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Record W2072555984 · doi:10.1115/1.4027977

Laser Texturing of Plasma Electrolytically Oxidized Aluminum 6061 Surfaces for Improved Hydrophobicity

2014· article· en· W2072555984 on OpenAlex
Bekir Sami Yilbaş, A. Matthews, C. Karataş, A. Leyland, Mazen Khaled, Numan Abu-Dheir, N. Al‐Aqeeli, Xueyuan Nie

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.

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Windsor
FundersU.S. Department of Energy
KeywordsMaterials scienceContact angleLaserLaser ablationPlasmaScanning electron microscopeAluminiumTexture (cosmology)AlloyDiffractionSurface energyEnergy-dispersive X-ray spectroscopySpectroscopyLayer (electronics)Analytical Chemistry (journal)Composite materialOpticsChemistry

Abstract

fetched live from OpenAlex

Laser surface texturing of plasma electrolytically oxidized aluminum 6061 alloy has been carried out through a controlled surface ablation under a high pressure nitrogen gas assistance. Morphological and metallurgical changes in the laser-treated region were examined using optical, scanning electron, and atomic force microscopy, energy dispersive X-ray spectroscopy, and X-ray diffraction phase analysis. The hydrophobicity of the textured surface was assessed through water droplet contact angle measurements. It was found that a dense layer with a nanotexture/microtexture is developed at the surface after the laser treatment process. The assessment of the surface characteristics reveals that a superhydrophobic surface results from the laser treatment process; in which case, high water droplet contact angles are measured over the treated surface, which can be explained by known models of texture-induced superhydrophobicity.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.090
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.008
GPT teacher head0.211
Teacher spread0.204 · 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