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Record W1993099147 · doi:10.5539/mas.v4n9p157

Influence of Polymer Blending on Mechanical and Thermal Properties

2010· article· en· W1993099147 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceMiscibilityDifferential scanning calorimetryPolystyrenePolymerGlass transitionComposite materialPlastics extrusionTensile testingAcrylonitrile butadiene styreneUltimate tensile strengthWork (physics)ThermalThermodynamics

Abstract

fetched live from OpenAlex

Polymer blends are capable of providing materials with extended useful properties beyond the range that can be obtained from single polymer equivalents. Blends of polystyrene (PS) and Acrylonitrile-Butadiene-Styrene (ABS) are prepared in different ratios by melt blending technique which was carried out using a single screw extruder. The tensile test and Differential Scanning Calorimetry (DSC) are used to study mechanical and thermal properties. The results from this work show that the mechanical properties for blend system are better than those of pure polymers, also the (DSC) test gives good indications of improving state of miscibility for most blend ratios; there is only one glass transition temperature between the two values of pure polymers.

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.

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 score0.030
Threshold uncertainty score0.267

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 head0.011
GPT teacher head0.199
Teacher spread0.188 · 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