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Record W1965113629 · doi:10.1002/polb.23076

Teflon hierarchical nanopillars with dry and wet adhesive properties

2012· article· en· W1965113629 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanopillarMaterials scienceFluoropolymerComposite materialvan der Waals forceAdhesiveNanoporousDielectricLayer (electronics)NanotechnologyNanostructurePolymerChemistry

Abstract

fetched live from OpenAlex

Abstract The superior material properties of β‐keratin along with the hierarchical high‐aspect‐ratio structure of geckos' foot pad have enabled geckos to stick readily and rapidly to almost any surfaces in both dry and wet conditions. In this research, nonsticky fluoropolymer (Teflon AF) resembling β‐keratin rigidity and having an extremely low surface energy and dielectric constant was applied to fabricate a novel dry adhesive consisting of high‐aspect‐ratio nanopillars terminated with a “fluffy” top layer. Both the nanopillars and the terminating layer are fabricated concurrently by replica molding using a nanoporous anodic aluminum oxide membrane as the mold. These Teflon AF hierarchical nanostructures are shown to have an exceptional capacity to generate strong adhesion in both dry conditions and under water because of combined actions of van der Waals forces, electrostatic attractions, and hydrophobic effects. © 2012 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2012

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.

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 score0.087
Threshold uncertainty score0.551

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 communication0.0000.002
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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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