Plasma Dynamics Research Articles

Nonparallel Wave Propagation in an Asymmetric Magnetic Slab

Abstract Theoretical and numerical analyses of the behavior of magnetohydrodynamic (MHD) waves in solar atmospheric structures have a vital role in understanding the plasma dynamics of the Sun. Magneto-helioseismology is indebted to the insight gained from simple magnetic slab structures accompanied by varying conditions within the slab and its environment. This paper builds on the existing literature on these structures by presenting an analytical approach to deriving the dispersion relation for MHD wave propagation in a nonparallel case. Analogous to the parallel case, a plethora of modes emerges that can be classified into quasi-kink or quasi-sausage, body or surface, as well as fast or slow waves. The slab itself can be viewed as thin or wide similarly to previous works, however due to the nonparallel condition it can also be categorised as short or long in the direction of the tilt of the wavevector. This is the analog of the thin or wide slab classification in the parallel direction, expanding our established knowledge regarding propagating MHD waves in magnetic slabs. The variance of the wavenumber along the nonparallel dimension brings to light a number of intriguing features, such as modes changing character with variation of the angle of the wavevector while the propagation speed remains the same. Further new information is provided by the newly derived classification limits, u ±, which act as a form of generalised Alfvén and sound speeds in the dispersion relation.

A relativistic model for quantum plasmas

Abstract A new model to study the dynamics of relativistic quantum plasmas using the quantum electrodynamical (QED) approach has been constructed to analyze the quantum effects, relativistic corrections, and electromagnetic interactions. Considering the covariant Lagrangian function and Euler-Lagrange equation, the equations of motion have been established describing the interaction of strong electromagnetic waves in plasma. These equations of motion constitute a model for the propagation of relativistic laser pulse through high density quantum plasma. Our model specifically takes the effects of four spin and four velocity into account during the interaction process. This model is applicable to high density plasmas in all ranges of electromagnetic fields which includes astrophysical environments, high power laser plasma interactions, etc.

Nonlinear Mixing of Waves in a Yukawa One Component Plasma

Abstract The phenomenon of nonlinear wave mixing is investigated in a Yukawa
one-component plasma using two-dimensional classical Langevin molecular dynamics
simulations. The wave spectrum indicates that nonlinear interactions between the excited
modes are primarily governed by a three-wave mixing mechanism, as confirmed by bispectral
analysis. In particular, the mixing characteristics observed in the simulations closely resemble
those reported in previous numerical studies of the forced Korteweg-de Vries (fKdV) model
[Phys. Plasmas 29, 032303 (2022)]. This similarity further validates the applicability of
the fKdV fluid model in capturing the weakly nonlinear dynamics of dusty plasmas with
reasonable accuracy.

T3ST code: turbulent transport in tokamaks via stochastic trajectories

Abstract We introduce the Turbulent Transport in Tokamaks via Stochastic Trajectories (T3ST) code, designed to address the problem of turbulent transport using a statistical approach complementary to gyrokinetics. The code employs test-particle methods to track the dynamics of charged particles in axisymmetric magnetic equilibria, accounting for both turbulence and Coulomb collisions. The turbulence is decoupled from plasma dynamics and represented through a statistical ensemble of synthetic random fields with specified spectral properties. This approach enables T3ST to compute transport coefficients as Lagrangian correlations—orders of magnitude faster than gyrokinetic codes.

Experimental results and analysis of plasma dynamics and radiation output of the 100 kV dense plasma focus FAETON-I

FAETON-I is the highest direct-charged voltage plasma focus (PF), at 100 kV, 1 MA peak current. F-I produces consistent D-D neutrons/shot, over 3 MeV X-rays and keV deuterons, demonstrating unique combined neutron-gamma environment. Its peak neutron yield was recorded at neutrons/shot at 12 Torr deuterium. The best peak dynamics-induced pinch voltage was measured at 194 kV. A major difficulty anticipated for PF operation at high-voltage and high-current is the likelihood of re-strikes which divert current away from the compressing plasma. F-I shows excellent current sheath dynamics and above-scaling D-D neutron yield, despite severe re-strikes. This study, correlating current and voltage time profiles with radial trajectories, reveals that the dynamics-induced voltage peak of kV, produces deuteron beam first, then the re-strikes, which do not affect the target pinch plasma in geometry and areal density. Thus, this first neutron pulse is hardly affected by re-strikes, and the very high-voltage results in above-scaling out-performance, despite degradation of the second neutron pulse from pinch instabilities. Moreover, upgrading to D-T operation, it is expected that the first pulse at keV (peak D-T cross section) ion energy, will completely dominate the second pulse with micro-beams at MeV (low D-T cross section).

