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Record W2066631879 · doi:10.1002/cjce.21639

CFD simulation for biomagnetic separation involving dilute suspensions

2012· article· en· W2066631879 on OpenAlexvenueaboutno aff
Saud Khashan, Yousef Haik, Emad Elnajjar

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsnot available
FundersUtah Agricultural Experiment Station
KeywordsMagnetic fieldMechanicsMass transferMagnetic nanoparticlesMaterials scienceComputational fluid dynamicsPhysicsNanotechnologyNanoparticle

Abstract

fetched live from OpenAlex

Abstract Full‐Eulerian simulation of the separation of magnetic particles carried by a Newtonian fluid through a planar channel under the influence of a magnetic field is presented. The simulation is based on the application of the Navier–Stokes and concentration equations. The scheme for the magnetic separation of particles is achieved by applying an external magnetic dipole field. The hydrodynamic and magnetophoretic interactions between the particles and the carrier fluid are analysed. Analysis of the competing tendencies of mass transfer indicates that the magnetophoresis migration of magnetic particles is dominant over the molecular diffusion. This dominance becomes more evident at lower diffusivities leading to a drastic magnetic separation confined within a small region in the proximity of the magnetic field source. © 2012 Canadian Society for Chemical Engineering

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 score0.314
Threshold uncertainty score0.310

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 head0.018
GPT teacher head0.225
Teacher spread0.207 · 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

Citations7
Published2012
Admission routes2
Has abstractyes

Explore more

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