Conversion of biomass lignin to high-value polyurethane: A review
Bibliographic record
Abstract
Lignin, as a major by-product of pulp and paper industry, has attracted extensive interest for the preparation of high value-added products, due to the merits of abundant, sustainable, inexpensive, and unique functional groups. This review focuses on the strategies to develop high performance polyurethane (PU) materials from lignin on the basis of main reports, in which lignin was used not only as macromonomer to substitute petroleum-based polyols, but also as blending filler for PU industry. Pre-treatment approaches, especially lignin fractions extracted with various solvents and chemical modifications, e.g., depolymerization, hydroxyalkylation, dealkylation, and esterication, were widely explored to enable lignin more reactive and available to synthesize PU products. In addition, lignin/PU blends were also prepared to fulfill industrial demand. With adjustment of lignin structure, the PU formulation, and synthesis procedures, various lignin-based PU products with advanced properties and a higher bio-substitution ratio have been developed, demonstrating the potential industrial application of lignin for high value-added sustainable materials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".