Perpendicular‐Parallel Asymmetry of Venus Bow Shock Under Different Parker Spiral Angles

Abstract Several typical asymmetries in the Venusian bow shock (BS) location, including the magnetic north‐south asymmetry, the pole‐equator asymmetry, and the perpendicular‐parallel asymmetry, have been proven to be controlled or affected by the interplanetary magnetic field orientation. The physical reasons behind the perpendicular‐parallel shock asymmetry remain inadequately explained. The effects of ion‐scale dynamics have not been adequately addressed in both previous observational data and numerical simulations. Using global multifluid simulations, we demonstrate that the electric field strength differs significantly between the two types of BS, resulting in their asymmetric positions relative to the planet. The quasi‐perpendicular BS generates a stronger Hall electric field, which decelerates the solar wind at a greater distance from Venus. In contrast, the weaker electric field at the quasi‐parallel BS only effectively slows down the solar wind closer to the planet, leading to further compression of the induced magnetosphere and an enhanced ambipolar electric field due to increased electron pressure gradients. The differential energy transfer from the solar wind at the two BS types contributes to the asymmetry in plasma flow and magnetic field accumulation downstream. These findings provide new insights into the plasma dynamics around unmagnetized planets and highlight the role of electric field structure in shaping the induced magnetosphere of Venus.

Generalized treatment of 1D investigations of plasma dynamics under thermo-collisional effects

In the present work, one-dimensional investigations are carried out in non-isothermal weakly collisional plasma to study the plasma dynamics and characteristics of excited plasma current densities due to the propagation of moderate intensity lasers under the ponderomotive force regime. In the non-relativistic regime, ponderomotive nonlinearity is dominated over nonlocal heat transport; therefore, the effect of collision frequency and thermal motion of plasma electrons on subsequent plasma current densities are analysed. Such investigations are helpful in leading the development of tabletop efficient accelerators and radiation sources based on laser-plasma interactions for medical applications.

Multiscale autonomous forecasting of plasma systems’ dynamics using neural networks

Abstract Plasma systems exhibit complex multiscale dynamics, resolving which poses significant challenges for conventional numerical simulations. Machine learning (ML) offers an alternative by learning data-driven representations of these dynamics. Yet existing ML time-stepping models suffer from error accumulation, instability, and limited long-term forecasting horizons. This paper demonstrates the application of a hierarchical multiscale neural network architecture for autonomous plasma forecasting. The framework integrates multiple neural networks trained across different temporal scales to capture both fine-scale and large-scale behaviors while mitigating compounding error in recursive evaluation. By structuring the model as a hierarchy of sub-networks, each trained at a distinct time resolution, the approach effectively balances short-term resolution with long-term stability. Fine-scale networks accurately resolve fast-evolving features, while coarse-scale networks provide broader temporal context, reducing the frequency of recursive updates and limiting the accumulation of small prediction errors over time. We first evaluate the method using canonical nonlinear dynamical systems and compare its performance against classical single-scale neural networks. The results demonstrate that single-scale neural networks experience rapid divergence due to recursive error accumulation, whereas the multiscale approach improves stability and extends prediction horizons. Next, our ML model is applied to two plasma configurations of high scientific and applied significance, demonstrating its ability to preserve spatial structures and capture multiscale plasma dynamics. By leveraging multiple time-stepping resolutions, the applied framework is shown to outperform conventional single-scale networks for the studied plasma test cases. Additionally, another great advantage of our approach is its parallelizability by design, which enables the development of computationally efficient forecasters. The results of this work position the hierarchical multiscale neural network as a promising tool for efficient plasma forecasting and digital twin applications.

