Experimental Investigation of Pervaporation Membranes for Biobutanol Separation
Bibliographic record
Abstract
Biotechnological production of chemical building blocks is one important step towards a more sustainable production. Unfortunately, the products to be separated are often highly diluted. Pervaporation has received increasing attention for the separation of small amounts of organic compounds from aqueous solutions, especially in the separation of butanol from water or from fermentation broth. To evaluate the potential of pervaporation for biobutanol recovery a consistent database is required, describing the dependency of permeate fluxes and selectivities on process variables like temperature, permeate pressure as well as feed concentrations and compositions. Therefore, within this work we investigated the separation behaviour of a commercially available polydimethylsiloxane (PDMS) membrane and membranes based on poly(ether block amide) (PEBA) fabricated in our own laboratory. The membranes were tested under varying operating conditions. Fermentation by-products or impurities may affect the pervaporation separation performance. Therefore, in addition, the permeate fluxes and the influence of acetone, ethanol, acetic and butyric acid and 1,3-propanediol have been investigated in detail as well. Several differences in the permeability and selectivity of PDMS and PEBA were observed during the experimental study. Swelling experiments were applied to further analyse the separation behaviour of PDMS and PEBA more in detail. Finally the influence of the observed separation performances on the overall butanol pervaporation process is discussed. It was found that especially well permeating by-products like acetone can drastically influence the subsequent downstreaming process.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".