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Record W4407330766 · doi:10.1021/acs.biomac.4c01802

Cellulose Nanocrystals Modified with Cationic Block Copolymers

2025· article· en· W4407330766 on OpenAlexafffund
Olga Lidia Torres‐Rocha, Julien Pinaud, Patrick Lacroix‐Desmazes, Pascale Champagne, Michael F. Cunningham

Bibliographic record

VenueBiomacromolecules · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsNational Research Council CanadaQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCopolymerCationic polymerizationCelluloseChemistryPolymer chemistryChemical modificationNanocrystalChemical engineeringPolymerMaterials scienceOrganic chemistryNanotechnology

Abstract

fetched live from OpenAlex

Cellulose nanocrystals (CNC) offer unique mechanical and optical properties but face challenges that often prevent its commercial development, foremost its high hydrophilicity, which makes it incompatible with most polymers. Covalent polymer graft modification can address this issue; however, these processes are often complex and expensive. We present a simple, inexpensive route for the noncovalent modification of a CNC surface with block copolymers. Five new block copolymers, composed of a butyl vinyl imidazolium bromide anchoring (cationic) and a nonionic stabilizing block, were synthesized via nitroxide-mediated polymerization. The degree of polymerization (DPn) of the stabilizing and anchoring blocks was systematically varied. Dispersibility of modified CNC in various organic solvents was evaluated. It was found that the DPn of both the anchoring and stabilizing blocks has a significant impact on the amount of the polymer that can be noncovalently bound to the CNC surface as well as in dispersibility in various solvents.

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 score0.024
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.276
Teacher spread0.264 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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