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Record W2026755712 · doi:10.1002/pen.23168

Rotational molding of polyethylene composites based on agave fibers

2012· article· en· W2026755712 on OpenAlexaff
Rubén Horacio López-Bañuelos, Francisco Moscoso, Pedro Ortega‐Gudiño, E. Mendizábal, Denis Rodrigue, Rubén González‐Núñez

Bibliographic record

VenuePolymer Engineering and Science · 2012
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceComposite materialAgaveUltimate tensile strengthPolyethyleneFiberMolding (decorative)Compression moldingFlexural strengthRotational speedHigh-density polyethyleneMoldMechanical engineering

Abstract

fetched live from OpenAlex

Abstract In this study, agave fiber/linear medium density polyethylene composites were manufactured by rotational molding. A laboratory scale biaxial machine was used, where the internal air temperature during the processing cycle was measured. Two sizes of agave fibers (50 and 100 mesh) were used separately and mixed together (50/50) at concentrations varying between 0 and 15 wt%. The initial mixtures were obtained by dry blending, rotomolded under different operation conditions (oven temperature, processing cycle time, and rotational speeds), and the final pieces were compared. For each process condition, a complete morphological analysis was performed to relate with mechanical properties in terms of tensile, impact, and flexural strength. The results show that there is an optimum fiber concentration around 10%, and blending fiber sizes gave better tensile properties than using each size alone. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.222
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations76
Published2012
Admission routes1
Has abstractyes

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