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Record W4283378834 · doi:10.1002/aic.17816

Comprehensive reaction kinetics model of <scp>CO<sub>2</sub></scp> absorption into 1‐dimethylamino‐2‐propanol solution

2022· article· en· W4283378834 on OpenAlexafffund
Helei Liu, Xiaotong Jiang, Raphael Idem, Shoulong Dong, Paitoon Tontiwachwuthikul

Bibliographic record

VenueAIChE Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of ReginaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaBeijing Institute of Technology
KeywordsKineticsAbsorption (acoustics)ChemistryPropanolAmine gas treatingChemical kineticsWork (physics)ThermodynamicsLaminar flowReaction rateAnalytical Chemistry (journal)Materials scienceCatalysisOrganic chemistryMethanolPhysics

Abstract

fetched live from OpenAlex

Abstract In the present work, the kinetics of the reactive absorption of CO 2 in 1‐dimethylamino‐2‐propanol (1DMA2P) solution were experimentally measured using a laminar jet absorber over a temperature range of 298–313 K, 1DMA2P concentration range of 0.5–2.0 mol/L, and CO 2 loading range of 0–0.06 mol CO 2 /mol amine. The measured kinetics data were then used to develop a comprehensive numerical kinetics model using a FEM‐based COMSOL software. The reaction rate model of the CO 2 absorption into 1DMA2P solution were then validated by comparing model rates with the experimental rates. An excellent agreement of model data with experimental data was achieved with an absolute average deviation (AAD) of 6.5%. In addition, vapor–liquid equilibrium plots of all ions in the 1DMA2P‐H 2 O‐CO 2 system were also developed. Further, this work has provided an effective criterion for evaluating CO 2 absorption, that can be used for both the conventional amines and alternative amines for the purpose of providing guidelines or information on how to effectively screen solvents.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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

Citations53
Published2022
Admission routes2
Has abstractyes

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