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Record W125771683

Improvement of Barrier Properties of Poly(Ethylene Terephthalate)with Nanoclay

2010· article· en· W125771683 on OpenAlexfundno aff
Hesam Ghasemi

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolymer chemistryThermoplastic polymerMaterials scienceChemistryPolymerComposite material
DOInot available

Abstract

fetched live from OpenAlex

RESUME Le polyethylene terephtalate (PET) comme polymere d’ingenierie semi-cristallin trouve enormement d’applications dans l’industrie des emballages. Cependant, pour certaines applications comme celles des boissons gazeuses et des bieres, diminuer sa permeabilite au gaz, autrement dit augmenter ses proprietes barrieres, demeure un defi considerable. L’introduction de feuillets de nano-argile de silicate en tant que phase impermeable dans la matrice polymere devient ainsi une alternative interessante. Le melange a l’etat fondu et la polymerisation in situ sont des techniques generalement utilisees pour produire des nano-composites de PET. La premiere methode reste cependant preferable car elle presente des avantages economiques et environnementaux, puisqu’elle ne necessite pas la presence de solvants ni de monomeres. Dans la premiere phase de la presente etude, les nano-composites de PET (NCPs) ont ete prepares en utilisant differentes argiles organiquement modifiees. La compatibilite avec la matrice, ainsi que la stabilite thermique de l’ensemble, jouent un role preponderant dans l’evolution morphologique des NCPs. Dans la deuxieme phase, des films minces de NCP ont ete produits avec succes par extrusion suivi d’un etirage. L’effet de l’incorporation des argiles sur les proprietes mecaniques, barrieres, thermiques et optiques des produits finaux a ete etudie. Aussi, l’importance de la cristallinite lors de la solidification en sortie d’extrusion et l’influence de la presence des argiles sur le degre de cristallinite en conditions isothermes comme non-isothermes ont ete investiguees.----------ABSTRACT Polyethylene terephthalate (PET), as a semi crystalline engineering polymer, is used extensively in packaging applications. However, gas permeability is a challenge in some applications such as soft drinks and beers. The introduction of layered silicate nanoclay, as an impermeable nanoparticle phase in a polymer matrix, is an attractive approach to enhance gas barrier properties. Melt compounding and in situ polymerization are the main techniques employed to produce PET nanocomposites. The former is the preferred method for preparation of polymer nanocomposites, which has environmental and cost advantages, due to the absence of solvents and monomers. In the first phase of this work, PET clay nanocomposites (PCN) were prepared using different types of organo-modified clay, including ammonium, phosphonium and imidazolium surfactants. Both compatibility and thermal stability play an important role in morphological development of PCNs. In the second and main part of this project, PCN thin films were prepared successfully, using cast film extrusion. The effect of incorporated clay on mechanical, barrier, thermal and optical properties of the products was studied. Incorporating 3 wt% Cloisite30B into PET matrix, led to 23% reduction in oxygen permeability and 20% improvement in tensile modulus. The effect of processing conditions, including screw profile, screw speed and feeding rate, on properties of PCN films were also studied. It was found that screw speed and, accordingly, applied shear has stronger effect on barrier and mechanical properties of the final products than feeding rate (residence time). At the highest screw speed, 27% and 30% improvement in barrier properties and tensile modulus were achieved, respectively.

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 categoriesMeta-epidemiology (narrow)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.202
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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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