Abatement of perfluorinated compounds using microwave plasmas at atmospheric pressure
Bibliographic record
Abstract
Microwave plasmas sustained at atmospheric pressure, for instance by electromagnetic surface waves, can be efficiently used to abate greenhouse-effect gases such as perfluorinated compounds. As a working example, we study the destruction and removal efficiency (DRE) of SF6 at concentrations ranging from 0.1% to 2.4% of the total gas flow where N2, utilized as a purge gas, is the carrier gas. O2 is added to the mixture at a fixed ratio of 1.2–1.5 times the concentration of SF6 to ensure full oxidation of the SF6 fragments, providing thereby scrubbable by-products. Fourier-transform infrared spectroscopy has been utilized for identification of the by-products and quantification of the residual concentration of SF6. Optical emission spectroscopy was employed to determine the gas temperature of the nitrogen plasma. In terms of operating parameters, the DRE is found to increase with increasing microwave power and decrease with increasing gas flow rate and discharge tube radius. Increasing the microwave power, in the case of a surface-wave discharge, or decreasing the gas flow rate increases the residence time of the molecules to be processed, hence, the observed DRE increase. In contrast, increasing the tube radius or the gas-flow rate increases the degree of radial contraction of the discharge and, therefore, the plasma-free space close to the tube wall: this comparatively colder region favors the reformation of the fragmented SF6 molecules, and enlarging it lowers the destruction rate. DRE values higher than 95% have been achieved at a microwave power of 6 kW with 2.4% SF6 in N2 flow rates up to 30 standard l/min.
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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 | 0.000 |
| 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) | 0.001 | 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".