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: Plasma is gaining increasing interest for N2 fixation, being a flexible, electricity-driven alternative for the current conventional fossil fuel-based N2 fixation processes. As the vibrational-induced dissociation of N2 is found to be an energy-efficient pathway to acquire atomic N for the fixation processes, plasmas that are in vibrational nonequilibrium seem promising for this application. However, an important challenge in using nonequilibrium plasmas lies in preventing vibrational−translational (VT) relaxation processes, in which vibrational energy crucial for N2 dissociation is lost to gas heating. We present here both experimental and modeling results for the vibrational and gas temperature in a microsecond-pulsed microwave (MW) N2 plasma, showing how power pulsing can suppress this unfavorable VT relaxation and achieve a maximal vibrational nonequilibrium. By means of our kinetic model, we demonstrate that pulsed plasmas take advantage of the long time scale on which VT processes occur, yielding a very pronounced nonequilibrium over the whole N2 vibrational ladder. Additionally, the effect of pulse parameters like the pulse frequency and pulse width are investigated, demonstrating that the advantage of pulsing to inhibit VT relaxation diminishes for high pulse frequencies (around 7000 kHz) and long power pulses (above 400 μs). Nevertheless, all regimes studied here demonstrate a clear vibrational nonequilibrium while only requiring a limited power-on time, and thus, we may conclude that a pulsed plasma seems very interesting for energyefficient vibrational excitation.

Abstract: Plasma has been studied for several years to convert CO2 into value-added products. If CO2 could be converted in the presence of H2O as a cheap H-source for making syngas and oxygenates, it would mimic natural photosynthesis. However, CO2/H2O plasmas have not yet been extensively studied, not by experiments, and certainly not computationally. Therefore, we present here a kinetic modelling study to obtain a greater understanding of the vibrational kinetics of a CO2/H2O microwave plasma. For this purpose, we first created an electron impact cross section set for H2O, using a swarm-derived method. We added the new cross section set and CO2/H2O-related chemistry to a pure CO2 model. While it was expected that H2O addition mainly causes quenching of the CO2 asymmetric mode vibrational levels due to the additional CO2/H2O vibrational-translational relaxation, our model shows that the modifications in the vibrational kinetics are mainly induced by the strong electron dissociative attachment to H2O molecules, causing a reduction in electron density, and the corresponding changes in the input of energy into the CO2 vibrational levels by electron impact processes.

Abstract: Plasma degradation is one of the most effective methods for the abatement of greenhouse gas sulfur hexafluoride
(SF6). To evaluate the potential of MgO as a catalyst in plasma degradation, we investigate the catalytic properties
of MgO on SF6 adsorption and activation by density functional theory (DFT) where the O-defective and
hydroxylated surfaces are considered as two typical plasma-generated surfaces. Our results show that perfect
MgO (001) and (111) surfaces cannot interact with SF6 and only physical adsorption happens. In case of Odefective
MgO surfaces, the O vacancy is the most stable adsorption site. SF6 undergoes a decomposition to SF5
and F over the O-defective MgO (001) surface and undergoes an elongation of the bottom S-F bond over the Odefective
(111) surface. Besides, SF6 shows a physically adsorption at the stepsite of the MgO (001) surface,
accompanied by small changes in its bond angle and length. Furthermore, SF6 is found to be physically and
chemically adsorbed over 0.5 and 1.0 ML (monolayer) H-covered O-terminated MgO (111) surfaces, respectively.
The SF6 molecule undergoes a self-decomposition on the 1.0 ML hydroxylated surface via a surface bonding
process. This study shows that defective and hydroxylated MgO surfaces have the surface capacities for SF6
activation, which shows that MgO has potential as packing material in SF6 waste treatment in packed-bed
plasmas.

Abstract: Plasma catalysis is promising for various environmental, energy and chemical synthesis applications, but the underlying mechanisms are far from understood. Modeling can help to obtain a better insight in these mechanisms. Some burning questions relate to the plasma behavior inside packed bed reactors and whether plasma can penetrate into catalyst pores. In this paper, we try to provide answers to these questions, by means of both fluid modeling and particle-in-cell/Monte Carlo collision simulations. We present a short overview of recent findings obtained in our group by means of modeling, i.e., the enhanced electric field near the contact points and the streamer propagation through the packing in packed bed reactors, as well as the plasma behavior in catalyst pores, to determine the minimum pore size in which plasma streamers can penetrate.

