Recovery of Volatile Aroma Compounds by Membranes
Bibliographic record
Abstract
This research investigates the potential application of poly(ether block amide) (PEBA) membranes for the separation of volatile aroma compounds from wine and the effect of non-volatile components on the separation performance using the pervaporation process. \nThe study examined the selective retrieval of two aroma compounds (4-ethyl guaiacol and 4-ethyl phenol) from binary dilute aqueous solutions through pervaporation utilizing the PEBA 2533 membrane. It was observed that this membrane effectively recovers hydrophobic aroma compounds. The influence of feed concentration and temperature on aroma recovery was also analyzed. The performance of PEBA 2533 for aroma recovery was assessed, and experimental data were analyzed using a batch pervaporation model. \nIt was discovered that both the flux of aroma compounds and their selectivity were notably influenced by the concentration of aroma compounds in the feed. The permeation flux and their selectivity in separating the volatile aroma compound in a binary solution followed the sequence of 4-ethyl phenol > 4-ethyl guaiacol, showing an inverse relationship with their molecular size. Generally, the permeation flux of aroma was found to be directly proportional to the concentration of aroma compounds in the solution within the tested concentration range (10-110 ppm). The impact of temperature on permeation flux followed an Arrhenius-type relationship and 4-EG with larger molecular size showed higher apparent activation energy than 4-EP and water. \nIt was observed that the recovery of 4-Ethyl guaiacol from its dilute aqueous solution was affected by non-volatile wine components (sugar, yeast, and salt) and alcohol. Specifically, the presence of glucose as a model sugar and NaCl as a model salt in the feed solution did not notably affect the pervaporative performance of 4-EG, maybe because of their low contents in the feed mixture and low interactions with aroma. The addition of agar initially increased the permeate flux of 4-EG due to its insolubility and ability to absorb water molecules, boosting the concentration of 4-EG and enhancing the driving force. However, at higher agar concentrations, precipitation formed a thick layer of swollen agar in the tank, trapping 4-EG molecules and reducing their concentration in the solution. This led to a peak flux followed by a decline, reaching a maximum turning point at a specific agar concentration. Finally, the presence of ethanol as a model alcohol in the binary solution of 4-ethyl guaiacol was found to significantly reduce the permeation of 4-ethyl guaiacol. However, the total flux of the mixture considerably increased. The presence of ethanol affected the partitioning and activity coefficients of the components in the mixture as well as membrane swelling and plasticization, which ultimately affected the solubility and diffusivity properties of the membrane.
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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) | 0.001 | 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 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".