Abstract: Low-temperature plasma chemical kinetic models are particularly important to the plasma community. These models typically require dozens of inputs, especially rate coefficients. The latter are not always precisely known and it is not surprising that the error on the rate coefficient data can propagate to the model output. In this paper, we present a model that uses N = 400 different combinations of rate coefficients based on the uncertainty attributed to each rate coefficient, giving a good estimation of the uncertainty on the model output due to the rate coefficients. We demonstrate that the uncertainty varies a lot with the conditions and the type of output. Relatively low uncertainties (about 15%) are found for electron density and temperature, while the uncertainty can reach more than an order of magnitude for the population of the vibrational levels in some cases and it can rise up to 100% for the CO2 conversion. The reactions that are mostly responsible for the largest uncertainties are identified. We show that the conditions of pressure, gas temperature and power density have a great effect on the uncertainty and on which reactions lead to this uncertainty. In all the cases tested here, while the absolute values may suffer from large uncertainties, the trends observed in previous modeling work are still valid. Finally, in accordance with the work of Turner, a number of ‘good practices’ is recommended.

Abstract: Although CO2 conversion by plasma technology is gaining increasing interest, the
underlying mechanisms for an energy-efficient process are still far from understood. In this work, a reduced non-equilibrium CO2 plasma chemistry set, based on level lumping of the vibrational levels, is proposed and the reliability of this level-lumping method is tested by a self-consistent zero-dimensional code. A severe reduction of the number of equations to be solved is achieved, which is crucial to be able to model non-equilibrium CO2 plasmas by 2-dimensional models. Typical conditions of pressure and power used in a microwave plasma for CO2 conversion are investigated. Several different sets, using different numbers of lumped groups, are considered. The lumped models with 1, 2 or 3 groups are able to reproduce the gas temperature, electron density and electron temperature profiles, as calculated by the full model treating all individual excited levels, in the entire pressure range investigated. Furthermore, a 3-groups model is also able to reproduce the shape of the vibrational distribution function (VDF) and gives the most reliable prediction of the CO2 conversion. A strong influence of the vibrational excitation on the plasma characteristics is observed. Finally, the limitations of the lumped-levels method are discussed.

Abstract: The behavior of nanoparticles in a low-pressure silane discharge is studied with the use of a self-consistent one-dimensional fluid model. Nanoparticles of a given (prescribed) radius are formed in the discharge by the incorporation of a dust growth mechanism, i.e., by including a step in which large anions (typically Si12H−25), produced in successive chemical reactions of anions with silane molecules, are transformed into particles. Typically a few thousand anions are used for one nanoparticle. The resulting particle density and the charge on the particles are calculated with an iterative method. While the spatial distribution and the charge of the particles are influenced by the plasma, the presence of the nanoparticles will in turn influence the plasma properties. Several simulations with different particle radii are performed. The resulting density profile of the dust will greatly depend on the particle size, as it reacts to the shift of the balance of the different forces acting on the particles.

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: CO2 dissociation and its subsequent conversion into added-value chemicals is a promising strategy for recycling CO2 gas into reusable products. One of the possible methods is direct plasma-induced dissociation. In this work we study the efficiency of CO2 dissociation in pulsed atmospheric-pressure gas discharge between two conducting electrodes by a 0-D numerical plasma model. The purpose of the study is to provide results on the optimal conditions of CO2 conversion with respect to the energy efficiency and dissociation by varying the maximum power density value and the pulse length. The power density is directly related to the discharge current and the reduced electric field in the discharge. We consider pulse lengths in the range from hundreds of nanosecond up to milliseconds. The results obtained show that the dissociation degree and energy efficiency are sensitive to the pulse length (duration) and the power density, so that a considerable improvement of the discharge performance can be achieved by fine-tuning these parameters. The study is intended to provide guidance in designing an experimental set-up and a power supply with the characteristics necessary to achieve optimal conversion.

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.