Enzymatic synthesis of kraft lignin-acrylate copolymers using an alkaline tolerant laccase
Bibliographic record
Abstract
Softwood kraft lignin is a major bioresource relevant to the production of sustainable bio-based products. Continued challenges to lignin valorization, however, include poor solubility in organic solvents and in aqueous solutions at neutral pH. Herein, an alkaline tolerant laccase was used to graft acrylate functionalities onto softwood kraft lignin, which is expected to enhance the reactivity of lignin with isocyanate when producing bio-based polyurethanes. Proton nuclear magnetic resonance, Fourier-transform infrared spectroscopy, and high-performance liquid chromatography were used to confirm successful grafting of the acrylate monomer onto lignin and verify the importance of including tert-butyl hydroperoxide as an initiator in the grafting reaction. Laccase-mediated grafting of softwood kraft lignin under alkaline conditions produced lignin products with approximately 30% higher hydroxyl value and higher reactivity toward isocyanate. The reported enzymatic and aqueous process presents an opportunity for the sustainable valorization of softwood kraft lignin. KEY POINTS: • Softwood kraft lignin displayed high phenolic hydroxyl content, polydispersity index and average molecular weight • Grafting hydroxyethyl acrylate (HEA) monomer onto kraft lignin by laccase was successful at 60 °C and alkaline conditions • Lignin-HEA grafted copolymer showed an increase in total OH value and an increase in average molecular weight.
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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".