Evaluation of Cylindrical Asymmetric Surface Dielectric Barrier Discharge Actuators for Surface Decontamination and Mixing

Surface dielectric barrier discharge (SDBD) was used to evaluate cylindrical plasma actuators for inactivation of Salmonella enterica. A cylindrical SDBD configuration was evaluated to determine if the inherent induced body force could be leveraged to impel plasma species, such as reactive oxygen and nitrogen species (RONS), as an apparatus to sterilize surfaces. The cylindrical structure is evaluated in this study to observe whether an increase in mixing is possible to efficiently distribute the plasma species, thereby improving bacterial inactivation efficiency. The increase in induced airflow of SDBD actuators with increased numbers of electrodes correlates with increased bacterial inactivation. These results suggest that improving the particle velocity, airflow mixing tendencies, and plasma volume for the same power inputs (same net power to the actuators) results in increased surface decontamination efficiency.

Development of a reduced model for energetic particle transport by sawteeth in tokamaks

The sawtooth instability is known for inducing transport and loss of energetic particles (EP), and for generating seed magnetic islands that can trigger tearing modes. Both effects degrade the overall plasma performance. Several theories and numerical models have been previously developed to quantify the expected EP transport caused by sawteeth, with various degrees of sophistication to differentiate the response of EPs at different energies and on different orbits (e.g. passing vs. trapped), although the analysis is frequently limited to a single time slice during a tokamak discharge. This work describes the development and initial benchmark of a framework that enables a reduced model for EP transport by sawteeth retaining the full EP phase-space information. The model, implemented in the ORBIT hamiltonian particle-following code, can be used either as a standalone post-processor taking input data from codes such as TRANSP, or as a preprocessor to compute transport coefficients that can be fed back to TRANSP for time-dependent simulations including the effects of sawteeth on energetic particles. The advantage of the latter approach is that the evolution of the EP distribution can be simulated quantitatively for sawtoothing discharges, thus enabling a more accurate modeling of sources, sinks and overall transport properties of EP and thermal plasma species for comprehensive physics studies that require detailed information of the fast ion distribution function and its evolution over time.

Energy Exchange Between Electromagnetic Ion Cyclotron (EMIC) Waves and Thermal Plasma: From Theory to Observations

The cold plasmaspheric plasma, the ring current and the radiation belts constitute three important populations of the inner magnetosphere. The overlap region between these populations gives rise to wave-particle interactions between different plasma species and wave modes observed in the magnetosphere, in particular, electromagnetic ion cyclotron (EMIC) waves. These waves can resonantly interact with multiple particle species, being an important loss process for both ring current ions and radiation belt electrons, as well as a cold plasma heating mechanism. This mini-review will focus on the interaction between EMIC waves and cold and thermal plasma, specifically the role of EMIC waves in cold and thermal electron and ion heating. It will discuss early theoretical results in conjunction with numerical modelling and recent satellite observations, and address outstanding problems and controversies in this field.

Electric properties of Titan’s dusty ionosphere

<p>Recent studies have shown that negatively charged dust dramatically alters the electric properties of plasmas, in particular planetary ionospheres. Utilizing Titan flybys from the entire Cassini mission and full plasma content of the moon’s ionosphere (electrons, positive ions and negative ions/dust grains) we derive the electric conductivities and currents, updating and extending previous results which did not include the charged dust and focused on a limited range of flybys.</p> <p>Compared to the previous estimates, using the full plasma content increases the Pedersen conductivities by a factor ~2 and Hall conductivities by a factor ~1.2. We identify dusty plasma as the reason for the sharp increase of Pedersen conductivity below 1000 km altitude reported previously. Using the full range of Titan flybys also reveals the conductivities on the dayside to be factor ~7-9 larger than on the nightside, owing to higher dayside plasma densities as well as generally heavier plasma species on the nightside.</p>

Analysis of Optical Emission Spectra during Nitrogen-Plasma Treatment to Control the Wettability of Polystyrene Surface

