Membrane Characterization Based on the Upstream Pressure Decay in a Dynamic Gas Permeation Test
Bibliographic record
Abstract
The time-lag method is believed to be the most usable method for extracting the membrane properties via a simple dynamic permeation experiment; however this method suffers from major drawbacks that limit its use for some materials and under certain conditions.One of the major drawbacks of the time-lag method is that it relies on monitoring the pressure rise downstream from the membrane due to gas permeation, whereas the method is derived by assuming that the pressure downstream from the membrane is maintained at zero during the entire permeation experiment.To rectify this problem, it is proposed to characterize the membrane based on the pressure decay upstream from the membrane during a conventional time-lag experiment, while continuously evacuating the downstream side of the membrane.This modification allows for a better adherence to the boundary conditions on which the time-lag method relies.Right after initiation of the gas permeation experiment, the membrane behaves as a semi-infinite solid, and the rate of pressure decay is directly proportional to the square root of time.Once the permeating gases emerge downstream from the membrane, the membrane no longer behaves as a semi-infinite solid and the pressure decay becomes a non-linear function of the square root of time.In the proposed new method, the membrane properties are extracted based on the deviation of the recorded pressure decay from the semi-infinite behavior in the square root of the time domain.In this paper, we present the mathematical bases of the new method along with preliminary experimental results.Results indicate that diffusivity, solubility and permeability of nitrogen in polyphenylene oxide (PPO) membrane used in this study are very close to the literature values.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".