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Record W2809265948 · doi:10.3139/217.3523

Enhancement of Heat Seal Properties of Polypropylene Films by Elastomer Incorporation

2018· article· en· W2809265948 on OpenAlexafffund
Redouane Boutrouka, Seyed H. Tabatabaei, Abdellah Ajji

Bibliographic record

VenueInternational Polymer Processing · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolypropyleneComposite materialElastomerSeal (emblem)Thermoplastic elastomerAtmospheric temperature rangeCrystallinityPolymerCopolymerThermodynamics

Abstract

fetched live from OpenAlex

Abstract Seal strength at high and low temperatures as well as the width of the heat sealing temperature range are important properties in packaging industry. In addition, for sterilisable and retort applications, having those properties at elevated temperatures is crucial. Polypropylenes (PP) are usually used for these applications, however, the sealing temperatures are too high and the temperature range for the seal process is narrow, thus blending with a PP elastomer copolymer can be an alternative. In this study, hot-tack and heat seal properties were determined for a homo-polypropylene, a random co-polypropylene and an elastomer co-polypropylene based films and their blends. It is found that the seal initiation temperature (for hot tack and heat seal) is governed by the melting temperature and crystallinity and the increase of the elastomer content in the blends leads to a decrease of the seal initiation temperature. It is also shown that the sealing force depends on the ease of chains diffusion across the sealing interface. Finally, it was found that the strength of the heat sealing increases by recrystallization in the sealing interface after cooling.

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 categoriesInsufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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