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Record W2946664064 · doi:10.1039/c9na00265k

Tailored cellulose nanocrystals as a functional ultraviolet absorbing nanofiller of epoxy polymers

2019· article· en· W2946664064 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNanoscale Advances · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersInnotech Alberta
KeywordsEpoxyMaterials sciencePolymerNanocompositeFourier transform infrared spectroscopyAbsorption of waterChemical engineeringUltravioletPolymer nanocompositeNanomaterialsCelluloseAbsorption (acoustics)Composite materialNanotechnology

Abstract

fetched live from OpenAlex

elemental analysis. The modified CNCs were then incorporated into an epoxy polymer and their efficacy in mitigating the photo-degradation of epoxy was evaluated. For this, a neat epoxy control, native CNCs and modified CNC based nanocomposite specimens were subjected to controlled UV irradiation and the resulting structure-property changes were assessed. Results of UV absorption and discoloration showed that the neat epoxy was impacted the most as a result of the UV irradiation. While the incorporation of native CNCs displayed some UV absorption and reduction in the UV mediated discoloration of the epoxy polymer, the most pronounced effect was obtained in PABA decorated CNC based epoxy nanocomposites. The use of such tailored CNCs has great potential to mitigate UV induced degradation of a range of polymers that are used especially in outdoor applications where direct exposure to UV is significant.

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)0.000
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.263
Teacher spread0.251 · 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