Energetics of Noble Gas Dielectric Barrier Discharges: Novel Results Related to Electrode Areas and Dielectric Materials
Bibliographic record
Abstract
Two dielectric barrier discharge (DBD) reactors, one small, the other about 40 times larger, associated equipment, and a dedicated MATLAB code have been used to carry out precise determinations of electrical energy, E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> , dissipated per discharge cycle of the applied a.c. voltage, Va. In the smaller reactor, this was done over the frequency range 5 f 50 kHz and using twin pairs of several different insulating materials (2.54-cm-diameter disks) with relative permittivities between 2.1 κ' <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">die</sub> 9.5 as dielectric barriers in DBDs for four different gases: He, Ne, Ar, and N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . In the large reactor, f was restricted to 20 kHz in Ar and He; this latter system primarily serves for plasma polymerization experiments in which organic “monomers” are admixed with the flow of Ar as carrier gas. We report the method for exactly evaluating E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> , and then present and compare values measured under different conditions. To the extent possible, these are compared between the small and large reactors, and with results published in the literature. The reliability of the method is confirmed, for example, by reproducing published breakdown fields of the gases examined, and by several other original results.
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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 | 0.001 | 0.002 |
| 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".