Continuous removal of ethanol from dilute ethanol-water mixtures using hot microbubbles
Bibliographic record
Abstract
Product inhibition is a barrier to many fermentation processes, including bioethanol production, and is responsible for dilute product streams which are energy intensive to purify. The main purpose of this study was to investigate whether hot microbubble stripping could be used to remove ethanol continuously from dilute ethanol–water mixtures expected in a bioreactor and maintain ethanol concentrations below the inhibitory levels for the thermophile Parageobacillus thermoglucosidasius (TM242), that can utilize a range of sugars derived from lignocellulosic biomass. A custom-made microbubble stripping unit that produces clouds of hot microbubbles (~120 °C) by fluidic oscillation was used to remove ethanol from ~2% (v/v) ethanol–water mixtures maintained at 60 °C. Ethanol was continuously added to the unit to simulate microbial metabolism. The initial liquid height and the ethanol addition rate were varied from 10 to 50 mm and 2.1–21.2 g h−1 respectively. In all the experiments, ethanol concentration was maintained well below the inhibition threshold of the target organism (~2% [v/v]). This microbubble stripping unit has the potential to operate in conjunction with a 0.5–1.0 L fermenter to allow an ethanol productivity of 14.9–7.8 g L−1h−1 continuously.
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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 | 0.001 |
| 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".