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Record W2326290409 · doi:10.1021/ie401816w

Prospects of Using Room-Temperature Ionic Liquids as Corrosion Inhibitors in Aqueous Ethanolamine-Based CO<sub>2</sub> Capture Solvents

2013· article· en· W2326290409 on OpenAlexafffund
Muhammad Hasib‐ur‐Rahman, Faı̈çal Larachi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsUniversité Laval
FundersCanada Research Chairs
KeywordsIonic liquidAlkanolamineCorrosionTafel equationAqueous solutionElectrochemistryMaterials scienceInorganic chemistryEthanolamineChemistryChemical engineeringOrganic chemistryMetallurgyCatalysisPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

Corrosion is one of the major concerns being encountered in aqueous alkanolamine-based CO 2 capture processes. The present work examines the capability of thermally stable and virtually nonvolatile room-temperature ionic liquids (RTILs) to curb corrosion in aqueous monoethanolamine solvents. Four imidazolium-based RTILs with ethyl side chains were chosen for this purpose: [emim][Otf], [emim][DCA], [emim][acetate], and [emim][tosylate]. Carbon steel 1020 has been used as a test material, since it is widely used as construction material in industrial installations. Electrochemical corrosion experiments were carried out using the linear polarization resistance (LPR) technique for measuring corrosion current thus enabling subsequent calculation of corrosion rate via the Tafel fit method. The outcomes illustrate that, out of the tested ionic liquids, [emim][acetate] is the most capable of rectifying the severe operational problem of corrosion in alkanolamine-based state-of-the-art CO 2 capture systems.

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 score0.025
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 integrity0.0010.002
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 head0.038
GPT teacher head0.291
Teacher spread0.252 · 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

Citations45
Published2013
Admission routes2
Has abstractyes

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