Abstract: Plasma catalysis is gaining increasing interest for various applications, but the underlying mechanisms are still far from understood. Hence, more fundamental research is needed to understand these mechanisms. This can be obtained by both modelling and experiments. This foundations paper describes the fundamental insights in plasma catalysis, as well as efforts to gain more insights by modelling and experiments. Furthermore, it discusses the state-of-the-art of the major plasma catalysis applications, as well as successes and challenges of technology transfer of these applications.

Abstract: In recent years there is increased interest in plasma-based CO2 conversion. Several plasma setups are being investigated for this purpose, but the most commonly used ones are a dielectric barrier discharge (DBD), a microwave (MW) plasma and a gliding arc (GA) reactor. In this proceedings paper, we will show results from our experiments in a (packed bed) DBD reactor and in a vortex-flow GA reactor, as well as from our model calculations for the detailed plasma chemistry in a DBD, MW and GA, for pure CO2 as well as mixtures of CO2 with N-2, CH4 and H2O.

Abstract: In this review paper, we present several examples of reactive molecular dynamics simulations, which contribute to a better understanding of the underlying mechanisms in plasma medicine on the atomic scale. This includes the interaction of important reactive oxygen plasma species with the outer cell wall of both gram-positive and gram-negative bacteria, and with lipids present in human skin. Moreover, as most biomolecules are surrounded by a liquid biofilm, the behavior of these plasma species in a liquid (water) layer is presented as well. Finally, a perspective for future atomic scale modeling studies is given, in the field of plasma medicine in general, and for cancer treatment in particular.

Abstract: Plasma–liquid interactions represent a growing interdisciplinary area of research involving plasma science, fluid dynamics, heat and mass transfer, photolysis, multiphase chemistry and aerosol science. This review provides an assessment of the state-of-the-art of this multidisciplinary area and identifies the key research challenges. The developments in diagnostics, modeling and further extensions of cross section and reaction rate databases that are necessary to address these challenges are discussed. The review focusses on nonequilibrium plasmas.

Abstract: A 2d3v Particle-in-cell/Monte Carlo collisions (PIC/MCC) model was constructed for an Ar/N2 reactive gas mixture in a magnetron discharge. A titanium target was used, in order to study the sputter deposition of a TiNx thin film. Cathode currents and voltages were calculated self-consistently and compared with experiments. Also, ion fluxes to the cathode were calculated, which cause sputtering of the target. The sputtered atom fluxes from the target, and to the substrate were calculated, in order to visualize the deposition of the TiNx film.

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image

Abstract: The conversion of methane to value-added chemicals and fuels is considered to be one of the challenges of the 21st century. In this paper we study, by means of fluid modeling, the conversion of methane to higher hydrocarbons or oxygenates by partial oxidation with CO2 or O2 in a dielectric barrier discharge. Sixty-nine different plasma species (electrons, ions, molecules, radicals) are included in the model, as well as a comprehensive set of chemical reactions. The calculation results presented in this paper include the conversion of the reactants and the yields of the reaction products as a function of residence time in the reactor, for different gas mixing ratios. Syngas (i.e. H2 + CO) and higher hydrocarbons (C2Hx) are typically found to be important reaction products.

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: Plasma bioscience and medicine are both rapidly growing fields. Their aim is to utilize cold physical plasmas for desired biological outcomes in medicine, biotechnology, agriculture, and general hygienic purposes. Great success has been achieved in many applications with individually designed plasma sources and plasma parameters. Although lab and application-specific tuning of plasmas is a great advantage of this technology, standardized units to define plasma treatments are required to facilitate comparison of the effects found by different researchers who do not use the same plasma sources. By drawing conclusions from over a century of plasma biomedical research, we propose that all researchers adopt the use of a standardized value, the plasma treatment unit (PTU), to describe the biological effects of different cold plasma sources and treatment regimens. It quantifies a key plasma effector in biological systems as an indicator and may provide the foundation for an analogous and clinically relevant unit in the future.