MétaCan
Menu
Back to cohort
Record W2901617810 · doi:10.1039/c8ra09859j

Microparticle self-assembly induced by travelling surface acoustic waves

2019· article· en· W2901617810 on OpenAlexaff
Ghulam Destgeer, Ali Hashmi, Jinsoo Park, Husnain Ahmed, Muhammad Afzal, Hyung Jin Sung

Bibliographic record

VenueRSC Advances · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsKootenay Association for Science & Technology
FundersKorea Advanced Institute of Science and TechnologyNational Research Foundation of KoreaKorea Polar Research InstituteNational Research Foundation
KeywordsMicroparticleSurface (topology)Materials scienceAcousticsPhysicsOpticsGeometryMathematics

Abstract

fetched live from OpenAlex

We present an acoustofluidic method based on travelling surface acoustic waves (TSAWs) to induce self-assembly of microparticles inside a microfluidic channel. The particles are trapped above an interdigitated transducer, placed directly beneath the microchannel, by the TSAW-based direct acoustic radiation force (ARF). This approach was applied to trap 10 μm polystyrene particles, which were pushed towards the ceiling of the microchannel by 72 MHz TSAWs to form single- and multiple-layer colloidal structures. The repair of cracks and defects within the crystal lattice occurs as part of the self-assembly process. The sample flow through the first inlet can be switched with a buffer flow through the second inlet to control the number of particles assembled in the crystalline structure. The constant flow-induced Stokes drag force on the particles is balanced by the opposing TSAW-based ARF. This force balance is essential for the acoustics-based self-assembly of microparticles inside the microchannel. Moreover, we studied the effects of varying input voltage and fluid flow rate on the position and shape of the colloidal structure. The active self-assembly of microparticles into crystals with multiple layers can be used in the bottom-up fabrication of colloidal structures with dimensions greater than 500 μm × 500 μm, which is expected to have important applications in various fields.

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 score0.015
Threshold uncertainty score0.611

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 head0.210
Teacher spread0.202 · 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

Citations33
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueRSC AdvancesSame topicMicrofluidic and Bio-sensing TechnologiesFrench-language works237,207