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: Cold atmospheric plasma (CAP) is a promising technology for several medical applications, including the removal of biofilms from surfaces. However, the molecular mechanisms of CAP treatment are still poorly understood. Here we unravel the possible mechanisms of CAP‐induced oxidation of oligosaccharides, employing reactive molecular dynamics simulations based on the density functional‐tight binding potential. Specifically, we find that the interaction of oxygen atoms (used as CAP‐generated reactive species) with cellotriose (a model system for the oligosaccharides) can break structurally important glycosidic bonds, which subsequently leads to the disruption of the oligosaccharide molecule. The overall results help to shed light on our experimental evidence for cellotriose CAP. This oxidation by study provides atomic‐level insight into the onset of plasma‐induced removal of biofilms, as oligosaccharides are one of the main components of biofilm.

Abstract: Native wheat starch was oxidized by benign acidic bromate in water at room temperature. HPLC-ELSD study indicated that starch degraded in the course of oxidation but it still had a polymeric structure characterized by H-1, C-13, HSQC and HMBC NMR measurements. Products were generally water-soluble fragments but the use of a short reaction time and dilute reaction mixture yielded water-insoluble products. Titration of the products showed, that the increase of the starch content and reaction time increased the content of carbonyl and carboxyl groups in the range of 0.5-2.5% and 1.7-17.2%, respectively, in the product fragments. A mechanism for the oxidation reaction was proposed. (C) 2012 Elsevier Ltd. All rights reserved.

Abstract: A chemical kinetics model was developed to characterise the gas‐phase dynamics of H₂production in nanosecond‐pulsed CH₄plasmas. Pulsed behaviour was observed in the calculated electric field, electron temperature and species densities at all pressures. The model agrees reasonably with experimental results, showing CH₄conversion at 30% and C₂H₂and H₂as major products. The underlying mechanisms in CH₄dissociation and H₂formation were analysed, highlighting the large contribution of vibrationally excited CH₄and H₂to coupling energy from the plasma into gas‐phase heating, and revealing that H₂synthesis is not affected by applied pressure, with selectivity remaining unchanged at ~42% in the 1–5 bar range.

Abstract: A crucial step, which is still not well understood in the destruction of volatile organic compounds (VOCs) with low temperature plasmas, is the initiation of the process. Here, we present a kinetic model for the destruction of ethylene in low temperature plasmas that allows us to calculate the relative importance of all plasma species and their related reactions. Modifying the ethylene concentration and/or the SED had a major impact on the relative importance of the radicals (i.e., mainly atomic oxygen) and the metastable nitrogen (i.e., more specifically N2(equation image)) in the destruction process. Our results show that the direct destruction by electron impact reactions for ethylene can be neglected; however, we can certainly not neglect the influence of N2(equation image)).

Abstract: A one-dimensional fluid model for a dielectric barrier discharge in methane, used as a chemical reactor for gas conversion, is developed. The model describes the gas phase chemistry governing the conversion process of methane to higher hydrocarbons. The spatially averaged densities of the various plasma species as a function of time are discussed. Besides, the conversion of methane and the yields of the reaction products as a function of the residence time in the reactor are shown and compared with experimental data. Higher hydrocarbons (C2Hy and C3Hy) and hydrogen gas are typically found to be important reaction products. Furthermore, the main underlying reaction pathways are determined.

