Development of a surface plasma method for negative ion beams production
Bibliographic record
Abstract
Abstract By now, the fluxes of accelerated negative ions of steel an indispensable tool for accelerators, plasma physics, solid state physics, chemistry, biology, medicine, important areas of new technique and technology. It arouses increased interest to the development of intensive sources of these particles. The cesiation effect - a significant increase in the emission of negative ions from the discharge with a simultaneous decrease in the flux of accompanying electrons below the current of negative ions after adding a small amount of cesium or other substances with a low ionization potential to the discharge was discovered 50 years ago, on July 1, 1971 in the Budker Institute of Nuclear Physics (BINP), Novosibirsk, Russia. The cesiation effect has opened the door to high-intensity, high-brightness negative ion beams production. The efficiency of generating beams of negative ions was significantly increased due to the invention at the BINP of geometric focusing of generated negative ions. Based on the cesiation effect a surface-plasma method for producing beams of negative ions was developed at the BINP, which provided the creation of surface plasma sources of negative ions for accelerators with a current of hundreds of mA and sources for Controlled Nuclear Fusion with a current of tens of A. (the previous intensity record was 5 mA). Surface plasma sources are being developed all over the world in England, France, Germany, Switzerland, Italy, Japan, Korea, China, India, USA, Canada, Sweden, Spain, New Zealand, Russia, Ukraine, Finland with investments in billions of USD. Specialists in surface plasma sources are trained at the Plasma Physics Department of Novosibirsk State University.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".