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Record W2508739809 · doi:10.1021/acsami.6b05673

Rapid Development of Wet Adhesion between Carboxymethylcellulose Modified Cellulose Surfaces Laminated with Polyvinylamine Adhesive

2016· article· en· W2508739809 on OpenAlexafffund
Emil Gustafsson, Robert Pelton, Lars Wågberg

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaWallenberg Wood Science CenterMcMaster UniversityBASF
KeywordsAdhesiveMaterials scienceAdhesionCelluloseComposite materialPolymer scienceChemical engineeringLayer (electronics)

Abstract

fetched live from OpenAlex

The surface of regenerated cellulose membranes was modified by irreversible adsorption of carboxymethylcellulose (CMC). Pairs of wet CMC-modified membranes were laminated with polyvinylamine (PVAm) at room temperature, and the delamination force for wet membranes was measured for both dried and never-dried laminates. The wet adhesion was studied as a function of PVAm molecular weight, amine content, and deposition pH of the polyelectrolyte. Surprisingly the PVAm-CMC system gave substantial wet adhesion that exceeded that of TEMPO-oxidized membranes with PVAm for both dried and never-dried laminates. The greatest wet adhesion was achieved for fully hydrolyzed high molecular weight PVAm. Bulk carboxymethylation of cellulose membranes gave inferior wet adhesion combined with PVAm as compared to CMC adsorption which indicates that a CMC layer of the order of 10 nm was necessary. There are no obvious covalent cross-linking reactions between CMC and PVAm at room temperature, and on the basis of our results, we are instead attributing the wet adhesion to complex formation between the PVAm and the irreversibly adsorbed CMC at the cellulose surface. We propose that interdigitation of PVAm chains into the CMC layer is responsible for the high wet adhesion values.

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 categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.211
Teacher spread0.197 · 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.

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

Citations20
Published2016
Admission routes2
Has abstractyes

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