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Record W2027858148 · doi:10.1016/j.egypro.2011.01.106

Membrane contacting process for CO2 desorption

2011· article· en· W2027858148 on OpenAlexaff
Sakarin Khaisri, David deMontigny, Paitoon Tontiwachwuthikul, Ratana Jiraratananon

Bibliographic record

VenueEnergy Procedia · 2011
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsDesorptionStripping (fiber)MembraneHollow fiber membraneChemistryContactorFlux (metallurgy)Analytical Chemistry (journal)Carbon dioxideChromatographyChemical engineeringMaterials scienceThermodynamicsAdsorptionComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

A membrane contactor based desorption process was developed to strip carbon dioxide (CO 2 ) from loaded monoethalamine (MEA) solution. Nitrogen (N 2 ) gas was used as a stripping gas instead of steam in a conventional column. Polytetrafluoroethylene (PTFE) hollow fiber membranes were used to test the desorption performance. The liquid solution was fed in the lumen while the stripping gas was fed through the shell side. The stripping gas, liquid velocities, operating temperature, and MEA concentration were all investigated for their effect on CO 2 desorption flux. It was found that the CO 2 desorption flux was relatively constant with an increase stripping gas velocity while the liquid velocity, operating temperature, and solution concentration could enhance CO 2 desorption flux in the membrane contactor based desorption process. However, an increase the solution concentration to 5 kmol m 3 resulted in a decrease in the CO 2 desorption flux due to the effect of viscosity.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.213
Teacher spread0.186 · 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

Citations12
Published2011
Admission routes1
Has abstractyes

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