Pure and mixed gas permeation study of silica incorporated polyurethane‐urea membrane modified by MOCA chain extender
Bibliographic record
Abstract
Abstract Polyurethane‐urea (PUU) nanocomposite membranes have been prepared using various loadings of silica (SiO 2 ) nanoparticles. A Novel PU was fabricated by a two‐step bulk polymerization technique based on polycaprolactone (PCL), hexamethylene diisocyanate (HDI), and diamine chain extender, 4,4‐methylenebis(2‐chloroaniline) (MOCA). The FTIR spectra indicated that the extent of phase separation reduces with increasing SiO 2 content. The presence of crystal regions in the soft and hard segments was confirmed by DSC and XRD analyses. The obtained results illustrated a decrement in the gases' permeation in the presence of SiO 2 particles. By increasing the filler content up to 15 wt% and pressure of 8 bar, the gas permeation value of the CO 2 , O 2 , and N 2 decreased 36%, 54%, and 59%, respectively. However, the permselectivity of the CO 2 /N 2 and O 2 /N 2 increased considerably, 55% and 13% respectively. On the contrary, by raising the temperature, a dramatic augmentation in the permeability of all gases with a simultaneous reduction in the selectivity values of both gas pairs was revealed. Increasing the pressure led to a decrease in the permeability values of all membranes for O 2 and N 2 , whereas the permeability for CO 2 increased with the pressure. Nevertheless, the selectivity values for the pair of gases increased (at a pressure of 10 bar, 1.66 and 1.17 times the neat PU for CO 2 /N 2 and O 2 /N 2 , respectively). Furthermore, the permeability of the CO 2 , O 2 , and N 2 for the mixed gases was smaller than for pure ones at the same gas upstream pressure. Nonetheless, like the pure gas, the selectivity of both pair gases increased.
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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".