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Record W2057411693 · doi:10.1002/cjce.5450810336

On the Numerical Modeling of Gas Absorption into Reactive Liquids in a Laminar Jet Absorber

2003· article· en· W2057411693 on OpenAlexafffundvenue
Ahmed Aboudheir, Paitoon Tontiwachwuthikul, A. Chakma, Raphael Idem

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of WaterlooUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKineticsAbsorption (acoustics)Laminar flowChemical kineticsMass transferKinetic energyThermodynamicsChemistryReaction rateChemical reactionJet (fluid)Rate equationMaterials sciencePhysicsOrganic chemistryClassical mechanicsCatalysis

Abstract

fetched live from OpenAlex

Abstract A comprehensive numerically solved absorption‐rate/ kinetics model that takes into account the coupling between chemical equilibrium, mass transfer, and the chemical kinetics of all the possible chemical reactions involved was developed for the absorption of a gas into a reactive liquid. Also, absorption rate measurements to determine the kinetics of the process were obtained in a laminar jet absorber and used to validate this new model. The results show that the model used in conjunction with our numerical method is capable of predicting the gas absorption rates, enhancement factors, and the kinetics of the reaction. Also the model predicted kinetic data for the absorption of CO2 into monoethanolamine (MEA) solutions that were found to be in accordance with published kinetic data. These results show that the developed numerically solved absorption‐rate/kinetics model is both accurate and efficient.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.181
Teacher spread0.173 · 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 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

Citations12
Published2003
Admission routes3
Has abstractyes

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