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Record W34012692 · doi:10.5006/c2007-07396

Inhibition Performance of Copper Carbonate in CO2 Absorption Process Using Aqueous MEA

2007· article· en· W34012692 on OpenAlexaff
Immanuel Raj Soosaiprakasam, Amornvadee Veawab

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCopperAqueous solutionCarbonateAbsorption (acoustics)Materials scienceProcess (computing)Inorganic chemistryMetallurgyChemistryComposite materialComputer science

Abstract

fetched live from OpenAlex

Abstract This work investigated the inhibition performance of copper carbonate (CuCO3) which is less-toxic than conventional heavy-metal corrosion inhibitors in the CO2 absorption process using amine solutions. The investigation was experimentally carried out in an electrochemical cell containing an aqueous solution of 5 kmol/m3 monoethanolamine (MEA) loaded with 0.20 mol/mol CO2 loading at 40 and 80°C. The inhibition performance was examined as a function of process parameters including inhibitor concentration, the presence of dissolved oxygen, solution velocity, solution temperature, CO2 loading and the presence of heat-stable salts. The results show that CuCO3 functions as an anodic inhibitor forming passive film to inhibit the corrosion. It performs well in most tested environments. However, the absence of oxygen may cause copper to plate out, leading to pitting.

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)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.011
GPT teacher head0.225
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

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

Citations2
Published2007
Admission routes1
Has abstractyes

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