Evaluating the effects of Kraft and Hydroxymethylated lignin on particleboard performance and environmental impact
Bibliographic record
Abstract
In this study we investigate the effects of two industrial lignins, Kraft (KL) and hydroxymethylated lignin (HL), on the physicochemical properties of urea-formaldehyde (UF) adhesives and the performance of bonded particleboards. KL and HL were used to partially replace up to 15 wt% of UF adhesives, increasing viscosity beyond industrial requirements but enhancing internal bond strength. The curing peak temperature decreased from 84.3 °C (UF) to 83.3 °C (UF–5 % HL), while the heat of curing rose from 86.8 J/g to 107.5 J/g, confirming enhanced reactivity over KL. Mechanical performance improved notably, with the best results obtained for panels containing 10 wt% KL and 5 wt% HL, showing MOE, MOR, and IB increases of 38.4 %, 12.3 %, and 30.3 %, respectively, relative to control panels. Formaldehyde emissions were significantly reduced from 0.174 ppm for neat UF to 0.094 ppm for UF–15 % KL, approaching the Canadian regulatory limit. Despite viscosity challenges associated with both lignins, these findings highlight its potential as a bio-based UF adhesive modifier, offering enhanced performance and reduced formaldehyde emissions. Further optimization is required to lower HL's molecular weight and ensure industrial feasibility. This research provides a pathway for lignin valorization in sustainable wood composites, advancing eco-friendly alternatives for the forest products industry.
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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".