Multidimensional Plasma Research Articles

Multidimensional Plasma Lipids Affect Preeclampsia/Eclampsia: A Mendelian Randomization Study.

Circulating lipids play a crucial role during pregnancy and may impact various pregnancy-related diseases. This study employed a two-sample Mendelian randomization (MR) framework to investigate the causal relationship between alterations in multidimensional plasma lipid levels and the risk of preeclampsia or eclampsia, offering deeper insight into this association. The inverse variance weighted (IVW) method was utilized as the main analysis. Summary statistics from plasma lipidomics of 7174 Finnish individuals and summary data on preeclampsia/eclampsia from the FinnGen consortium involving 219 817 European participants were employed. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. The study identified 17 lipid species from a total of 179 lipid species associated with susceptibility to preeclampsia/eclampsia. Notably, ten species, including six triacylglycerols (TAGs) (50:1, 48:1, 56:4, 49:2, 48:2, 54:3), a diacylglycerol (DAG) (16:1_18:1), and three sphingomyelins (SMs) (d36:1, d34:1, d38:1), were found to increase the risk of preeclampsia/eclampsia. Conversely, seven species, including five phosphatidylcholines (PCs) (16:1_20:4, O-18:1_20:4, 18:1_20:4, 16:0_20:4, 17:0_20:4) and two phosphatidylethanolamines (PEAs) (18:0_20:4, 16:0_20:4), all containing arachidonic acid (ARA) in the sn-2 position, were associated with a reduced risk of preeclampsia/eclampsia (all p < 0.05). The results of thestratified analysis were consistent with these findings. Furthermore, reverse MR analysis indicated that preeclampsia/eclampsia does not causally affect plasma levels of these lipids. Our findings established a causal relationship between specific plasma lipid species and modulation of preeclampsia/eclampsia risk, providing improved resolution for risk assessment and potential therapeutic targets in the disease.

Oblique collision of low-frequency dust-acoustic solitons and rogue waves in a multi-dimensional anisotropic self-gravitating electron-depleted complex plasmas

Oblique collision of low-frequency dust-acoustic solitons and rogue waves in a multi-dimensional anisotropic self-gravitating electron-depleted complex plasmas

A spectral bias-error stepwise correction method of plasma image-spectrum fusion based on deep learning for improving the performance of LIBS

Poor spectral stability seriously hinders the wide application of laser-induced breakdown spectroscopy (LIBS), so how to improve its stability is the focus, hotspot, and difficulty of current research. In this study, to achieve high precision quantitative analysis under complex detection conditions, utilizing the fusion of multi-dimensional plasma information and the integration of physical models and algorithmic models, a spectral bias-error stepwise correction method of plasma image-spectrum fusion based on deep learning (SBESC-PISF) was proposed. In this method, based on the statistical properties of LIBS spectra, the actual obtained spectra were decomposed into three parts: the ideal spectral intensity related only to the element concentration, and the spectral bias and spectral error caused by the fluctuation of complex high-dimensional plasma parameters. Further, the deep learning methods were used to fully excavate all the effective features in the plasma images and spectra to invert the complex high-dimensional plasma parameters according to the physical models. Finally, the estimation models of spectral bias and spectral error were established based on these features, to realize the high-precision correction of spectral intensity. To verify the feasibility of SBESC-PISF, the spectra of aluminum alloy samples obtained under three complex detection conditions were used for analysis. Under the experimental condition of laser energy fluctuation, after correction by SBESC-PISF, R2 of the three calibration curves was all increased to 0.999, RMSE and STD of the validation set (RMSEV, STDV) were reduced by 55.246 % and 50.167 %, respectively. Under the experimental condition of defocusing amount fluctuation, R2 was also all increased to 0.999, RMSEV and STDV were decreased by 58.201 % and 51.006 %, respectively. When the laser energy and defocusing amount fluctuate simultaneously, R2 was increased to 0.999, 0.996 and 0.988, RMSEV and STDV were reduced by 58.776 % and 54.397 %, respectively. These experimental results demonstrate that the spectral fluctuation correction of SBESC-PISF under complex detection conditions is effective and has wide applicability.

