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Record W3084638006 · doi:10.1002/anie.202008477

Evaporation Induced Spontaneous Micro‐Vortexes through Engineering of the Marangoni Flow

2020· article· en· W3084638006 on OpenAlexaff
Zheren Cai, Zhandong Huang, Zheng Li, Meng Su, Zhipeng Zhao, Feifei Qin, Zeying Zhang, Jun Yang, Yanlin Song

Bibliographic record

VenueAngewandte Chemie International Edition · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsWestern University
FundersK. C. Wong Education Foundation
KeywordsMicroscale chemistryVortexMarangoni effectMicrofluidicsMechanicsMaterials scienceFlow (mathematics)NanotechnologyPhysicsConvection

Abstract

fetched live from OpenAlex

Vortex flow fields are widely used to manipulate objects at the microscale in microfluidics. Previous approaches to produce the vortex flow field mainly focused on inertia flows. It remains a challenge to create vortexes in Stokes flow regime. Here we reported an evaporation induced spontaneous vortex flow system in Stokes flow regime by engineering Marangoni flow in a micro-structured microfluidic chip. The Marangoni flow is created by nonuniform evaporation of surfactant solution. Various vortexes are constructed by folding the air-water interface via microstructures. Patterns of vortexes are programmable by designing the geometry of the microstructures and are predictable using numerical simulations. Moreover, rotation of micro-objects and enrichment of micro-particles using vortex flow is demonstrated. This approach to create vortexes will provide a promising platform for various microfluidic applications such as biological analysis, chemical synthesis, and nanomaterial assembly.

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 score0.038
Threshold uncertainty score0.400

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 head0.016
GPT teacher head0.202
Teacher spread0.186 · 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

Citations30
Published2020
Admission routes1
Has abstractyes

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