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Record W2079799843 · doi:10.1002/pc.22154

Mechanical and rheological behavior of highly filled polystyrene with lignin

2012· article· en· W2079799843 on OpenAlexaff
Mohamad Reza Barzegari, Ayşe Alemdar, Yaolin Zhang, Denis Rodrigue

Bibliographic record

VenuePolymer Composites · 2012
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsFPInnovationsUniversité Laval
Fundersnot available
KeywordsMaterials scienceLigninComposite materialRheologyUltimate tensile strengthPolystyreneFlexural strengthDynamic mechanical analysisPolymerOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract The mechanical, rheological, and morphological properties of polystyrene (PS)/lignin blends over a wide range of lignin content (0–80 wt%) have been studied in this work. PS/lignin blends were compounded in an internal batch mixer with and without the addition of a linear triblock copolymer based on styrene, ethylene, and butylene (SEBS). A morphological analysis was carried out by scanning electron microscopy to determine the state of dispersion and the interfacial adhesion between the lignin particles and the PS matrix. It was found that the flexural and torsion moduli both increased, while the tensile properties decreased with increasing lignin content. Nevertheless, compatibilizer addition was found to improve the tensile properties of the lignin/PS blend. The shear rheological behavior of the lignin/PS blends was also studied in this work where viscosity, dynamic moduli, and activation energy were found to be very sensitive to both lignin and compatibilizer contents. POLYM. COMPOS., 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 score0.004

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 head0.007
GPT teacher head0.195
Teacher spread0.187 · 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

Citations81
Published2012
Admission routes1
Has abstractyes

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