Non-linear effects in ICP: theory and experiments
Bibliographic record
Abstract
Summary form only given. Operation of a low pressure inductively coupled plasma (ICP) at low driving frequency leads to increased values of the RF magnetic field and thus to enhancement of nonlinear effects due to RF Lorentz force typically negligible at 13.56 MHz. In recent years ICP experiments in low frequency regime have demonstrated generation of strong upper harmonics of the electrostatic potential and electric current in the ICP skin layer. A significant modification of the plasma profile by ponderomotive force has been demonstrated in a low frequency ICP, but the ponderomotive force found in experiment appeared to be significantly smaller than that predicted by classical formula for cold plasma. We review recently obtained experimental results on nonlinear effects in a low frequency cylindrical ICP with a planar coil and present a theory of these phenomena. We show that generation of nonlinear harmonics in RF potential and RF current are due to action of different parts of the RF Lorentz force; its potential part gives rise to potential oscillations, while its solenoidal part (existing only in a dissipative plasma) is responsible for generation of nonlinear current. A generalized theoretical model for nonlinear effects in two-dimensional cylindrical ICP, accounting for potential and solenoidal parts of the RF Lorentz force, has been formulated within a magneto-hydrodynamic approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".