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Record W2312410067 · doi:10.1002/pen.24273

UV degradation of clay‐reinforced polypropylene nanocomposites

2016· article· en· W2312410067 on OpenAlexafffund
Hend Ben Hadj Salah, Hachmi Ben Daly, Johanne Denault, Florence Perrin

Bibliographic record

VenuePolymer Engineering and Science · 2016
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsMaterials scienceNanocompositePolypropyleneNanoindentationCrystallinityMontmorilloniteComposite materialDegradation (telecommunications)PolymerExfoliation jointFourier transform infrared spectroscopyModulusChemical engineeringGrapheneNanotechnology

Abstract

fetched live from OpenAlex

The aim of this work is to experimentally characterize the UV‐degradation process at both the surface and at different layers across the thickness of injection‐molded polypropylene (PP) matrix containing different amounts of nanosized montmorillonite (MMT) clay particles. These nanocomposite materials have been exposed to UV irradiations ( λ = 320 nm) at different preset temperatures (25, 45, and 65°C) in the presence of oxygen and during different exposure times. The extent of such process at these layers was determined using both the FTIR spectroscopy and the wide‐angle X‐ray diffraction analyses. The micromechanical properties across the thickness have been characterized using the nanoindentation technique. The obtained results have indicated that the UV‐degradation process for the nanocomposite materials is much more intense than the one observed for the neat PP. Moreover, it has been noted that such degradation process is not uniform across the thickness of the exposed materials. Results obtained from the X‐ray analysis have shown an increase of the crystallinity of the polymer molecules at only the external surface of the exposed materials. This was confirmed using the nanoindentation test as an increase of the Young's modulus at this layer was noted. POLYM. ENG. SCI., 56:469–478, 2016. © 2016 Society of Plastics Engineers

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 score0.005
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

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