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Record W7037152339

Development of epoxidized soybean oil and soy fibre composites with polyhedral oligomeric silsequioxane (poss) nano reinforcement

2010· dissertation· en· W7037152339 on OpenAlexafffund

Bibliographic record

VenueThe Atrium (University of Guelph) · 2010
Typedissertation
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of GuelphLibrary and Archives Canada
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural AffairsGrain Farmers of Ontario
KeywordsUltimate tensile strengthEpoxidized soybean oilSoybean oilAbsorption of waterEpoxyModulusYoung's modulusTitanate
DOInot available

Abstract

fetched live from OpenAlex

Soy fibre and soybean oil were utilized to produce a bio-composite targeted as a substitute for conventional petroleum-based materials. The study was divided into two parts; the first was the development of a bio-epoxy that consisted of conventional epoxy, epoxidized soybean oil, and two types of functionalized POSS. The second part of the study involved blending of the bio-epoxy with titanate treated soy fibre. Combined incorporation of epoxide and amine functionalized POSS in the bio-epoxy matrix resulted in a 29% impact strength improvement compared to the petroleum-based epoxy. Incorporation of the epoxide functionalized POSS resulted in improvements in tensile strength by 8%, tensile modulus by 2%, and an increase in the glass transition temperature by 4% compared to the petroleum-based epoxy and epoxidized soybean oil hybrid. The coupling of titanate to soy fibre in comparison to the soy fibre without titanate treatment resulted in an impact strength improvement of 37%. Furthermore, the coupling of titanate increased the tensile strength and tensile modulus by 24% and 22% respectively, and reduced the water absorption by 70%.

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 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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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 teacher head, not a consensus.

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

Citations0
Published2010
Admission routes2
Has abstractyes

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