, van Grieken R, Gijbels R, , 523 (1985)
Keywords: P3 Proceeding; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT); AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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Conti S (2020) Multi-band superfluidity and BEC-BCS crossover in novel ultrathin materials. 123 p
Keywords: Doctoral thesis; Sociology; History; Condensed Matter Theory (CMT)
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“Morphology and fractal dimension of soot and carbon black aggregates determined by image analysis”. Smekens A, Vervoort M, Pauwels J, Berghmans P, van Espen P, Van Grieken R, (1998)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Chemometrics (Mitac 3)
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“Monte Carlo simulation of X-ray fluorescence and scattering tomography experiments”. Vincze L, Janssens K, Vekemans B, Adams F page 328 (1999).
Keywords: H1 Book chapter; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1117/12.363736
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“Monte Carlo simulation for X-ray fluorescence spectroscopy”. Vincze L, Janssens K, Vekemans B, Adams F page 435 (2004).
Keywords: H3 Book chapter; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Molecular structure, crystal field and orientational order in solid C60”. Lamoen D, Michel KH s.l., page 183 (1994).
Keywords: H1 Book chapter; Condensed Matter Theory (CMT)
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“Molecular spectroscopy study of human tooth tissues affected by high dose of external ionizing radiation (caused by the nuclear catastrophe of the Chernobyl plant)”. Darchuk LA, Zaverbna LV, Worobiec A, Van Grieken R page 349 (2012).
Keywords: H1 Book chapter; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Laboratory Experimental Medicine and Pediatrics (LEMP)
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Razzokov J (2019) Molecular level simulations for plasma medicine applications. 173 p
Keywords: Doctoral thesis; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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Batuk D (2014) Modular structures with lone electron pair cations. Antwerpen
Keywords: Doctoral thesis; Electron microscopy for materials research (EMAT)
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Grieten E (2016) Modifications to the nano-texture of old photographs & daguerreotypes by degradation and atmospheric plasma treatment. Universiteit Antwerpen, Faculteit Ontwerpwetenschappen, Opleiding Conservatie-Restauratie, Antwerpen
Keywords: Doctoral thesis; Art; Electron microscopy for materials research (EMAT)
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“Modification of the 2D electronic properties in Si-δ-doped InSb due to surface effects”. de Keyser A, Bogaerts R, van Bockstal L, Herlach F, Karavolas VC, Peeters FM, van de Graaf W, Borghs G, , 383 (1997)
Keywords: P3 Proceeding; Condensed Matter Theory (CMT)
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“Modern micro-analytical techniques to elucidate the causes and mechanisms of damage to cultural property”. Van Grieken R, Vleugels G, Roekens E, Veny P page 101 (1991).
Keywords: H3 Book chapter; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Modern micro-analytical techniques for the elucidation of causes and mechanisms of material deterioration”. Van Grieken R, Dewolfs R, (1992)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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Arslan Irmak E (2022) Modelling three-dimensional nanoparticle transformations based on quantitative transmission electron microscopy. 169 p
Abstract: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.
Keywords: Doctoral thesis; Electron microscopy for materials research (EMAT)
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Van Alphen S (2023) Modelling plasma reactors for sustainable CO2 conversion and N2 fixation. 202 p
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.
Keywords: Doctoral thesis; Engineering sciences. Technology; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modelling of radio frequency capacitively coupled plasma at intermediate pressures”. Berezhnoi S, Kaganovich I, Bogaerts A, Gijbels R Kluwer Academic, Dordrecht, page 525 (1999).
Keywords: H3 Book chapter; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modelling of formation and transport of nanoparticles in silane discharges”. de Bleecker K, Bogaerts A, Goedheer WJ, Gijbels R, , 0 (2004)
Keywords: P3 Proceeding; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modelling of a direct current glow discharge: combined models for the electrons, argon ions and metastables”. Bogaerts A, Gijbels R, , 292 (1995)
Keywords: P3 Proceeding; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modelling of a dielectric barrier glow discharge at atmospheric pressure in nitrogen”. Madani M, Bogaerts A, Gijbels R, Vangeneugden D, , 130 (2002)
Keywords: P3 Proceeding; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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Fenu A (2016) Modelling and operations of municipal membrane bioreactors : from conventional to novel applications. 180 p
Keywords: Doctoral thesis; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)
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Ysebaert T (2023) Modelling and experimental validation of deposition on vegetation to facilitate urban particulate matter mitigation. xxvi, 234 p
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.
Keywords: Doctoral thesis; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)
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Wendelen W (2014) Modeling ultrashort pulsed laser induced electron emission. Antwerpen
Keywords: Doctoral thesis; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modeling of the magnetron discharge”. Bogaerts A, Kolev I, Buyle G Springer, Berlin, page 61 (2008).
Keywords: H1 Book chapter; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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Van de Put ML (2016) Modeling of quantum electron transport with applications in energy filtering nanostructures. Antwerpen
Keywords: Doctoral thesis; Condensed Matter Theory (CMT)
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Berthelot A (2018) Modeling of microwave plasmas for carbon dioxide conversion. University of Antwerp, Antwerp
Keywords: Doctoral thesis; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modeling of bombardment induced oxidation of silicon with and without oxygen flooding”. de Witte H, Vandervorst W, Gijbels R, , 327 (1998)
Keywords: P3 Proceeding; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modeling of a dielectric barrier discharge used as a flowing chemical reactor”. Petrovic D, Martens T, van Dijk J, Brok WJM, Bogaerts A, , 262 (2008)
Keywords: P1 Proceeding; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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“Modeling network for argon glow discharges: the output cannot be better than the input”. Bogaerts A, Gijbels R American Institute of Physics, Melville, N.Y., page 49 (2000).
Keywords: H1 Book chapter; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Times cited: 1
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“Modeling network for argon glow discharge plasmas with copper cathode”. Bogaerts A, Gijbels R Nova, New York, page 1 (2002).
Keywords: H3 Book chapter; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
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