Session BO06: Fundamental Plasmas: Dusty and Strongly Coupled Plasmas

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The experimental excitation of dynamic as well as stationary structures in a flowing complex plasma is presented. The experiments are performed in $\pi $-shaped Dusty Plasma Experimental (DPEx) device having a disc anode and a long grounded tray cathode. A dusty plasma is created in the DC glow discharge Ar plasma using kaolin particles. A floating copper wire is installed radially on the cathode that acts as a charged object in a flowing dusty plasma environment. The flow of the dust particle is initiated by manipulating the sheath potential around the wire using various resistances connected with the wire. The flow ranging from subsonic to supersonic to highly supersonic is generated to excite nonlinear dynamic and stationary structures. In case of subsonic flow, the wake structures are found to propagate in the upstream direction from the frame of fluid. In case of supersonic flow, the highly nonlinear structures (called as precursor solitons) are found to propagate in the upstream directions whereas the wakes propagate in the downstream direction. The propagation characteristics of these precursor solitons depend on the shape and size of the charged object over which the fluid flows. Interestingly, the stationary structures get excited for the case of highly supersonic fluid flow, which does not change its identity with time. The experimental details as well as propagation characteristics of these nonlinear structures will be presented in details in the conference.   

Live

Over the past several years, an inductively-heated plasma generator IPG6-B located at the Center for Astrophysics, Space Physics and Engineering Research (CASPER) at Baylor University has been established as a flexible experimental research facility for problems in physics and engineering. A primary application for the IPG6-B from initial development forward has been the investigation of complex (dusty) plasma. This talk will examine the interaction between dust particles and spherical obstacles under sub- and supersonic flow conditions. The MHD interaction between the plasma and applied magnetic fields will be examined using charged dust within the plasma to provide an estimate of the feasibility of using the dust as a diagnostic in flowing plasma. Once established, charged dust could then be used to `map' the electric and magnetic field properties of a plasma, in a manner similar to how dust is currently used in PIV measurements to visualize velocities within neutral gas flows. Concurrent experiments examining the manner in which dust interacts with a magnetic field will be conducted in a GEC Reference Cell to provide data under controlled conditions which can be used for refinement of the model.   

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Dust clouds in microgravity have proven a versatile analog for the study of self-ordered (soft matter) systems, particularly those where structuring is determined by the redistribution of flow kinetic energy and local and global confinement. In this talk, data collected using the PK-4 device on the International Space Station (ISS) as part of Campaigns {\#}7 and {\#}9 will be discussed. This data will be compared to PK-4 BU data collected under gravity to allow examination of dust systems employing DC polarity switching and a RF field with a movable electrode. The redistribution of flow kinetic energy at the onset of polarity switching and the resulting formation and self-excited dynamics of multi-chain dust clouds during the application of polarity switching will also be examined..   

Live

In a dusty plasma, the large sizes and long time scales of dust particles provide access to plasma dynamics at the kinetic level. Dust particle trajectories and collective behaviors act as probes for ion and electron dynamics. However, the large gravitational force in terrestrial experiments hides many interesting dust-plasma interactions. The PK4 device onboard the International Space Station allows for the study of these interactions. An investigation of waves in one dimensional dust chains in the streaming plasma PK4 environment is presented. The chains are modeled by the N-body simulation DRIAD (Dynamic Response of Ions and Dust) with plasma boundary conditions provided by a hybrid PIC/MCC model of the DC discharge. The resulting ion flow fields around the grains are used to find the asymmetric particle interaction potentials and pair correlation functions. These functions are used as input for a quasi-localized charge approximation (QLCA) theory. Dispersion relations calculated with QLCA are then compared with the PK4 experiment.   

Live

The PK-4 device on the International Space Station (ISS) provides a platform for the investigation of complex plasma systems in microgravity. The charged particles in the dust clouds have proven a versatile analog for the study of self-ordered (soft matter) systems. Recent experiments and numerical simulations have shown that the seemingly homogeneous DC discharge column is highly inhomogeneous on microsecond time scales. Simulations of the plasma discharge using our 2D particle-in-cell with Monte Carlo Collisions (PIC/MCC) code show that ionization waves dominate the plasma structure. In addition, the DC polarity switching used to keep the dust cloud from drifting causes strong radial gradients in the electric field. Here we apply the time-varying plasma conditions from the PIC/MCC model to an N-body simulation of the ions and dust to examine the effect on the dust dynamics and the formation of stringy dusty fluids.   