Spectroscopic investigation of nanosecond pulsed discharges in underwater plasma for flowing water treatment applications

Abstract Ensuring access to clean water, particularly in industrial settings, remains a significant challenge in the 21st century. Conventional wastewater treatment methods often suffer from inefficiencies, high operational costs, and limited scalability, necessitating the development of advanced, cost-effective, and sustainable alternatives. This study investigates the potential of underwater plasma discharge for flowing wastewater treatment under high fluid flow rates, focusing on the impact of discharge parameters—particularly applied voltage and frequency—on plasma dynamics. Optical emission spectroscopy was used to characterize key plasma parameters, including electron temperature ( T e ) , gas temperature ( T g ) , and electron number density ( n e ) . Degradation experiments were conducted in both oxygen-enriched and ambient air conditions at a fixed flow rate of 0.3 l min−1, achieving a degradation efficiency of 63.57 % for methylene blue (MB) and 65.24 % for rhodamine B (Rh-B) in the presence of 400 SCCM oxygen flow rate. In contrast, degradation efficiencies in air were 52.47 % for MB and 55.50 % for Rh-B. Compared to conventional dye degradation techniques, this method offers rapid and efficient pollutant breakdown in continuously flowing samples, demonstrating its potential as a scalable and energy-efficient plasma-based water treatment technology.

Plasma dynamics of modulated pulsed power magnetron sputtered Cr target in an Ar-He atmosphere

This study investigates the behavior of plasma discharge and particle transport in Modulated Pulsed Power Magnetron Sputtered Cr targets by introducing helium (He), an inert gas with the highest first ionization potential, into working gas argon (Ar). As the helium flow ratio was increased from 0% to 60%, there was a gradual increase in the peak discharge current. Conversely, the peak discharge voltage experienced a slight decrease. Furthermore, the energy per single pulse exhibited an upward trend, while the deposition rate demonstrated a decline. The ratio of the energy of the pulse to the deposition rate demonstrated an ascending trend with a higher He flow ratio, although its growth became limited when the He flow ratio was beyond 40%. A plasma global model was established to compare the discharge plasma characteristics of Ar-Cr and He-Cr discharge plasma. The electron temperature and electron density of He-Cr discharge plasma reach 6.3 eV and 9.7 × 1018 m−3, respectively, which are 2.3 times and 1.8 times that in Ar-Cr discharge plasma. Moreover, He effectively promotes further ionization of Cr species, increasing the densities of Cr+ and Cr2+ in He-Cr discharge plasma by 1.5 times and 67.5 times, respectively, compared to Ar-Cr discharge plasma. Although the introduction of He can promote plasma ionization, the ionized divalent ions do not contribute to the deposition flux in a pronounced way due to cathode back-attraction effects.

Power and efficiency of a self-field magnetoplasmadynamic thruster estimated with resistive MHD simulations

Existing numerical work on self-field Magnetoplasmadynamic Thrusters (MPDTs) adopt injection conditions that assume the propellant to be “hot” (T∼ 1 eV) and fully ionized. Although such simulations are capable of recovering the experimental values of integral quantities, such as thrust and voltage, it is not clear how the plasma dynamics and thruster’s efficiency are affected by these simplified boundary conditions. Our goal is to build upon and extend a multi-physics computational platform specifically for studying MPDTs under realistic conditions. Here, we focus on understanding the effects of different propellant injection boundary conditions on the energy budget and efficiency. We carry out simulations of argon-fed self-field MPDTs in 2D cylindrical axisymmetric geometry. We use the single-fluid, two-temperature magnetohydrodynamic (MHD) code FLASH with tabulated equation of state calculated with the IONMIX code. A weakly ionized, “cold” propellant (T∼ 0.13 eV) injection boundary condition is implemented. The resistivity model is extended to take into account the effects of electron-neutral collisions, which are non-negligible in this case. The simulation results show the importance of injecting a “cold” propellant and its effects on the power balance, Lorentz and thrust efficiencies. Although injecting “cold” propellant boundary results in the similar electromagnetic thrust as the “hot” case, it leads to significant changes in the distribution of MHD parameters and, overall, a more complicated flow pattern. At the same time we are able to eliminate the large powers associated with the pre-heated, fully ionized, and fast inlet, while achieving realistic Lorentz efficiency, consistent with the thrust efficiency. Finally, the work lays the basis for future studies of a more accurate propellant injection model.

