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Record W2424701735 · doi:10.1021/acs.iecr.6b00981

Reaction Kinetics of Carbon Dioxide (CO<sub>2</sub>) with Diethylenetriamine and 1-Amino-2-propanol in Nonaqueous Solvents Using Stopped-Flow Technique

2016· article· en· W2424701735 on OpenAlexaff
Nan Zhong, Helei Liu, Xiao Luo, Mohammed J. Al‐Marri, Abdelbaki Benamor, Raphael Idem, Paitoon Tontiwachwuthikul, Zhiwu Liang

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2016
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
FundersChina Scholarship CouncilQatar National Research FundMinistry of Science and Technology of the People's Republic of ChinaMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsDiethylenetriamineChemistryMethanolZwitterionPropanolKineticsAmine gas treatingCarbon dioxideEthanolReaction rate constantReaction mechanismChemical kineticsInorganic chemistryOrganic chemistryCatalysisMolecule

Abstract

fetched live from OpenAlex

In this work, the reaction kinetics of carbon dioxide (CO 2 ) with diethylenetriamine (DETA) and 1-amino-2-propanol (1-AP) in methanol and ethanol systems were measured using the stopped flow technique over a temperature range of 293–313 K in terms of pseudo-first-order rate constant ( k 0 ). Concentration in the range of 10 to 50 mol/m 3 for diethylenetriamine, and 20 to 100 mol/m 3 for 1-amino-2-propanol were studied. The experimental data show that the pseudo-first-order rate constants ( k 0 ) increase with the increase of both amine concentration and temperature. The zwitterion mechanism and the termolecular mechanism were used to represent the data for DETA in methanol and ethanol systems with excellent ADDs of 3.5% and 2.4%, respectively, and 1-AP in methanol and ethanol systems with excellent ADDs of 2.4% and 2.6%, respectively. In comparison with EDA and AEEA in terms of k 2, DETA exhibits a better reaction kinetics performance for capturing CO 2 . Those results will be useful in finding an efficient method for the removal of CO 2 from industrial gases.

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 score0.003
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.044
GPT teacher head0.271
Teacher spread0.227 · 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

Citations37
Published2016
Admission routes1
Has abstractyes

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