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Record W2178562267 · doi:10.1002/aic.15073

Experimental study on the solvent regeneration of a CO<sub>2</sub>‐loaded MEA solution using single and hybrid solid acid catalysts

2015· article· en· W2178562267 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIChE Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
FundersNational Natural Science Foundation of China
KeywordsCatalysisChemistrySolventMesoporous materialLewis acids and basesStripping (fiber)Nuclear chemistryChemical engineeringMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The performance of a hybrid solid acid catalyst consisting of a physical mixture of γ‐Al 2 O 3 and H‐ZSM‐5 in terms of the rate and heat duty for solvent regeneration (i.e., CO 2 stripping) of a CO 2 ‐rich MEA solution was compared with the individual performance of γ‐Al 2 O 3 , H‐ZSM‐5, and H‐Y solid acid catalysts using MEA (2–7 mol/L), with initial CO 2 loading of 0.5 mol CO 2 /mol MEA at 378 K. It was observed that any catalyst significantly decreased the energy required for CO 2 regeneration. The performance of the catalysts investigated ranked as follows: γ‐Al 2 O 3 /H‐ZSM‐5 = 2/1 &gt; γ‐Al 2 O 3 &gt; H‐ZSM‐5 &gt; H‐Y if the process is in the lean CO 2 loading region whereas it was H‐ZSM‐5 &gt; γ‐Al 2 O 3 /H‐ZSM‐5 = 2/1 &gt; γ‐Al 2 O 3 &gt; H‐Y if the process is in the rich CO 2 loading region. These results highlight the joint dependence on Brønsted/Lewis acidity and mesopore surface area of heat duty for solvent regeneration. © 2015 American Institute of Chemical Engineers AIChE J , 62: 753–765, 2016

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.

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)0.000
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 score0.004
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.051
GPT teacher head0.266
Teacher spread0.214 · 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