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Record W2994548048 · doi:10.1002/mame.201900630

Injection Molded Strong Polypropylene Composite Foam Reinforced with Rubber and Talc

2019· article· en· W2994548048 on OpenAlexaff
Jinchuan Zhao, Qingliang Zhao, Guilong Wang, Chongda Wang, Chul B. Park

Bibliographic record

VenueMacromolecular Materials and Engineering · 2019
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsMaterials sciencePolypropyleneComposite materialTalcComposite numberToughnessUltimate tensile strengthNatural rubberMolding (decorative)Silicone rubber

Abstract

fetched live from OpenAlex

Abstract Lightweight plastic foams are of great significance for saving resources and reducing energy consumption. Foam injection molding (FIM) shows a promising future to provide lightweight and shape‐complex plastic components. However, it is still challenging to produce lightweight and strong polypropylene (PP) foams by FIM due to PP's poor foaming ability. Herein, rubber and talc are employed to improve PP's foaming ability, and hence to enhance PP foam's mechanical properties. Due to the significantly enhanced rheological properties, injection molded PP composite foam exhibits greatly refined and homogenized cellular structure compared with pure PP foam. Thanks to rubber toughening effect and improved cellular morphology, PP/rubber foam shows much higher ductility than pure PP foam. Moreover, talc particles lead to remarkably enhanced rigidity of PP/rubber foams. Thus, lightweight and strong PP/rubber/talc composite foam is achieved with tensile toughness increased by 82.58% and impact strength increased by 106.21%, and they show broad industrial application prospects.

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 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 score0.700

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)0.0000.000

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 head0.003
GPT teacher head0.167
Teacher spread0.164 · 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

Citations28
Published2019
Admission routes1
Has abstractyes

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