Diffusion in Randomly Overlapping Parallel Pore and Fiber Networks: How Pore Geometry and Surface Mobility Impact Membrane Selectivity
Bibliographic record
Abstract
Pore-resolved computations are undertaken, within a continuum model framework, to explore surface diffusion as a selective mechanism for gas separations using membranes of randomly overlapping parallel cylindrical pores or fibers. Orders of magnitude of the model parameters are established using an intrinsic gas diffusivity that is self-consistent with the Knudsen diffusivity obtained from Monte Carlo simulations reported in the literature. The relative contributions of surface and gas diffusion to the overall permeation show that the surface-diffusion flux increases with the specific surface area, whereas the gas flux increases with porosity. Thus, gas diffusion that is perpendicular to pores and fibers can be hindered by the increasing tortuosity while simultaneously promoting permeation via surface diffusion. The selectivity of pore structures with fibrous networks is examined for the dehumidification of air, natural gas, and carbon dioxide. Selectivities, defined as the ratio of the effective diffusion coefficients for the adsorbed phases (moisture) and the void-diffusing gas (air, natural gas, or carbon dioxide), reveal that selectivity is higher for (i) heavier gases, which have lower gas-diffusion fluxes, and (ii) capillary pores, which have higher surface connectivity than fibers.
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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 | 0.002 | 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 | 0.002 |
| 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".