The role of the number of filaments in the dissociation of CO<sub>2</sub> in dielectric barrier discharges
Bibliographic record
Abstract
Abstract An experimental investigation of the dissociation of CO2 in a symmetric pin-to-pin dielectric barrier discharge (DBD) is presented. The reactor geometry allows for an accurate control of the number of filaments (microdischarges) and is used to study the impact of one single filament on the CO2 dissociation. We show the number of filaments per half cycle follows a power-law as a function of the injected power and does not depend on pressure, flow or other process parameters. It is shown that for pressures between 200 and 700 mbar approximately 0.5 W per filament is required and the charge transferred per filament remains constant at 0.5 nC. Furthermore, the dependence of CO2 conversion on only specific energy input (SEI) is shown to be valid down to a single filament. Additionally, by using quantum cascade laser absorption spectroscopy the absolute number of CO molecules produced per filament is measured and is found to be in the range from 5.1011 to 2.1012. The conversion degree of CO2 into CO is estimated to be lower than 0.1% within a single filament and increases with SEI. In the presence of a couple of filaments, the maximum energy efficiency obtained is 25%. A comparison of the conversion degrees in pin-to-pin DBD and plane-to-plane DBD configuration shows that these two reactor geometries follow the same power law. This means the geometry is not the most important parameter in CO2 dissociation in DBDs, but the SEI and thus the number of filaments ignited per unit of time. This result means that the dependence of conversion degree on the SEI can be extended to a single filament. This observation leads to the conclusion that the SEI appears to be valid as a universal scaling parameter down to very low values.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".