Multidimensional plasma lipid composition and its causal association with type 2 diabetes mellitus: A Mendelian randomization study

Background and aimRecent research extends our knowledge of plasma lipid species, building on established links between serum lipid levels and Type 2 Diabetes Mellitus (T2DM) risk. Identifying the causal roles of these lipid species is key to improving T2DM risk assessment. Methods and resultsThis study employs Mendelian randomization (MR) to investigate the causal relationship between 179 lipid species across 13 lipid categories and T2DM. Summary-level data were sourced from genome-wide association studies. The primary analytical methods included the inverse variance weighted (IVW) approach and the Wald ratio, complemented by a series of sensitivity analyses to ensure the robustness of results. The IVW analysis reveals a significant causal association between elevated levels of ceramide (d40:2) (OR = 1.071, 95% CI 1.034–1.109, P = 1.36 × 10−4), sphingomyelin (d38:1) (OR = 1.052, 95% CI 1.028–1.077, P = 1.80 × 10−5), and triacylglycerol (56:8) (OR = 1.174, 95% CI 1.108–1.243, P = 4.65 × 10−8), and an increased risk of T2DM. Conversely, Wald ratio analysis indicates that higher levels of phosphatidylcholine (O-16:1_16:0) (OR = 0.928, 95% CI 0.892–0.966, P = 2.37 × 10−4), phosphatidylcholine (O-16:1_20:4) (OR = 0.932, 95% CI 0.897–0.967, P = 2.37 × 10−4), and phosphatidylcholine (O-18:2_20:4) (OR = 0.872, 95% CI 0.812–0.935, P = 1.24 × 10−4) are significantly associated with a reduced risk of T2DM. Furthermore, suggestive causal evidence for 22 additional lipid species was identified. ConclusionsThis MR study establishes a causal relationship between specific lipid classes in modulating the risk of T2DM. It offers new insights for risk assessment and potential therapeutic targets in T2DM.

Effects of multi-dimensionality and energy exchange on electrostatic current-driven plasma instabilities and turbulence

Large-amplitude current-driven plasma instabilities, which can transition to the Buneman instability, were observed in one-dimensional simulations to generate high-energy back-streaming ions. We investigate the saturation of multi-dimensional plasma instabilities and its effects on energetic ion formation. Such ions directly impact spacecraft thruster lifetimes and are associated with magnetic reconnection and cosmic ray inception. An Eulerian Vlasov–Poisson solver employing the grid-based direct kinetic method is used to study the growth and saturation of 2D2V collisionless, electrostatic current-driven instabilities spanning two dimensions each in the configuration (D) and velocity (V) spaces supporting ion and electron phase-space transport. Four stages characterise the electric potential evolution in such instabilities: linear modal growth, harmonic growth, accelerated growth via quasi-linear mechanisms alongside nonlinear fill-in and saturated turbulence. Its transition and isotropisation process bears considerable similarities to the development of hydrodynamic turbulence. While a tendency to isotropy is observed in the plasma waves, followed by electron and then ion phase spaces after several ion-acoustic periods, the formation of energetic back-streaming ions is more limited in the 2D2V than in the 1D1V simulations. Plasma waves formed by two-dimensional electrostatic kinetic instabilities can propagate in the direction perpendicular to the net electron drift. Thus, large-amplitude multi-dimensional waves generate high-energy transverse-streaming ions and eventually limit energetic backward-streaming ions along the longitudinal direction. The multi-dimensional study sheds light on interactions between longitudinal and transverse electrostatic plasma instabilities, as well as fundamental characteristics of the inception and sustenance of unmagnetised plasma turbulence.

Plasma propulsion modeling with particle-based algorithms

This Perspective paper deals with an overview of particle-in-cell/Monte Carlo collision models applied to different plasma-propulsion configurations and scenarios, from electrostatic (E×B and pulsed arc) devices to electromagnetic (RF inductive, helicon, electron cyclotron resonance) thrusters, as well as plasma plumes and their interaction with the satellite. The most important items related to the modeling of plasma–wall interaction are also presented. Finally, the paper reports new progress in the particle-in-cell computational methodology, in particular, regarding accelerating computational techniques for multi-dimensional simulations and plasma chemistry Monte Carlo modules for molecular and alternative propellants.

