Aqueous ethanol fractionation of softwood and hardwood kraft lignins: Impact on purity and properties
Bibliographic record
Abstract
Industrial kraft lignins are mixtures of macromolecular components variable in both structure and composition. To maximize their value in commercial applications, they often need to be homogenized and purified. Several fractionation methods have been reported to improve the properties of kraft lignins, but these reports have been mostly limited to kraft lignins of single origins. In this study, the physicochemical properties of fractions from four industrial kraft lignins were compared. Fractionation was performed on both softwood and hardwood lignins by partial dissolution in aqueous ethanol followed by precipitation with water. The yields of each fraction varied greatly between the lignins, with differences reaching up to 35% for a single fraction. All fractions were characterized which showed that fractions having remarkably similar properties and compositions can be obtained from different lignins. Organic and inorganic impurities were found to concentrate in specific fractions which allowed the isolation of highly purified fractions of kraft lignin. These results highlight the importance of matching individual kraft lignins with suitable applications.
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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".