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Record W2114183009 · doi:10.1142/s0218625x08011470

MODIFICATION OF WETTING PROPERTIES OF PMMA BY IMMERSION PLASMA ION IMPLANTATION

2008· article· en· W2114183009 on OpenAlexaff
N. Mireault, G.G. Ross

Bibliographic record

VenueSurface Review and Letters · 2008
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsWettingPlasma-immersion ion implantationX-ray photoelectron spectroscopyContact angleIonMaterials scienceIon implantationImmersion (mathematics)PlasmaDangling bondArgonOxygenDerivatizationSurface modificationAnalytical Chemistry (journal)Chemical engineeringChemistryComposite materialSiliconChromatographyOrganic chemistryMass spectrometryMetallurgy

Abstract

fetched live from OpenAlex

Advancing and receding contact angles below 5° have been obtained on PMMA surfaces with the implantation of argon and oxygen ions. The ion implantations were performed by means of the Immersion Plasma Ion Implantation (IPII) technique, a hybrid between ion beams and immersion plasmas. Characterization of treated PMMA surfaces by means of XPS and its combination with chemical derivatization (CD-XPS) have revealed the depletion of oxygen and the creation of dangling bonds, together with the formation of new chemical functions such as –OOH , –COOH and C = C . These observations provide a good explanation for the strong increase of the wetting properties of the PMMA surfaces.

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 score0.003

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 head0.031
GPT teacher head0.261
Teacher spread0.230 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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