Transient Performance of a Two-Phase Partitioning Bioscrubber Treating a Benzene-Contaminated Gas Stream
Bibliographic record
Abstract
The dynamic performance of a prototype, two-phase partitioning bioscrubber in response to fluctuating benzene waste gas feeds has been characterized through a series of spike, step, and shutdown-restart experiments. From stable operation at a nominal loading capacity of 62 +/- 6 g/(m3 h) and removal efficiencies of over 99%, the bioscrubber was subjected to influent benzene concentration step changes and spikes as high as 10- and 20-fold, respectively. The bioscrubber responded rapidly and effectively to all feed concentration spikes and steps, as well as to step changes in the feed flow rate, maintaining nearly undisturbed performance. Although benzene absorption by the two liquid phases was found to dominate the early stages of each transient, Achromobacter xylosoxidans Y234 responded quickly to prolonged disturbances, readily consuming most of the excess absorbed substrate. The results demonstrate that the two-phase partitioning bioscrubber can rapidly acclimate to and recover from fluctuations, ensuring that stable performance can be maintained both during and aftertransients. The presence of n-hexadecane promotes benzene capture in the two-phase system by increasing the absorption driving force, an important characteristic during high intermittent loadings. Rapid recovery from two different shutdown scenarios further demonstrates the practical potential of the two-phase partitioning bioscrubber as a high-performance biotechnology alternative for the treatment of toxic waste gases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".