A Strong, Tough and Fire-Retardant Biomimetic Multifunctional Wooden Laminate
Bibliographic record
Abstract
Mildly delignified wood showed a well-preserved wood cell wall framework, and its derived compressed materials demonstrate excellent mechanical properties and advanced functional material potential. Here, we proposed a simple yet effective approach for making strong, tough, and fire-retardant wooden laminate by a three-step process of mild delignification, infiltrating potassium nonafluoro-1-butanesulfonate (PFBS), and hot-pressing to densify the material. PFBS can be infiltrated into the micro/nano-structures of the mildly delignified wood to achieve a good flame-resistant protective barrier. Flame retardant tests showed that this strong, tough, and fire-retardant wooden laminate has a superior flame-retardant performance to natural wood. Additionally, the wooden laminate also exhibits a simultaneously enhanced tensile strength (175.6 MPa vs. 89.9 MPa for natural wood) and toughness (22.9 MJ m−3 vs. 10.9 MJ m−3 for natural wood). Given these attributes, the resulting wooden laminates are identified as promising candidates for high-performance structural applications, fulfilling stringent requirements for both mechanical resilience and flame-retardant efficacy.
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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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".