MétaCan
Menu
Back to cohort
Record W1968483358 · doi:10.1002/aic.13858

Numerical investigation of the hydrodynamics of split‐and‐recombination and multilamination microreactors

2012· article· en· W1968483358 on OpenAlexafffund
Lionel S. Méndez‐Portillo, Mourad Héniche, Charles Dubois, Philippe A. Tanguy

Bibliographic record

VenueAIChE Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsMicroreactorResidence time distributionMixing (physics)Flow (mathematics)MechanicsHomogeneousConvectionDiffusionDistribution (mathematics)Manifold (fluid mechanics)Intensity (physics)ChemistryMaterials sciencePhysicsThermodynamicsOpticsMechanical engineeringMathematicsEngineering

Abstract

fetched live from OpenAlex

The hydrodynamics and residence time distribution (RTD) of two microreactors based on the split‐and‐recombination (SAR), and multilamination mixing mechanisms, respectively were investigated. It was found that the design of the distribution manifolds of the SAR mechanism produces an unbalanced flow distribution. For feeding ratios different than one, bypassing and recirculation occur within the SAR manifolds. For equal flow rates the SAR flow behavior can be accurately described by the pure convection model. The manifold used in the multilamination microreactor achieves a homogeneous distribution of flow and its interdigital mixing structure generates an alternated pattern of fluid layers which is maintained for Re < 140. After this point the ordered arrangement is broken and two large segregated zones are formed. In the absence of molecular diffusion both microreactors reach limiting values of scale and intensity of segregation that were found to be independent of the energy applied to the system. © 2012 American Institute of Chemical Engineers AIChE J, 59: 988–1001, 2013

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 score0.282
Threshold uncertainty score0.197

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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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

Citations6
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueAIChE JournalSame topicInnovative Microfluidic and Catalytic Techniques InnovationFrench-language works237,207