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Record W4389584892 · doi:10.17118/11143/20925

Molecular investigations of droplet behaviors on nano-pillaredsurfaces

2023· article· en· W4389584892 on OpenAlexaff
M. Rayhani, Cuiying Jian

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsYork University
Fundersnot available
KeywordsNano-Materials scienceNanotechnologyChemical physicsChemistryComposite material

Abstract

fetched live from OpenAlex

Superhydrophobic surfaces are being employed in various applications, including self-cleaning, anti-corrosion, anti-icing, drag reduction, and separation of oil from water.This superhydrophobic property is mostly derived by surface wettability, which is associated with the surface energy and presence of pillars/grooves.In the latter case, mainly the air is trapped in the spacings of microstructures, restricting the wetting property of the surface.Generally, the surface superhydrophobicity is assessed by gauging contact angles at the interface of solid surface and water droplet.This can be done by implementing two models, namely Cassie-Baxter wetting state and Wenzel wetting state.In the former, the air is trapped between the microstructure grooves and the water droplet, placing above the microstructures.Contrarily, in the Wenzel state, the water droplet places inside the microstructure grooves.Thus, in the latter condition, a stronger bond exists between the structured surface and the water droplet.The sizes and initial states of the droplet define whether a droplet is in the Cassie or Wenzel state.In both models, the height, lateral, and gap dimensions of pillars on a solid surface as well as their shapes play important roles in determining the behaviors of the droplets.Thus, the current study seeks to shed light on the impacts of surface roughness on the development of superhydrophobic surfaces, using Wenzel wetting state.To do so, the behavior of a water droplet on a nanopillared copper solid surface is studied through molecular dynamic simulations.Herein, a water droplet consisting of 1000 water molecules is placed above two solid surfaces of pillared copper (10*10*10 A ) with 5A groove size in three directions and smooth copper (20*20*20 A ). Also, the NPT ensemble of 300 K was employed the system was equilibrated for 1 fs. it was found that the water droplet on the smooth copper surface depicted a hydrophilic state, as the contact angle altered from 32 to 103 (i.e. >90, suggesting a hydrophilic surface).On the other hand, in the presence of pillars, the contact angle shifted from 60 to 50 (i.e. <90, suggesting a hydrophobic surface).The effects of pillar dimensions will be further quantified.The results obtained can help to quantitatively understand the effects of pillars/grooves for generating superhydrophobic surfaces.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.023
GPT teacher head0.254
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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Same topicnanoparticles nucleation surface interactionsFrench-language works237,207