Enhanced scrubbing of chlorinated compounds from air streams
Bibliographic record
Abstract
Abstract This paper addresses an investigation of mass transfer issues associated with an innovative hybrid process to treat air streams containing chlorinated organics. Three target compounds [dichloromethane (DCM), carbon tetrachloride (CT) and tetra chloroethylene (PCE)] we re evaluated to assess a range of chemical and physical properties. Vegetable oil was found to be an effective scrubbing solution in removing the target compounds from the air streams and was employed in continuous flow tests of a bench‐scale countercurrent packed co lumn. Removal efficiencies approached 90% for all three target compounds with gas‐liquid flow ratios less than 200. A gas‐liquid mass transfer model was developed and compared to the existing Onda correlations, to characterize mass transfer under various operating conditions when water and vegetable oil were employed as scrubbing solutions. It was found that the Onda correlations did not fit the experimental data of vegetable oil very well. The existing Onda correlations we re modified by assuming that the gas phase resistance was controlling mass transfer. In order to enhance mass transfer from the oil phase to an aqueous phase a liquid‐liquid contacting reactor was proposed. The results of the liquid‐liquid reactor suggested that mass transfer could be achieved for compounds that were not highly hydrophobic.
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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) | 0.015 | 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; both teacher heads agree on what is shown here.
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".