Influence of lignin's <scp>pH</scp> on polyurethane flexible foam formation and how to control it
Bibliographic record
Abstract
Abstract Low pH of commercial lignins has a catastrophic impact on the polyurethane foaming reactions. Experiments were performed with 10 wt% of lignin with various pHs in polyols. Virgin lignin (pH 2.5, 35% moisture) has the most negative impact as it reduces the initial foam rising rate by 85% and the foam's final height by 35% as compared to the reference foam, lignin free. Drying of this lignin at 80°C for 12 h can reduce this impact while alkaline treatment to bring the lignin's pH to 6.6 almost cancel it. As revealed by in situ dielectric constant measurements, both reactions, gelling via polymerization and blowing via CO 2 degassing, are impacted. In situ Fourier transform infrared analysis of the foaming process demonstrated that blowing reaction is the most pH sensitive. Two methods to counter the pH influence by pH modification were tested and provide interesting results but also significant drawbacks limiting their applicability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".