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Record W6990762199

Effect of particle characteristics on the rheology of polymer-metallic particle suspensions

2005· article· en· W6990762199 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2005
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsRheologyRheometerParticle (ecology)Suspension (topology)ViscosityPolyethyleneViscoelasticityMolding (decorative)
DOInot available

Abstract

fetched live from OpenAlex

Particle suspensions are used in a variety of material processes including powder injection molding, polymer composite molding and metallic foam production. The flow behavior of the suspensions is critical for the adequate processing of such materials. It is well known that particle characteristics have a significant impact on the flow behavior of these solid-liquid systems. In order to better understand the effect of particle characteristics on the rheology of these filled systems, the elastic and viscous moduli G' and G'' of suspensions prepared with particles of different chemical natures (Ni, Cu, Ti, Ti6Al4V, Fe, bronze, SS316L) in molten low-density polyethylene were evaluated under stress sweep using a plate-plate dynamic controlled-stress rheometer (DSR). Correlations between the moduli, and several particle properties (size, shape, surface area, apparent and tap density) were evaluated and hypotheses on the mechanisms of suspension deformation are proposed.

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 score0.074
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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