Abstract: Plasma catalysis is gaining increasing interest for various gas conversion applications, such as CO2 conversion into value-added chemicals and fuels, CH4 activation into hydrogen, higher hydrocarbons or oxygenates, and NH3 synthesis. Other applications are already more established, such as for air pollution control, e.g. volatile organic compound remediation, particulate matter and NOx removal. In addition, plasma is also very promising for catalyst synthesis and treatment. Plasma catalysis clearly has benefits over ‘conventional’ catalysis, as outlined in the Introduction. However, a better insight into the underlying physical and chemical processes is crucial. This can be obtained by experiments applying diagnostics, studying both the chemical processes at the catalyst surface and the physicochemical mechanisms of plasma-catalyst interactions, as well as by computer modeling. The key challenge is to design cost-effective, highly active and stable catalysts tailored to the plasma environment. Therefore, insight from thermal catalysis as well as electro- and photocatalysis is crucial. All these aspects are covered in this Roadmap paper, written by specialists in their field, presenting the state-of-the-art, the current and future challenges, as well as the advances in science and technology needed to meet these challenges.

Abstract: Plasma catalysis is gaining increasing interest for various environmental applications, but the crucial question is whether plasma can be created inside catalyst pores and under which conditions. In practice, various catalytic support materials are used, with various dielectric constants. We investigate here the influence of the dielectric constant on the plasma properties inside catalyst pores and in the sheath in front of the pores, for various pore sizes. The calculations are performed by a two-dimensional fluid model for an atmospheric pressure dielectric barrier discharge in helium. The electron impact ionization rate, electron temperature, electron and ion density, as well as the potential distribution and surface charge density, are analyzed for a better understanding of the discharge behavior inside catalyst pores. The results indicate that, in a 100 μm pore, the electron impact ionization in the pore, which is characteristic for the plasma generation inside the pore, is greatly enhanced for dielectric constants below 300. Smaller pore sizes only yield enhanced ionization for smaller dielectric constants, i.e., up to εr = 200, 150, and 50 for pore sizes of 50, 30, and 10 μm. Thus, the most common catalyst supports, i.e., Al2O3 and SiO2, which have dielectric constants around εr = 8−11 and 4.2, respectively, should allow more easily that microdischarges can be formed inside catalyst pores, even for smaller pore sizes. On the other hand, ferroelectric materials with dielectric constants above 300 never seem to yield plasma enhancement inside catalyst pores, not even for 100 μm pore sizes. Furthermore, it is clear that the dielectric constant of the material has a large effect on the extent of plasma enhancement inside the catalyst pores, especially in the range between εr = 4 and εr = 200. The obtained results are explained in detail based on the surface charge density at the pore walls,
and the potential distribution and electron temperature inside and above the pores. The results obtained with this model are
important for plasma catalysis, as the production plasma species in catalyst pores might affect the catalyst properties, and thus
improve the applications of plasma catalysis.

Abstract: Plasma catalysis is gaining increasing interest for CO2 conversion, but the interaction between the plasma and catalyst is still poorly understood. This is caused by limited systematic materials research, since most works combine a plasma with commercial supported catalysts and packings. In the present paper, we study the influence of specific material and reactor properties, as well as reactor/bead configuration, on the conversion and energy efficiency of CO2 dissociation in a packed bed dielectric barrier discharge (DBD) reactor. Of the various packing materials investigated, BaTiO3 yields the highest conversion and energy efficiency, i.e., 25% and 4.5%.
Our results show that, when evaluating the influence of catalysts, the impact of the packing (support) material itself cannot be neglected, since it can largely affect the conversion and energy efficiency. This shows the large potential for further improvement of packed bed plasma reactors for CO2 conversion and other chemical conversion reactions by adjusting both packing (support) properties and catalytically active sites. Moreover, we clearly prove that comparison of results obtained in different reactor setups should be done with care, since there is a large effect of the reactor setup and reactor/bead configuration.

Abstract: Plasma catalysis is emerging for plasma-assisted gas conversion
processes. However, the underlying mechanisms of plasma catalysis are poorly
understood. In this work, we present a 1D heterogeneous catalysis model with axial
dispersion (i.e., accounting for back-mixing and molecular diffusion of fluid elements in
the process stream in the axial direction), for plasma-catalytic NO production from
N2/O2 mixtures. We investigate the concentration and reaction rates of each species
formed as a function of time and position across the catalyst, in order to determine the
underlying mechanisms. To obtain insights into how the performance of the process
can be further improved, we also study how changes in the postplasma gas flow
composition entering the catalyst bed and in the operation conditions of the catalytic
stage affect the performance of NO production.