Abstract: This paper demonstrates that the CO2 conversion in a dielectric barrier discharge rises drastically upon addition of Ar or He, and the effect is more pronounced for Ar than for He. The effective CO2 conversion, on the other hand, drops upon addition of Ar or He, which is logical due to the lower CO2 content in the gas mixture, and the same is true for the energy efficiency, because a considerable fraction of the energy is then consumed into ionization/excitation of Ar or He atoms. The higher absolute CO2 conversion upon addition of Ar or He can be explained by studying in detail the Lissajous plots and the current profiles. The breakdown voltage is lower in the CO2/Ar and CO2/He mixtures, and the discharge gap is more filled with plasma, which enhances the possibility for CO2 conversion. The rates of electron impact excitationdissociation of CO2, estimated from the electron densities and mean electron energies, are indeed higher in the CO2/Ar and (to a lower extent) in the CO2/He mixtures, compared to the pure CO2 plasma. Moreover, charge transfer between Ar+ or Ar2+ ions and CO2, followed by electron-ion dissociative recombination of the CO2+ ions, might also contribute to, or even be dominant for the CO2 dissociation. All these effects can explain the higher CO2 conversion, especially upon addition of Ar, but also upon addition of He.

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: Dielectric Barrier Discharges operating in CO and CO2 form solid products at atmospheric pressure. The main differences between both plasmas and their deposits were analyzed, at similar energy input. GC measurements revealed a mixture of CO2, CO, and O2 in the CO2 DBD exhaust, while no O2 was found in the CO plasma. A coating of nanoparticles composed of Fe, O, and C was produced by the CO2 discharge, whereas, a microscopic dendrite-like carbon structure was formed in the CO plasma. Fe3O4 and Fe crystalline phases were found in the CO2 sample. The CO
deposition was characterized as an amorphous structure, close to polymeric CO (p-CO). Interestingly, p-CO is not formed in the CO2 plasma, in spite of the significant amounts of CO produced (up to 30% in the reactor exhaust).

Abstract: An extensive CO2 plasmamodel is presented that is relevant for the production of ‘‘solar fuels.’’ It is based on reaction rate coefficients fromrigorously reviewed literature, and is augmented with reactionrate coefficients that are obtained fromscaling laws.The input data set,which is suitable for usage with the plasma simulation software Plasimo (https://plasimo.phys.tue.nl/), is available via the Plasimo and publisher’s websites.1 The correctness of this model implementation has been established by independent ZDPlasKin implementation (http://www.zdplaskin.
laplace.univ-tlse.fr/), to verify that the results agree. Results of these ‘‘global models’’ are presented for a DBD plasma reactor.

Abstract: The modelling of a gliding arc discharge (GAD) is studied by means of the quasineutral (QN) plasma modelling approach. The model is first evaluated for reliability and proper description of a gliding arc discharge at atmospheric pressure, by comparing with a more elaborate non-quasineutral (NQN) plasma model in two different geometries – a 2D axisymmetric and a Cartesian geometry. The NQN model is considered as a reference, since it provides a continuous self-consistent plasma description, including the near electrode regions. In general, the results of the QN model agree very well with those obtained from the NQN model. The small differences between both models are attributed to the approximations in the derivation of the QN model. The use of the QN model provides a substantial reduction of the computation time compared to the NQN model, which is crucial for the development of more complex models in three dimensions or with complicated chemistries. The latter is illustrated for (i) a reverse vortex flow(RVF) GAD in argon, and (ii) a GAD in CO2. The RVF discharge is modelled in three dimensions and the effect of the turbulent heat transport on the plasma and gas characteristics is
discussed. The GAD model in CO2 is in a 1D geometry with axial symmetry and provides results for the time evolution of the electron, gas and vibrational temperature of CO2, as well as for the molar fractions of the different species.

Abstract: This paper gives an overview of our plasma chemistry modeling for CO2 and CH4 conversion in a dielectric barrier discharge (DBD) and microwave (MW) plasma. We focus on pure CO2 splitting and pure CH4 reforming, as well as mixtures of CO2/CH4, CH4/O2, and CO2/H2O. We show calculation results for the conversion, energy efficiency, and product formation, in comparison with experiments where possible. We also present the underlying chemical reaction pathways, to explain the observed
trends. For pure CO2, a comparison is made between a DBD and MW plasma, illustrating that the higher energy efficiency of the latter is attributed to the more important role of the vibrational levels.