Modelling in mixed matrix membranes for gas separation
Bibliographic record
Abstract
Various gas permeation models including Maxwell model, Bruggeman model, Lewis‐Nielson model and Pal model were compared via a modelling approach with the relative permeance of CO 2 against published experimental data on silica filled polysulfone/polyimide (PSF/PI) mixed matrix membranes (MMMs). However, none of the tested models were able to predict the data with good accurately. A closer look at the cross‐sectional image by scanning electron microscopy (SEM) indicated that the fillers were actually prolate ellipsoids dispersed within the matrix. Maxwell‐Wagner‐Sillar model was then employed to investigate the prolate effect and it was observed that the optimization curves of maximum packing ( φ m ) and shape factor (n) showed least deviations. The percentage average absolute relative error (AARE %) value for fitted shape factor (n f ) was found to be in the range of 1.12–2.17 at 2–10 bar pressure which showed its robustness. A further evaluation from SEM image showed that the shape factor along z‐direction (n z ) displayed a minimum deviation of 17.52 % for prolates at 0.102 ± 0.01. By using n z as upper limit and estimated shape factor n e through generalization, the error was reduced to 6.01 %. The AAR % deviation was found in the order of n f <n e < n z, which indicated the importance of shape factor parameter for estimating true CO 2 permeance.
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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".