Investigation of light ion fusion reactions with plasma discharges
Bibliographic record
Abstract
The scaling of reaction yields in light ion fusion to low reaction energies is important for our understanding of stellar fuel chains and the development of future energy technologies. Experiments become progressively more challenging at lower reaction energies due to the exponential drop of fusion cross sections below the Coulomb barrier. We report on experiments where deuterium-deuterium (D-D) fusion reactions are studied in a pulsed plasma in the glow discharge regime using a benchtop apparatus. We model plasma conditions using particle-in-cell codes. Advantages of this approach are relatively high peak ion currents and current densities (0.1 to several A/cm2) that can be applied to metal wire cathodes for several days. We detect neutrons from D-D reactions with scintillator-based detectors. For palladium targets, we find neutron yields as a function of cathode voltage that are over 100 times higher than yields expected for bare nuclei fusion at ion energies below 2 keV (center of mass frame). A possible explanation is a correction to the ion energy due to an electron screening potential of 1000 ± 250 eV, which increases the probability for tunneling through the repulsive Coulomb barrier. Our compact, robust setup enables parametric studies of this effect at relatively low reaction energies.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".