Functional Lignin Building Blocks: Reactive Vinyl Esters with Acrylic Acid
Bibliographic record
Abstract
Introducing vinyl groups onto the backbone of technical lignin provides an opportunity to create highly reactive renewable polymers suitable for radical polymerization. In this work, the chemical modification of softwood kraft lignin was pursued with etherification, followed by direct esterification with acrylic acid (AA). In the first step, phenolic hydroxyl and carboxylic acid groups were derivatized into aliphatic hydroxyl groups using ethylene carbonate and an alkaline catalyst. The lignin was subsequently fractionated using a downward precipitation method to recover lignin of defined molar mass and solubility. After recovery, the resulting material was then esterified with AA, resulting in lignin with vinyl functional groups. The first step resulted in approximately 90% of phenolic hydroxyl groups being converted into aliphatic hydroxyls, while the downward fractionation resulted in three samples of lignin with defined molar masses. For the esterification reaction, the weight ratio of reagents, reaction temperature, and reaction time were evaluated as factors that would influence the modification efficacy. 13 C NMR spectroscopy analysis of lignin samples before and after esterification showed that the optimized reaction conditions could reach approximately 40% substitution of aliphatic hydroxyl groups. Both steps only used lignin and the modifying reagent (no solvent), with the possibility of recovery and reuse of the reagent by dilution and distillation. An additional second esterification step of the resulting lignin sample with acetic acid or propionic acid converted 90% of remaining hydroxyl groups into short-chain carbon aliphatic esters, making a hydrophobic material suitable for further copolymerization with synthetic hydrophobic monomers.
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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".