Early detection of squamous cell carcinoma of the oral tongue using multidimensional plasma protein analysis and interpretable machine learning

AbstractBackgroundInterpretable machine learning (ML) for early detection of cancer has the potential to improve risk assessment and early intervention.MethodsData from 261 proteins related to inflammation and/or tumor processes in 123 blood samples collected from healthy persons, but of whom a sub‐group later developed squamous cell carcinoma of the oral tongue (SCCOT), were analyzed. Samples from people who developed SCCOT within less than 5 years were classified as tumor‐to‐be and all other samples as tumor‐free. The optimal ML algorithm for feature selection was identified and feature importance computed by the SHapley Additive exPlanations (SHAP) method. Five popular ML algorithms (AdaBoost, Artificial neural networks [ANNs], Decision Tree [DT], eXtreme Gradient Boosting [XGBoost], and Support Vector Machine [SVM]) were applied to establish prediction models, and decisions of the optimal models were interpreted by SHAP.ResultsUsing the 22 selected features, the SVM prediction model showed the best performance (sensitivity = 0.867, specificity = 0.859, balanced accuracy = 0.863, area under the receiver operating characteristic curve [ROC‐AUC] = 0.924). SHAP analysis revealed that the 22 features rendered varying person‐specific impacts on model decision and the top three contributors to prediction were Interleukin 10 (IL10), TNF Receptor Associated Factor 2 (TRAF2), and Kallikrein Related Peptidase 12 (KLK12).ConclusionUsing multidimensional plasma protein analysis and interpretable ML, we outline a systematic approach for early detection of SCCOT before the appearance of clinical signs.

Concept of the generalized reduced-order particle-in-cell scheme and verification in an axial-azimuthal Hall thruster configuration

The reduced-order particle-in-cell (PIC) scheme is a novel modeling approach that enables computationally efficient electrostatic kinetic simulations of plasma. In our previous publications, we demonstrated that a proof-of-concept implementation of this novel PIC scheme resolves the multi-dimensional plasma processes and their interactions in a Hall thruster in a manner close to traditional electrostatic PIC codes. In this work, we extend our efforts on this topic and present a mathematically mature formulation for the dimensionality reduction of Poisson’s equation in the Vlasov–Poisson system, which enables the generalized reduced-order ‘quasi-multi-dimensional’ PIC scheme. The applicability of the dimensionality-reduction approach to solve general 2D Poisson problems is numerically verified. Next, we present several reduced-order quasi-2D (Q2D) simulations of a well-defined axial-azimuthal simulation case from the literature using approximation orders of the 2D problem whose computational costs are 2%–15% of a full-2D simulation. It is shown that these reduced-order simulations allow us to recover the same characteristics, behaviors and effects reported in the literature regarding the azimuthal instabilities in Hall thrusters. Moreover, in terms of the time-averaged plasma properties, it was found that, when increasing the approximation order, the error associated with the Q2D simulations’ predictions decreases from 15% to 4% for the electric field and from 20% to 2% for the ion number density. We have additionally discussed a series of sensitivity analysis results, including the influence of the initial number of macroparticles per cell on the predictions of the Q2D simulations. According to the detailed results and analyses presented, we conclude that the generalized reduced-order PIC scheme serves as a rigorous foundation for eventual cost-effective and comprehensive three-dimensional kinetic studies of the physics in Hall thrusters and similar electrostatic plasma technologies.

Breakdown Spectroscopy Induced by Nonlinear Interactions of Femtosecond Laser Filaments and Multidimensional Plasma Gratings

Breakdown spectroscopy is a valuable tool for determining elements in solids, liquids, and gases. All materials in the breakdown region can be ionized and dissociated into highly excited fragments and emit characteristic fluorescence spectra. In this sense, the elemental composition of materials can be evaluated by detecting the fluorescence spectrum. This paper reviews the recent developments in laser-induced breakdown spectroscopy. The traditional laser-induced breakdown spectroscopy, filament-induced breakdown spectroscopy, plasma grating, and multidimensional plasma grating-induced breakdown spectroscopy are introduced. There are also some proposals for applications of plasma gratings, such as laser ablation, laser deposition, and laser catalysis of chemical reactions in conjunction with research on the properties of plasma gratings.

On the global well-posedness and optimal large-time behavior of strong solution for a multi-dimensional two-fluid plasma model

On the global well-posedness and optimal large-time behavior of strong solution for a multi-dimensional two-fluid plasma model

Resolving multi-dimensional plasma phenomena in Hall thrusters using the reduced-order particle-in-cell scheme

Plasma in Hall thrusters exhibits a complex behavior, characterized by the interplay between various dominant processes in each of the thruster’s coordinates. The emergence of high-power Hall thrusters in the recent years and the design modifications intended to extend the lifetime of these devices have further amplified the three-dimensional nature of the plasma behavior. In this regard, the novel reduced-order particle-in-cell (PIC) scheme provides the possibility to resolve the multi-dimensional interactions in a Hall thruster at a computational cost up to two orders of magnitude lower than current multi-dimensional PIC simulations. To demonstrate this point, we present in this article the results from a series of pseudo-two-dimensional simulations we performed in three configurations: axial-azimuthal, azimuthal-radial, and axial-radial. We show that, in each configuration, the pseudo-2D PIC scheme provides a significantly improved picture of the involved physics compared to a one-dimensional PIC simulation and captures self-consistently the coupling between the plasma processes in different directions, notably similar to the observations from full-2D kinetic simulations.

