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Record W2779408232 · doi:10.1002/adv.21928

Polylactic acid–agave fiber biocomposites produced by rotational molding: A comparative study with compression molding

2017· article· en· W2779408232 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Polymer Technology · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceComposite materialCompression moldingPolylactic acidCrystallinityMolding (decorative)Ultimate tensile strengthPorosityFiberPolymerMold

Abstract

fetched live from OpenAlex

Abstract In this work, the possibility to produce polylactic acid ( PLA ) and agave fiber biocomposites by dry‐blending and rotational molding was studied. The samples were also produced by compression molding to compare the effect of processing conditions on the biocomposites properties. In particular, the effect of fiber content (0–40 wt.%) on morphology, density, porosity, thermal ( DSC ) and mechanical properties (tension, flexion, impact and hardness) was studied. Also, a complete analysis of the internal air temperature profiles was performed to determine the thermal behavior of PLA during the rotational molding cycle. The results showed that rotomolded biocomposites were successfully produced but had higher porosity than compression molded ones due to the absence of pressure while forming. This led to different level of mechanical properties reduction as fiber content increases. Nevertheless, for compression‐molded biocomposites, crystallinity (30% at 30 wt.%), tensile modulus (14% at 30 wt.%) and impact strength (71% at 40 wt.%) improvements were obtained compared to neat PLA .

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 categoriesMeta-epidemiology (narrow)
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 score0.012
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.012
GPT teacher head0.309
Teacher spread0.296 · 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