MétaCan
Menu
Back to cohort
Record W2093463261 · doi:10.1002/app.11994

Surface characteristics of hydrosilylated polypropylene

2003· article· en· W2093463261 on OpenAlexaff
Jiangyou Long, Costas Tzoganakis, P. Chen

Bibliographic record

VenueJournal of Applied Polymer Science · 2003
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWettingMaterials sciencePolypropyleneSurface energyX-ray photoelectron spectroscopyMicrostructureContact anglePolydimethylsiloxaneSurface finishComposite materialSurface roughnessSessile drop techniqueChemical engineeringSurface tensionPolymer chemistryThermodynamics

Abstract

fetched live from OpenAlex

Abstract Polypropylene containing terminal unsaturation was modified with a hydride‐terminated polydimethylsiloxane (PDMS) at three different temperatures through a catalytic hydrosilylation reaction in the melt phase. A comprehensive study on the surface characteristics of hydrosilylated polypropylene (SiPP) was conducted by combining macroscopic thermodynamics, microstructure, and chemical composition measurements. Axisymmetric drop shape analysis–profile (ADSA‐P) was used to characterize the surface wettability. The morphology, roughness, and heterogeneity of the surfaces were investigated by the lateral‐force mode of atomic force microscopy (LFM). X‐ray photoelectron spectroscopy (XPS) was used to quantify the surface chemical composition. LFM images showed that all sample surfaces were rough and heterogeneous on a micrometer scale. XPS analysis showed that the surfaces investigated were complicated in composition and that various oxides existed on the surfaces. The surface wettability was well correlated to the surface microstructure and composition. The surfaces investigated were modeled based on the microstructure observed, and a new scheme was developed to calculate surface free energy and adhesion work. For SiPPs, the lower the reaction temperature, the more PDMS incorporation was observed, the smaller the surface free energy and the work of adhesion, the more hydrophobic the surface, and the lower the permeability. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 3117–3131, 2003

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)0.002
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 score0.004
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations13
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Polymer ScienceSame topicSurface Modification and SuperhydrophobicityFrench-language works237,207