Kinetic effects in a plasma crystal induced by an external electron beam

Ticoş, C. M.; Ticoş, D.; Williams, Jeremiah

doi:10.1063/1.5092749

Cited by 10 publications

(10 citation statements)

References 44 publications

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“…Low shear rates can be attained at lower e-beam currents, e.g. at 4 mA when we observe the formation of multiple vortices at different space scales and with a wide range of vorticities 20 . Tuning the viscosity of the charged dust flow means that its Reynolds number can be modified, which is one key asset of our platform.…”

Section: Rotational Dust Flow Applicationsmentioning

confidence: 74%

“…In previous works we have shown for the first time that an e-beam incident upon a PC can induce a dust flow in the crystal by the drag fore of the electrons acting on the individual dust particles. The flow speed vectors have been mapped in 2D and their evolution in space and time has led to the simultaneous formation of multiple small speed vortices 20 , 21 . The dust flow was dissipated towards the spatial limit of the crystal.…”

Section: Rotational Dust Flow Applicationsmentioning

confidence: 99%

“…In a RF plasma the drag force on a dust particle exerted by these low temperature plasma electrons is weak, much smaller than the electric force which levitates the dust particle and therefore can be neglected 31 . By contrast, an e-beam with energy at the level of keV can push the dust particles and accelerate them up to large terminal speeds 1–10 mm s , inducing interesting kinetic effects 20 , 21 .…”

Section: Introductionmentioning

confidence: 99%

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A laboratory platform for studying rotational dust flows in a plasma crystal irradiated by a 10 keV electron beam

Ticoş

Constantin

Mitu

et al. 2023

Sci Rep

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A novel laboratory platform has been designed and built for the irradiation of a plasma crystal (PC) with an electron beam (e-beam) having an energy around 10 keV and a current of tens of milliamperes. The pulsed e-beam collimated to a few millimeter-size spot is aimed at a crystal made of dust particles levitated in a radio-frequency (RF) plasma. The platform consists of three vacuum chambers connected in-line, each with different utility: one for generating free electrons in a pulsed hollow-anode Penning discharge, another for the extraction and acceleration of electrons at $$\sim 10$$ ∼ 10 kV and for focusing the e-beam in the magnetic field of a pair of circular coils, and the last one for producing PCs above a RF-driven electrode. The main challenge is to obtain both a stable e-beam and PC by insuring appropriate gas pressures, given that the e-beam is formed in high vacuum ($$\lesssim 10^{-4}$$ ≲ 10 - 4 Torr), while the PC is produced at much higher pressures ($$\gtrsim 10^{-1}$$ ≳ 10 - 1 Torr). The main diagnostics include a high speed camera, a Faraday cup and a Langmuir probe. Two applications concerned with the creation of a pair of dust flow vortices and the rotation of a PC by the drag force of the e-beam acting on the strongly coupled dust particles are presented. The dust flow can become turbulent as demonstrated by the energy spectrum, featuring vortices at different space scales.

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Section: Rotational Dust Flow Applicationsmentioning

confidence: 74%

Section: Rotational Dust Flow Applicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A laboratory platform for studying rotational dust flows in a plasma crystal irradiated by a 10 keV electron beam

Ticoş

Constantin

Mitu

et al. 2023

Sci Rep

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“…Terabyte datasets are available from dusty plasma experiments through particle tracking and imaging [336]. Dusty plasma movies have been recorded at about 1500 to 5000 frame length, at the rates between 100 -500 frames s −1 and each image size of a few MB per frame [337]. For an experimental campaign consisting of a few hundred runs, more than 1.5 million movie frames or more than 1 TB of raw data becomes available [338].…”

