Sustainable Bio-Based Phenol-Formaldehyde Resoles Using Hydrolytically Depolymerized Kraft Lignin
Bibliographic record
Abstract
In this study bio-based bio-phenol-formaldehyde (BPF) resoles were prepared using hydrolytically depolymerized Kraft lignin (DKL) as bio-phenol to partially substitute phenol. The effects of phenol substitution ratio, weight-average molecular weight (Mw) of DKL and formaldehyde-to-phenol (F/P) ratio were also investigated to find the optimum curing temperature for BPF resoles. The results indicated that DKL with Mw ~ 1200 g/mol provides a curing temperature of less than 180 °C for any substitution level, provided that F/P ratios are controlled. Incorporation of lignin reduced the curing temperature of the resin, however, higher Mw DKL negatively affected the curing process. For any level of lignin Mw, the curing temperature was found to increase with lower F/P ratios at lower phenol substitution levels. At 25% and 50% phenol substitution, increasing the F/P ratio allows for synthesis of resoles with lower curing temperatures. Increasing the phenol substitution from 50% to 75% allows for a broader range of lignin Mw to attain low curing temperatures.
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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) | 0.000 | 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 | 0.001 |
| 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".