Improving the Mechanical Performance of Wood Fiber Reinforced Bio-based Polyurethane Foam
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".