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Record W2076218110 · doi:10.1002/cjce.22210

Modelling and Experimental Study of Membrane Wetting in Microporous Hollow Fiber Membrane Contactors

2015· article· en· W2076218110 on OpenAlexvenueno aff
Liyun Cui, Zhongwei Ding, Liying Liu, Yunpeng Li

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsHollow fiber membraneWettingMembraneMaterials sciencePolyvinylidene fluorideMicroporous materialContactorFiberRotating biological contactorChemical engineeringPolypropyleneAbsorption (acoustics)Composite materialChromatographyChemistryThermodynamicsEnvironmental engineeringPolymerEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

A kinetic model has been developed to predict the distribution of wetness along a hollow fiber and the average wetness as a function of time in hollow fiber membrane (HFM) contactors. The membrane absorption experiments were conducted using the diethanolamine (DEA) solution as absorbent to absorb CO 2 in polyvinylidene fluoride (PVDF) and polypropylene (PP) HFM contactors. The influences of operating conditions (such as solution concentration, temperature, liquid and gas flow rates) on the membrane wetting process in a HFM contactor were also investigated in experiments. The experimental data were fitted to the proposed kinetic equations. The fitting results indicate that the proposed kinetic equation successfully described the membrane wetting process and prove that the membrane wetting rate was controlled by the solute adsorption on the bare pore wall. Therefore, this model may provide support for the design of membrane contactors suffering from membrane wetting.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.563

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 head0.014
GPT teacher head0.195
Teacher spread0.180 · 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 designBench or experimental
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

Citations11
Published2015
Admission routes1
Has abstractyes

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