Abstract: Plasma catalysis is a rapidly growing field, often employing a packed-bed dielectric barrier discharge plasma reactor. Such dielectric barrier discharges are complex, especially when a packing material (e.g., a catalyst) is introduced in the discharge volume. Catalysts are known to affect the plasma discharge, though the underlying mechanisms influencing the plasma physics are not fully understood. Moreover, the effect of the catalysts on the plasma discharge and its subsequent effect on the overall performance is often overlooked. In this work, we deliberately design and synthesize catalysts to affect the plasma discharge in different ways. These Ni or Co alumina-based catalysts are used in plasma-catalytic dry reforming of methane and ammonia synthesis. Our work shows that introducing a metal to the dielectric packing can affect the plasma discharge, and that the distribution of the metal is crucial in this regard. Further, the altered discharge can greatly influence the overall performance. In an atmospheric pressure dielectric barrier discharge reactor, this apparently more uniform plasma yields a significantly better performance for ammonia synthesis compared to the more conventional filamentary discharge, while it underperforms in dry reforming of methane. This study stresses the importance of analyzing the plasma discharge in plasma catalysis experiments. We hope this work encourages a more critical view on the plasma discharge characteristics when studying various catalysts in a plasma reactor.

Abstract: Plasma catalysis has emerged as a promising approach for driving thermodynamically unfavorable chemical
reactions. Nevertheless, comprehending the mechanisms involved remains a challenge, leading to uncertainty
about whether the optimal catalyst in plasma catalysis aligns with that in thermal catalysis. In this research, we
explore this question by studying monometallic catalysts (Fe, Co, Ni and Mo) and bimetallic catalysts (Fe-Co, Mo-
Co, Fe-Ni and Mo-Ni) in both thermal catalytic and plasma catalytic NH3 decomposition. Our findings reveal that
the Fe-Co bimetallic catalyst exhibits the highest activity in thermal catalysis, the Fe-Ni bimetallic catalyst
outperforms others in plasma catalysis, indicating a discrepancy between the optimal catalysts for the two
catalytic modes in NH3 decomposition. Comprehensive catalyst characterization, kinetic analysis, temperature
program surface reaction experiments and plasma diagnosis are employed to discuss the key factors influencing
NH3 decomposition performance.

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.

Abstract: Plants mainly rely on a mixture of Fe complexes with different organic ligands, like carboxylates and soluble fractions of water-extractable humic substances (WEHSs), to sustain the supply of this micronutrient. It has been demonstrated that the Fe-WEHS complex is more efficiently acquired by plant roots as it enhances functionality of the mechanisms involved in Fe acquisition at the root and leaf levels, allowing a faster recovery of the Fe-deficiency symptoms. The aim of this work is to verify whether this recovery involves also the allocation and accumulation of nutrients other than Fe to and within the leaf tissues. Iron-deficient plants treated with Fe-WEHS recovered more quickly the functionality both to uptake nitrate at the root level and to fixate CO2 in the leaves than those supplied with Fe-citrate. Concomitantly, Fe-WEHS-treated plants also accumulated other cationic nutrients faster and at a higher extent. Synchrotron 2D-scanning μ-X-ray fluorescence analyses of the leaves revealed that the recovery promotes a change in the allocation of these nutrients from the vascular system (K, Cu, and Zn) or trichomes (Ca and Mn) to the entire leaf blade. Fe-WEHS treatment efficiently promotes the recovery from Fe-deficiency-induced chlorosis with an enhanced allocation of other nutrients into the leaves and promoting their distribution into the entire leaf blade.

Abstract: Plant leaves exhibit diverse shapes that enable them to utilize a light resource maximally. If there were a general parametric model that could be used to calculate leaf area for different leaf shapes, it would help to elucidate the adaptive evolutional link among plants with the same or similar leaf shapes. We propose a simplified version of the original Gielis equation (SGE), which was developed to describe a variety of object shapes ranging from a droplet to an arbitrary polygon. We used this equation to fit the leaf profiles of 53 species (among which, 48 bamboo plants, 5 woody plants, and 10 geographical populations of a woody plant), totaling 3310 leaves. A third parameter (namely, the floating ratio c in leaf length) was introduced to account for the case when the theoretical leaf length deviates from the observed leaf length. For most datasets, the estimates of c were greater than zero but less than 10%, indicating that the leaf length predicted by the SGE was usually smaller than the actual length. However, the predicted leaf areas approximated their actual values after considering the floating ratios in leaf length. For most datasets, the mean percent errors of leaf areas were lower than 6%, except for a pooled dataset with 42 bamboo species. For the elliptical, lanceolate, linear, obovate, and ovate shapes, although the SGE did not fit the leaf edge perfectly, after adjusting the parameter c, there were small deviations of the predicted leaf areas from the actual values. This illustrates that leaves with different shapes might have similar functional features for photosynthesis, since the leaf areas can be described by the same equation. The anisotropy expressed as a difference in leaf shape for some plants might be an adaptive response to enable them to adapt to different habitats.

Abstract: Pinning of magnetic-field-induced Wigner molecules (WMs) confined in parabolic two-dimensional quantum dots by a charged defect is studied by an exact diagonalization approach. We found a re-entrant pinning of the WMs as a function of the magnetic field, a magnetic-field-induced re-orientation of the WMs and a qualitatively different pinning behaviour in the presence of a positive and negative Coulomb impurity.