Experimental Investigation of Pervaporation Membranes for Biobutanol Separation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it