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Record W4224266373 · doi:10.1002/pc.26672

Evaluation of mechanical, optical, and antibacterial properties of metal‐oxide dispersed <scp>HDPE</scp> nanocomposites processed by rotational molding

2022· article· en· W4224266373 on OpenAlexaff
Barmak Ghanbarpour, Amin Moslemi

Bibliographic record

VenuePolymer Composites · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceHigh-density polyethyleneNanocompositeComposite materialUltimate tensile strengthPolymerFlexural strengthTitanium dioxideNanoparticleRutileFlexural modulusPolymer nanocompositePolyethyleneChemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Abstract To investigate the impact of zinc oxide/titanium dioxide nanoparticles on the characteristics of high‐density polyethylene, researchers used the rotational molding technique to produce polymeric nanocomposites. The nanocomposites' morphological, mechanical, optical, as well as biological characteristics, were studied using a range of characterizations. SEM analysis revealed a uniform morphology of ZnO and TiO 2 nanoparticles in the polymer matrix, with 80–120 nanometers middle particle dimensions. The existence of ZnO with hexagonal wurtzite form as well as TiO 2 with rutile phase was verified by XRD and XRF. Corresponded to the pure polymer, the HDPE‐ZnO/TiO 2 nanocomposites' flexural modulus and tensile strength increased, but elongation at break reduced, according to mechanical characterization. UV–visible spectroscopy revealed that the HDPE‐ ZnO/TiO 2 nanocomposites showed UV light absorption at wavelengths ranging from 250 to 390 nm. According to antibacterial tests and contact angle measurements, adding metal oxide NPs to HDPE improved hydrophilicity and antibacterial activity.

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)0.001
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 score0.004
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.027
GPT teacher head0.250
Teacher spread0.223 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

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