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Record W2084956543 · doi:10.1002/app.32373

Rheology of bitumen modified by EVA—Organoclay nanocomposites

2010· article· en· W2084956543 on OpenAlexaff
Subramanian Sureshkumar Markanday, Jiri Stastna, Giovanni Polacco, Sara Filippi, Igor B. Kazatchkov, Ludovit Zanzotto

Bibliographic record

VenueJournal of Applied Polymer Science · 2010
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOrganoclayMaterials scienceRheologyNanocompositeComposite materialCreepEthylene-vinyl acetateMixing (physics)Phase (matter)Ternary operationPolymerCopolymerChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Ternary systems, bitumen/ethylene‐vinyl acetate (EVA)/organoclay, were prepared by two mixing methods (physical mixing and melt blending) and then studied in small amplitude oscillations, start‐up of shear flow and repeated creep and recovery tests. The effect of mixing method and the role of two organoclays on the rheological properties of the studied systems were investigated. Improved thermomechanical properties of bitumen/EVA/organoclay nanocomposites, prepared by melt blending, were demonstrated by the low accumulated strain/compliance in the repeated creep and recovery tests. Structural differences between the studied systems were reflected in the behavior of the dynamic phase angle, specifically in the shape of the derivative of phase angle w.r.t. the reduced frequency. Similarly, the structural differences between the prepared nanocomposites were reflected by the behavior of the stress growth function η + in the transient experiments. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010

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 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 score0.019
Threshold uncertainty score0.381

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 science0.0010.000
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 head0.005
GPT teacher head0.222
Teacher spread0.218 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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