Deep learning-based spatiotemporal sequence forecasting of physical fields in tin droplet laser-produced plasma

To address the computational challenges in modeling laser-produced plasma spatiotemporal evolution, this study pioneers the application of neural operators for 2D radiation hydrodynamics (RHD) simulations in fiber-laser-produced plasma systems employing liquid tin droplets for extreme ultraviolet lithography (EUVL) sources. Our novel framework enables rapid prediction of multi-physics field evolution by learning the underlying physical operators governing the complex interplay between radiation transport, hydrodynamic motion and plasma dynamics in EUV light source configurations. Through comparative analysis with convolutional long short-term memory (ConvLSTM) and convolutional neural operator (CNO) architectures, using over 50,000 spatiotemporal snapshots generated by FLASH software, the multi-variable Fourier neural operator (FNO) demonstrates superior performance in all three cases. In the case of single-laser pulse scenarios, it achieves an electron density mean squared error (MSE) of 7.49×10−5, representing a 53% improvement over ConvLSTM (1.58×10−4) and a 50% improvement over the CNO (1.51×10−4) in the normalized domain. The FNO exhibits unique zero-shot super-resolution capabilities, reconstructing high-fidelity 96×192 grid solutions from low-resolution 48×96 inputs while maintaining a normalized MSE of 10−4 relative to ground truth simulations. Demonstrating six-order-of-magnitude acceleration compared to conventional RHD solvers, this approach enables real-time analysis of plasma evolution patterns critical for EUVL source optimization, including tin droplet fragmentation dynamics and extreme ultraviolet emission characteristics. The demonstrated multi-physics modeling capability and memory-efficient super-resolution reconstruction positions FNO as a potential transformative tool for next-generation plasma diagnostics and EUVL system monitoring.

Theoretical study of single ionization of the oxygen atom

Abstract Understanding electron-impact ionization of oxygen is crucial because of its abundance and key role in influencing plasma dynamics in both cosmic and laboratory environments. This work examines the single ionization from energy levels of the ground configuration of atomic oxygen. The direct ionization (DI) and excitation-autoionization (EA) processes are examined for the 2s and 2p subshells of the ground configuration. The scaled distorted wave (sDW) cross sections, calculated using the experimental ionization threshold, show a good agreement with measurements. Additionally, the sDW results closely follow those obtained using the binary encounter Bethe model. A comparison of the DI 2s and 2p cross sections, previously calculated using the B-spline R-matrix-with-pseudostates (BSR) method, to the sDW data reveals similar peak values, except for the 1 S 0 level, where the BSR calculations predict ∼15% higher contribution for the DI 2p channel relative to the sDW data. For the EA process, the sDW cross sections exceed the BSR calculations by approximately a factor of two. For spin-forbidden transitions, 2 p 4 3 P → 2 p 3 3 s 5 S and 2 p 4 3 P → 2 p 3 3 p 5 P , the sDW cross sections are slightly lower than those predicted by the BSR method. These findings highlight reliability of the sDW method for oxygen ionization modeling and suggest correlation effects may explain discrepancies with BSR.

Therapeutic Plasma Exchange in Various Clinical Settings at a Tertiary Hospital – A Retrospective Analysis from a Technical Point of View

Introduction: Therapeutic plasma exchange (TPE) is an extracorporeal blood purification procedure widely used in neurological and immunological diseases. While established protocols exist, patient variability necessitates individualized approaches to optimize efficacy and safety. Methodology: This retrospective observational study analyzed all TPE procedures performed in a tertiary hospital and blood center from January to December 2024. Clinical indications were categorized, and key parameters—including demographic characteristics, body mass index (BMI), hematocrit, calculated plasma volume (PVcalc), exchanged plasma volume (PVex), and PVex/PVcalc ratio—were recorded. Replacement fluid strategies and treatment cycles were evaluated, and statistical significance was set at p < 0.01. Results: A total of 723 TPE procedures were performed on 181 patients. Neurological disorders accounted for 83.4% of cases, mainly Guillain–Barré syndrome (62.5%), transverse myelitis (11%), and neuromyelitis optica (3.3%). Immunological diseases and vasculitis comprised 14.4%, including myasthenia gravis (11%), TTP (1.2%), and SLE (0.96%). Neurological patients had higher median hematocrit (40.2%) than the immunological group (35.7%), resulting in lower PVcalc (2376 mL vs. 2728 mL; p < 0.01). Despite these differences, treatment cycles remained around five across groups. Neurological patients exhibited a higher PVex/PVcalc ratio (0.92 vs. 0.77; p < 0.01), suggesting a more aggressive exchange approach. Conclusion: Significant clinical improvements occurred across all groups, even with lower-than-recommended plasma exchange volumes. These findings highlight the need for individualized TPE protocols based on disease-specific plasma dynamics. Further multi-center studies are warranted to refine evidence-based guidelines for optimal TPE outcomes. Keywords: Therapeutic plasma exchange (TPE), neurological disorders, immunological diseases, plasma volume.

