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Record W2030177891 · doi:10.1021/ie051368d

Novel Dual-Membrane Gas−Liquid Contactors:  Modelling and Concept Analysis

2006· article· en· W2030177891 on OpenAlexafffund
Shunyu Wang, Kelly Hawboldt, Majid Abedinzadegan Abdi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsContactorMembraneAbsorption (acoustics)ChemistryChromatographyChemical engineeringSolventVolumetric flow ratePermeationAnalytical Chemistry (journal)Porous mediumPorosityMaterials scienceMechanicsThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

Absorption processes have traditionally been used in the removal of contaminants from natural gas. A dual-membrane concept is proposed to improve the performance of membrane gas−liquid contactors. In the proposed configurations, a second membrane was added to a single-membrane system and a sweeping gas or a lower pressure applied on the permeate side of either a porous or nonporous second membrane. Theoretically, the new configurations can partially regenerate the solvent stream simultaneously with the absorption process, and, therefore, better absorption efficiencies can be obtained. The proposed configurations and the ordinary single-membrane contactor were simulated using partial differential equations based on a single-component absorption scheme. The solutions showed that the proposed dual-membrane contactor could remove gas components more efficiently, when compared to the ordinary contactor. A significant improvement in solvent flow rate and regeneration efficiency and, therefore, overall gas purification performance will be achieved using a dual-membrane absorption system.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.050
GPT teacher head0.267
Teacher spread0.217 · 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.

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

Citations5
Published2006
Admission routes2
Has abstractyes

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