Crosslinking of Hardwood Lignin with Citric Acid for Sustainable Wood Adhesives
Bibliographic record
Abstract
The toxicity of petroleum-based crosslinkers raises health and environmental concerns, prompting interest in bio-based alternatives. This study reports the facile crosslinking of hardwood lignin (HWL) with citric acid (CA) as a bio-crosslinker for application as a lignin-based wood adhesive. HWL is characterized by GPC and DSC to determine its molecular weight and glass transition temperature, respectively. The successful crosslinking and esterification reactions of the HWL-CA-based resin are confirmed by the exothermic peaks observed in the DSC thermogram and by FT-IR analysis. The HWL-based adhesives with various proportions of CA meet the Korean standard shear strength requirement of 0.60 MPa, with 12% CA (HWL-CA12) giving the maximum value of 1.07 MPa. The successful surface modification of the veneer pre-treatment with CA is also confirmed by FT-IR analysis. Although the adhesive strength of the HWL-CA12 is decreased on the pre-treated veneer relative to the untreated veneer, it remains above the standard requirement on the veneers that were treated with 10% and 15% of CA. These findings demonstrate the potential of CA-crosslinked lignin as a sustainable alternative to petroleum-based wood adhesives.
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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".