Optimization of an atmospheric pressure direct-contact DBD for the treatment of aqueous pharmaceutical solutions
Bibliographic record
Abstract
Summary form only given. Ozone has been widely used in water treatment due to its extreme reactivity and its strong oxidizing properties. Technologies using electrical discharges generated directly over or in the fluid to be treated are being studied because they may prove to be cheap and effective. In this research project, a hybrid gas-liquid atmospheric pressure dielectric barrier discharge (DBD) reactor has been designed and used to treat pharmaceutical solutions. The liquid is sandwiched inside a parallel plate DBD and thus, directly exposed to the plasma-forming region. Oxygen or air flows above the liquid to be treated. The application of 10 kV on the high voltage electrode, at an average frequency of 17.5 kHz, induces plasma streamers in the gas phase. The power dissipated in the DBD (50 W on average) is monitored from the measure of the Lissajou figure. It is believed that the transport of ozone generated in the gaseous gap into the liquid solution is enhanced by the agitation of the free surface, itself induced by the streamers. The formation of additional oxidizers in the liquid solution such as hydroxyl radicals and hydrogen peroxide is also suspected. The effects of treatment time (1-15 minutes), discharge gap (3-4 mm), gas flow rate (20-400 cc/min), composition of the gas (pure oxygen or air) is being investigated to determine the optimum parameters for the treatment of aqueous pharmaceutical solutions. The optimization is being performed by monitoring the absorbance at 600 nm of solutions in which potassium indigo trisulfonate is diluted. This molecule dyes water in blue due to its C=C bond which can be broken by oxidation, resulting in the decrease in absorbance of the solution at 600 nm. The DBD reactor is more efficient with oxygen than with air; the difference in color removal is 30% when comparing the results obtained with an oxygen flow of 160 cc/min to an air flow of 160 cc/min after a treatment time of 7 minutes and with a discharge gap of 3.9 mm. It is also found that the extent of color removal increases with treatment time; color removal is 93% after 7 minutes compared to 47% after 3 minutes with an oxygen flow of 25 cc/min and a discharge gap of 3.9 mm. The optimum values for the operating parameters will be used to degrade sulfamethoxazole, an antibiotic, in water. The results will be compared to those of collaborators obtained using conventional degradation procedures
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".