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Record W2033255110 · doi:10.1021/ie040264k

Comparing the Absorption Performance of Packed Columns and Membrane Contactors

2005· article· en· W2033255110 on OpenAlexafffund
David deMontigny, Paitoon Tontiwachwuthikul, A. Chakma

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of ReginaUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPacked bedMicroporous materialAbsorption (acoustics)PolypropyleneMembraneChemical engineeringMass transferMaterials scienceCarbon dioxideChemistryChromatographyAnalytical Chemistry (journal)Composite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Several technologies have been developed for capturing carbon dioxide (CO 2 ), but absorption remains the most suitable method for large-scale industrial operations. In recent years the use of gas absorption membrane (GAM) systems has been explored as an alternative to traditional packed columns. This paper evaluates the performance of a GAM system and a packed column using the overall mass transfer coefficient ( K G a v ) as a basis for comparison. The GAM system tested microporous polypropylene (PP) and poly(tetrafluoroethylene) (PTFE) hollow fiber membranes while the packed column contained Sulzer DX structured packing. Aqueous solutions of monoethanolamine (MEA) and 2-amino-2-methyl-1-propanol (AMP) were used in both absorbers. Experimental results showed that the GAM system performed better than the packed column. GAM systems deserve the attention they have been receiving from researchers as they have significant potential to replace packed columns.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.067
GPT teacher head0.269
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations177
Published2005
Admission routes2
Has abstractyes

Explore more

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