Section: Dusty and Complex Plasmasmentioning

confidence: 99%

2022 Review of Data-Driven Plasma Science

Archibald¹,

Asif²,

Becker³

et al. 2022

Preprint

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Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS). A large amount of data and machine learning algorithms go hand in hand. Most plasma data, whether experimental, observational or computational, are generated or collected by machines today. It is now becoming impractical for humans to analyze all the data manually. Therefore, it is imperative to train machines to analyze and interpret (eventually) such data as intelligently as humans but far more efficiently in quantity. Despite the recent impressive progress in applications of data science to plasma science and technology, the emerging field of DDPS is still in its infancy. Fueled by some of the most challenging problems such as fusion energy, plasmaprocessing of materials, and fundamental understanding of the universe through observable plasma phenomena, it is expected that DDPS continues to benefit significantly from the interdisciplinary marriage between plasma science and data science into the foreseeable future. CONTENTSI. Introduction 6 II. Fundamental Data Science 6 A. Introduction 6 B. Data Reduction/Compression 7 C. Dimensional reduction and sparse modeling 8 D. ML-enhanced modeling and simulation 9 E. ML Hardware and integration with models 10 F. Workflow Automation 11 G. Uncertainty Quantification 12 H. Visualization and Data Understanding 13 I. ML Control Theory 15 III. Basic Plasma Physics and Laboratory Experiments A. Introduction B. Spectroscopy, imaging and tomography C. Sparse measurement and noise D. Synthetic instruments and data E. Experimental data visualization F. High-rep rate laser experiments G. Charged particle beams H. Control and Optimisation of Plasma Accelerator Experiments I. Dusty and complex plasmas J. Physics and machine learning K. Challenges and outlook 5 IV. Magnetic Confinement Fusion 36 A. Introduction 36 B. Data-Driven Physics Models 36 C. Optimizing experimental workflows with data-driven methods 37 D. Diagnostics and Fusion Data Streams 38 E. Prediction of Tokamak Disruption 39 F. Surrogate models of fusion plasma 40 G. Magnetic Fusion Energy Data Challenges and Solutions 41 H. Data Science for extreme scale simulation 43 I. Challenges and outlook 44 V. Inertial confinement fusion and high-energy-density physics 45 A. Introduction 45 B. Representation learning for multimodal data 45 C. Transfer learning for simulation and experimen 47 D. Uncertainty quantification and Bayesian inference 47 E. High-performance computing and simulation acceleration 49 F. Design exploration and optimization 49 G. Self-driving experimental facilities 51 H. Challenges and outlook 52 VI. Space and astronomical plasmas 52 A. Introduction 52 B. Space and ground instruments 53 C. Space weather prediction 55 D. Transfer learning to improve historic data 56 E. Surrogate models of fluid closures using machine learning 56 F. Magnetic reconnection 58 G. Challenges and outlook 60 VII. Plasma tec...

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“…This allows us to investigate an inverse energy cascade from small to large scales for given system parameters. The direct Kolmogorovian energy cascade from large to small scales is also possible in dusty plasmas, for example, using electron beams or optical lasers to induce a large-scale shear flow in the structure [46], [47]. This concept will be explored in our future work.…”

Section: Introductionmentioning

confidence: 99%

Fractional Laplacian spectral approach to turbulence in a dusty plasma monolayer

et al. 2021

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This work presents a theoretical investigation of active turbulence in a dusty plasma monolayer, where energy is injected at the individual particle level and transported to larger scales, leading to the spontaneous formation of spatially disordered flow patterns. Many-body simulations of 10,000-particle dusty plasma monolayers are used to demonstrate how the global dynamics depend on the statistical properties of the dust assembly for realistic laboratory conditions. We find that spatial defects due to variations in the dust size distribution and charge-driven nonlocal interactions resulting in anomalous dust diffusion, are key factors for the onset of instabilities. The resulting dynamics exhibits features of inertial turbulence over slightly less than one decade of scales, down to scales on the order of the particle diameter. These processes are examined analytically using a recently developed Fractional Laplacian Spectral (FLS) technique, which identifies the active energy channels as a function of scale, disorder concentration, and nonlocality. The predictions from the theoretical (spectral) analysis demonstrate agreement with the results from the many-body (kinetic) simulations, thus providing a powerful tool for the study of active turbulence.

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Kinetic effects in a plasma crystal induced by an external electron beam

Cited by 10 publications

References 44 publications

A laboratory platform for studying rotational dust flows in a plasma crystal irradiated by a 10 keV electron beam

A laboratory platform for studying rotational dust flows in a plasma crystal irradiated by a 10 keV electron beam

2022 Review of Data-Driven Plasma Science

Fractional Laplacian spectral approach to turbulence in a dusty plasma monolayer

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