MétaCan
Menu
Back to cohort
Record W7133054819

Capillarity and convection-controlled assembly in the spreading of particulate suspensions on an air-liquid interface

2018· dissertation· W7133054819 on OpenAlexaff
Rajesh Ranjan

Bibliographic record

VenueTSpace · 2018
Typedissertation
Language
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSuspension (topology)Silicone oilCapillary actionViscosityDrop (telecommunication)ParticulatesParticle (ecology)CoatingConvection
DOInot available

Abstract

fetched live from OpenAlex

Self-assembly of particles at interfaces has immense potential for printing and coating applications in biological and industrial processes. Several studies on the spreading of pure fluids on an air-liquid interface have been conducted; however, none have examined the spreading characteristics of two-phase fluid materials. In this work, a drop of concentrated suspension of PMMA particles in silicone oil was placed on an aqueous glycerol solution – air interface. Depending on the initial rate of spreading of the suspension, two outcomes were observed: the particles were either swept away by the spreading suspension or organized into an array of two-dimensional networks. The two outcomes were explained by describing the particle motion as being a result of a competition between fluid convection and capillary attraction. This description was confirmed by performing experiments for different particle sizes, volume fractions, the viscosity and salinity of the substrate on the spreading behavior and pattern.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.030
GPT teacher head0.362
Teacher spread0.332 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicPickering emulsions and particle stabilizationFrench-language works237,207