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Record W4295152266 · doi:10.1002/app.52999

Compatibilized thermoplastic elastomers based on highly filled polyethylene with ground tire rubber

2022· article· en· W4295152266 on OpenAlexaff
Shuang Liu, Zonglin Peng, Yong Zhang, Denis Rodrigue, Shifeng Wang

Bibliographic record

VenueJournal of Applied Polymer Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversité Laval
FundersNational Major Science and Technology Projects of China
KeywordsMaterials scienceComposite materialVulcanizationLinear low-density polyethyleneNatural rubberCompatibilizationPolyethyleneThermoplastic elastomerElastomerMaleic anhydrideUltimate tensile strengthDifferential scanning calorimetryThermoplasticPolymerCopolymerPolymer blend

Abstract

fetched live from OpenAlex

Abstract Thermoplastic elastomers (TPE) based on ground tire rubber (GTR) are good strategies for the circular economy and sustainable development of waste tire rubber recycling. However, several parameters must be optimized to produce valuable TPE. The most important ones are GTR concentration and dispersion, as well as crosslinking degree, combined with interfacial interactions between the GTR and the thermoplastic matrix. In this work, TPE based on highly filled linear low‐density polyethylene (LLDPE) with GTR (50%–90%) was prepared via dynamic vulcanization. In particular, different reclaimed GTR (RR) was used alone or with a compatibilizer (maleic anhydride grafted polyethylene, PE‐g‐MAH) to prepare compatibilized TPE. The interactions between the rubber and plastic were quantified by a series of characterizations including mechanical tests, rheological measurements, differential scanning calorimetry, dynamic mechanical analysis and scanning electron microscopy. The results showed that the mechanical properties and processability decreased with increasing GTR content. Although the interfacial compatibility was improved with a higher GTR reclamation degree, the TPE mechanical properties were still gradually decreasing. To improve on these results, PE‐g‐MAH was added to increase the GTR‐LLDPE interfacial interactions. The results showed improvement in terms of mechanical properties and processability, especially for compatibilized TPE based on RR (tensile strength increased from 3.34 to 4.82 MPa and elongation at break from 91% to 101%).

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)0.001
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 score0.005
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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

Citations22
Published2022
Admission routes1
Has abstractyes

Explore more

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