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Preparation and Characterization of Superhydrophobic Modification of Polyvinylidene Fluoride Membrane by Dip-Coating

2014· article· en· W2122730462 on OpenAlexvenueno aff
Yuzhong Zhang, YingNa Li, HuaFeng Zhang, Hui Ye, Ying Chen, Yue Li

Bibliographic record

VenueJournal of Membrane and Separation Technology · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsnot available
FundersSpecialized Research Fund for the Doctoral Program of Higher Education of ChinaState Oceanic AdministrationOcean Public Welfare Scientific Research ProjectNatural Science Foundation of Tianjin CityNational Natural Science Foundation of China
KeywordsPolyvinylidene fluorideContact angleMembraneMaterials scienceSurface modificationCoatingDip-coatingChemical engineeringFourier transform infrared spectroscopySuperhydrophobic coatingPorosityPolymer chemistryComposite materialPolymerChemistry

Abstract

fetched live from OpenAlex

The superhydrophobicity polyvinylidene fluoride (PVDF) membranes were modified via reducing surface energy by dip-coating perfluoroalkyl methacrylic copolymer (Zonyl 8740) onto the membranes prepared on mat glass. The chemical component of the unmodified and modified PVDF membranes surface was investigated by ATR-FTIR. Morphology and hydrophobicity of the unmodified and modified PVDF membranes were examined by scanning electronic microscopy and water contact angle, respectively. The effects of concentration of Zonyl 8740, coating time, conditions of heat treatment on hydrophobic capability of PVDF membranes were investigated. The results showed that the water contact angle increased from 141˚ to 151˚ by the dip-coating modification, therefore getting superhydrophobic PVDF membrane. Moreover, the porosity and the morphology of modified PVDF membrane were unchanged by the dip-coating modification. This results suggested that the hydrophobicty stability of the modified PVDF membrane was also good.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2014
Admission routes1
Has abstractyes

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