Scalable Production of Robust and Tough Biomimetic Composite by Rapid In‐Situ Mineralization
Bibliographic record
Abstract
Abstract Nacre‐inspired materials with combined high strength and toughness have been widely developed and utilized for various engineering applications. However, existing preparation techniques suffer from intricate processes, high energy‐consumption, and lack of scalability, all of which collectively impede the efficient production of three‐dimensional materials. Here, a viable strategy is reported for the efficient and scalable production of bulk nacre‐mimetic materials, drawing inspiration from the intricate structures found in both nacre and wood. The prepared millimeter‐thick wooden artificial nacres (WANs) exhibit the presence of multi‐hierarchical lamellar structures, organic bridges, and micro‐asperities. Those features lead to the WANs exhibiting impressive mechanical performances, presenting excellent bending strength (≈93.31 MPa), toughness (≈7.40 MPa m 1/2 ), tensile strength (≈122.59 MPa), and work of fracture (≈4.61 MJ m −3 ). In addition, owing to the low density (≈1.59 g cm −3 ), the WANs show much higher specific mechanical properties compared to nacre and related artificial nacre materials. Considering both its production process and exceptional properties, this material holds great promise for practical applications within the realm of engineering and structural fields.
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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) | 0.001 | 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 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".