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Record W2038365324 · doi:10.1002/app.22980

Adhesion interactions between poly(vinyl alcohol) and iron‐oxide surfaces: The effect of acetylation

2006· article· en· W2038365324 on OpenAlexaff
Birol Üner, M. Ramasubramanian, Stefan Zauscher, John F. Kadla

Bibliographic record

VenueJournal of Applied Polymer Science · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVinyl alcoholAdhesionHydrogen bondColloidOxideMaterials scienceBase (topology)Polymer chemistryAlcoholAcetylationSurface energyChemistryAdhesiveChemical engineeringMoleculeNanotechnologyComposite materialPolymerPhysical chemistryOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Atomic force microscopy with chemically functionalized colloidal probes was used to study “acid–base” interactions between poly(vinyl alcohol) (PVA) and a metal surface. By using well‐defined model surfaces, we have studied the adhesion forces between a hydroxylated surface and cantilever tips with varying hydroxyl content. Decreasing the amount of available hydroxyl groups dramatically reduced the observed adhesion force. The calculated bond energy for each cantilever tip was found to be in the range of typical hydrogen bond energies, i.e., 10–40 kJ/mol, suggesting that the acid–base interactions are predominately hydrogen bonding. Similarly, the force versus distance curves using PVA functionalized colloidal probes showed a strong dependence on the chemical functionality of the tip and the degree of acetylation of the intervening PVA. It was observed that, with an increase in the acetyl content of the PVA, the adhesion force decreased. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 99: 3528–3534, 2006

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 score0.037
Threshold uncertainty score0.242

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 head0.006
GPT teacher head0.274
Teacher spread0.268 · 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

Citations16
Published2006
Admission routes1
Has abstractyes

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