Comparison of CO<sub>2</sub>and oxygen DC submerged thermal plasmas for decomposition of carboxylic acid in aqueous solution
Bibliographic record
Abstract
The feasibility of the carboxylic acid decomposition with two different direct current (DC) thermal plasma torches was investigated. An oxygen DC submerged thermal plasma torch and a newly designed submerged DC plasma torch operating with a mixture of carbon dioxide and methane (CO2/CH4) were used. Sebacic acid was selected as a representative of pollutants in the most wastewater produced by chemical process industries. The effect of different operational conditions including treatment time, the reactor pressure as well as the role of oxidizing agents such as (H2O2) were investigated on the decomposition rate of sebacic acid. Concentration of sebacic acid was quantified by Ion Chromatography/Mass Spectrometry (IC/MS). The oxygen plasma showed higher decomposition rate in basic medium. Adding H2O2 into aqueous solution enhanced the sebacic acid decomposition rate with the CO2/CH4 plasma up to the same decomposition rate of the oxygen plasma. Increasing the pressure also increased the decomposition rate for both plasmas with an increase twice higher for the CO2/CH4 plasma than that of the oxygen plasma. This work therefore presents the conditions in which these plasmas can provide the same decomposition rate for contaminants in aqueous solution.
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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".