Enhancement of <scp>VOCs</scp> removal using a novel double‐tube packed bed catalytic dielectric barrier discharge ( <scp>DPDBD</scp> ) reactor
Bibliographic record
Abstract
Abstract We developed a novel double‐tube packed bed catalytic dielectric barrier discharge (DPDBD) reactor to degrade toluene. The DPDBD reactor contains four discharge cells with one power supply, namely, A–D. NiO/γ‐Al 2 O 3 is packed in cell A to effectively destroy the branched chains in toluene. TiO 2 /γ‐Al 2 O 3 is packed in cell B owing to its high catalytic oxidation activity to weaken the benzene rings and mineralize the generated partial aromatic compounds. Cell C is a pure DBD process without any catalyst packed to thoroughly mineralize all the generated aromatic compounds and convert CO into CO 2 and NO into NO 2 . γ‐Al 2 O 3 is packed in cell D to reduce the concentrations of byproducts, including O 3 and NO generated by air through oxidation. The combinations of the four discharge cells are optimized by the treatment of −3000 mg m −3 of toluene at 11 kV. In comparison with a double‐tube dielectric barrier discharge (DDBD) reactor without catalyst packing and with a total discharge length of 6 cm, the selectivity of CO 2 was significantly improved from 45% to 57% when the discharge lengths of A, B, C, and D are 2, 4, 4, and 2 cm, respectively. Furthermore, the concentrations of O 3 and NO in the outlet can also be effectively reduced from 2.80 and 210 mg m −3 to 1.30 and 60 mg m −3 , respectively. We also investigated the effects of applied voltage and styrene initial concentration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".