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Record W2782199801 · doi:10.1021/acsanm.7b00126

UV-Absorbing Cellulose Nanocrystals as Functional Reinforcing Fillers in Poly(vinyl chloride) Films

2018· article· en· W2782199801 on OpenAlexafffund
Zhen Zhang, Gilles Sèbe, Xiaosong Wang, Kam Chiu Tam

Bibliographic record

VenueACS Applied Nano Materials · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooEuropean Commission
KeywordsMaterials scienceVinyl chlorideNanocompositeAtom-transfer radical-polymerizationCelluloseUltimate tensile strengthUltravioletMethacrylateChemical engineeringPolymer chemistryPolymerizationNanocrystalIrradiationPolymerComposite materialCopolymerNanotechnology

Abstract

fetched live from OpenAlex

Ultraviolet (UV)-responsive poly(cinnamoyloxy ethyl methacrylate) (PCEM) was grafted on cellulose nanocrystals (CNCs) via the surface-initiated atom transfer radical polymerization technique. The resultant PCEM-grafted CNCs (PCEM- g -CNCs) exhibit high UV absorption properties and undergo cross-linking when subjected to UV radiation. When the PCEM- g -CNC nanohybrids were incorporated into poly(vinyl chloride) (PVC) matrix, transparent nanocomposite films with UV-blocking characteristics were obtained. Comparison of the optical and mechanical properties of the films before and after UV irradiation confirmed that the PCEM- g -CNCs are excellent thermal and UV stabilizers for PVC. In addition, the tensile properties of the PVC film were increased significantly and further enhanced after UV irradiation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.021
GPT teacher head0.263
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

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

Citations72
Published2018
Admission routes2
Has abstractyes

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