Incorporating ethylene glycol into hydrophilic poly(ether‐b‐amide) membranes for enhanced gas dehumidification performance
Bibliographic record
Abstract
Abstract In the present study, ethylene glycol (EG) was incorporated into hydrophilic poly(ether‐b‐amide) matrix membranes to enhance the membrane performance for gas dehumidification (e.g., H 2 O/N 2 , H 2 O/CH 4 , and H 2 O/CO 2 separations). Exploiting EG as a hygroscopic agent, enhanced water vapour permeability was achieved. This study was also expanded to evaluate potential CO 2 capture (i.e., CO 2 /N 2 and CO 2 /CH 4 separations) using the membranes. As high as 20 wt.% of EG could be incorporated into the membrane to enhance water vapour permeability without compromising the membrane stability. The membranes were characterized using contact angle measurements, Fourier transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), and thermogravimetric analysis (TGA). The water vapour permeability of the membrane was shown to increase exponentially with an increase in temperature and water vapour concentration in the feed. However, the membrane selectivity was compromised at higher temperatures for the gas pairs of interest, and the adverse impact of temperature on the membrane selectivity was lessened by the presence of EG in the membrane. The membrane stability for gas dehydration was demonstrated, and the membrane performance was shown to be largely constant over a testing period of 28 days when subjected to continuous separation of water vapour from humidified nitrogen.
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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".