Understanding membrane selectivity in pervaporation of water‐rich water:ethanol mixtures
Bibliographic record
Abstract
Abstract In pervaporation, membrane selectivity is defined as the ratio of the ratios of two components of a liquid:liquid mixture in the permeate and in the feed. In a thermodynamically‐controlled system, this value will be the same as the difference between vapour and liquid composition in the absence of a membrane. We demonstrate this to be the case for water:ethanol pervaporation at high water:ethanol ratios both for an unmodified polydimethylsiloxane membrane and for a membrane modified by grafting a layer of hydrophilic polyacrylamide. We observe transient kinetic deviations toward greater selectivity on addition of salts which push the thermodynamic vapour pressure equilibrium towards ethanol, and to a more significant degree with grafting of polyacrylamide to the hydrophobic membrane, suggesting that these modifications retard the flow of water through the membrane. The physical plausibility of the chemical potential gradient used in interpretation of pervaporation data by the solution‐diffusion model is critiqued.
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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) | 0.000 | 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".