Multi-dimensional electrostatic plasma simulations using the particle-in-cell method for the low-temperature plasmas for materials processing

Multi-dimensional electrostatic plasma simulations using the particle-in-cell method for the low-temperature plasmas for materials processing

Femtosecond laser-induced breakdown spectroscopy by multidimensional plasma grating

The multi-dimensional-plasma-grating-induced spectroscopy (MIBS) technique that uses a 2D plasma grating formed by the interaction of three filaments to ablate the sample can achieve better detection of trace elements in soil.

Conservative semi-Lagrangian kinetic scheme coupled with implicit finite element field solver for multidimensional Vlasov Maxwell system

In this paper, a conservative semi-Lagrangian (CSL) kinetic scheme coupled with an implicit finite element method (IFEM) is developed for multidimensional electromagnetic plasma simulations. The present method (CSL-IFEM) enjoys the respective advantages of the CSL and IFEM, including mass conservation, high-order spatial accuracy, as well as being free from the Courant-Friedrichs-Lewy (CFL) condition. In present CSL-IFEM, the CSL scheme with a general high order positivity-preserving limiter is utilized for the spatial discretization of the Vlasov equation, which enables the proposed method to remove the CFL limitation in phase space, exactly conserve mass, and preserve the positivity of the distribution function. The IFEM solver is developed for the spatial discretization of the Maxwell equation, which makes the current method free from CFL limitation induced by the speed of light and easily handles general field boundary conditions. To make the proposed CSL-IFEM more efficient in multidimensional simulations, the dimensional splitting procedure and sparse matrix technology are implemented in CSL and IFEM, respectively. Then the Vlasov solver CSL and Maxwell solver IFEM are coupled via the current density calculated from the general Ohm law. Finally, several numerical experiments, including electromagnetic wave (2d0v), particle gyromotion (0d2v), streaming Weibel instability (1d2v) and magnetic reconnection (2d3v), are performed to demonstrate the capabilities of the proposed method.

Modeling Nanosecond-Pulsed Spark Discharge and Flame Kernel Evolution

Abstract Dilute combustion, either using exhaust gas recirculation or with excess air, is considered a promising strategy to improve the thermal efficiency of internal combustion engines. However, the dilute air-fuel mixture, especially under intensified turbulence and high-pressure conditions, poses significant challenges for ignitability and combustion stability, which may limit the attainable efficiency benefits. In-depth knowledge of the flame kernel evolution to stabilize ignition and combustion in a challenging environment is crucial for effective engine development and optimization. To date, a comprehensive understanding of ignition processes that result in the development of fully predictive ignition models usable by the automotive industry does not yet exist. Spark-ignition consists of a wide range of physics that includes electrical discharge, plasma evolution, joule-heating of gas, and flame kernel initiation and growth into a self-sustainable flame. In this study, an advanced approach is proposed to model spark-ignition energy deposition and flame kernel growth. To decouple the flame kernel growth from the electrical discharge, a nanosecond-pulsed high-voltage discharge is used to trigger spark-ignition in an optically accessible small ignition test vessel with a quiescent mixture of air and methane. Initial conditions for the flame kernel, including its thermodynamic state and species composition, are derived from a plasma-chemical equilibrium calculation. The geometric shape and dimension of the kernel are characterized using a multi-dimensional thermal plasma solver. The proposed modeling approach is evaluated using a high-fidelity computational fluid dynamics procedure to compare the simulated flame kernel evolution against flame boundaries from companion Schlieren images.

Oblate electron holes are not attributable to anisotropic shielding

The influence of shielding mechanisms on the ratio of perpendicular to parallel scale lengths of multidimensional plasma electron hole equilibria is analyzed theoretically and computationally. It is shown that the “gyrokinetic” model, invoking perpendicular polarization, is based on a misunderstanding and cannot explain the observational trend that greater transverse extent accompanies a lower magnetic field. Instead, the potential in the wings of the hole, outside the region of trapped-electron depletion, has isotropic shielding giving ϕ∝e−r/L/r, with the shielding length L equal to the Debye length for holes much slower than the electron thermal speed. Particle in cell simulations confirm the analysis. Trapped electron charge distribution anisotropy must, therefore, instead underlie the oblate shape of electron holes.