Quantified causality dependence of dynamical relation between zonal flow and heat transport on isotope mass in tokamak edge plasmas

Abstract The isotope effect on zonal flows (ZFs) and turbulence remains a key issue that is not completely solved in fusion plasmas. This Letter presents the first experimental results of the ab initio prediction of causal relation between geodesic acoustic mode (GAM) and ambient turbulence within different isotopes in the edge of HL-2A tokamak, where transfer entropy method based on information-theoretical approach is utilized as a quantified indicator of causality. Analysis shows that GAM is more pronounced in deuterium plasmas than in hydrogen, leading to a lower heat transport as well as more peaked profiles in the former situation. The causal impact of GAM on conductive heat flux component is stronger than the convective component, which is resulted from a larger causal influence of zonal flow on temperature fluctuation. While a stronger GAM in deuterium plasmas has larger influence on all flux components, the relative change in temperature fluctuation and coefficient is more obvious when the ion mass varies. These findings not only offer an in-depth understanding of the real causality between zonal flow and turbulence in the present isotope experiments, but also provide useful ways for the physical understandings of transport and zonal flow dynamics in future deuterium-tritium fusion plasmas.

Quantum-inspired information entropy in multifield turbulence

An information entropy for turbulence systems with multiple field quantities is formulated, as a new paradigm to explore the nonlinear dynamics and pattern formations. Combining quantum state descriptions in quantum mechanics into the turbulence field analysis, the von Neumann entropy (vNE) and the entanglement entropy (EE) are derived from a density matrix for the turbulence state in terms of the multifield singular value decomposition (MFSVD). Applying the information-theoretic entropy analyses to spatio-temporal dynamics in turbulent plasmas with phase-transition–like behavior, we discover a new nontrivial transition threshold regarding the vNE, which significantly deviates from the transition threshold of the field energy considered in the conventional approaches. These findings provide us with physically more diverse classifications of the turbulence state from the new perspective of “information”, in addition to the energetics of turbulent vortices. It is also revealed that the EE for nonlinear interactions in turbulence extracts the information regarding the strength of nonlinear mode couplings and the direction of net energy transfer. A plausible application of the EE to the turbulence measurements is demonstrated, as well as the associated reconstruction technique for fluctuation fields. Published by the American Physical Society 2025

Dynamics of Plasma and Magnetic Fields in a Quiescent Prominence Formation

Dynamics of Plasma and Magnetic Fields in a Quiescent Prominence Formation

Mechanistic optimization of wide-gap ultrafast laser quartz glass welding with plasma dynamics

Mechanistic optimization of wide-gap ultrafast laser quartz glass welding with plasma dynamics

Bounce-averaged fluid equations for interchange dynamics in a dipole-confined plasma

The drift dynamics of electrons confined in a dipole field are described by the evolution of the bounce-averaged particle distribution with adiabatic invariants on time scales longer than the particle's bounce period. The bounce-averaged fluid equations are derived from moments of the collisionless bounce-averaged kinetic equations by performing phase-space integrals for an isotropic plasma in a point dipole geometry. We show that the bounce-averaged fluid equations are equivalent to the flux-tube integrated two-fluid equations for describing low-frequency, flute-like fluctuations in a dipole-confined plasma.

Sub-micrometer spatial resolution Nomarski interferometer for time-resolved complex-amplitude imaging of femtosecond laser-induced air plasma

Characterizing the air plasma generated by the intense femtosecond laser pulses focused in air has gained attention in recent years to understand its role in many applications, such as terahertz generation and laser processing. Time-resolved complex-amplitude imaging is a powerful technique for characterizing such plasmas. Among various ways of obtaining the complex amplitude of the probe light, the Nomarski interferometer is one of the well-established configurations. However, despite its advantages in simplicity, conventional Nomarski interferometers are often limited in their spatial resolution to tens of micrometers, resulting in the obtained images being spatially averaged and losing accuracy. Here, we report on the development of a time-resolved Nomarski interferometer setup with sub-micrometer spatial resolution realized by incorporating a wide-separation-angle Wollaston prism used in the Nomarski interferometer. With this setup, we show that it is possible to image the time-resolved dynamics of laser-induced air plasmas, succeeding in observing even the internal structure of the plasma electron density distribution, such as spatial splitting, on the micrometer scale. Furthermore, our results were compared with numerical simulations and were found to demonstrate good qualitative agreement. Our results pave the path to the accurate characterization of air plasma, furthering our understanding of its basic physics and enabling more advanced applications.