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Record W3175959240 · doi:10.3390/nano11071641

Preparation and Surface Functionalization of Carboxylated Cellulose Nanocrystals

2021· review· en· W3175959240 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNanomaterials · 2021
Typereview
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCelluloseNanomaterialsSurface modificationMaterials scienceNanocelluloseNanotechnologyCrystallinityNanocrystalRaw materialSulfuric acidChemical engineeringChemistryOrganic chemistryComposite materialMetallurgy

Abstract

fetched live from OpenAlex

In recent years, cellulose nanocrystals (CNCs) have emerged as a leading biomass-based nanomaterial owing to their unique functional properties and sustainable resourcing. Sulfated cellulose nanocrystals (sCNCs), produced by sulfuric acid-assisted hydrolysis of cellulose, is currently the predominant form of this class of nanomaterial; its utilization leads the way in terms of CNC commercialization activities and industrial applications. The functional properties, including high crystallinity, colloidal stability, and uniform nanoscale dimensions, can also be attained through carboxylated cellulose nanocrystals (cCNCs). Herein, we review recent progress in methods and feedstock materials for producing cCNCs, describe their functional properties, and discuss the initial successes in their applications. Comparisons are made to sCNCs to highlight some of the inherent advantages that cCNCs may possess in similar applications.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.046
GPT teacher head0.358
Teacher spread0.312 · 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