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Record W1999588809 · doi:10.4155/cmt.11.55

Part 2: Solvent management: solvent stability and amine degradation in CO<sub>2</sub>capture processes

2011· article· en· W1999588809 on OpenAlexaff
Teeradet Supap, Chintana Saiwan, Raphael Idem, Paitoon Tontiwachwuthikul

Bibliographic record

VenueCarbon Management · 2011
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsFlue gasAmine gas treatingDegradation (telecommunications)SolventNOxDecompositionChemistrySulfurNitrogen oxideAbsorption (acoustics)NitrogenChemical engineeringEnvironmental chemistryWaste managementInorganic chemistryEnvironmental scienceMaterials scienceOrganic chemistryCombustionComputer science

Abstract

fetched live from OpenAlex

Solvent stability in CO2 capture from industrial flue gases is one of the most significant parameters that needs to be closely monitored to maintain the highest efficiency in the carbon CO2 absorption operation. Amines used in the capture process are known to degrade, resulting in the most serious degree of solvent loss in CO2 capture from flue gases. Reactive constituents in flue gas, specifically O2, SO2, nitrogen oxides (NOx) and inorganic oxide fly ash, competitively react with amines, leading to irreversible decomposition of amine into various degradation products. Because of degradation, the absorption efficiency deteriorates and corrosion problems occur. In this article, we review research activities in amine degradation from past to present for CO2 and sulfur compound-induced degradation. Research conducted on oxidative degradation of amines before and after 2000 is also reviewed, including our works undertaken at the International Test Centre for CO2 Capture and works by other researchers.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.198
Teacher spread0.179 · 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 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

Citations31
Published2011
Admission routes1
Has abstractyes

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