Phase-resolved profiles of electron energy deposition in inductively coupled radio-frequency plasmas driven under confronting divergent magnetic fields

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We investigate the partial resonance as one of the mechanisms of the electron heating to sustain inductively coupled plasmas driven under confronting divergent magnetic fields having an electron confinement function. Dependence of the partial resonance on operating conditions are observed. The electron energy gain (EEG), defined as a measure for evaluation of the partial resonance, was calculated by a Monte Carlo method under various magnetic field strengths and the RF antenna positions. It is confirmed that the partial resonance is observed in the resonant region even in low electric field and strong magnetic field. As an attempt to utilize the partial resonance, we demonstrate enhancement of the EEG and resulting ionization in the resonant region by placing the RF antenna near a region where the magnetic field lines running through the resonant region reach. 

Section: Chamber Dimensions and Coordinatesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of electron heating due to partial resonance in an inductively coupled plasma under confronting divergent magnetic fields

Okazaki

Sugawara

2023

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“…81) The azimuthal velocity of electron motion in a cylindrical chamber under an RF electric field and confronting divergent magnetic fields was simulated to evaluate the phase-resolved profiles of power deposition on electrons in a low-pressure inductively coupled magnetized plasma. 82) The average velocity of electron motion under crossed fields of alternative current (AC) electric and DC magnetic components was formulated analytically. The velocity vector draws elliptical loci with alternating electric fields.…”

Section: 5mentioning

confidence: 99%

Science-based, data-driven developments in plasma processing for material synthesis and device-integration technologies

Kambara

Kawaguchi

Lee

et al. 2022

Low-temperature plasma processing technologies is essential for material synthesis, device fabrication, and surface treatment. The development of plasma-related products and services requires an understanding of the multiscale complex behaviors of plasma and the hierarchical integration of plasma generation, energy and mass transports through sheath region, surface reactions, and other processes. The importance of science-based and data-driven approaches to controlling systems is argued. The state-of-the-art of deep learning, machine learning, and artificial intelligence in low-temperature plasma science and technology is reviewed. In this review, the requirements and challenges for plasma parameter prediction and processing recipe discovery are asserted by researchers in the fields of material science and plasma processing. It also outlined a science-based, data-driven approach for development of virtual metrology in plasma processes.

“…Phase-resolved EEG distribution was observed to analyze the causes of high EEG in several regions in the X-point plasmas. 10,27 It was indicated that a specific configuration of electric and magnetic fields induced a directionality of electron drift and an asymmetric power deposition between the first and second halves of an rf period. In the vicinity of the sidewall of the chamber, it was revealed that a directionality caused by electron reflection under a magnetic field leads to a stochastic EEG.…”

Section: Introductionmentioning

confidence: 99%

“…[5][6][7][8] We focus on the plasma flow controllability through the adjustment of coil currents inducing the magnetic fields. 9,10) The magnetic fields are expected as magnetic filter/shutter, [11][12][13][14][15][16][17][18][19][20][21][22] and their potential applications would be advanced plasma modulation and downsizing of remote plasmas. On the other hand, it is known that magnetic fields have cooling effect on electrons in plasmas.…”

Section: Introductionmentioning

confidence: 99%

Stochastic electron energy gain under sheath electric field near sidewall of chamber to drive inductively coupled magnetized plasmas

Takahashi

Sugawara

2020

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Single-electron motions near the sidewall of a chamber to drive a type of inductively coupled magnetized plasmas are analyzed using a Monte Carlo method in a simulation model with sheath electric field (E sh ) to understand the mechanism of electron energy gain (EEG). The analysis reveals that the E × B drift caused by E sh , along the rf electric field induced in parallel to the sidewall, makes the EEG high and asymmetric between the first and second halves of an rf period. We observe spatial distributions of the EEG as a function of the distance from the wall under several sheath conditions. The EEG is higher under higher E sh and high EEG values are more concentrated in the sheath whose potential gradient is larger. Finally, observation of the phase-resolved EEG distributions demonstrates statistically that the EEG mechanism found in stochastic individual electron behaviors also works for a majority of electrons.