MétaCan
Menu
Back to cohort
Record W2786622099 · doi:10.1021/acs.iecr.7b04654

Reaction Kinetics of Carbon Dioxide with 2-Amino-1-butanol in Aqueous Solutions Using a Stopped-Flow Technique

2018· article· en· W2786622099 on OpenAlexaff
Abdelbaki Benamor, Nafis Mahmud, Mustafa S. Nasser, Paitoon Tontiwachwuthikul

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2018
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
FundersQatar Foundation
KeywordsZwitterionDiethanolamineChemistryKineticsCarbon dioxideReaction rate constantAmine gas treatingAqueous solutionActivation energyChemical kineticsThermodynamicsPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Carbon capture and management plays an important role in the development of new technologies to mitigate anthropogenic global warming. In this work, for the first time, the kinetics of CO 2 with aminobutanol (AB) using a stopped-flow method are presented. The temperature changed from 293 to 313 K for a total amine concentration up to 0.3 mol/L. The kinetics data were analyzed using both zwitterion and termolecular reaction mechanisms with a preference to the zwitterion mechanism. AB was found to react with CO 2 (aq) with k 2 (M –1 s –1 ) = 2.93 × 10 9 exp(−4029.9/ T (K)) with an estimated activation energy of 33.51 kJ/mol. Compared to other popular amines, CO 2 reaction with aminobutanol has faster kinetics than that of CO 2 with diethanolamine (DEA) and 2-amino-2-methyl-1-propanol (AMP) but slower than that with monoethanolamine (MEA). The Brønsted relationship between the rate constant ( k 2 ) and p K a values was found to predict well the rate constant with an average absolute deviation (AAD) of 6.1%.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.072
GPT teacher head0.291
Teacher spread0.219 · 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.

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

Citations11
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicCarbon Dioxide Capture TechnologiesFrench-language works237,207