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Record W2112834334 · doi:10.1002/cjce.5450790510

Trickle‐bed scrubbing of flue gas SO<sub>2</sub> using non‐aqueous solvents

2001· article· en· W2112834334 on OpenAlexafffundvenue
Mahiyar A. Panthaky, Radu V. Vladea, Ali Lohi, R. R. Hudgins, P.L. Silveston

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaAtomic Energy of Canada Limited
KeywordsData scrubbingActivated carbonPacked bedTrickle-bed reactorCatalysisFlue gasAqueous solutionChemistrySulfuric acidWaste managementChemical engineeringTRICKLEAdsorptionOrganic chemistryChromatography

Abstract

fetched live from OpenAlex

Abstract Experiments were carried out on the performance of several ketone solvents for the scrubbing of dilute SO 2 from a gas stream and its conversion to sulfuric acid in a trickle‐bed reactor packed with activated carbon. Using a bench‐scale trickle bed packed with a structured packing based on Sulzer static mixers coated with Centaur TM activated carbon and a Teflon binder, measurements of SO 2 removal, conversion to acid and catalyst productivity showed that all were considerably greater than levels achieved with water flushing. The combination of Teflon‐coated Centaur activated carbon with a non‐aqueous solvent as the flushing agent provided from 10 to 100 times higher catalyst productivity than those obtained with water alone and other activated carbons. Also, the productivities obtained by this combination were up to 40 times higher than the productivity of typical vanadium pentoxide catalyst operating at 350°C to 400°C.

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)0.000
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 score0.028
Threshold uncertainty score0.858

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 integrity0.0000.001
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 head0.013
GPT teacher head0.192
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 teacher head, 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

Citations3
Published2001
Admission routes3
Has abstractyes

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