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Record W2884369164

Improving the Mechanical Performance of Wood Fiber Reinforced Bio-based Polyurethane Foam

2014· dissertation· en· W2884369164 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTSpace · 2014
Typedissertation
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFPInnovations
KeywordsPolyurethaneMaterials scienceComposite materialFiberFourier transform infrared spectroscopyScanning electron microscopeCompressive strengthBendingCompression (physics)Chemical engineering
DOInot available

Abstract

fetched live from OpenAlex

Because of the environmental impact of fossil fuel consumption, soybean-based polyurethane (PU) foam has been developed as an alternative to be used as the core in structural insulated panels (SIPs). Wood fibers can be added to enhance the resistance of foam against bending and buckling in compression. The goal of this work is to study the effect of three modifications: fiber surface treatment, catalyst choice, and mixing method on the compression performance of wood fiber-reinforced PU foam. Foams were made with a free-rising process. The compression performance of the foams was measured and the foams were characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray computed tomography (CT). The foam reinforced with alkali-treated fibers had improved compression performance. The foams made with various catalysts shared similar performance. The foam made using a mechanical stirrer contained well-dispersed fibers but the reinforcing capability of the fibers was reduced.

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)0.001
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 score0.030
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.011
GPT teacher head0.266
Teacher spread0.255 · 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