Effects of emitting surfaces and trapped ions on the sheath physics and current flow in multidimensional plasma systems

Recent one-dimensional simulations of planar sheaths with strong electron emission have shown that trapping of charge-exchange ions causes transitions from space-charge limited (SCL) to inverse sheaths. However, multidimensional emitting sheath phenomena with collisions remained unexplored, due in part to high computational cost. We developed a novel continuum kinetic code to study the sheath physics, current flow and potential distributions in two-dimensional unmagnetized configurations with emitting surfaces. For small negatively biased thermionic cathodes in a plasma, the cathode sheath can exist in an equilibrium SCL state. The SCL sheath carries an immense density of trapped ions, neutralized by thermoelectrons, within the potential well of the virtual cathode. For further increases of emitted flux, the trapped ion cloud expands in space. The trapped ion space charge causes an increase of thermionic current far beyond the saturation limit predicted by conventional collisionless SCL sheath models without ion trapping. For sufficiently strong emission, the trapped ion cloud consumes the entire 2D plasma domain, forming a mode with globally confined ions and an inverse sheath at the cathode. In situations where the emitted flux is fixed and the bias is swept (e.g. emissive probe), the trapped ions cause a large thermionic current to escape for all biases below the plasma potential. Strong suppression of the thermionic emission, required for the probe to float, only occurs when the probe is above the plasma potential.

P-DRGEP: a novel methodology for the reduction of kinetics mechanisms for plasma-assisted combustion applications

Detailed kinetics mechanisms for plasma-assisted combustion contain numerous species and reactions that model the interplay between non-equilibrium plasma processes and hydrocarbon oxidation. While physically accurate and comprehensive, such detailed mechanisms are impractical for simulations of unsteady multi-dimensional plasma discharges and their effect on reactive mixtures in practical devices. In this work, we develop and apply a novel methodology for the reduction of large detailed plasma-assisted combustion mechanisms to smaller skeletal ones. The methodology extends the Directed Relation Graph with Error Propagation (DRGEP) approach in order to consider the energy branching characteristics of plasma discharges during the reduction. Ensuring tight error tolerances on the relative proportions of energy lost by the electrons to the various classes of impact processes (i.e. vibrational and electronic excitation, ionization, and impact dissociation) is key to preserving the correct discharge physics in the skeletal mechanism. To this end, new targets that include energy transfers are defined and incorporated in DRGEP. The performance of the novel framework, called P-DRGEP, is assessed for the simulation of ethylene-air ignition by nanosecond repetitive pulsed discharges at conditions relevant to supersonic combustion and flame holding in scramjet cavities, i.e. from 600 K to 1000 K, 0.5 atm, and equivalence ratios between 0.75 and 1.5. P-DRGEP is found to be greatly superior to the traditional reduction approach applied to plasma-assisted ignition in that it generates a smaller skeletal mechanism with significantly lower errors. For ethylene-air ignition at the target conditions, P-DRGEP generates a skeletal mechanism with 54 species and 236 reactions, resulting in a 84% computational speed-up for ignition simulations, while guaranteeing errors below 10% on the time required for ignition following the first pulse, 1% on the mean electron energy, between 4 and 35% on electron energy losses depending on the process, and 5% on the laminar flame speed.

A Modified Thrombin Generation Analysis to Measure the Plasma Coagulation Potency in the Presence of Anti-FIXa/FX Bispecific Antibody, Emicizumab

