Nacre from mollusk shells: a model for high-performance structural materials
Bibliographic record
Abstract
Nacre is the iridescent layer found inside a large number of mollusk shells. This natural composite has a very high mineral content, which makes it hard and stiff. However it is the toughness of nacre which is the most impressive: it is three orders of magnitude tougher than the mineral it is made of. No manmade composite material can boast such amplification in toughness, and for this reason nacre has become a biomimetic model material. The mineral in nacre comes in the form of microscopic polygonal tablets, which have the ability to 'slide' on one another in large numbers when the material is loaded in tension. This key mechanism makes nacre a quasi-ductile material, which in turn greatly increases its toughness and makes it damage tolerant. Numerous 'artificial nacres' were developed in the past but none of them can truly duplicate the remarkable mechanism of tablet sliding. In this work selected structural features of nacre were implemented in a PMMA-based composite, which for the first time could replicate the collective tablet sliding mechanism. This material demonstrates that the powerful toughening mechanism operating in natural nacre can be duplicated and harnessed in engineering materials.
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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".