Reinforcement of Lignin-Based Phenol-Formaldehyde Adhesive with Nano-Crystalline Cellulose (NCC): Curing Behavior and Bonding Property of Plywood
Bibliographic record
Abstract
The curing behavior of lignin-based phenol-formaldehyde (LPF) resin with different contents of nano-crystalline cellulose (NCC) was studied by differential scanning calorimetry (DSC) at different heating rates (5, 10 and 20°C/min) and the bonding property was evaluated by the wet shear strength and wood failure of two-ply plywood panels after soaking in water (48 hours at room temperature and followed by 1-hour boiling). The test results indicated that the NCC content had little influence on the peak temperature, activation energy and the total heat of reaction of LPF resin at 5 and 10°C/min. But at 20°C/min, LPF0.00% (LPF resin without NCC) showed the highest total heat of reaction, while LPF0.25% (LPF resin containing 0.25% NCC content) and LPF0.50% (LPF resin containing 0.50% NCC content) gave the lowest value. The wet shear strength was affected by the NCC content to a certain extent. With regard to the results of one-way analysis of variance, the bonding quality could be improved by NCC and the optimum NCC content ranged from 0.25% to 0.50%. The wood failure was also affected by the NCC content, but the trend with respect to NCC content was not clear.
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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 | 0.000 |
| 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".