Live

The complex plasma is modeled as an isotropic system of $N$ charged grains (radius $a_{p}$ and charge $z_{p})$ interacting with each other through a screened Coulomb potential with a fixed Debye length $\lambda_{D}$ in an isotropic periodic domain, without including a confining potential and the systematic drift of charged species. The equilibrium thermodynamic state is investigated using Langevin Dynamics simulations to capture the effect of grain-neutral gas interactions (parameterized by the grain Knudsen number $Kn\mathrm{\equiv }\frac{\lambda_{g}}{a_{p}})$ across the various $\Gamma \mathrm{\equiv }\frac{z_{p}^{\mathrm{2}}e^{\mathrm{2}}}{\mathrm{4}\pi \varepsilon _{o}k_{b}T_{d}n_{p}^{\mathrm{-}\frac{\mathrm{1}}{\mathrm{3}}}}\mathrm{,\thinspace }\kappa \mathrm{=}\frac{n_{p}^{\mathrm{-}\frac{\mathrm{1}}{\mathrm{3}}}}{\lambda _{D}}$-based electrostatic coupling regimes, where $n_{p}$ is number concentration and $k_{B}T_{d}$ is the kinetic temperature of the grains. The Langevin-computed internal energy $u_{d}$, pressure $p_{d}$ and $k_{B}T_{d}$ of the grain phase are parameterized as equations of state $f\left( u_{d}\mathrm{,}p_{d}\mathrm{,}k_{B}T_{d} \right)\mathrm{=0}$ and compared with experimental reports of dust kinetic temperature to refine the modeling assumptions. The non-trivial influence of grain-neutral gas interactions is discussed by calculating the pair correlation functions in the gas, liquid, and solid-like regimes of grain correlated behavior. A unified thermodynamic model will further the understanding of phase transitions and the transport properties of the dust phase across the entire $\Gamma \mathrm{,\thinspace }\kappa \mathrm{,\thinspace }Kn$ regimes.   

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Grain charging is modeled in instances wherein the ions are dense and strongly coupled: $\Gamma_{i}\mathrm{\equiv }\frac{e^{\mathrm{2}}}{\mathrm{4}\pi \varepsilon _{o}n_{i}^{\mathrm{-}\frac{\mathrm{1}}{\mathrm{3}}}k_{B}T_{i}}\mathrm{>1}$. Langevin Dynamics is used to simulate the motion of multiple ions around a negatively charged grain in a periodic domain for $\mathrm{\sim }{\mathrm{10}}^{\mathrm{1}}\mathrm{-}{\mathrm{10}}^{\mathrm{5}}\mathrm{\thinspace }Pa$. The ion flux coefficient is calculated using the grain-ion collision time distribution and the grain-ion pair correlation function $g^{\left( \mathrm{2} \right)}\mathrm{(}r\mathrm{)}$ is used to deduce the influence of the ion space charge on the collision of individual ions with the grain during charging. In addition to $\Gamma_{i}$, the ion flux coefficient is influenced by the diffusive Knudsen number $Kn_{D}\mathrm{\equiv }\frac{\sqrt {m_{i}k_{B}T_{i}} }{f_{i}n_{i}^{\mathrm{-}\frac{\mathrm{1}}{\mathrm{3}}}}$ (an ion-neutral gas interaction parameter) and $\chi_{p}\mathrm{\equiv }\frac{a_{p}}{n_{i}^{\mathrm{-}\frac{\mathrm{1}}{\mathrm{3}}}}$ (that compares the size of the grain to the mean inter-ion spacing). We also demonstrate that an effective grain-ion potential computed using $g^{\left( \mathrm{2} \right)}\mathrm{(}r\mathrm{)}$ according to the effective potential theory accurately describes the grain-ion dynamics in a binary framework for $\Gamma_{i}\mathrm{<\sim 20}$, without the need to simulate multiple ions. Ion concentration has a significant effect across different ion coupling regimes and the analysis of the pair-correlation functions reveals the perturbation of ion structure in the plasma by the presence of grains. We hope our model development will spark experimental validation efforts.   

