Effects of Alcell Lignin Methylolation and Lignin Adding Stage on Lignin-Based Phenolic Adhesives
Bibliographic record
Abstract
To investigate the effects of lignin methylolation and lignin adding stage on the resulted lignin-based phenolic adhesives, Alcell lignin activated with NaOH (AL) or methylolation (ML) was integrated into the phenolic adhesives system by replacing phenol at various adhesive synthesis stages or directly co-polymerizing with phenolic adhesives. Lignin integration into phenolic adhesives greatly increased the viscosity of the resultant adhesives, regardless of lignin methylolation or adding stage. ML introduction at the second stage of adhesive synthesis led to much bigger viscosity than ML or AL introduction into phenolic adhesives at any other stages. Lignin methylolation and lignin adding stage did not affect the thermal stability of lignin based phenolic adhesives, even though lignin-based adhesives were less thermally stable than NPF. Typical three-stage degradation characteristics were also observed on all the lignin-based phenolic adhesives. Three-ply plywoods can be successfully laminated with lignin based adhesives, and it was interesting that after 3 h of cooking in boiling water, the plywoods specimens bonded with lignin-based phenolic adhesives displayed higher bonding strength than the corresponding dry strength obtained after direct conditioning at 20 °C and 65% RH. Compared with NPF, lignin introduction significantly reduced the bonding strength of lignin based phenolic adhesives when applied for plywood lamination. However, no significant variation of bonding strength was detected among the lignin based phenolic adhesives, regardless of lignin methylolation or adding stages.
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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".