Physics and instabilities of low-temperature <i>E</i> <b>×</b> <i>B</i> plasmas for spacecraft propulsion and other applications
Bibliographic record
Abstract
Low-temperature E×B plasmas are used in various applications, such as Hall thrusters for satellite propulsion, ion sources and magnetron discharges for plasma processing, and negative ion sources for neutral beam injection in fusion. The plasmas in these devices are partially magnetized, meaning that the electrons are strongly magnetized while the ions are not. They are subject to various micro- and macro-instabilities that differ significantly from instabilities in fusion plasmas. These instabilities are often triggered by the large difference in electron and ion drift velocities in the E×B direction. The possibility of maintaining a large electric field in the quasineutral plasma of Hall thrusters despite anomalous electron transport, or the presence of strong double layers associated with the azimuthal rotation of plasma structures (“rotating spokes”) in magnetron discharges and Hall thrusters are examples of the very challenging and exciting physics of E×B devices. The turbulence and instabilities present in E×B plasma devices constitute a major obstacle to the quantitative description of these devices and to the development of predictive codes and are the subject of intense research efforts. In this tutorial, we discuss the key aspects of the physics of low-temperature partially magnetized E×B plasmas, as well as recent advances made through simulations, theory, and experiments in our understanding of the various types of instabilities (such as gradient-drift/Simon-Hoh and lower hybrid instabilities, rotating ionization waves, electron cyclotron drift instability, modified two-stream instability, etc.) that occur in these plasmas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".