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Silane-modified cellulose nanocrystals (CNCs) based natural rubber composites

2024· article· en· W4404905546 on OpenAlexafffund
Ewomazino Ojogbo, Costas Tzoganakis, Tizazu H. Mekonnen

Bibliographic record

VenueComposites Part A Applied Science and Manufacturing · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Waterloo
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialSilaneCelluloseNatural rubberNatural fiberComposite numberChemical engineering

Abstract

fetched live from OpenAlex

This research explored the use of cellulose nanocrystals (CNC) modified with 3-isocyanotopropyltriethoxysilane (IPTS) as a reinforcing agent of natural rubber (NR). A single-step heterogeneous reaction was employed to modify the surface hydroxyl (OH) groups of the CNC using IPTS. Various characterizations were employed to evaluate the surface modification of CNCs. X-ray diffractometry (XRD) showed 18 % reduction in crystallinity demonstrated the preservation of the crystal structure of the modified CNC, while an increase in the contact angle verified the altered polarity. Subsequently, nanocomposites of NR- modified CNCs (mCNC) were fabricated, and resulted showed that the CNC modification significantly enhanced the interaction between CNCs and NR, leading to reduced cure time, ease of processibility, and improved mechanical properties with a 71 % increase in tensile strength. The findings highlighted the effectiveness of CNCs modification in enhancing the properties of NR nanocomposites and provide valuable insights into the optimal loading concentration for effective reinforcement.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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

Citations12
Published2024
Admission routes2
Has abstractyes

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