MétaCan
Menu
Back to cohort
Record W2783718257 · doi:10.1088/1361-648x/aaa81c

Hydrodynamic shrinkage of liquid CO <sub>2</sub> Taylor drops in a straight microchannel

2018· article· en· W2783718257 on OpenAlexafffund
Na Qin, John Z. Wen, Carolyn L. Ren

Bibliographic record

VenueJournal of Physics Condensed Matter · 2018
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Waterloo
FundersCarbon Management Canada
KeywordsMicrochannelPressure dropDrop (telecommunication)MechanicsVolumetric flow rateMass transferChemistryShrinkageThermodynamicsMaterials scienceAnalytical Chemistry (journal)Composite materialChromatographyPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Hydrodynamic shrinkage of liquid CO 2 drops in water under a Taylor flow regime is studied using a straight microchannel (length/width ~100). A general form of a mathematical model of the solvent-side mass transfer coefficient ( k s ) is developed first. Based on formulations of the surface area ( A ) and the volume ( V ) of a general Taylor drop in a rectangular microchannel, a specific form of k s is derived. Drop length and speed are experimentally measured at three specified positions of the straight channel, namely, immediately after drop generation (position 1), the midpoint of the channel (position 2) and the end of the channel (position 3). The reductions of drop length ( L x , x = 1, 2, 3) from position 1 to 2 and down to 3 are used to quantify the drop shrinkage. Using the specific model, k s is calculated mainly based on L x and drop flowing time ( t ). Results show that smaller CO 2 drops produced by lower flow rate ratios ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mstyle displaystyle="false"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>Q</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi mathvariant="normal">C</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> <mml:mrow> <mml:mo>/</mml:mo> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>Q</mml:mi> </mml:mrow> <mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">H</mml:mi> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:mstyle> </mml:math> ) are generally characterized by higher (nearly three times) k s and Sherwood numbers than those produced by higher <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mstyle displaystyle="false"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>Q</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi mathvariant="normal">C</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> <mml:mrow> <mml:mo>/</mml:mo> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>Q</mml:mi> </mml:mrow> <mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">H</mml:mi> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">O</mml:mi> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:mstyle> </mml:math> , which is essentially attributed to the larger effective portion of the smaller drop contributing in the mass transfer under same levels of the flowing time and the surface-to-volume ratio (~10 4 m −1 ) of all drops. Based on calculated pressure drops of the segmented flow in microchannel, the Peng–Robinson equation of state and initial pressures of drops at the T-junction in experiments, overall pressure drop (Δ P t ) in the straight channel as well as the resulted drop volume change are quantified. Δ P t from position 1–3 is by average 3.175 kPa with a ~1.6% standard error, which only leads to relative drop volume changes of 0.3‰ to 0.52‰.

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 score0.123
Threshold uncertainty score0.718

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 head0.008
GPT teacher head0.226
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 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

Citations11
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Physics Condensed MatterSame topicInnovative Microfluidic and Catalytic Techniques InnovationFrench-language works237,207