In this work, we apply optical emission spectroscopy to investigate active plasma species to study that plasma nitrogen treatment affects polystyrene surfaces. Data concerning these active plasma species are crucial for exploring the polystyrene layer's functionality deposited on quartz crystal microbalance (QCM) surface. Wettability function in biosensors development is essential aspects for biomolecule immobilization. The surface of the polystyrene layer was modified by plasma nitrogen treatment. The process parameters affecting plasma species and characteristic, and hence the treatment results studied in this work were chamber pressure, flow rate, and DC bias. The plasma analysis was conducted by optical emission spectroscopy. The spectroscopy was utilized to predict the active species of plasma, the electron temperature Te and the electron density Ne. The dominant reactive species was N2+ which go through different plasma interactions and on the polystyrene surface depending on the DC bias voltage, the nitrogen- gas flow rate, and the chamber pressure. The plasma treatment results suggest that the ion bombardment was the dominant mechanism that changes the polystyrene's surface. The plasma behavior and surface interactions were found complex with the variation of the process parameter. Keywords: Electron density, Electron temperature, OES, Nitrogen-plasma treatment, Wettability

Electrostatic Dust-Acoustic Rogue Waves in an Electron Depleted Dusty Plasma

The formation of gigantic dust-acoustic (DA) rouge waves (DARWs) in an electron depleted unmagnetized opposite polarity dusty plasma system is theoretically predicted. The nonlinear Schrödinger equation (NLSE) is derived by employing the reductive perturbation method. It is found that the NLSE leads to the modulational instability (MI) of DA waves (DAWs), and to the formation of DARWs, which are caused by to the effects of nonlinearity and dispersion in the propagation of DAWs. The conditions for the MI of DAWs and the basic properties of the generated DARWs are numerically identified. It is also seen that the striking features (viz., instability criteria, amplitude and width of DARWs, etc.) of the DAWs are significantly modified by the effects of super-thermality of ions, number density, mass and charge state of the plasma species, etc. The results obtained from the present investigation will be useful in understanding the MI criteria of DAWs and associated DARWs in electron depleted unmagnetized opposite polarity dusty plasma systems like Earth’s mesosphere (where the D-region plasma could suffer from electron density depletion), cometary tails, Jupiter’s magnetosphere, and F-ring of Saturn, etc.

Encoder–decoder neural network for solving the nonlinear Fokker–Planck–Landau collision operator in XGC

An encoder–decoder neural network has been used to examine the possibility for acceleration of a partial integro-differential equation, the Fokker–Planck–Landau collision operator. This is part of the governing equation in the massively parallel particle-in-cell code XGC, which is used to study turbulence in fusion energy devices. The neural network emphasizes physics-inspired learning, where it is taught to respect physical conservation constraints of the collision operator by including them in the training loss, along with the $\ell _2$ loss. In particular, network architectures used for the computer vision task of semantic segmentation have been used for training. A penalization method is used to enforce the ‘soft’ constraints of the system and integrate error in the conservation properties into the loss function. During training, quantities representing the particle density, momentum and energy for all species of the system are calculated at each configuration vertex, mirroring the procedure in XGC. This simple training has produced a median relative loss, across configuration space, of the order of $10^{-4}$ , which is low enough if the error is of random nature, but not if it is of drift nature in time steps. The run time for the current Picard iterative solver of the operator is $O(n^2)$ , where $n$ is the number of plasma species. As the XGC1 code begins to attack problems including a larger number of species, the collision operator will become expensive computationally, making the neural network solver even more important, especially since its training only scales as $O(n)$ . A wide enough range of collisionality has been considered in the training data to ensure the full domain of collision physics is captured. An advanced technique to decrease the losses further will be subject of a subsequent report. Eventual work will include expansion of the network to include multiple plasma species.

Ion-Acoustic Rogue Waves in Double Pair Plasma Having Non-Extensive Particles

The modulational instability (MI) of ion-acoustic (IA) waves (IAWs) and associated IA rogue waves (IARWs) are studied in double-pair plasma containing inertial positive and negative ions, inertialess non-extensive electrons and iso-thermal positrons. A standard nonlinear Schrödinger equation (NLSE) is derived by employing reductive perturbation method. It can be seen from the numerical analysis that the plasma system supports both modulationally stable (unstable) parametric regime in which the dispersive and nonlinear coefficients of the NLSE have opposite (same) sign. It is also found that the basic features of IAWs (viz., MI criteria of IAWs, amplitude, and width of the IARWs, etc.) are rigorously changed by the plasma parameters such as mass, charge state, and number density of the plasma species. The outcomes of our present investigation should be useful in understanding the propagation of nonlinear electrostatic IAWs and associated IARWs in astrophysical and laboratory plasmas.