Efficiency of plasma treatment of water contaminated with persistent organic molecules
Bibliographic record
Abstract
The authors examined the efficiency of plasma-pulse-driven dielectric barrier discharge oxidation of a solution of methylene blue (C16H18ClN2S) and wastewater from dye-producing plants, in which the main component is 2,4-dinitrotoluene (CH3C4H3(NO2)2), as well as models of the organic component of wastewater of nuclear power plants, the main constituent of which is a phosphate (PO4 3−)-based detergent with a 26.8% surfactant content. Water films with a thickness of 0.1 mm were processed with a discharge voltage equal to 3 × 1011 V/s. The energy efficiency of water treatment was studied against the specific energy input, the frequency of the repetition of the discharge pulses and the parameters of the fluid and gas going through the discharge chamber. The highest energy output was reached at an air velocity in the discharge chamber of ∼1 cm/s, which provides a concentration of ozone (O3) of ∼1.5 mg/l. The highest energy output, the processing of 87 g of wastewater with 1 kWh, was obtained by treating an aqueous solution of methylene blue with an initial concentration of 50 mg/l at 65% decomposition. An energy consumption of 10 J is the most efficient value for treatment of the tested 10 ml wastewater samples.
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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".