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Record W2906718818 · doi:10.1002/app.47476

The addition effect of hollow glass microsphere on the dispersion behavior and physical properties of polypropylene/clay nanocomposites

2018· article· en· W2906718818 on OpenAlexfundno aff
Bich Nam Jung, DongHo Kang, Solmi Cheon, Jin Kie Shim, Sung Wook Hwang

Bibliographic record

VenueJournal of Applied Polymer Science · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsnot available
FundersMinistry of Rural AffairsMinistry of Agriculture, Food and Rural Affairs
KeywordsMaterials sciencePolypropyleneNanocompositeComposite materialUltimate tensile strengthDispersion (optics)PolymerPolyethyleneBall mill

Abstract

fetched live from OpenAlex

ABSTRACT Polypropylene (PP) nanocomposites have been widely researched for last decade due to its high mechanical property and multiple usages in various industrial fields from automobile to consumer packaging. Dispersion of nanoclay in polyethylene and PP is the key factor due to their hydrophobic property. Adding surfactant or introducing a polymer with a functional group, and modifying a natural clay with organic ions have been tried to achieve the better dispersion of clay in polymer matrix. In this study, the PP/clay nanocomposite with maleic anhydride grafted PP and hollow glass microspheres (HGMs) at various compositions were prepared and characterized. The addition of HGMs to PP/clay nanocomposites significantly improved the tensile stress at yield point except 7 wt % of HGMs. It is assumed that this could be due to not only the reinforcing effect of HGMs in PP, but the crushing effect of HGMs on the clay resulting in interlayer increase of clay as well. The barrier properties was also found to be improved about 32% max resulting from the better dispersion and presence of HGMs. It could be assumed that the HGMs could act as a ball creating a ball milling crush force to achieve the better dispersion of clay in the polymer and improve nanocomposite performance. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136 , 47476.

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 categoriesScience and technology studies
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 score0.007
Threshold uncertainty score0.999

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 studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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.

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

Citations22
Published2018
Admission routes1
Has abstractyes

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