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Record W4289171403 · doi:10.1016/j.jcomc.2022.100301

Sustainable Biocomposites from Biofuel Co-Product and Biodegradable Plastic: Effect of Pyrolysis and Compatibilizer on Performance

2022· article· en· W4289171403 on OpenAlexafffund
Jeffrey Lim, Ehsan Pesaranhajiabbas, Michael R. Snowdon, Amar K. Mohanty, Manjusri Misra

Bibliographic record

VenueComposites Part C Open Access · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Guelph
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsOntario Ministry of Agriculture, Food and Rural AffairsUniversity of Guelph
KeywordsUltimate tensile strengthMaterials scienceFlexural strengthHeat deflection temperatureBiocompositeMaleic anhydrideCompatibilizationComposite materialPolybutylene succinateThermal stabilityDistillers grainsIzod impact strength testPulp and paper industryFood sciencePolymerChemistryPolymer blendComposite numberOrganic chemistry

Abstract

fetched live from OpenAlex

Distillers’ dried grains with soluble (DDGS), a by-product of the corn ethanol industry, has been shown to be useful as a filler in biocomposites. Work was done comparing the impacts of heat treatment (torrefaction, at 300°C) of DDGS and inclusion of compatibilizer on properties of a DDGS-filled biocomposite. The untreated or heat-treated DDGS (30 wt.%) was blended with poly (butylene succinate co butylene adipate) (PBSA) (70 wt.%), or PBSA offset with 3 wt.% maleic anhydride-grafted PBSA. As a result of the inclusion of DDGS, tensile and flexural modulus increased by 68% and 72%, respectively. The torrefaction heat treatment was shown to degrade the hemicellulosic content of the DDGS, which restored thermal stability lost with the addition of untreated DDGS. The improved compatibility with the addition of MA-g-PBSA resulted in improvement in heat deflection temperature , as well as tensile strength and flexural strengths, in both untreated and heat-treated samples. Notably, tensile and flexural strengths were further enhanced in the case of the untreated DDGS. Overall, this study shows how filler treatment combined with compatibilization in PBSA biocomposites impact material performance and their variability in specific properties when it comes to application options.

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 score0.003

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 head0.022
GPT teacher head0.311
Teacher spread0.290 · 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

Citations10
Published2022
Admission routes2
Has abstractyes

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