MétaCan
Menu
Back to cohort
Record W2986717660 · doi:10.3390/molecules24224026

Injection Molded Novel Biocomposites from Polypropylene and Sustainable Biocarbon

2019· article· en· W2986717660 on OpenAlexafffund
Mohamed A. Abdelwahab, Arturo Rodriguez‐Uribe, Manjusri Misra, Amar K. Mohanty

Bibliographic record

VenueMolecules · 2019
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centres of Excellence
KeywordsMaterials scienceComposite materialPolypropyleneTalcThermal expansionCompoundingComposite numberMolding (decorative)ExtrusionRheologyPolymer

Abstract

fetched live from OpenAlex

Achieving sustainability in composite materials for high-performance applications is a key issue in modern processing technologies. In this work, the structure-property relationships of injection molded polypropylene (PP)/biocarbon composites were investigated with a focus on the thermal properties and specific emphasis on the coefficient of linear thermal expansion (CLTE). Biocomposites were produced using 30 wt.% biocarbon in a PP matrix, and two different sources of biocarbon produced at ~650 and 900 °C were used. The overall results were compared with 30 wt.% glass- and talc-filled PP composites. Due to the lamellar morphology of the talc developed during the extrusion-injection molding processing, talc-filled composites showed an increase in the CLTE in the normal direction (ND), and a reduction in the flow direction (FD) with respect to the neat polymer. Glass fiber composites also showed an improvement in the CLTE with respect to the neat polymer. However, the biocarbon-based composites showed the best properties in the ND, with improved values in biocarbon produced at higher temperature. The FD values for both biocarbon composites were improved with respect to the matrix, while biocarbon created at lower temperature showed slightly lower expansion values. A comprehensive explanation of these overall phenomena is supported by a series of morphological, thermal, mechanical and rheological tests.

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 score0.006
Threshold uncertainty score0.606

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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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

Citations32
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueMoleculesSame topicNatural Fiber Reinforced CompositesFrench-language works237,207