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Record W3108630786 · doi:10.1021/acs.iecr.0c03641

Experimental Analysis of the Mass Transfer Coefficient and Interfacial Area in an Aerated Coaxial Mixing System Comprising a Non-Newtonian Solution

2020· article· en· W3108630786 on OpenAlexafffund
Maryam Jamshidzadeh, Farhad Ein‐Mozaffari, Ali Lohi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsImpellerBubbleMass transferMixing (physics)Carboxymethyl celluloseNon-Newtonian fluidAerationCoaxialMass transfer coefficientNewtonian fluidMechanicsChemistryMaterials scienceViscosityThermodynamicsChromatographyComposite materialMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Volumetric mass transfer coefficient, k L a, bubble size, and interfacial area were investigated in an aerated coaxial mixing system with an aspect ratio of 1.25 furnished with two central impellers and an anchor. The simplified dynamic pressure method and a combination of the dynamic gas disengagement and electrical resistance tomography methods were utilized for measuring k L a and bubble sizes, respectively. Carboxymethyl cellulose (CMC) solutions were used as the power-law non-Newtonian fluids. New correlations for the prediction of k L a in aerated coaxial mixing systems containing non-Newtonian solutions were developed. The pitched blade impeller in downward pumping generated the highest mass transfer and interfacial area and smaller bubble sizes at all anchor speeds and concentrations of the CMC solution. The anchor speed had a positive impact on the oxygen mass transfer up to 20 rpm. Bubble stability increased while the interfacial area decreased with an increase in the fluid apparent viscosity.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.280
Teacher spread0.218 · 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

Citations27
Published2020
Admission routes2
Has abstractyes

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