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Record W2289606660 · doi:10.3390/ma9030151

Recent Advances in Superhydrophobic Electrodeposits

2016· review· en· W2289606660 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

VenueMaterials · 2016
Typereview
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsIntegran (Canada)University of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceWettingMicrostructureInertCeramicSurface finishComposite numberSurface roughnessNanotechnologyComposite materialDeposition (geology)Surface energyContact angleMetallurgy

Abstract

fetched live from OpenAlex

In this review, we present an extensive summary of research on superhydrophobic electrodeposits reported in the literature over the past decade. As a synthesis technique, electrodeposition is a simple and scalable process to produce non-wetting metal surfaces. There are three main categories of superhydrophobic surfaces made by electrodeposition: (i) electrodeposits that are inherently non-wetting due to hierarchical roughness generated from the process; (ii) electrodeposits with plated surface roughness that are further modified with low surface energy material; (iii) composite electrodeposits with co-deposited inert and hydrophobic particles. A recently developed strategy to improve the durability during the application of superhydrophobic electrodeposits by controlling the microstructure of the metal matrix and the co-deposition of hydrophobic ceramic particles will also be addressed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.007

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 head0.035
GPT teacher head0.320
Teacher spread0.286 · 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