Abstract: Although plasma catalysis is gaining increasing interest for various environmental applications, the underlying mechanisms are still far from understood. For instance, it is not yet clear whether and how plasma streamers can propagate in catalyst pores, and what is the minimum pore size to make this happen. As this is crucial information to ensure good plasma-catalyst interaction, we study here the mechanism of plasma streamer propagation in a catalyst pore, by means of a twodimensional particle-in-cell/Monte Carlo collision model, for various pore diameters in the nm range to μm-range. The so-called Debye length is an important criterion for plasma penetration into catalyst pores, i.e. a plasma streamer can penetrate into pores when their diameter is larger than the Debye length. The Debye length is typically in the order of a few 100 nm up to 1 μm at the conditions under study, depending on electron density and temperature in the plasma streamer. For pores in the range of ∼50 nm, plasma can thus only penetrate to some extent and at
very short times, i.e. at the beginning of a micro-discharge, before the actual plasma streamer reaches the catalyst surface and a sheath is formed in front of the surface. We can make plasma streamers penetrate into smaller pores (down to ca. 500 nm at the conditions under study) by increasing the applied voltage, which yields a higher plasma density, and thus reduces the Debye length. Our simulations also reveal that the plasma streamers induce surface charging of the catalyst pore sidewalls, causing discharge enhancement inside the pore, depending on pore diameter and depth.

Abstract: The electrical asymmetry effect is realized by applying multiple frequency power sources
(13.56 MHz and 27.12 MHz) to a capacitively biased substrate electrode in a specific inductively
coupled plasma reactor. On the one hand, by adjusting the phase angle θ between the multiple
frequency power sources, an almost linear self-bias develops on the substrate electrode, and
consequently the ion energy can be well modulated, while the ion flux stays constant within a
large range of θ. On the other hand, the plasma density and ion flux can be significantly
modulated by tuning the inductive power supply, while only inducing a small change in the self-
bias. Independent control of self-bias/ion energy and ion flux can thus be realized in this specific
inductively coupled plasma reactor.

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: A gliding arc (GA) plasma has great potential for CO2 conversion into value-added chemicals, because of its high energy efficiency. To improve the application, a 2D/3D fluid model is needed to investigate the CO2 conversion mechanisms in the actual discharge geometry. Therefore, the complex CO2 chemical kinetics description must be reduced due to the huge computational cost associated with 2D/3D models. This paper presents a chemistry reduction method for CO2 plasmas, based on the so-called directed relation graph method. Depending on the defined threshold values, some marginal species are identified. By means of a sensitivity analysis, we can further reduce the chemistry set by removing one by one the marginal species. Based on the socalled flux-sensitivity coupling, we obtain a reduced CO2 kinetics model, consisting of 36 or 15 species (depending on whether the 21 asymmetric mode vibrational states of CO2 are explicitly included or lumped into one group), which is applied to a GA discharge. The results are compared with those predicted with the full chemistry set, and very good agreement is reached. Moreover, the range of validity of the reduced CO2 chemistry set is checked, telling us that this reduced set is suitable for low power GA discharges. Finally, the time and spatial evolution of the CO2 plasma characteristics are presented, based on a 2D model with the reduced kinetics.

Abstract: Fundamental and applied research on plasma‐treated liquids for biomedical applications was boosted in the last few years, dictated by their advantages with respect to direct treatments. However, often, the lack of consistent analysis at a molecular level of these liquids, and of the processes used to produce them, have raised doubts of their usefulness in the clinic. The aim of this article is to critically discuss some basic aspects related to the use of plasma‐treated liquids in medicine, with a focus on their chemical composition. We analyze the main liquids used in the field, how they are affected by non‐thermal plasmas, and the possibility to replicate them without plasma treatment.

Abstract: In recent years there has been growing interest in the use of plasma technology for CO2 conversion. To improve this application, a good insight into the underlying mechanisms is of great importance. This can be obtained from modeling the detailed plasma chemistry in order to understand the chemical reaction pathways leading to CO2 conversion (either in pure form or mixed with another gas). Moreover, in practice, several plasma reactor types are being investigated for CO2 conversion, so in addition it is essential to be able to model these reactor geometries so that their design can be improved, and the most energy efficient CO2 conversion can be achieved. Modeling the detailed plasma chemistry of CO2 conversion in complex reactors is, however, very time-consuming. This problem can be overcome by using a combination of two different types of model: 0D chemical reaction kinetics models are very suitable for describing the detailed plasma chemistry, while the characteristic features of different reactor geometries can be studied by 2D or 3D fluid models. In the first instance the latter can be developed in argon or helium with a simple chemistry to limit the calculation time; however, the ultimate aim is to implement the more complex CO2 chemistry in these models. In the present paper, examples will be given of both the 0D plasma chemistry models and the 2D and 3D fluid models for the most common plasma reactors used for CO2 conversion in order to emphasize the complementarity of both approaches. Furthermore, based on the modeling insights, the paper discusses the possibilities and limitations of plasma-based CO2 conversion in different types of plasma reactors, as well as what is needed to make further progress in this field.