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Record W2020070461 · doi:10.1002/cjce.21960

Pore network simulation for diffusion through a porous membrane: A comparison between Knudsen and Oscillator models

2013· article· en· W2020070461 on OpenAlexvenueno aff
Hadi Adloo, Mohsen Nasr Esfahany, Mohammad Reza Ehsani

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsnot available
FundersUniversity of Queensland
KeywordsKnudsen numberKnudsen diffusionMembraneThermal diffusivityPorosityDiffusionMaterials sciencePermeability (electromagnetism)Molecular dynamicsMonte Carlo methodPermeationActivation energyThermodynamicsChemistryPhysical chemistryComputational chemistryPhysicsComposite material

Abstract

fetched live from OpenAlex

Low density permeations of some gases (He, H 2 , N 2 , CH 4 , CO 2 and CF 4 ) through micro‐ and mesocarboneous pores were investigated using Knudsen and Oscillator models. Lennard‐Jones model in single layer pores was used to simulate the gas–solid interactions in the Oscillator model. The effects of the pore radius as well as the molecular size and the temperature on the pore diffusivity and the activation energy were studied. The Monte Carlo simulation was then performed to calculate the permeability of these gases in three‐dimensional cubic networks of different connectivities (2.5–6) and different pore size distributions ( r a = 2.74 and 6.95 nm). It was shown that for networks with larger pores there is a minor difference between the two models, while a large discrepancy exists in networks with fine pores. Both models tend to have the same permeability as the coordination number decreases. To investigate the accuracy of the models, the simulation results were compared with the experimental selectivities of some pure gases in two different membranes extracted from the literature. It was shown that the Oscillator model can better predict the experimental data in the membranes of smaller pores (i.e. r a = 2.74 nm). However, both models were comparable in membranes of larger pores ( r a = 6.95 nm). The capability of the models to predict the activation energy of the diffusion was also studied.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.223
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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