Development of Ligno-Polyol for the production of Polyurethanes
Bibliographic record
Abstract
The overall objective of this work is to explore a new non-food renewable supply of industrially viable polyol to make polyurethane products for industrial applications. Lignin has been considered as an industrial waste coming from the paper and textile fiber industries. From a chemical point of view lignin is a natural polyphenol and polyol. Due to its high molecular weight and its complex structure, however, those functional groups are not easily accessible. As a consequence the industrial application of lignin is very limited. In this work, different approaches have been used for the incorporation of kraft lignin in petroleum-derived commercial polyols for the production of polyurethanes (PU) with minimum energy and chemical used and also minimum negative impact on the environment. The results have demonstrated that, beside lignin chemistry, lignin size and morphology, applied shear force, mixing temperature, and chemistry of polyol have also great influence on the dispersion and interaction of lignin with petroleum based polyols and thus on the PU performance. In this development the studied lignin was well dispersed and interacted with the polyols and they also participated in the PU network structure, resulting in great improvement in the glass transition temperature and the mechanical properties as well.
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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) | 0.002 | 0.001 |
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".