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Water transport through epoxy-based powder pipeline coatings

2021· preprint· en· W3210629863 on OpenAlexafffund
Hossein Zargarnezhad, Edouard Asselin, Dennis Wong, C.N. Catherine Lam

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEpoxyCoatingMaterials sciencePermeationPolymerComposite materialChemical engineeringWater transportWater vaporMembraneChemistryWater flowOrganic chemistry

Abstract

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Hydration of epoxy coatings reduces adhesion performance and causes degradation of the material, such as microstructural failures. Quantification of water vapor transport at elevated temperatures is fundamental to understanding polymer coating performance, especially when the coating is exposed to extreme operating conditions. As the water activity increases, the permeability/selectivity of polymers against other permeants changes. In this study, we examined the water permeation kinetics of two common epoxy-based powder coating systems for pipelines (fusion-bonded epoxy, FBE, and high-performance powder coating, HPPC) across a range of industrially-relevant temperatures (from room temperature to 80°C). Specifically, we utilized vapor permeation features of FBE and HPPC films with quantification of equilibrium flux as a function of temperature and pressure. In addition, we analyzed the nonlinear dependency of water transport on the vapor concentration at 65°C. The vapor transport analysis demonstrated that although data for FBE were indicative of a decrease in permeability around 65°C, perhaps due to self-association of water molecules, the coating was likely to experience a plasticization pressure around this temperature. We also examined microstructural changes of the epoxy network due to water transport. Our results revealed evidence of irreversible damage to epoxy coatings under wet-state conditions above 65°C. It appears that the combination of thermal exposure and internal stresses in the glassy epoxy lead to a phase separation of filler particles from the epoxy matrix, as well as to a distinctive cavity formation in the coating membrane. Yet, despite formation of percolating paths for water transport, our results indicate that vapor permeation is primarily restrained due to self-association of water molecules. The vapor transport flux and its permeance are lowered by one order of magnitude in the multilayered HPPC thanks to the moisture-resistant polyethylene topcoat, thus reducing the extent of damage to the underlying substrate. Since barrier protection against gas phase diffusion is controlled by the FBE primer, however, consequences of coating hydration are more pronounced in the overall selectivity toward gaseous transport. Hydrothermal exposure is likely to increase aggregate porosity of the coating and a conservative implementation of standard coating requirements is therefore reasonable to avoid early degradation issues.

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 score0.002
Threshold uncertainty score0.004

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)0.0010.000

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 head0.024
GPT teacher head0.260
Teacher spread0.237 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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