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Improved understanding of the charging and forces on dust particles near the edge of a plasma sheath are of interest in developing mitigation strategies for dust contamination in semiconductor processing, as particles are observed to be trapped in plasma sheath regions While electron-particle collisions can often be described by the OML model, ion-particle collisions in sheath regions require a distinct modeling approach to quantify. In this work, the ion attachment rate, force, and energy on negatively charged particles are calculated using ion trajectory models accounting for a linear external electric field in the plasma sheath, ion inertia, and finite ion mobility. Results show that increasing ion Stokes number, defining the ratio of ion inertia to gas resistance to motion, decreases the ion attachment coefficients, ion drag forces, and energy transfer rate. Interestingly at the Stokes numbers above unity, ions take orbiting trajectories around particles with finite numbers of rotation before colliding or leaving the domain. While some ions can contribute negative momentum transfer to particles, in all cases, we find that the collection force is positive in the direction of the external electric field   

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Molecular Dynamics (MD) simulations are an important tool in plasma physics and are often used to compute transport coefficients in plasmas in the moderate or strong Coulomb coupling regimes. This work investigates the required number of particles needed in MD simulations of the strongly magnetized One-Component Plasma (OCP) in order to compute accurate self-diffusion coefficients. Here we define strongly magnetized as when the gyrofrequency is greater than the plasma frequency. We find that far more particles are required to reach convergence in the strongly magnetized OCP than is required in the unmagnetized OCP, and increases with the strength of the magnetic field. The reason is that a long-range correlation parallel to the magnetic field develops when particles are confined to gyrate within very narrow gyrocylinders aligned along the magnetic field. The simulations also reveal that this correlation significantly increases the timescale required to reach a hydrodynamic diffusive regime. We conclude that compared to previous expectations it is more computationally expensive to simulate plasmas that are strongly magnetized.   

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We have used the focussed output of the LCLS FEL to create solid-density Ge plasmas at temperatures of order 200 eV. ~We studied the L-shell x-ray emission from the targets as a function of their thickness. We find that the peak temperature, and the uniformity of temperature and electron density throughout the foils are strongly dependent on the photon energy of LCLS, which was varied from 1300 to 1700 eV. ~We compare the results with simulations from Cretin, and find that, in contrast to previous measurements on Mg plasmas [1], opacities derived from the thickness-dependent emission is heavily influenced by small residual temperature gradients across the targets. Furthermore, for these mid-Z targets the opacity itself is increased by the radiation field from the XFEL, owing to its photopumping effect on the atomic populations.~ [1] T. Preston et al., Phy. Rev. Lett. 119, 085001 (2017).   

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When an ion in a warm dense plasma moves through the medium, it experiences frictional forces arising from electronic excitations induced by the motion of all the ions, as well as rapidly changing forces from the electronic density fluctuations. The question of whether these nonadiabatic electron-ion interactions, which represent a violation of the widely used Born-Oppenheimer approximation, are sufficiently strong to be important remains largely unexplored. To assess the basic properties of electronic friction, we present ab-initio calculations of the full friction tensor in warm dense hydrogen and aluminum. The friction tensor is generally inhomogeneous, anisotropic and non-diagonal, especially at lower densities. The nonadiabatic interactions introduce hydrodynamic couplings between the ionic degrees of freedom, which are sizeable between nearest neigbors.   

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The thermodynamic and transport coefficients of warm dense matter and dense plasmas are of high interest for the modeling of inertial confinement fusion or planetary interiors. Using the Yukawa liquid as a model system for a dense plasma, it is shown that several of these coefficients can be extracted from the dynamic structure factor (DSF). To this end, the DSF is computed from molecular dynamics simulations over a wide range of coupling strengths and analyzed using two extensions of the hydrodynamic model to finite wavenumbers and frequencies. The results are found to be in good agreement with recent data in the literature from a variety of different methods.   

A Machine Learning (Bayesian Optimization) Based Solution to the Nonlinear Response Analysis in Dusty Plasma .

A machine learning based method for solving nonlinear response analysis for a single dust particle inside the plasma sheath of a complex plasma is presented. By matching the simulated response curves (both primary response and secondary response) to the corresponding experimentally measured counterparts in a Bayesian manner, the parameters characterizing the plasma environment can be derived efficiently. It will be shown that a correction to the parameters of higher order nonlinearities derived from perturbation method is indicated by this numerical method..