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Record W917515829 · doi:10.1063/1.4918449

Improvement of barrier properties of rotomolded PE containers with nanoclay

2015· article· en· W917515829 on OpenAlexaff
Shadi Jamshidi, Uttandaraman Sundararaj

Bibliographic record

VenueAIP conference proceedings · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials scienceComposite materialRheologyLinear low-density polyethyleneNanocompositePolyethyleneMontmorilloniteLow-density polyethyleneHigh-density polyethylenePolymerDispersion (optics)

Abstract

fetched live from OpenAlex

Polyethylene (PE) is widely used to make bulk containers in rotational molding process. The challenge in this study is to improve permeation resistance of PE to hydrocarbon solvents and gases. Adding organomodified clay improves the thermal, barrier and mechanical properties of PE. In fact, clay layers create a tortuous path against the permeant, yielding better barrier properties. Due to the non-polar hydrophobic nature of PE and polar hydrophilic structure of clay minerals, the compatibilizer plays a crucial role to enhance the dispersion level of clay in the matrix. In this study High Density Polyethylene (HDPE) and Linear Low Density Polyethylene (LLDPE) layered silicate nanocomposite were melt-compounded with two concentrations of organomodified clay (2 and 4 wt. %). The interaction between nanoclay, compatibilizer and rotomolding grade of PE were examined by using X-ray diffraction, transmission electron microscopy (TEM) and rheology test. Rheology was used to determine the performance of our material at low shear processing condition.

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 score0.007
Threshold uncertainty score0.514

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 head0.031
GPT teacher head0.224
Teacher spread0.193 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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