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Record W2004101944 · doi:10.1002/mame.201000210

Surface Modification of Wood Fiber and Preparation of a Wood Fiber–Polypropylene Hybrid by In situ Polymerization

2010· article· en· W2004101944 on OpenAlexaff
C. Ravindra Reddy, Leonardo C. Simon

Bibliographic record

VenueMacromolecular Materials and Engineering · 2010
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials sciencePolymerizationFiberSurface modificationSilanePolypropyleneIn situ polymerizationThermal stabilitySynthetic fiberPolymer chemistryComposite materialChemical engineeringPolymer

Abstract

fetched live from OpenAlex

Abstract The surface functionalization of wood fiber was performed by chemical modification with bi‐functional organo‐silane 7 ‐octenyldimethylchlorosilane ( 7 ‐ODMCS) and mono‐functional organo‐silane n ‐octyldimethylchlorosilane ( n ‐ODMCS). The chloro functionality of organo‐silane modifiers was utilized to functionalize wood fiber. The resulting modified fiber was characterized for thermal stability (thermal gravimetric analysis), presence of organic groups on the surface (Fourier‐transform IR), for particle size (microscopy) and for its hydrophobicity by dispersing in toluene. The modified fiber was used for in situ polymerization of propylene to obtain a wood fiber–polypropylene hybrid. The terminal olefin functionality of 7 ‐ODMCS was utilized for co‐polymerization of propylene during in situ polymerization. The wood fiber–polypropylene hybrid samples were characterized for thermal analysis. In order to confirm the co‐polymerization of propylene in 7 ‐ODMCS modified fiber during in situ polymerization, n ‐ODMCS modified fiber having no olefin functionality was also used in in situ polymerization. magnified image

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 score0.003
Threshold uncertainty score0.581

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 head0.004
GPT teacher head0.212
Teacher spread0.207 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

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