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Record W3009971260 · doi:10.1139/cjp-2019-0451

Various crust morphologies of colloidal droplets dried on a super-hydrophobic surface

2020· article· en· W3009971260 on OpenAlexvenueno aff
Yongjian Zhang, Xin Gao, Hai Chu, Bernard P. Binks

Bibliographic record

VenueCanadian Journal of Physics · 2020
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsnot available
FundersEducation Department of Shaanxi ProvinceNational Natural Science Foundation of China
KeywordsCrustEvaporationParticle (ecology)NanoparticleColloidChemical physicsRelative humidityMaterials scienceShrinkageNanotechnologySubstrate (aquarium)Layer (electronics)Chemical engineeringComposite materialChemistryPhysicsGeologyThermodynamics

Abstract

fetched live from OpenAlex

We have studied the evaporation of water droplets containing silica nanoparticles of various hydrophobicities deposited on a super-hydrophobic substrate. Evaporation induces particle accumulation at the droplet surface and results in the formation of a crust that buckles during further shrinkage. For droplets containing hydrophilic particles, a bowl-shaped crust was observed. For droplets containing hydrophobic particles, the crust develops a multi-buckled shape that could be completely suppressed by increasing the relative humidity. The varied buckling behavior of droplets may be attributed to the different mechanical properties of the gelled layer where particle hydrophobicity plays a role. Our work highlights the important role of particle hydrophobicity and relative humidity in the final crust morphology, thus shedding light on crust shape control and material design via the droplet evaporation approach.

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 score0.409
Threshold uncertainty score0.494

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 head0.185
Teacher spread0.167 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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