Functionalization of Phenolic Aldehydes for the Preparation of Sustainable Polyesters and Polyurethanes
Bibliographic record
Abstract
Biobased organic diols derived from the phenolic aldehyde by-products in the depolymerization of lignin (4-hydroxybenzaldehyde, vanillin, and syringaldehyde) for the synthesis of polyesters and polyurethanes is described. Methods to prepare lignin-based diols involved a two-step synthetic route using either a hydroxy alkylation and aldehyde reduction or an aldehyde reduction and Williamson-Ether substitution. The preparation of five polyesters (PEs) and ten polyurethanes (PUs) from lignin-based diols was also performed and their physical and thermal properties were analyzed. DSC analysis confirmed the amorphous nature of all synthesized polymers, and GPC analysis revealed broad dispersities and high molecular weights. Two PE polyols were also derived from a vanillin-based diol at concentrations of 10 and 25 wt% for their usage in sustainable PU foams. PU foams were prepared from these polyols, where it was found that only the foam containing the 10 wt% formulation was suitable for mechanical testing. The PU foam samples were found to have good hardness and tensile strengths compared to both control foams, showing potential for the incorporation of biobased polyols for PU foam formation.
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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) | 0.000 | 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".