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Record W2591880525 · doi:10.1002/cjce.22825

Large scale preparation of microbubbles by multi‐channel ceramic membranes: Hydrodynamics and mass transfer characteristics

2017· article· en· W2591880525 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersScience and Technology Support Program of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsMicrobubblesMass transferMass transfer coefficientSpargingBubbleCeramic membraneMaterials scienceMembraneFiltration (mathematics)CeramicSuperficial velocityMechanicsVolumetric flow rateFlow (mathematics)Analytical Chemistry (journal)Chemical engineeringChemistryChromatographyComposite materialAcousticsPhysics

Abstract

fetched live from OpenAlex

Abstract Microbubbles have potential applications in chemical engineering, water treatment, and medicine. By designing multi‐channel ceramic membrane distributors, large scale preparation of microbubbles is achieved in a co‐current bubble column. Oxygen and water are used as interacting gas‐liquid phases. Gas holdup, bubble size distribution, and mass transfer rate are influenced by the membrane pore size, superficial gas velocity, and cross flow velocity. The empirical correlations for gas holdup and volumetric mass transfer coefficient are formulated and good agreement with experimental data is obtained. The multi‐channel ceramic membranes can successfully produce a lot of microbubbles, resulting in larger values of gas holdup, volumetric mass transfer coefficient, and equilibrium dissolved oxygen concentrations as compared to the conventional gas sparger. These findings will aid the development of gas‐liquid reactors with high performances.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.493

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 head0.005
GPT teacher head0.184
Teacher spread0.180 · 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