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Record W2312942791 · doi:10.1021/la503362t

Study of Model Superoleophobic Surfaces Fabricated with a Modified Bosch Etch Method

2014· article· en· W2312942791 on OpenAlexafffund
Brendan Koch, Janet A.W. Elliott, Alidad Amirfazli

Bibliographic record

VenueLangmuir · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsYork UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHexadecaneContact angleMaterials sciencePillarRADIUSEthylene glycolDrop (telecommunication)Composite materialWettingNanotechnologyChemical engineeringChemistryStructural engineeringMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

A set of surfaces featuring pillars with overhanging cap structures, exhibiting superoleophobic behavior, were fabricated using a new method. While such structures have been previously reported, in contrast with previous literature this new method allows for the control of pillar cross-sectional diameter, pillar separation, and Cassie fraction independent from the pillar radius-to-height ratio. Once fabricated the contact angles of the surfaces were examined using water, ethylene glycol, and hexadecane. These surfaces were capable of maintaining a stable Cassie state with hexadecane where surfaces with similar Cassie fraction but vertical sidewalls we had examined previously collapsed into the Wenzel state. The overall behavior of the liquids conforms to prior experience with vertical sidewall structures, with the advancing contact angles tending to remain high and insensitive to changing Cassie fraction while the receding contact angles follow the trends predicted by the Cassie equation much more closely. All experimental evidence taken together, this seems to indicate that the cap structures increase the stability of the Cassie state, but at the expense of increasing drop pinning, over and above what such surface texturing already does.

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)0.001
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 score0.460
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.294
Teacher spread0.250 · 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

Citations17
Published2014
Admission routes2
Has abstractyes

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