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Record W2021197717 · doi:10.1002/app.41278

Study of the effect of processing conditions on the co‐injection of PBS/PBAT and PTT/PBT blends for parts with increased bio‐content

2014· article· en· W2021197717 on OpenAlexafffund
Matthew Zaverl, Oscar Valerio, Manjusri Misra, Amar K. Mohanty

Bibliographic record

VenueJournal of Applied Polymer Science · 2014
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaMinistero dello Sviluppo EconomicoOntario Ministry of Food and AgricultureMinistry of Rural AffairsOntario Ministry of Economic Development and Innovation
KeywordsMaterials scienceComposite materialIzod impact strength testUltimate tensile strengthMoldFactorial experimentPolybutylene succinatePolymer blendBrittlenessCore (optical fiber)Scanning electron microscopeAdipatePolymerPolylactic acidCopolymer

Abstract

fetched live from OpenAlex

ABSTRACT This work studies the effect of processing parameters on mechanical properties and material distribution of co‐injected polymer blends within a complex mold shape. A partially bio‐sourced blend of poly(butylene terephthalate) and poly(trimethylene terephthalate) PTT/PBT was used for the core, with a tough biodegradable blend of poly (butylene succinate) and poly (butylene adipate‐co‐terephthalate) PBS/PBAT for the skin. A ½ factorial design of experiments is used to identify significant processing parameters from skin and core melt temperatures, injection speed and pressure, and mold temperature. Interactions between the processing effects are considered, and the resulting statistical data produced accurate linear models indicating that the co‐injection of the two blends can be controlled. Impact strength of the normally brittle PTT/PBT blend is shown to increase significantly with co‐injection and variations in core to skin volume ratios to have a determining role in the overall impact strength. Scanning electron microscope images were taken of co‐injected tensile samples with the PBS/PBAT skin dissolved displaying variations of mechanical interlocking occurring between the two blends. © 2014 The Authors Journal of Applied Polymer Science Published by Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132 , 41278.

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)0.002
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 score0.006
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.248
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

Citations28
Published2014
Admission routes2
Has abstractyes

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