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Record W7162019481 · doi:10.82308/43092

Synergistic weathering of polystyrene representative of UV and freeze-thaw conditions in Canadian climates

2022· dissertation· en· W7162019481 on OpenAlexaboutno aff
Joel Grant

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsWeatheringPolystyreneMicroplasticsSurface roughnessDissolutionErosionTremolite

Abstract

fetched live from OpenAlex

Plastic pollution in aquatic and terrestrial environments is a growing global concern. While the identification of macro- and micro-plastics in outdoor samples has been well-documented in recent years, observing and characterizing nanoplastic formation remains a challenge. This is largely due to the presence of naturally occurring organic particulate matter and other contaminants when samples are collected from the natural environment. Thus, studies of plastic weathering under controlled conditions are of interest to investigate plastic fragmentation and degradation. This provides the opportunity to consider synergistic weathering with ultraviolet (UV) irradiation exposure followed by freeze-thaw cycling such as that observed in the climate of southern Quebec. This thesis details the effects of weathering on polystyrene sheets by investigating changes in bulk mechanical properties, surface roughness variations, and particle release. Polystyrene was chosen because it is frequently found in aquatic environments as a result of inappropriate disposal. Weathering polystyrene sheets via 18-weeks of UV exposure followed by fourteen 24-hr cycles of freeze-thaw in filtered reverse-osmosis water led to increases in bulk and surface hardness of the polystyrene. The storage modulus curve of weathered polystyrene underwent a shift and increase in glass transition temperature. This showed a change in stiffness and embrittlement of the surface layer due to the formation of crystallites and oxidation. Surface roughness measurements also increased because of erosion of the core surface. Particles released into the leachate were analyzed by Scanning Electron Microscopy and Nanoparticle Tracking Analysis. It was found that micron-sized and submicron-sized particles were released upon weathering of the plastic. Films of the particles were confirmed to be polystyrene with Fourier Transform Infrared Spectroscopy. These data suggest that seasonal variations may be associated with increased release of polystyrene particles from the bulk plastic

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.243
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

Citations0
Published2022
Admission routes1
Has abstractyes

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