【Introduction】 Emicizumab is a humanized anti-factor (F)IXa/FX bispecific antibody with FVIIIa cofactor function. Since emicizumab, unlike FVIII, does not require activation by thrombin, its aPTT-shortening effect is much greater than that of FVIII. Thus, aPTT, a conventional assay to assess intrinsic coagulation potency, would have limited utility in emicizumab-administered hemophilia A-patients (HA-pts), because emicizumab would mask the effect of residual FVIII or a FVIII agent on aPTT. Also, aPTT cannot differentiate between different levels of emicizumab.Recently we reported that clot waveform analysis (CWA) using a trigger reagent comprising a balanced mixture of ellagic acid (Elg) and tissue factor (TF) to reflect both intrinsic and extrinsic coagulation activities could provide a useful means of assessing plasma coagulation potential in HA-pts treated with emicizumab with enhanced activity neither masking nor being masked by FVIII or bypassing agents (BPAs)1). Thrombin generation assay (TGA) can provide multidimensional plasma coagulation potencies as well as CWA. We considered the possibility, therefore, that the TGA would also overcome the above issue on aPTT. In this study, we aimed to assess TGA using Elg/TF trigger and two reference triggers (FXIa, TF) to evaluate the coagulation potency of patients with HA receiving emicizumab.【Method】 TGA was assayed using Elg/TF trigger consisted of TF (0.5 pM) and Elg (0.3 μM) with phospholipids vesicles (PL, 4 μM), FXIa trigger consisted of FXIa (0.47 nM) with PL (20 μM), and TF trigger (PPP-Reagent LOW®). Various concentrations of emicizumab, FVIII agent, or BPAs (rFVIIa, aPCC) in clinical dosages were spiked into commercially available FVIII-deficient plasmas (George King) for testing. Then, FVIII or BPA was added to FVIII-deficient plasmas containing emicizumab.【Result】 Emicizumab or FVIII showed dose-dependent increase in thrombin peak height in Elg/TF trigger as well as FXIa and TF triggers, but TF trigger had weak sensitivity to emicizumab and low range FVIII (1-10 IU/dl). Spiking both rFVIIa or aPCC showed dose dependent increase in thrombin peak height under Elg/TF trigger and TF trigger conditions, but the values were lower than the level of normal peak height. On the other hand, rFVIIa and aPCC resulted in little increase in peak height under FXIa trigger condition, suggesting that the FXIa trigger is not suitable for assessment of BPAs. These results indicated that Elg/TF trigger system was the most useful to evaluate the single-spiked effect of these agents.Then, we examined the additional effects of FVIII or BPAs in the presence of emicizumab by Elg/TF trigger system. The combination of FVIII and emicizumab showed additive increase in peak thrombin height, but this effect was saturated at high dose of FVIII more than 100 IU/dl. rFVIIa and emicizumab showed additive effect on increased peak thrombin height, achieving normal level even at very low dose rFVIIa (0.67 μg/ml), but remains within normal ranges at high dose (6.0 μg/ml). aPCC and emicizumab showed increased peak thrombin height, but in this case, exceeding the normal level even at clinical dosage of aPCC (0.5-1.0 U/ml).【Conclusion】 TGA with Elg/TF trigger could provide a useful monitoring tool of assessing global coagulation potential during emicizumab prophyaxis including concomitant therapy with FVIII or BPAs.1) Nogami K, et al. Modified clot waveform analysis to measure plasma coagulation potential in the presence of the anti-factor IXa/factor X bispecific antibody emicizumab. J Thromb Haemost. 2018 Jun;16(6):1078-1088. DisclosuresOgiwara:CSL Behring: Research Funding. Nogami:Chugai Pharmaceutical Co., Ltd: Consultancy, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties: Anti-FIXa/X bispecific antibodies , Research Funding, Speakers Bureau. Matsumoto:Shire Japan Co. Ltd: Research Funding. Noguchi-Sasaki:Chugai: Employment. Soeda:Chugai: Employment, Patents & Royalties: Patents related to emicizumab. Matsumoto:Chugai Pharmaceutical Co., Ltd: Employment, Equity Ownership. Hirata:Chugai Pharmaceutical Co., Ltd: Employment, Equity Ownership. Shima:Chugai Pharmaceutical Co., Ltd: Consultancy, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties: Anti-FIXa/X bispecific antibodies , Research Funding, Speakers Bureau; F. Hoffmann-La Roche Ltd: Membership on an entity's Board of Directors or advisory committees.

Evidence of a turbulent ExB mixing avalanche mechanism of gas breakdown in strongly magnetized systems

Although gas breakdown phenomena have been intensively studied over 100 years, the breakdown mechanism in a strongly magnetized system, such as tokamak, has been still obscured due to complex electromagnetic topologies. There has been a widespread misconception that the conventional breakdown model of the unmagnetized system can be directly applied to the strongly magnetized system. However, we found clear evidence that existing theories cannot explain the experimental results. Here, we demonstrate the underlying mechanism of gas breakdown in tokamaks, a turbulent ExB mixing avalanche, which systematically considers multi-dimensional plasma dynamics in the complex electromagnetic topology. This mechanism clearly elucidates the experiments by identifying crucial roles of self-electric fields produced by space-charge that decrease the plasma density growth rate and cause a dominant transport via ExB drifts. A comprehensive understanding of plasma dynamics in complex electromagnetic topology provides general design strategy for robust breakdown scenarios in a tokamak fusion reactor.