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Record W2036019660 · doi:10.1002/cjce.5450800206

The mixing sensitivity of polysulphide generation

2002· article· en· W2036019660 on OpenAlexaffvenue
Heather K. Dobson, Chad P. J. Bennington

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpargingYield (engineering)SelectivityCatalysisMixing (physics)ChemistryPartial pressureOxygenReaction rateVolumetric flow rateChemical engineeringMaterials scienceAnalytical Chemistry (journal)ChromatographyThermodynamicsOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The effect of mixing and mass transfer on polysulphide generation by catalytic oxidation of sodium sulphide was studied using two batch‐operated reactors. One was a sparged reactor operated at atmospheric pressure and low mixing intensities (0.37 to 28 W/kg), the other was an unsparged pressurized reactor characterized by high mixing intensities (17 to 3100 W/kg). The reaction parameters examined included the impeller speed, sparged gas flowrate, oxygen partial pressure, and catalyst loading and type. In both reactors the maximum polysulphide yield, selectivity and rate of formation increased with increasing energy dissipation. Increased gas sparging increased the rate of reaction, but had little effect on either yield or selectivity. Increased oxygen partial pressure increased the rate of oxidation but decreased both the yield and selectivity. The type of catalyst dramatically affected the yield of polysulphide produced for a given set of reaction conditions with improved mixing increasing reaction rate, yield and selectivity.

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 score0.016
Threshold uncertainty score0.126

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 head0.010
GPT teacher head0.174
Teacher spread0.164 · 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

Citations4
Published2002
Admission routes2
Has abstractyes

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