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Record W7132905996

Dynamic and Gas Barrier Properties of Multifunctional Polymer Composites Under Extreme Conditions

2024· dissertation· W7132905996 on OpenAlexfundno aff
Ashkan Dargahi

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsCreepUltimate tensile strengthPolymerPolyethyleneFlexural strengthFracture toughnessHigh-density polyethyleneLinear low-density polyethyleneSupercritical fluid
DOInot available

Abstract

fetched live from OpenAlex

Thermoplastic polymers have shown a great potential for design and development of components and structures in high temperatures – high pressures environments. Recyclability, superior chemical resistance, low production and transportation costs and high strength to weight ratio have given a competitive edge to these polymeric candidates when compared to their metallic counterparts. With the focus on the dynamic, creep and gas barrier properties of thermoplastic polymers under extreme conditions, this study primarily aims to provide robust improvement strategies on the basis of composite science and engineering. Two experimental setups were designed and validated to measure the tensile creep behavior and barrier properties to supercritical carbon dioxide at elevated temperatures. Nonlinear creep characteristics of Polyvinylidene Fluoride copolymer were characterized under 5 MPa to 12.5 MPa tensile stress and at 40 °C to 80 °C, and a generalized temperature dependent model was formulated to generate time-temperature-compliance master curves for creep life predictions. Identification of gas barrier properties from the measured data was optimized using nonlinear regression, which significantly reduced the required time for long permeation tests for standard to advanced engineering thermoplastics. Laminar composite structures of polyethylene and ethylene vinyl alcohol were manufactured, which showed advantages of both utilized polymers in terms toughness in flexural mode and barrier to moisture at target service temperature of 82 °C. Full morphological analysis was performed on the multilayer design to address the fracture surface characteristics as well as the interfacial properties, which was also supported by the chemical composition analysis. Classical lamination theory was shown to effectively predict the experimentally measured data in terms of the equivalent dynamic flexural moduli over the measured temperature range of 35 °c to 85 °C. Graphene nanoplatelets were incorporated in high-density polyethylene to improve the mechanical and barrier properties. The effects of nanoparticles content and processing conditions on the crystallization of the matrix as well as the dispersion of nanoparticles were addressed quantitively using image processing methods. Substantial improvement in creep and barrier properties using laminar and particulate systems confirmed the potential of composite science strategies for improving the properties of thermoplastic polymers in high temperature – high pressure environments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.024
GPT teacher head0.288
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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