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Record W2084212385 · doi:10.1177/0892705714556829

Study of lignin dispersion in low-density polyethylene

2014· article· en· W2084212385 on OpenAlex
Amadou Diop, Fayçal Mijiyawa, Demagna Koffi, B. V. Kokta, Daniel Montplaisir

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

VenueJournal of Thermoplastic Composite Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversité du Québec à Trois-RivièresKruger (Canada)
Fundersnot available
KeywordsLow-density polyethyleneMaterials scienceDifferential scanning calorimetryCrystallinityPolyethyleneLigninMelting pointComposite materialMaleic anhydrideDispersion (optics)PolymerOrganic chemistryChemistryCopolymer

Abstract

fetched live from OpenAlex

A maximum of 20% (w/w) lignin was used as a filler in low-density polyethylene (LDPE), together with 3–6% maleic anhydride-grafted LDPE as compatibilizer and 3–10% copper(II) sulphate pentahydrate (CuSO 4 ·5H 2 O) as lignin’s dispersing agent. The resulting composites were investigated for both their mechanical properties and their melting point following the ASTM standards as well as their behaviour was compared with neat LDPE. The results reveal that addition of compatibilizer significantly improved the mechanical properties of lignin, yielding closer values to those of neat LDPE. In fact, the addition of 3% maleated polyethylene induced a 37% increase of the Young’s modulus, whilst 3% CuSO 4 ·5H 2 O provides a good lignin dispersion. The above observations are further supported by the scanning electron micrographs of the blend specimens. Finally, the differential scanning calorimetry analysis revealed that the melting temperature and the crystallinity of LDPE slightly increase with the addition of 3% CuSO 4 ·5H 2 O.

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 score0.008
Threshold uncertainty score0.437

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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