Effects of non-Maxwellian electron velocity distribution function on two-stream instability in low-pressure discharges
Bibliographic record
Abstract
Electron emission from discharge chamber walls is important for plasma maintenance in many low-pressure discharges. The electrons emitted from the walls are accelerated by the sheath electric field and are injected into the plasma as an electron beam. Penetration of this beam through the plasma is subject to the two-stream instability, which tends to slow down the beam electrons and heat the plasma electrons. In the present paper, a one-dimensional particle-in-cell code is used to simulate these effects both in a collisionless plasma slab with immobile ions and in a cross-field discharge of a Hall thruster. The two-stream instability occurs if the total electron velocity distribution function of the plasma-beam system is a nonmonotonic function of electron speed. Low-pressure plasmas can be depleted of electrons with energy above the plasma potential. This study reveals that under such conditions the two-stream instability depends crucially on the velocity distribution function of electron emission. It is shown that propagation of the secondary electron beams in Hall thrusters may be free of the two-stream instability if the velocity distribution of secondary electron emission is a monotonically decaying function of speed. In this case, the beams propagate between the walls with minimal loss of the beam current and the secondary electron emission does not affect the thruster plasma properties.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".