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Record W4400885861 · doi:10.3390/polym16142071

Degradation of Bioderived Polyurethane Composites by Spectroscopy in ISO20200 Composting Conditions

2024· article· en· W4400885861 on OpenAlexaff
Alexander Caschera, Tristan Calayan, Nicola Piccolo, Adel Ramezani Kakroodi, Jason James Robinson, Guerino Sacripante

Bibliographic record

VenuePolymers · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPolyurethanePolyolThermogravimetric analysisMaterials scienceDegradation (telecommunications)PolyesterComposite materialLigninChemical engineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Polyurethane foam compositions derived from bioderived polyester polyols with various additives were evaluated for disintegration under composting conditions using the ISO 20200 standard and were characterized by thermogravimetric analysis, microscopy, infrared spectroscopy, and imaging to provide additional insight. Compared to polyether polyol-based polyurethanes, the bioderived polyurethanes were found to display increased disintegration with an average mass loss of 25.4 ± 3.6 weight percent when subjected to composting conditions for 45 days, suggesting that these materials are less likely to persist in the environment when compared to other types of commodity plastics. Additives such as carbon black and lignin added within the foam composition did not accelerate the disintegration.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.048
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0020.000

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 head0.226
Teacher spread0.220 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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