Solar driven in-air plasma discharge for effective activation of water flow through self-suction mechanism
Bibliographic record
Abstract
Plasma activated water(PAW) is water that is treated with cold plasma discharge. The dissolved reactive oxygen and nitrogen species in PAW are desirable for wastewater treatment, environment remediation, food processing and storage, enhanced plant growth in agriculture and many other applications. In this work, we develop microbubble-enhanced PAW production through a self-suction mechanism. Microbubbles form under the strong turbulence effect at the throat of a cavitation tube, transferring active species into a stream of water. As demonstrated by degradation rate of sulfathiazole, a model antibiotic compound in water, the main parameters identified from our experiments to be essential for the activation efficiency are the design of the cavitation tube, the flow rate of the water stream, and the distance from the discharge to the flow. Our three-dimensional numerical simulations reveal the impact of the tube dimensions on the multiphase flow characteristics. The simplicity of self-suction mechanism allowed us to set up a solar-driven, stand-alone cold plasma system to generate PAW outdoor. The as-prepared PAW can boost the growth rate of bean and peanut sprouts in hydroponics about 80% and 66%, respectively. The portable PAW production may open the door to even broader applications of field activated water for applications in sustainable agriculture and in environment remediation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".