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Record W2273636644 · doi:10.5539/jmsr.v5n2p111

Effect of Maleic Anhydride Modification on the Mechanical Properties of a Highly Filled Glass Fibre Reinforced, Low-Viscosity Polypropylene for Injection Moulding

2016· article· en· W2273636644 on OpenAlexvenueno aff
Jürgen Tröltzsch, Jonas Stiller, Katja Hase, Isabelle Roth, Frank Helbig, Lothar Kroll

Bibliographic record

VenueJournal of Materials Science Research · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
FundersTechnische Universität Chemnitz
KeywordsMaterials scienceComposite materialUltimate tensile strengthIzod impact strength testPolypropyleneMaleic anhydrideBrittlenessGlass fiberModulusStiffnessInjection mouldingViscosityYoung's modulusPolymerCopolymer

Abstract

fetched live from OpenAlex

<p class="1Body">Short glass fibre reinforcement is one of the most important measures to improve the mechanical properties of injection moulded parts. The need for increasing performance leads to high fibre contents which is a critical fact due to the contrasting behaviour of strength, stiffness and impact properties. In this study a high-fluidity polypropylene (PP) is compounded with short glass fibres up to 70 weight percent and comparatively investigated with the adding of maleic anhydride (MAH) as compatibilizer. Due to the high fluidity of the PP, which ensures a good embedding of the fibres, the tensile modulus increases up to 65 weight percent, tensile strength up to 50 weight percent of glass fibre content. Adding the MAH increases strength and impact properties, while the tensile modulus only shows an improvement at high fibre content. The influence of the compatibilizer effect diminishes at higher fibre contents, especially for the impact strength which could so far not be clarified exactly. Reasons could be the reduction of fibre length at higher fibre contents and the increasing influence of the brittle fibre component. With the adding of MAH the contrasting behaviour of the impact properties in comparison to strength and stiffness can be reduced and the optimum over all mechanical properties can be shifted to higher fibre contents.</p>

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)0.017
metaresearch head score (Gemma)0.004
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 score0.013
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.053
GPT teacher head0.344
Teacher spread0.291 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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