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Record W1988404355 · doi:10.1021/ie900540v

Comparative Mass Transfer Performance Studies of CO<sub>2</sub> Absorption into Aqueous Solutions of DEAB and MEA

2010· article· en· W1988404355 on OpenAlexafffund
Kreangkrai Maneeintr, Raphael Idem, Paitoon Tontiwachwuthikul, Andrew G. H. Wee

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2010
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMass transferMass transfer coefficientChemistryStructured packingAbsorption (acoustics)Aqueous solutionSolubilityVolumetric flow rateSolventAnalytical Chemistry (journal)Inert gasChromatographyThermodynamicsMaterials sciencePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The mass transfer performance of the absorption of CO 2 in an aqueous solution of a new amino alcohol, 4-diethylamino-2-butanol (DEAB), which has been developed as an effective postcombustion CO 2 capture solvent, was investigated and compared with the performance of CO 2 absorption in a conventional amine, MEA. The absorption experiments were conducted in an absorption column containing structured packing, whereas the absorption performance was evaluated in terms of the overall mass transfer coefficient, K G a v . In particular, the effects of parameters such as inert gas flow rate, liquid flow rate, and solution concentration were compared for both DEAB and MEA. The results show that K G a v increases as both the liquid flow rate and concentration of solution increase whereas inert gas flow rate has little or no effect on K G a v . An empirical correlation for the mass transfer coefficient for the CO 2 -DEAB system has been developed as a function of the process parameters. In terms of comparison, the results show that the mass transfer performance of MEA was greater than that of DEAB. However, with the extremely high solubility and ease of regeneration of DEAB based on our previous study, it may be extremely beneficial to formulate an absorption solvent involving both MEA and DEAB in order to take advantage of the synergy effects of high solubility, ease of regeneration as well as the high mass transfer performance of the mixture.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.101
GPT teacher head0.321
Teacher spread0.220 · 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

Citations61
Published2010
Admission routes2
Has abstractyes

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