Non-thermal plasma technology for air pollution control and bacterial deactivation
Bibliographic record
Abstract
The exploration of innovative technologies for effective pollution control is crucial for both environmental and human health. Non-thermal plasma has emerged as a promising solution due to its dynamic nature and versatile applications. This work investigates the role of non-thermal plasma in air pollution control, covering the decomposition of various volatile organic compounds, including toluene, formaldehyde, ethanol, hydrogen sulfide, and sulfur dioxide, as well as the deactivation of E. coli . The findings revealed that toluene, formaldehyde, and ethanol reach more than 90% decomposition, while hydrogen sulfide undergoes a complete conversion. Meanwhile, the sulfur dioxide removal efficiency stands at 27%. Additionally, E. coli deactivation in fixed feeding mode demonstrates robust bactericidal capabilities within 30 min, while continuous feeding for 4 h achieves 100% bacterial inactivation. These quantitative outcomes provide insights for optimizing non-thermal plasma systems in pollution control, environmental remediation, and sterilization processes.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".