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Record W2127123000 · doi:10.1002/polb.10566

Effect of surface‐grafted ionic groups on the performance of cellulose‐fiber‐reinforced thermoplastic composites

2003· article· en· W2127123000 on OpenAlexaff
Xiaolin Cai, Bernard Riedl, A. Aı̈t-Kadi

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2003
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceFiberComposite materialCellulosePolymerPolystyreneRegenerated celluloseCellulose fiberAdhesionGraftingSurface modificationPolymer chemistryChemical engineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The influence of the surface chemistry of the cellulose fiber and polymer matrix on the mechanical and thermal dynamic mechanical properties of cellulose‐fiber‐reinforced polymer composites was investigated. The cellulose fiber was treated either with a coupling agent or with a coupling‐agent treatment followed by the introduction of quaternary ammonium groups onto the fiber surface, whereas the polymer matrix, with opposite polar groups such as polystyrene incorporated with sulfonated polystyrene and poly(ethylene‐co‐methacrylic acid), was compounded with the fiber. The grafting of the fiber surface was investigated with Fourier transform infrared spectroscopy and X‐ray photoelectron spectroscopy. Experimental results showed that an obvious improvement in the mechanical strength could be achieved for composites with an ionic interface between the fiber and the polymer matrix because of the adhesion enhancement of the fiber and the matrix. The improved adhesion could be ascribed to the grafted ionic groups at the cellulose‐fiber surface. © 2003 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 41: 2022–2032, 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 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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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 head0.012
GPT teacher head0.263
Teacher spread0.250 · 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

Citations25
Published2003
Admission routes1
Has abstractyes

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