Modified raw cellulose filaments material as polyol substitute in rigid insulating polyurethane foam
Bibliographic record
Abstract
Current research in building insulation is primarily focused on enhancing the performance of polyurethane foam or exploring alternatives with biobased materials, with particular attention placed on polyols. This study investigated the use of modified cellulose filaments as a polyol to enhance the environmental performance of polyurethane foam. Two distinct etherification methods were employed to modify cellulose filaments (CFs), yielding accessible and reactive ether functions from the hydroxyl (OH) groups of CFs. Polyols and the resulting polyurethane foam were characterized. Kinetics of foam formation, morphology, density, thermal conductivity, and mechanical properties in compression were studied. Analysis revealed reduced reactivity with modified CFs as a substitute of the petroleum-based polyol, affecting foaming. Impacts on the resulting properties of the foam were observed, such as the size of the cells (from 0.14 ± 0.06 mm2 for petroleum-based polyol foams to 0.03 ± 0.03 mm2 for foams with 70% substitution with biobased polyols 1 and 2), and cells opening (from 92 ± 2% for petroleum-based polyol foams to 8 ± 3% with 70% substitution with biobased polyols). These results lead to non-compliance with the canadian polyurethane foam standard, requiring a closed cell rate of over 90%. A deterioration in mechanical properties through loss of stiffness and a drastic reduction in the maximum strength (yield strength) the material can withstand below the required standard were also measured. However, noteworthy conductivity results were obtained (0.041 ± 0.004 W m−1‧K−1 with 70% of substitution with biobased polyols 1 and 2). Foam properties were partly due to different polyol properties, such as functionality and viscosity.
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 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".