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Record W3111472632 · doi:10.1088/1361-6528/abd276

Synthesis and characterization of MWCNT-covered stainless steel mesh with Janus-type wetting properties

2020· article· en· W3111472632 on OpenAlexafffund
A. Karthikeyan, Evelyne Kasparek, Anne‐Marie Kietzig, Pierre‐Luc Girard‐Lauriault, Sylvain Coulombe

Bibliographic record

VenueNanotechnology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMaterials scienceWettingJanusContact angleCarbon nanotubeComposite materialScanning electron microscopeX-ray photoelectron spectroscopySurface roughnessSurface finishPolymerChemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Various multi-step methods to fabricate Janus membranes have been reported in literature. However, no article so far reports the durability of the Janus membranes when exposed to liquids. We report on a novel method to fabricate a Janus-type multi-walled carbon nanotubes (MWCNT)-covered stainless steel (SS) mesh, which retains dual-wetting properties even after exposure to water for 540 d. The MWCNTs are grown directly on stainless steel mesh coupons by chemical vapor deposition using acetylene as the carbon source, and are then plasma functionalized using an ammonia-ethylene gas mixture to achieve dual-wettability. We found by x-ray photoelectron spectroscopy that the MWCNTs on the top face of the novel Janus MWCNT-SS mesh, which was directly exposed to the plasma, are coated by a plasma polymer rich in nitrogen-containing functional groups, while the MWCNTs on the bottom face are almost devoid of the plasma polymer coating. Atomic force microscopy studies confirmed that the surface roughness of the bottom face of the mesh is lower than the minimum roughness that allows the capillary ingress of water to sustain its superhydrophobic behavior. In addition, scanning electron microscopy studies also confirmed that the MWCNTs on the bottom face of the treated MWCNT mesh are vertically aligned compared to the MWCNTs on the top face of the mesh. The vertically aligned dense MWCNT forest on the bottom face attributes to its superhydrophobic nature.

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 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 score0.003
Threshold uncertainty score0.335

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 communication0.0000.000
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 head0.025
GPT teacher head0.206
Teacher spread0.181 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

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