Effectiveness of Hydrogen Peroxide in H2S Removal by a Packed High Specific Surface Area Bed Scrubber
Bibliographic record
Abstract
Removal of H 2 S from waste air streams was investigated in a chemical scrubber packed with new low-cost and high specific surface area media and in the presence of H 2 O 2 in scrubbing liquid.The experimental conditions included superficial gas velocities of n = 500 and n = 840 m h -1 , inlet H 2 S volume fraction in the range of j = 50 to 250 • 10 -6 , scrubbing liquid flow rate ranging from Q L = 1 to 10 L min -1 and liquid phase pH of 7 to 12.The results showed H 2 S removal efficiencies of h = 97.5 % to more than h = 99 % at liquid flow rate of Q L = 5 L min -1 and pH of 10 to 11.Overall, it was determined that the media tested and H 2 O 2 can be used in scrubbers for efficient H 2 S removal without the possibility of forming any toxic byproducts.
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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) | 0.001 | 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".