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Record W2569492725 · doi:10.1021/acs.iecr.6b04498

Kinetic Behavior of Solid K<sub>2</sub>CO<sub>3</sub> under Postcombustion CO<sub>2</sub> Capture Conditions

2017· article· en· W2569492725 on OpenAlexafffund
Abhimanyu Jayakumar, Arturo Gomez, Nader Mahinpey

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2017
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbonationFlue gasChemistryAdsorptionChemical reactionChemisorptionThermodynamicsChemical kineticsChemical engineeringKinetic energyReaction rateAnalytical Chemistry (journal)KineticsPhysical chemistryCatalysisEnvironmental chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Trends in CO 2 and H 2 O uptakes by solid K 2 CO 3 were studied at different carbonation temperatures and flue gas compositions over 50 consecutive regeneration–carbonation cycles. Differences in carbonation behavior between the initial and final cycles evidence changes in the phase composition of K 2 CO 3 during cycling, which stabilize in accordance with the operating conditions. Rates of carbonation and hydration were observed to decrease at higher temperatures, indicating that the forward reactions are limited by adsorption, not chemical reaction. Multiple regression analysis of the uptake data yielded negative apparent activation energies for both forward reactions modeled as simple chemical reactions, thus proving the assumption invalid. A proposed Langmuir–Hinshelwood model yielded consistent apparent activation energies for the forward reactions, showing that adsorption limitations are significant in this chemisorption process. Important process design considerations, for realizing high carbonation rates and selecting promising support materials to enhance the CO 2 capture capacity of K 2 CO 3, are also discussed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
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 score0.032
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.004
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 head0.052
GPT teacher head0.317
Teacher spread0.265 · 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; both teacher heads agree on what is shown here.

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

Citations19
Published2017
Admission routes2
Has abstractyes

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