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Record W2151615552 · doi:10.1080/00218460490477107

ADHESION ENHANCEMENT THROUGH CONTROL OF ACID-BASE INTERACTIONS

2004· article· en· W2151615552 on OpenAlexaff
M. Ouhlal, Riwei Xu, H. P. Schreiber

Bibliographic record

VenueThe Journal of Adhesion · 2004
Typearticle
Languageen
FieldChemistry
TopicAdsorption, diffusion, and thermodynamic properties of materials
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsLinear low-density polyethyleneMaterials scienceAdhesiveComposite materialAdhesionDiffusionPolyethyleneBond strengthDispersion (optics)PolymerShear strength (soil)Base (topology)Intermolecular forceLayer (electronics)MoleculeOrganic chemistryChemistryThermodynamics

Abstract

fetched live from OpenAlex

Adhesive bond strengths have been determined for lap-shear joints of PS/LLDPE and PS/CPE, a chlorinated version of polyethylene. Joints were formed at temperatures in the range of 180–280°C. In PS/LLDPE, bond strength at lower joining temperatures is compromised by the inability of LLDPE to act as electron acceptor to the donor properties of PS. However, at T ≥ 260°C, PS becomes a fluid capable of interacting through dispersion forces only, leading to enhanced diffusion across the PS/LLDPE interface and much stronger adhesive bonds. An acid–base pairing is in effect in joints of PS/CPE, resulting in strong joints made at T ≤ 240°C. The probable loss of acid-base interaction between the polymers at higher T, coupled with a failure of diffusion across the interface, leads to a lowering of the joint bond strength. Control over interfacial interactions is demonstrated to be a vital factor in the development of adhesive bonds.

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 score0.004

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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

Citations5
Published2004
Admission routes1
Has abstractyes

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