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Record W4417134405 · doi:10.1038/s41598-025-30883-9

Optimizing maleic anhydride content to enhance mechanical performance and thermal stability of recycled polyolefin blends

2025· article· en· W4417134405 on OpenAlexafffund
Sung Woong Choi, Seongeun Jang, Garam Do, Patrick Lee, Du Young Choi

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of Toronto
FundersMinistry of Science and ICT, South KoreaNational Research Council of Science and TechnologyNatural Sciences and Engineering Research Council of CanadaKorea Institute of Industrial Technology
KeywordsMaleic anhydridePolyolefinThermogravimetric analysisThermal stabilityUltimate tensile strengthDurabilityDegradation (telecommunications)

Abstract

fetched live from OpenAlex

This study evaluated the effects of maleic anhydride (MA) coupling agent on the mechanical and thermal properties and long-term stability of post-consumer recycled (PCR) plastics. The addition of MA coupling agent increased the tensile strength by 32.12%, enhancing the mechanical durability of the recycled plastic. Furthermore, the melt index (MI) increased by 366.23%, significantly improving processability. Thermogravimetric analysis (TGA) results showed a significant improvement in thermal stability, and a lifetime prediction model estimated an extension of the material's life by 532.66% at 200 °C. These results demonstrate that MA coupling agent effectively suppresses long-term degradation at high temperatures. Therefore, MA coupling agents can simultaneously improve mechanical properties and recyclability and offer a potent solution for creating sustainable plastics within a circular economy.

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 score0.003
Threshold uncertainty score0.399

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 studies0.0000.000
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 head0.026
GPT teacher head0.258
Teacher spread0.232 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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