PDMS coated asymmetric PES membrane for natural gas sweetening: Effect of preparation and operating parameters on performance
Bibliographic record
Abstract
The present study is an attempt to investigate the effects of preparation and operation parameters on ideal and real selectivity of polydimethylsiloxane (PDMS) coated asymmetric polyethersulfone (PES) membranes for natural gas sweetening. Scanning electron microscopy (SEM) was used to study the effect of PES concentration and solvent type on membrane morphology. The effects of operating parameters on the performance of membranes were investigated by using binary CO 2 /CH 4 , H 2 S/CH 4 and ternary H 2 S/CO 2 /CH 4 gas mixtures. Higher concentrations of PES and a higher sequential coating number increase CO 2 /CH 4 selectivity and decrease CO 2 permeance. As a notable and interesting result, the membrane exhibits rubbery PDMS behaviour for H 2 S containing feeds and displays a glassy PES membrane for CO 2 /CH 4 mixed gas. An increase in the feed pressure decreases CO 2 and CH 4 permeance and increases CO 2 /CH 4 selectivity for CO 2 /CH 4 feed. For H 2 S/CH 4 and H 2 S/CO 2 /CH 4 mixed gas, enhancing the feed pressure results in higher CH 4 and lower CO 2 and H 2 S permeance and a declined CO 2 /CH 4 and H 2 S/CH 4 selectivity. Increasing temperature in binary CO 2 /CH 4 enhances CO 2 and CH 4 permeance and decreases CO 2 /CH 4 selectivity. Increasing the temperature increases CH 4 permeance and decreases H 2 S permeance for binary H 2 S/CH 4 mixture. For ternary mixture, increasing the temperature leads to a higher permeance for CO 2 and H 2 S and a lower CH 4 permeance. For binary CO 2 /CH 4 , a higher CO 2 concentration increases the membrane gas permeance and decreases CO 2 /CH 4 selectivity. Increasing the H 2 S concentration in the feed results in a reduction in gas pressure normalised flux of gases in ternary gas feed because of an increase in Flory–Huggins interaction parameter.
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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".